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Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline the key aspects of designing, implementing and evaluating these agents. The data sources were empirical studies, including peer‐reviewed conference papers and journal articles, and the most recent publications, from the ACM Digital Library, IEEE Xplore, ProQuest, ScienceDirect, Scopus, SpringerLink, Taylor & Francis Online, Web of Science and Wiley Online Library. The remaining papers underwent a rigorous quality assessment. A filter study meeting the objective was based on keywords. Comparative analysis and synthesis of results were used to handle data and combine study outcomes. Out of 1162 search results, 13 studies were selected. The results indicate that agents promote dialogic learning, proficiency in knowledge domains, personalized feedback and empathic abilities as essential design principles. Most implementations employ a quantitative approach, and two variables are used for evaluation. Feedback types play a vital role in achieving positive results in learning performance and student perceptions. The main limitations and gaps are the time range for literature selection, the level of integration of the empathic field and the lack of a detailed development stage report. Moreover, future directions are the ethical implications of agents operating beyond scheduled learning times and the adoption of Responsible AI principles. In conclusion, this review provides a comprehensive framework of empathic PCAs, mostly in their evaluation. The systematic review registration number is osf.io/3xk6a.Practitioner notesWhat is already known about this topicEmotions play a pivotal role in shaping the interaction process, making it essential to consider them when designing methodological strategies or learning tools.Empathic Pedagogical Conversational Agents (PCAs) have emerged as a crucial approach for enhancing and personalizing the learning experience (24/7) for pupils and supporting human teachers in their teaching process.Despite the creation of numerous empathic PCAs, there is a scarcity of Systematic Literature Reviews (SLRs) on their application in the educational field, particularly concerning the integration of emotional abilities in combination with the competencies of each subject.What this paper addsIt offers new insights into the design principles underlying the integration of the empathic field.It reviews different approaches for incorporating students' prior knowledge in real time.It provides a comprehensive and up‐to‐date overview of the research designs used for implementation, including quantitative, qualitative and mixed methods.It examines the factors that influence the effectiveness of empathic PCA in teaching and learning.It evaluates the types of feedback that enhance the impact of the empathic field on learning outcomes.Implications for practice and/or policyIt is crucial to grasp the topics that this paper introduces in order to effectively integrate new learning tools into any context.Techno‐pedagogical designers seeking to gain insights into empathic PCAs will find immense value in this SLR, as it comprehensively covers each stage of the process.For future research endeavours, this study offers a wealth of ideas to draw upon, enabling researchers to address the challenges outlined and explore new avenues of investigation. [ABSTRACT FROM AUTHOR]

The paper introduces the student‐coined term digital instinct which describes students' disposition to resorting to digital technology for solving problems and doing school assignments. Taking cues from the term digital instinct, the paper describes a student perspective on digital literacy emerging from 100 lived experience descriptions and interviews with 37 Danish upper secondary students. The findings show that students' digital practice is characterised by experience‐based, intuitive and familiar use of technologies. Most notably, students employ digital technologies as cognitive partners that help them carry on with assignments that they initially did not understand, but that they were able to complete with the help of the computer. The study examines the nature of this partnership through the words of the students and identifies how technologies expand student agency but fall short of a reflective use of digital technologies. Recognising the strengths and weaknesses of students' digital practices may inform the concept of digital literacy and encourage teachers to acknowledge the digital instinct as a steppingstone to foster students' reflective use of digital technologies. Practitioner notesWhat is already known about this topic Students have inadequate command of digital literacies as described in curricular terminology.Students have positive as well as negative perceptions of the value and usefulness of digital technologies in school.Students both over‐ and underestimate their own digital literacies.What this paper adds Students have a fundamental utilitarian conception of digital technologies that either make schoolwork easier or more difficult, and they do not articulate that their use of digital technologies provides them with digital literacies.Students' conception of a digital instinct describes an intuitive and familiar, albeit unreflected, use of technologies where students employ experience‐based and self‐taught methods for using digital technologies.The digital instinct accounts for a feeling of agency among students, manifested in a widespread confidence that they can do assignments and solve problems when they make use of their computer.Implications for practice and/or policy Curricular terminologies struggle to capture what students can and cannot do with technology, and how much they understand the underlying technology.Teachers can involve and build on students' experience‐based digital practices as a starting point for developing digital literacy among students—also as an entry to a curricular perspective.Teachers should acknowledge students' conception of a 'digital instinct' as an important disposition in its own right. [ABSTRACT FROM AUTHOR]

Computational thinking is a necessary skill for the 21st century. While previously examined in computer‐rich settings, researchers are increasingly studying computational thinking in unplugged environments such as board games. Focusing on the African board game Songo, this study shows that computational thinking practices are embedded in Songo board gameplay and interact with the cultural context. The study also reveals a computing practice peculiar to Songo gameplay, songoputation. This paper suggests that researchers can benefit from exploring computational thinking and computing practices beyond board games in western contexts. Practitioner notesWhat is already known about this topicComputational thinking can be cultivated in non‐digital environments.Board games are spaces where computational thinking can be developed.The relationship between African board games and computational thinking is still unknown.What this paper addsAfrican board games such as Songo are spaces where players engage with computational thinking and songoputationCulture informs computational thinking practices players engaging in when playing Songo.Computational thinking is not a new practice and should be explored in different culture contexts and settings.Implications for practice and/or policyAfrican board games should be used to develop computational thinking skills.Board games should be used to foster computational thinking skills among students in context with limited access to digital technology. [ABSTRACT FROM AUTHOR]

Research on fostering learning about percentages within intelligent tutoring systems (ITSs) is limited. Additionally, there is a lack of data‐driven approaches for improving the design of ITS to facilitate learning about percentages. To address these gaps, we first investigated whether students' understanding of basic mathematical skills (eg, arithmetic, measurement units and geometry) and fractions within an ITS predicts their understanding of percentages. We then applied a psychological network analysis to evaluate interdependencies within the data on 44 subtopics of basic mathematical concepts, fractions and percentages. We leveraged a large‐scale dataset consisting of 2798 students using the ITS bettermarks and working on approximately 4.1 million mathematical problems. We found that advanced arithmetic, measurement units, geometry and fraction understanding significantly predicted percentage understanding. Closer inspection indicated that percentage understanding was best predicted by problems sharing similar features, such as fraction word problems and fraction/natural number multiplication/division problems. Our findings suggest that practitioners and software developers may consider revising specific subtopics which share features with percentage problems for students struggling with percentages. More broadly, our study demonstrates how evaluating interdependencies between subtopics covered within an ITS as a data‐driven approach can provide practical insights for improving the design of ITSs. Practitioner notes What is already known about this topic Longitudinal studies showed that basic mathematical skills predict fraction understanding. There is only limited evidence on whether similar predictions can be observed for percentage understanding—in general and within intelligent tutoring systems. Process data from such intelligent tutoring systems can be leveraged to pursue both educational research questions and optimizing digital learning software. Problems involving percentages typically are word problems requiring multiplications and/or divisions. What this paper adds Similar to the case of fractions, students' performance on advanced arithmetic, measurement units and geometry significantly predicted performance with percentages. Students' performance with fractions also predicted performance with percentages significantly. A psychological network analysis was applied to evaluate specific interdependencies between a range of subtopics (eg, Multiplying and dividing fractions, Adding and subtracting fractions and Calculating with percentages). Fraction word problems and fraction problems involving multiplication/division turned out to be the best predictors of understanding percentages. Implications for practice and/or policy When facing difficulties with percentages, revision of previous mathematical concepts sharing similar features (eg, fraction word problems, fraction/natural number multiplication/division problems) may be advised. Software developers may consider implementing such data‐driven revision recommendations for students facing difficulties within intelligent tutor systems. Psychological network analysis can be utilized as a learning analytics method for easy‐to‐access visualizations illustrating relationships between a large range of different subtopics. What is already known about this topic Longitudinal studies showed that basic mathematical skills predict fraction understanding. There is only limited evidence on whether similar predictions can be observed for percentage understanding—in general and within intelligent tutoring systems. Process data from such intelligent tutoring systems can be leveraged to pursue both educational research questions and optimizing digital learning software. Problems involving percentages typically are word problems requiring multiplications and/or divisions. What this paper adds Similar to the case of fractions, students' performance on advanced arithmetic, measurement units and geometry significantly predicted performance with percentages. Students' performance with fractions also predicted performance with percentages significantly. A psychological network analysis was applied to evaluate specific interdependencies between a range of subtopics (eg, Multiplying and dividing fractions, Adding and subtracting fractions and Calculating with percentages). Fraction word problems and fraction problems involving multiplication/division turned out to be the best predictors of understanding percentages. Implications for practice and/or policy When facing difficulties with percentages, revision of previous mathematical concepts sharing similar features (eg, fraction word problems, fraction/natural number multiplication/division problems) may be advised. Software developers may consider implementing such data‐driven revision recommendations for students facing difficulties within intelligent tutor systems. Psychological network analysis can be utilized as a learning analytics method for easy‐to‐access visualizations illustrating relationships between a large range of different subtopics. [ABSTRACT FROM AUTHOR]

Agency, or the capacity to take intentional actions, is considered one of the primary affordances of virtual reality (VR) for learning. VR is expected to increase learners' agency because it allows for full‐body interactivity from a first‐person perspective, giving them novel ways of interacting with the digital environment. Yet, agency in immersive learning has not been well‐studied relative to other affordances like presence, and more evidence is needed to understand how varied media and designs heighten or diminish agency. This mixed‐method study addressed this need by developing and validating measures of sense of agency with 30 high school students who used VR field trips in their engineering class over four lessons. By comparing immersive videos to video game‐like interactive graphical environments, the study illustrates some of the complexities of agency in VR. The findings indicate agency is not a unidimensional construct nor is it equivalent to full‐body interactivity in VR as learners felt some types of agency when using immersive videos. Furthermore, learners' identities moderated associations between the type of VR media and their sense of agency, and agency did not change over time as the novelty of VR waned. These results suggest VR designers should consider varied ways of interacting in VR that are beneficial for learning. They also support the use of immersive videos when the educator's goal is to increase agency over learning or focus, and provide measures and direction for future research to assess the relationship between varied types of agency, features of VR experiences and learning outcomes. Practitioner notes What is already known about this topic Virtual reality (VR) can enhance learning by giving learners a strong sense of presence in the virtual environment and giving them agency over their learning through novel forms of interactivity. Many studies have looked at increasing the learner's presence in VR, but fewer have assessed learners' agency. Prior work found the impact of increased interactivity on learning was mixed: sometimes it increased learning outcomes and motivation, other times it did not. What this paper adds This study develops and validates measures of learners' sense of agency within VR learning environments. This study finds that more interactivity in VR increases how much agency learners feel over their actions but not necessarily their agency over learning and attention. This study also finds variation in students' experiences of agency based on their culturally defined sense of self‐construal. Implications for practice and/or policy Practitioners interested in immersive learning technologies should consider the design of the media used rather than focusing only on the device's capability. Immersive videos may be effective tools for enhancing student agency, depending on the aims of the learning experience. Designers and educators should consider learners' identities such as self‐construal, and understand student experiences may vary. What is already known about this topic Virtual reality (VR) can enhance learning by giving learners a strong sense of presence in the virtual environment and giving them agency over their learning through novel forms of interactivity. Many studies have looked at increasing the learner's presence in VR, but fewer have assessed learners' agency. Prior work found the impact of increased interactivity on learning was mixed: sometimes it increased learning outcomes and motivation, other times it did not. What this paper adds This study develops and validates measures of learners' sense of agency within VR learning environments. This study finds that more interactivity in VR increases how much agency learners feel over their actions but not necessarily their agency over learning and attention. This study also finds variation in students' experiences of agency based on their culturally defined sense of self‐construal. Implications for practice and/or policy Practitioners interested in immersive learning technologies should consider the design of the media used rather than focusing only on the device's capability. Immersive videos may be effective tools for enhancing student agency, depending on the aims of the learning experience. Designers and educators should consider learners' identities such as self‐construal, and understand student experiences may vary. [ABSTRACT FROM AUTHOR]

This paper presents a multidimensional view of AI's role in education, emphasising the intricate interplay among AI, analytics and human learning processes. Here, I challenge the prevalent narrow conceptualisation of AI as tools in Education, exemplified in generative AI tools, and argue for the importance of alternative conceptualisations of AI for achieving human–AI hybrid intelligence. I highlight the differences between human intelligence and artificial information processing, the importance of hybrid human–AI systems to extend human cognition and posit that AI can also serve as an instrument for understanding human learning. Early learning sciences and AI in Education Research (AIED), which saw AI as an analogy for human intelligence, have diverged from this perspective, prompting a need to rekindle this connection. The paper presents three unique conceptualisations of AI: the externalisation of human cognition, the internalisation of AI models to influence human mental models and the extension of human cognition via tightly coupled human–AI hybrid intelligence systems. Examples from current research and practice are examined as instances of the three conceptualisations in education, highlighting the potential value and limitations of each conceptualisation for human competence development, as well as the perils of overemphasis on approaches that replace human learning opportunities with AI tools. The paper concludes with advocacy for a broader approach to AIED that goes beyond considerations on the design and development of AI and includes educating people about AI and innovating educational systems to remain relevant in an AI ubiquitous world. [ABSTRACT FROM AUTHOR]

Given their easy accessibility and dual‐channel model of content presentation, instructional videos have become a favoured tool for EFL vocabulary learning tool among many students. Teachers often use various nonverbal behaviours to elicit social reactions and guide learners' attention in instructional videos. The current study conducted three eye‐tracking experiments to examine the circumstances under which a teacher's happy facial expressions are beneficial in instructional videos, with or without pointing gestures and mouse pointing. Experiments 1 and 2 demonstrated that the combination of happy facial expressions and pointing gestures attracted learners' attention to the teacher and hindered students' learning performance, regardless of the complexity of slides. Experiment 3 showed that in instructional videos with complex slides, using happy facial expressions along with mouse pointing can enhance students' learning performance. Teachers are advised to show happy facial expressions and avoid using pointing gestures when designing instructional videos. Practitioner notes What is already known about this topic Given easy accessibility and dual‐channel model of content presentation, instructional videos have become a favoured tool for EFL vocabulary learning. When teachers record instructional videos while standing alongside slides, they often use nonverbal cues to support their speech. Teachers' social and attentional cues interactively influence students' learning processes and performance. What this paper adds A teacher's happy facial expressions evoke more positive emotions and greater motivation in learners compared to bored expressions. A teacher's pointing gestures, when combined with happy facial expressions, divert students' attention away from slides and towards the teacher. A teacher's happy facial expressions enhance students' learning performance when no pointing gestures are used in videos with simple slides. Implications for practice/policy Teachers are advised to display happy facial expressions and avoid using pointing gestures in instructional videos, regardless of the complexity of the slides. Practitioners should consider how to incorporate teachers' facial expressions pointing gestures and mouse pointing effectively. What is already known about this topic Given easy accessibility and dual‐channel model of content presentation, instructional videos have become a favoured tool for EFL vocabulary learning. When teachers record instructional videos while standing alongside slides, they often use nonverbal cues to support their speech. Teachers' social and attentional cues interactively influence students' learning processes and performance. What this paper adds A teacher's happy facial expressions evoke more positive emotions and greater motivation in learners compared to bored expressions. A teacher's pointing gestures, when combined with happy facial expressions, divert students' attention away from slides and towards the teacher. A teacher's happy facial expressions enhance students' learning performance when no pointing gestures are used in videos with simple slides. Implications for practice/policy Teachers are advised to display happy facial expressions and avoid using pointing gestures in instructional videos, regardless of the complexity of the slides. Practitioners should consider how to incorporate teachers' facial expressions pointing gestures and mouse pointing effectively. [ABSTRACT FROM AUTHOR]

Incorporating immersive technologies in education has become increasingly popular due to their ability to facilitate active learning and engage students in the acquisition of concepts and skills. One form of immersive technology includes educational games that incorporate movement interaction, allowing children to engage with in‐game elements by either immersing their own image within the game environment or by controlling an avatar using their hand and body gestures. Nonetheless, successfully incorporating these technologies into classrooms with sizable student populations presents a challenge, necessitating the implementation of a well‐considered design approach. This paper introduces a systematic learning design approach facilitating the integration of a movement‐based learning platform as a core curriculum tool in multimodal learning stations within authentic Kindergarten classroom settings. The design approach was evaluated in a case study involving three kindergarten teachers and 49 students conducted over a full school year. Progress data were gathered utilizing a combination of quantitative and qualitative evaluation tools. Analysis of the data suggests that integrating multimodal learning activities led to improvements in overall academic performance, particularly in critical mathematical skills compared to pre‐test scores. Teachers expressed a positive attitude towards the integration of movement‐based games using the learning design approach, finding it to be beneficial and effective for student learning. The study emphasizes the importance of purposeful design in creating immersive learning experiences and underscores the significance of utilizing multiple representations to enhance student motivation and engagement. The proposed systematic learning design approach has the potential to be applied to a broad range of grade levels, academic subjects and educational contexts to facilitate the integration of immersive technologies. Practitioner notes What is already known about this topic? Immersive technologies are becoming popular in education. Immersive technologies have been shown to enhance skills and enable the collection of multimodal data to better understand learning processes. The movement‐based learning games fall under the category of immersive technologies that merge real and virtual worlds. Designing effective immersive learning experiences for these new technology‐enhanced learning environments remains a question. What this paper adds A proposed systematic learning design approach that demonstrates the way that movement‐based learning games can be used seamlessly as core curriculum tool in authentic kindergarten settings for an entire school year. Ways to engage effectively a large classroom of 20 or more students with movement‐based learning games. Findings regarding the impact of the movement‐based games on student engagement, academic achievement, cognitive development and social–emotional growth. Teachers' perceptions and attitudes towards executing movement‐based learning experiences in their classrooms using the proposed systematic learning design approach. Implications for practice and/or policy In‐service kindergarten and primary school teachers can adopt the proposed systematic learning design approach to integrate immersive technologies into the curriculum. This ensures that these technologies are used consistently throughout the school year, providing continuous and engaging learning experiences. School district administrators can use the proposed approach to develop training programs for pre‐service and in‐service kindergarten and primary school teachers, focusing on understanding the immersive technology, managing large classrooms and integrating the games into daily lesson plans. School administrators can implement the proposed systematic learning design approach to establish robust systems for monitoring and assessing the impact of immersive technologies on student engagement, academic achievement, cognitive development and social–emotional growth. Special education in‐service teachers can leverage the flexibility of the movement‐based learning games to design personalized learning experiences for their students with special needs. This involves adjusting the difficulty level, pace and type of interaction to meet individual requirements. Special education administrators can promote the use of the proposed approach to foster an inclusive learning environment where all students, regardless of their abilities, can participate and benefit from the immersive technologies. What is already known about this topic? Immersive technologies are becoming popular in education. Immersive technologies have been shown to enhance skills and enable the collection of multimodal data to better understand learning processes. The movement‐based learning games fall under the category of immersive technologies that merge real and virtual worlds. Designing effective immersive learning experiences for these new technology‐enhanced learning environments remains a question. What this paper adds A proposed systematic learning design approach that demonstrates the way that movement‐based learning games can be used seamlessly as core curriculum tool in authentic kindergarten settings for an entire school year. Ways to engage effectively a large classroom of 20 or more students with movement‐based learning games. Findings regarding the impact of the movement‐based games on student engagement, academic achievement, cognitive development and social–emotional growth. Teachers' perceptions and attitudes towards executing movement‐based learning experiences in their classrooms using the proposed systematic learning design approach. Implications for practice and/or policy In‐service kindergarten and primary school teachers can adopt the proposed systematic learning design approach to integrate immersive technologies into the curriculum. This ensures that these technologies are used consistently throughout the school year, providing continuous and engaging learning experiences. School district administrators can use the proposed approach to develop training programs for pre‐service and in‐service kindergarten and primary school teachers, focusing on understanding the immersive technology, managing large classrooms and integrating the games into daily lesson plans. School administrators can implement the proposed systematic learning design approach to establish robust systems for monitoring and assessing the impact of immersive technologies on student engagement, academic achievement, cognitive development and social–emotional growth. Special education in‐service teachers can leverage the flexibility of the movement‐based learning games to design personalized learning experiences for their students with special needs. This involves adjusting the difficulty level, pace and type of interaction to meet individual requirements. Special education administrators can promote the use of the proposed approach to foster an inclusive learning environment where all students, regardless of their abilities, can participate and benefit from the immersive technologies. [ABSTRACT FROM AUTHOR]

Virtual Reality (VR) has demonstrated significant advantages in various educational fields as it allows learners to actively learn in high interactivity and realism under their learning pace. However, for low‐achieving students, VR learning environments may introduce some challenges, which are problems encountered during their learning process, which lead to difficulties in self‐regulating their learning progress and becoming disoriented in the lack of guidance. This study aims to explore the improvement of self‐regulated VR learning environment based on the Cognitive Theory of Multimedia Learning and enhance the performance of low‐achieving students. We designed a VR course on electronic circuit hardware and programming, providing participants with a series of learning aids in the VR learning environment, including feedback, hints and guidance. Feedback aids provide correct or incorrect feedback after each task or test, guidance aids display progress following each task or test and hint aids offer guidance when inactivity is detected. A quasi‐experiment was conducted by using questionnaires and practical tasks to assess the participants' cognitive levels, practical hands‐on skills, self‐regulated learning abilities and learning engagement after VR learning. The results demonstrated significant improvements in all learning indicators for low‐achieving students. Practitioner notes What is already known about this topic Virtual Reality (VR) presents itself as a promising tool for self‐regulated learning (SRL). SRL abilities are of paramount importance within the learning environment of VR. In the context of the self‐regulated Virtual Reality (SRVR) learning environment, low‐achieving students have received little attention. What this paper adds It examines the effectiveness of learning aid mechanisms within the SRVR learning environment. These mechanisms support cognitive levels and increase engagement in SRVR learning. Low‐achieving learners benefit from the presence of learning aid mechanisms in the SRVR learning environment. Implications for practice and/or policy Providing learning aid mechanisms within the SRVR learning environment can potentially augment learning. Learning aids mechanism have the potential to provide comprehensive support within the SRVR setting. What is already known about this topic Virtual Reality (VR) presents itself as a promising tool for self‐regulated learning (SRL). SRL abilities are of paramount importance within the learning environment of VR. In the context of the self‐regulated Virtual Reality (SRVR) learning environment, low‐achieving students have received little attention. What this paper adds It examines the effectiveness of learning aid mechanisms within the SRVR learning environment. These mechanisms support cognitive levels and increase engagement in SRVR learning. Low‐achieving learners benefit from the presence of learning aid mechanisms in the SRVR learning environment. Implications for practice and/or policy Providing learning aid mechanisms within the SRVR learning environment can potentially augment learning. Learning aids mechanism have the potential to provide comprehensive support within the SRVR setting. [ABSTRACT FROM AUTHOR]

Learning with games requires two types of information, namely domain‐specific information and game‐specific information. Presenting these two types of information together with gameplay may pose a heavy demand on cognitive resources. This study investigates how timing of information presentation affects cognition (ie, mental effort and performance), motivation (ie, achievement goals) and emotion (ie, achievement emotions). Participants were secondary school students (N = 145). Participants participated in a 2 × 2 factorial experiment with two factors—timing of domain‐specific information presentation and timing of game‐specific information presentation, either before or during gameplay. We measured mental effort, chemistry knowledge, time on task, achievement goals and achievement emotions. Multiple regression and robust regression revealed that presenting domain‐specific information before gameplay promoted higher approach goals, higher avoidance goals and more enjoyment than presenting it during gameplay. There was no difference between presenting game‐specific information before gameplay and during gameplay except for performance‐avoidance goals. We conclude that timing of information presentation affects motivational and emotional processes and outcomes and that students feel more motivated and enjoyed when domain‐specific information is presented before learning than during learning. Educators may change the timing of domain‐specific information presentation accordingly. Practitioner notes What is already known about this topic Well‐designed game‐based learning can increase learning. Game‐based learning needs effective instructional design features. What this paper adds One instructional design feature, timing of information presentation, affects motivation and emotion in game‐based learning. Students feel more motivated and enjoyed when domain‐specific information is presented before learning than during learning. This study is one of the first to focus on cognitive, motivational and emotional processes and outcomes, and their interconnections. Implications for practice and policy Educators would do well to present domain‐specific information before learning than during learning. Researchers on instructional design features should attend to all cognitive, motivational and emotional processes and outcomes instead of just one or two. What is already known about this topic Well‐designed game‐based learning can increase learning. Game‐based learning needs effective instructional design features. What this paper adds One instructional design feature, timing of information presentation, affects motivation and emotion in game‐based learning. Students feel more motivated and enjoyed when domain‐specific information is presented before learning than during learning. This study is one of the first to focus on cognitive, motivational and emotional processes and outcomes, and their interconnections. Implications for practice and policy Educators would do well to present domain‐specific information before learning than during learning. Researchers on instructional design features should attend to all cognitive, motivational and emotional processes and outcomes instead of just one or two. [ABSTRACT FROM AUTHOR]

Spatial thinking is essential for nurturing spatially literate graduates in tertiary education. However, there is limited research on individual differences in cognitive processes and their impact on spatial problem solving in disciplinary contexts. This study aimed to investigate cognitive processes involved in spatial thinking in geography majors using a web‐based geographic information systems (GIS) mapping tool. The results revealed three clusters characterised by distinctive cognitive processes: spatial analytic, spatial diagrammatic and alternative. Each cluster adopted unique spatial strategies to solve problems with web‐based GIS. Notably, spatial analytic learners demonstrated the most optimal profile, resulting in high spatial task performance. These findings have implications for maximising students' learning potential in spatial thinking in the tertiary classroom, optimising performance outcomes in spatial problem solving and building intelligent tutoring systems for adaptive learning. Practitioner notes What is already known about this topic There are individual differences in spatial reasoning. The processes of spatial thinking may have an impact on learners' spatial performance outcomes. What this paper adds Three clusters characterised by distinctive processes of spatial thinking were identified: spatial analytic, spatial diagrammatic and alternative. Each cluster adopted unique spatial strategies to solve problems with web‐based GIS. Spatial analytic learners demonstrated the optimal profile, resulting in high‐level spatial performance, whereas alternative learners exhibited the maladaptive profile, which was associated with low task outcomes. Implications for practice and/or policy Web‐based GIS mapping tools make it possible to track the processes of spatial thinking that have remained largely unexplored. Cluster analysis and lag sequential analysis reveal differences in spatial reasoning, aiding educators in maximising the potential for university students to learn spatial thinking and optimising performance outcomes in spatial problem solving. Our findings could inform learning technology designers to build adaptive learning applications in which students receive automatic feedback and tailored support while completing spatial tasks at their own pace. What is already known about this topic There are individual differences in spatial reasoning. The processes of spatial thinking may have an impact on learners' spatial performance outcomes. What this paper adds Three clusters characterised by distinctive processes of spatial thinking were identified: spatial analytic, spatial diagrammatic and alternative. Each cluster adopted unique spatial strategies to solve problems with web‐based GIS. Spatial analytic learners demonstrated the optimal profile, resulting in high‐level spatial performance, whereas alternative learners exhibited the maladaptive profile, which was associated with low task outcomes. Implications for practice and/or policy Web‐based GIS mapping tools make it possible to track the processes of spatial thinking that have remained largely unexplored. Cluster analysis and lag sequential analysis reveal differences in spatial reasoning, aiding educators in maximising the potential for university students to learn spatial thinking and optimising performance outcomes in spatial problem solving. Our findings could inform learning technology designers to build adaptive learning applications in which students receive automatic feedback and tailored support while completing spatial tasks at their own pace. [ABSTRACT FROM AUTHOR]

Conversational user interfaces (CUI), including voice interfaces, which allow users to converse with computers via voice, are gaining wide popularity. VoiceBots allow users to receive a response in real‐time, regardless of the communication device. VoiceBots have been explored in fields such as customer service to automate repetitive queries and help reduce redundant tasks; however, they have not been widely applied in the classroom. This study aimed to explore the effects of VoiceBot implementation on student learning. A pre‐test–post‐test design was implemented with 65 participating undergraduate students in multimedia programming who were randomly allocated to scenarios representing a 2 × 2 design (experimental and control cohorts). Data were collected using an academic achievement test and semi‐structured interviews, which allowed for a more in‐depth analysis of the students' experiences with the VoiceBot. The results showed that how the VoiceBot was applied positively influenced student learning in the experimental cohort. Moreover, the focus group data demonstrated that the VoiceBot can be a valuable assistant for students and could be easily replicated in other courses. To the best of our knowledge, this study was the first to use VoiceBot to engage undergraduate students in Ghana, thus contributing to the growing literature stream on the development of VoiceBots to improve student learning experiences. This study elucidates the design process using a zero‐coding technique, which is considered a suitable approach for educational institutions with limited resources. Practitioner notes What is already known about this topic Conversational user interfaces (CUIs), including voice interfaces, have gained popularity and are used to interact with computers through natural language. VoiceBots have been utilised in various fields such as customer service to automate tasks and reduce redundancy. Instant messaging systems such as WhatsApp and Telegram have been used for communication in educational contexts. Advances in artificial intelligence (AI) and natural language processing (NLP) have led to significant improvements in voice‐enabled CUIs (VoiceBots). Existing studies indicate that chatbots affect students' motivation, learning experiences, and achievements; however, research on using VoiceBots for learning improvement is limited. What this paper adds A VoiceBot was introduced as an assistant to facilitate learning in a multimedia programming course. The study used an experimental design with an experimental cohort using a WhatsApp group platform equipped with a zero‐coding VoiceBot and a control cohort without the bot. The study found that students interacting with VoiceBot demonstrated better learning achievement than the control group. The study also provides clear suggestions on integrating VoiceBots into educational institutions. Implications for practice and/or policy The study's findings suggest that VoiceBots can play a significant role in improving student learning achievements, especially in subjects such as multimedia programming. Educational institutions could establish learning design and technology centres with subject matter experts to integrate VoiceBots effectively into the learning process. Instructors must possess adequate technological proficiency to engage students with VoiceBots and targeted in‐service training may be necessary. Future research can explore VoiceBot use across various academic domains and levels of education, analyse the impact of usage patterns on learning outcomes, and assess its long‐term effects on student engagement and motivation. What is already known about this topic Conversational user interfaces (CUIs), including voice interfaces, have gained popularity and are used to interact with computers through natural language. VoiceBots have been utilised in various fields such as customer service to automate tasks and reduce redundancy. Instant messaging systems such as WhatsApp and Telegram have been used for communication in educational contexts. Advances in artificial intelligence (AI) and natural language processing (NLP) have led to significant improvements in voice‐enabled CUIs (VoiceBots). Existing studies indicate that chatbots affect students' motivation, learning experiences, and achievements; however, research on using VoiceBots for learning improvement is limited. What this paper adds A VoiceBot was introduced as an assistant to facilitate learning in a multimedia programming course. The study used an experimental design with an experimental cohort using a WhatsApp group platform equipped with a zero‐coding VoiceBot and a control cohort without the bot. The study found that students interacting with VoiceBot demonstrated better learning achievement than the control group. The study also provides clear suggestions on integrating VoiceBots into educational institutions. Implications for practice and/or policy The study's findings suggest that VoiceBots can play a significant role in improving student learning achievements, especially in subjects such as multimedia programming. Educational institutions could establish learning design and technology centres with subject matter experts to integrate VoiceBots effectively into the learning process. Instructors must possess adequate technological proficiency to engage students with VoiceBots and targeted in‐service training may be necessary. Future research can explore VoiceBot use across various academic domains and levels of education, analyse the impact of usage patterns on learning outcomes, and assess its long‐term effects on student engagement and motivation. [ABSTRACT FROM AUTHOR]

Self‐regulated learning (SRL) is an essential skill to achieve one's learning goals. This is particularly true for online learning environments (OLEs) where the support system is often limited compared to a traditional classroom setting. Likewise, existing research has found that learners often struggle to adapt their behaviour to the self‐regulatory demands of OLEs. Even so, existing SRL analysis tools have limited utility for real‐time or individualised support of a learner's SRL strategy during a study session. Accordingly, we explore a reinforcement learning based approach to learning optimal SRL strategies for a specific learning task. Specifically, we utilise the sequences of SRL processes acted by 44 participants, and their assessment scores for a prescribed learning task, in a purpose‐built OLE to develop a long short‐term memory (LSTM) network based reward function. This is used to train a reinforcement learning agent to find the optimal sequence of SRL processes for the learning task. Our findings indicate that the developed agents were able to effectively select SRL processes so as to maximise a prescribed learning goal as measured by predicted assessment score and predicted knowledge gains. The contributions of this work will facilitate the development of a tool which can detect sub‐optimal SRL strategy in real‐time and enable individualised SRL focused scaffolding. Practitioner notesWhat is already known about this topic Learners often fail to adequately adapt their behavior to the self‐regulatory demands of e‐Learning environments.In order to promote effective Self‐regulated learning (SRL) capabilities, researchers and educators need tools that are able to analyze and diagnose a learner's SRL strategy use.Current methods for SRL analysis are more often descriptive as opposed to prescriptive and have limited utility for real‐time analysis or support of a learner's SRL behavior.What this paper adds This paper proposes the use of Reinforcement Learning for prescriptive analytics of SRL. We train a Reinforcement Learning agent on sequences of SRL processes acted by learners in order to learn the optimal SRL strategy for a given learning task.Implications for practice and/or policy Our work will facilitate the development of a tool which can detect sub‐optimal SRL strategy in real‐time and enable individualized SRL focused scaffolding.The implications of our work can aid in course design by predicting the self‐regulatory load imposed by a given task.The ability to model SRL strategies using Reinforcement Learning can be extended to simulate or test SRL theories. [ABSTRACT FROM AUTHOR]

A core focus of self‐regulated learning (SRL) research lies in uncovering methods to empower learners within digital learning environments. As digital technologies continue to evolve during the current hype of artificial intelligence (AI) in education, the theoretical, empirical and methodological nuances to support SRL are emerging and offering new ways for adaptive support and guidance for learners. Such affordances offer a unique opportunity for personalised learning experiences, including adaptive interventions. Exploring the application of adaptivity to enhance SRL is an important and emerging area of research that requires further attention. This editorial introduces the contributions of seven papers for the special section on adaptive support for SRL within digital learning environments. These papers explore various themes related to enhancing SRL strategies through technological interventions, offering valuable insights and paving the way for future advancements in this dynamic area. [ABSTRACT FROM AUTHOR]

In recent years, AI technologies have been developed to promote students' self‐regulated learning (SRL) and proactive learning in digital learning environments. This paper discusses a comparative study between generative AI‐based (SRLbot) and rule‐based AI chatbots (Nemobot) in a 3‐week science learning experience with 74 Secondary 4 students in Hong Kong. The experimental group used SRLbot to maintain a regular study habit and facilitate their SRL, while the control group utilized rule‐based AI chatbots. Results showed that SRLbot effectively enhanced students' science knowledge, behavioural engagement and motivation. Quantile regression analysis indicated that the number of interactions significantly predicted variations in SRL. Students appreciated the personalized recommendations and flexibility of SRLbot, which adjusted responses based on their specific learning and SRL scenarios. The ChatGPT‐enhanced instructional design reduced learning anxiety and promoted learning performance, motivation and sustained learning habits. Students' feedback on learning challenges, psychological support and self‐regulation behaviours provided insights into their progress and experience with this technology. SRLbot's adaptability and personalized approach distinguished it from rule‐based chatbots. The findings offer valuable evidence for AI developers and educators to consider generative AI settings and chatbot design, facilitating greater success in online science learning. Practitioner notesWhat is already known about this topic AI technologies have been used to support student self‐regulated learning (SRL) across subjects.SRL has been identified as an important aspect of student learning that can be developed through technological support.Generative AI technologies like ChatGPT have shown potential for enhancing student learning by providing personalized guidance and feedback.What this paper adds This paper reports on a case study that specifically examines the effectiveness of ChatGPT in promoting SRL among secondary students.The study provides evidence that ChatGPT can enhance students' science knowledge, motivation and SRL compared to a rule‐based AI chatbot.The study offers insights into how ChatGPT can be used as a tool to facilitate SRL and promote sustained learning habits.Implications for practice and/or policy The findings of this study suggest that educators should consider the potential of ChatGPT and other generative AI technologies to support student learning and SRL.Educators and students should be aware of the limitations of AI technologies and ensure that they are used appropriately to generate desired responses.It is also important to equip teachers and students with AI competencies to enable them to use AI for learning and teaching. [ABSTRACT FROM AUTHOR]

Effective collaboration and teamwork skills are critical in high‐risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real‐world scenarios, enabling students to safely improve their teamwork abilities. In such learning environments, multiple dialogue segments can occur concurrently as students independently organise themselves to tackle tasks in parallel across diverse spatial locations. This complex situation creates challenges for educators in assessing teamwork and for students in reflecting on their performance, especially considering the importance of effective communication in embodied teamwork. To address this, we propose an automated approach for generating teamwork analytics based on spatial and speech data. We illustrate this approach within a dynamic, immersive healthcare learning environment centred on embodied teamwork. Moreover, we evaluated whether the automated approach can produce transcriptions and epistemic networks of spatially distributed dialogue segments with a quality comparable to those generated manually for research objectives. This paper makes two key contributions: (1) it proposes an approach that integrates automated speech recognition and natural language processing techniques to automate the transcription and coding of team communication and generate analytics; and (2) it provides analyses of the errors in outputs generated by those techniques, offering insights for researchers and practitioners involved in the design of similar systems.Practitioner notesWhat is currently known about this topic Immersive learning environments simulate real‐world situations, helping students improve their teamwork skills.In these settings, students can have multiple simultaneous conversations while working together on tasks at different physical locations.The dynamic nature of these interactions makes it hard for teachers to assess teamwork and communication and for students to reflect on their performance.What this paper adds We propose a method that employs multimodal learning analytics for automatically generating teamwork‐related insights into the content of student conversations.This data processing method allows for automatically transcribing and coding spatially distributed dialogue segments generated from students working in teams in an immersive learning environment and enables downstream analysis.This approach uses spatial analytics, natural language processing and automated speech recognition techniques.Implications for practitioners Automated coding of dialogue segments among team members can help create analytical tools to assist in evaluating and reflecting on teamwork.By analysing spatial and speech data, it is possible to apply learning analytics advancements to support teaching and learning in fast‐paced physical learning spaces where students can freely engage with one another. [ABSTRACT FROM AUTHOR]

Adaptive learning technologies are closely related to learners' self‐regulatory processes in individual and collaborative learning. This study presents the outcomes of a systematic literature review of empirical evidence on adaptive learning environments to foster self‐regulation and shared regulation of learning in collaborative settings. We provide an overview of what and how adaptive technologies have been used to understand and promote self‐regulated learning in collaborative contexts. A search resulted in 38 papers being analysed. Specifically, we identified the seven main objectives (feedback and scaffolding, self‐regulatory skills and strategies, learning trajectories, collaborative learning processes, adaptation and regulation, self‐assessment, and help‐seeking behaviour) that the adaptive technology research has been focusing on. We also summarize the implications derived from the reviewed papers and frame them within seven thematic areas. Finally, this review stresses that future research should consider developing a converging theoretical framework that would enable concrete monitoring and support for self‐regulation and socially shared regulation of learning. Our findings set a baseline to support the adoption and proliferation of adaptive learning technology within self‐regulated learning research and development. Practitioner notesWhat is already known about this topic By providing personalized and learner‐centric adaptive learning environments (ADLEs), adaptive learning technology can support and foster self‐regulated learning (SRL) practices.It is possible to create a more student‐centred and effective learning environment by combining adaptive learning and collaborative learning.Socially shared regulatory activities can involve planning, monitoring, controlling and reflecting on a group's learning processes.What this paper adds Provides a systematic literature review of empirical evidence on ADLEs, SRL and socially shared regulation of learning (SSRL) in collaborative contexts.Summarizes the insights on (S)SRL through ADLEs in collaborative learning.Identifies challenges and opportunities for ADLEs to support (S)SRL in collaborative learning.Implications for practice and/or policy Learning analytics and educational technology researchers will be able to use the systematic review as a guide for future research.Learning analytics and educational technology practitioners will be able to use the systematic review as a summary of the field's current state. [ABSTRACT FROM AUTHOR]

Educational podcasts have become an increasingly prevalent media used to disseminate profession‐specific information through easily accessible means. Despite the potential of educational podcasts as convenient and effective medium, there is a dearth of literature dedicated to the topic. Thus, using the Uses and Gratification framework, the psychometric properties of the Educational Podcasts Motivation Scale were examined, as well as the motivational factors that influence intention to listen to educational podcasts and recommend podcasts to others were explored. A sample of individuals in the field of education (n = 606), such as in‐service K‐12 teachers and higher education professors, were recruited for this study. This sample were randomly divided, and an exploratory factor analysis (EFA) was conducted with the first set (n = 312) to identify underlying constructs, and confirmatory factor analysis (CFA) and structural equation modelling (SEM) were employed with the second set (n = 294). The scale demonstrated strong psychometric properties and five distinct motivational factors were identified: Information Gathering, Flexibility in Use, Social Interaction, Entertainment, and Professional Encouragement. Several motivational factors had significant associations with the constructs of "intention" and "word‐of‐mouth". This paper demonstrates both the unique motivational factors related to listening to educational podcasts and the motivational factors that overlap with other forms of media. Further examination of the underlying motivations to listen to educational podcasts is warranted. Practitioner notesWhat is already known about this topic Educational podcasts have become an increasingly prevalent media used to disseminate information to specific professions and fields that provide current practices and research information through easily accessible means.Educational podcasts have been found to be an effective tool to improve self‐efficacy and knowledge around topics with educators and college students, as well as a means to develop communities of practice where educators share knowledge and experiences.Results of studies using the uses and gratifications framework to examine the gratifications for listening to podcasts have found an array of overlapping, and sometimes conflicting, gratifications from the use of podcasts. Those most often identified include entertainment, multitasking and convenience, social interaction, escapism and educational purposes.What this paper adds This paper outlined the development of the Educational Podcasts Motivation Scale and used an exploratory factor analysis, confirmatory factor analysis and structural equation modelling to demonstrate its strong psychometric properties.Five distinct motivational factors for why educators engage with educational podcasts were identified: (a) Information Gathering, (b) Flexibility in Use, (c) Social Interaction, (d) Entertainment and (e) Professional Encouragement.This paper identifies that educators are often most motivated to listen to educational podcasts due to constructs such as social interaction, flexibility in use and information gathering.Implications for practice and/or policy The findings in this paper demonstrate the perceived benefits and uses of educational podcasts as a learning tool, further establishing educational podcasts as a useful tool that should be incorporated into learning environments.The findings in this paper indicate that those embedding educational podcasts within learning activities and professional development should consider how to emphasise the flexibility, social interactions and learning aspects of these tools to promote the attractive features of this tool.Although this study sheds light on the reasons those in the field of education use this medium, additional research is needed to explore how and why these individuals engage with educational podcasts. [ABSTRACT FROM AUTHOR]

Training to run is not straightforward since without proper personalised supervision and planning, people will not improve their performance and will increase the risk of injuries. This study aims to identify the different factors that influence running training programmes, examining the benefits, challenges or limitations of personalised plans. Moreover, this study explores how multimodal, immersive and artificial intelligence technologies can support personalised training. We conducted an exploratory sequential mixed research consisting of interviews with 11 running coaches from different countries and a survey of 12 running coaches. Based on the interviews and survey analysis, we identified and extracted relevant factors of the training process. We identified four relevant aspects for running training: physical, technical, mental and body awareness. Using these aspects as a reference, we derived a framework using a bottom‐up approach. This framework proposes multimodal, immersive and artificial intelligence technologies to facilitate personalised running training. It also allows coaches to personally guide their athletes on each aspect. Practitioner notesWhat is already known about this topic Running is a popular sport that provides health benefits and is practised by many people around the world.Training is a process that enables athletes to improve their development in various aspects of their sport; in the case of running, it helps them to increase their speed and endurance.Personalised training supports the needs and abilities of athletes, by helping them to achieve their potential through individualised activities or programmes.Sports science research indicates that personalised training can be improved by applying technology to tackle its challenges and limitations.What this paper adds We show that personalising the training requires not only focusing on the runners' physical condition but also on their mental, technical and body awareness aspects, where each of them has a different adaptation to training.We show that multimodal and immersive technologies offer suitable and portable ways to measure and target the mental and body awareness aspects during running training.Implications for practice and/or policy This paper presents a list of factors, measures and devices that coaches can use to plan and design their training sessions in a more personalised manner.This study can serve as a foundation for future research that aims to identify and target the various factors that influence the learning and training of sports. [ABSTRACT FROM AUTHOR]

The paper argues that learning analytics as a research field can benefit from a theory‐informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent descriptions of sensemaking, eclectically combining the paradigms that have underlying differences. I then propose a conceptualization of sensemaking that overcomes the differences between these theories and explains how the concepts of activity system, the definition of the situation and affordances can be used to capture individual differences in sensemaking. The paper concludes with a preliminary framework and examples demonstrating its utility in raising new theoretical questions, informing design principles and providing shared language for researchers in learning analytics.Practitioner notesWhat is already known about this topicSensemaking happens when individuals try to explain unknown situations.Learning analytics uses sensemaking as a lens to understand dashboard use.Systematic analysis of sensemaking is essential for learning analytics.What this paper addsThe paper notes that noticing and perceiving are commonly examined in learning analytics on dashboard use.The paper suggests a revision of fundamental assumptions in sensemaking.A paper proposes a toy model of sensemaking that includes operationalization of the definition of the situation, activity where sensemaking happens and processes of noticing and perceiving affordances.Implications for practice and/or policyLearning analytics must examine sensemaking of data about teaching and learning in a systematic manner.Internal perceptions of the social environment and activity that are informed by the data need to be considered in evaluating dashboard use. [ABSTRACT FROM AUTHOR]

Previous research showed that the parents acknowledged the technology's benefits for their young children's learning, however, they are still worried about the extended screen time, lack of physical activity and lack of social interactions. To address these concerns, we developed Kid Space to enable pedagogically appropriate technology use for children in early childhood education by combining various sensing technologies with a multi‐modal conversational artificial intelligence system that can interact with children, understand individual progress and provide personalised learning experiences. To understand the impact of Kid Space on the parents' initial concerns about technology use by their young children, we conducted a multi‐method user study: (1) a quasi‐experimental design and (2) formative research method using an exploratory case study with a set of children and their parents experiencing Kid Space in their homes. The results show that after experiencing Kid Space with their children, the parents felt significantly less concerned about screen time, social interactions and physical activity and reported positive perceptions towards pedagogical value of Kid Space. Detailed analysis on the multi‐modal data quantitatively and qualitatively validated why Kid Space alleviated these concerns. Future research is needed to validate long‐term educational value of Kid Space and generate insights for improvement for next iterations. Practitioner notesWhat is already known about this topic Play‐based learning is critical for young children's education, but digital games create major concerns around extended screen time, lack of physical activity and lack of social interactions.Blending digital and physical spaces could support pedagogically appropriate technology use for young children. Towards this end, there are some exemplary studies in the state–of‐the‐art reporting positive educational outcomes as an effect of utilising such spaces. However, none of these studies supported children's most natural mode of communication in their interactions with the systems—speaking.Pedagogical conversational agents (PCAs) are promising, but they are tricky when it comes to young children's speech because of unique technical challenges resulted from how children use language and communicate with digital systems.What this paper adds To our best knowledge, Kid Space is one of the earliest implementations of a PCA with a multi‐modal artificial intelligence (AI) system utilising physical and digital learning manipulatives for maths learning with a focus on early childhood education. The key contributions of this paper are (1) the design and development of an end‐to‐end multi‐modal system enabling Wizard‐of‐Oz experimentation for initial evaluations with users, (2) the creation of a multi‐modal, in‐the‐wild labelled dataset with children–agent, children–parent and children–physical/digital space interactions enabling advancements for AI components for later evaluations with users and (3) the generation of rich insights from an initial research study on user perceptions and engagement as well as actionable findings to improve Kid Space experiences for next iterations and inform key design features for similar systems.Implications for practice and/or policy The results of the study implied a set of areas for improvement—or design features—for Kid Space and other similar pedagogical conversational systems developed for children's home usages: (1) easier setup and usage with optimised setup size addressing diverse space limitations at homes, (2) minimised latency between Oscar (the conversational pedagogical agent) and child interactions (eg, adding multimodal dialogue system to reduce the need for a human wizard), (3) more advanced personalisation, social (including more verbal interactions) and pedagogical skills for Oscar with increased contextual awareness (eg, sending children's engagement), (4) scalability and higher visual quality of content with diverse games and learning outcomes, (5) parental control features over Kid Space platform and Oscar (eg, time limit, content, etc.) and (6) accessibility features (eg, captions turned on for multilingual children) and support for neurodiversity. [ABSTRACT FROM AUTHOR]

This study investigated the seamless mobile learning practices of UK government workers at various life stages, to understand how context impacted decisions about how, when and where learning was undertaken. Following Hedegaard, the context was understood as involving settings embedded within institutions. Drawing on analysis of data from public domain blogs and reports and anonymised trace data showing e‐learning visits via a mobile device, a picture of institutional practice and values was developed. Against this backdrop, a survey of 50 individuals followed by semi‐structured interviews provided information about seamless mobile learning projects. Mobile learning was often fragmented and ad hoc, rather than part of a longer, seamless learning project. A distinction between just‐in‐time learning and just‐in‐case learning was apparent, with the latter often postponed. For mobile workers, mobile learning focused on current work setting, whereas workers who could work in many interchangeable settings might move to somewhere they could concentrate. Mobile learning was sometimes motivated by a sense of a lack of time and a need to stay 'on top of things' as much as by interest in a topic. Sustained seamless mobile learning projects occurred if there was institutional support for learning that was also of individual interest and if learners had the ability to orchestrate their learning. Learners reported these seamless mobile learning projects to be enjoyable and compelling. This paper contributes to the evidence of seamless mobile learning practice over the life course and illustrates the value of considering an individual's relation to various institutions in conceptualisations of seamless mobile learning. It also offers pointers for the future design of seamless mobile learning tools including a need to offer learners the opportunity to sometimes separate ongoing learning which is related to distinct institutions.Practitioner notesWhat is already known about this topicMobile devices accompany their owners across settings that were previously considered separate, such as work, college and households.This has the potential to impact work/home and other boundaries.From a pedagogical perspective, mobile devices may support seamless learning, in which experiences across distinct settings result in a holistic and unified understanding.What this paper addsIt introduces the concept of the institution to conceptions of seamless learning.It illustrates the ways in which different institutions (workplaces or educational institutions) can shape individual experiences and decisions about when and where to learn.It provides evidence that some working adults engage in seamless learning projects and describe this as compelling and enjoyable, but that others prefer to separate distinct life spheres.Implications for practice and/or policyThere may be value in institutions and designers supporting people who want to engage in seamless mobile learning.However, it is important to be aware that not everyone wants to engage in seamless learning.Seamless learning is more likely to occur when individual and institutional priorities are aligned across several institutions, so there will be challenges for a single institution seeking to promote it. [ABSTRACT FROM AUTHOR]

Multimodal learning analytics (MMLA) research has made significant progress in modelling collaboration quality for the purpose of understanding collaboration behaviour and building automated collaboration estimation models. Deploying these automated models in authentic classroom scenarios, however, remains a challenge. This paper presents findings from an evaluation of collaboration quality estimation models. We collected audio, video and log data from two different Estonian schools. These data were used in different combinations to build collaboration estimation models and then assessed across different subjects, different types of activities (collaborative‐writing, group‐discussion) and different schools. Our results suggest that the automated collaboration model can generalize to the context of different schools but with a 25% degradation in balanced accuracy (from 82% to 57%). Moreover, the results also indicate that multimodality brings more performance improvement in the case of group‐discussion‐based activities than collaborative‐writing‐based activities. Further, our results suggest that the video data could be an alternative for understanding collaboration in authentic settings where higher‐quality audio data cannot be collected due to contextual factors. The findings have implications for building automated collaboration estimation systems to assist teachers with monitoring their collaborative classrooms. Practitioners notesWhat is already known about this topicMultimodal learning analytics researchers have established several features as potential indicators for collaboration quality, e.g., speaking time or joint visual attention.The current state of the art has shown the feasibility of building automated collaboration quality models.Recent research has provided preliminary evidence of the generalizability of developed automated models across contexts different in terms of given task and subject.What does this paper addThis paper offers collaboration indicators for different types of collaborative learning activities in authentic classroom settings.The paper includes a systematic investigation into collaboration quality automated model's generalizability across different tasks, types of tasks and schools.This paper also offers a comparison between different modalities' potential to estimate collaboration quality in authentic settings.Implications for practiceThe findings inform the development of automated collaboration monitoring systems for authentic classroom settings.This paper provides evidence on across‐school generalizability capabilities of collaboration quality estimation models. [ABSTRACT FROM AUTHOR]

This research employs the fuzzy‐set qualitative comparative analysis (fsQCA) method to investigate the configurations of multiple factors influencing scientific concept learning, including augmented reality (AR) technology, the concept map (CM) strategy and individual differences (eg, prior knowledge, experience and attitudes). A quasi‐experiment was conducted with 194 seventh‐grade students divided into four groups: AR and CM (N = 52), AR and non‐CM (N = 51), non‐AR and CM (N = 40), non‐AR and non‐CM (N = 51). These students participated in a science lesson on ‘The structure of peach blossom’. This study represents students' science learning outcomes by measuring their academic performance and cognitive load. The fsQCA results reveal that: (1) factors influencing students' academic performance and cognitive load are interdependent, and a single factor cannot constitute a necessary condition for learning outcomes; (2) multiple pathways can lead to the same learning outcome, challenging the notion of a singular best path derived from traditional analysis methods; (3) the configurations of good and poor learning outcomes exhibit asymmetry. For example, high prior knowledge exists in both configurations leading to good and poor learning outcomes, depending on how other conditions are combined. Practitioner notes What is already known about this topic Augmented reality proves to be a useful technological tool for improving science learning. The concept map can guide students to describe the relationships between concepts and make a connection between new knowledge and existing knowledge structures. Individual differences have been emphasized as essential external factors in controlling the effectiveness of learning. What this paper adds This study innovatively employed the fsQCA analysis method to reveal the complex phenomenon of the scientific concept learning process at a fine‐grained level. This study discussed how individual differences interact with AR and concept map strategy to influence scientific concept learning. Implications for practice and/or policy No single factor present or absent is necessary for learning outcomes, but the combinations of AR and concept map strategy always obtain satisfactory learning outcomes. There are multiple pathways to achieving good learning outcomes rather than a single optimal solution. The implementation of educational interventions should fully consider students' individual differences, such as prior knowledge, experience and attitudes. What is already known about this topic Augmented reality proves to be a useful technological tool for improving science learning. The concept map can guide students to describe the relationships between concepts and make a connection between new knowledge and existing knowledge structures. Individual differences have been emphasized as essential external factors in controlling the effectiveness of learning. What this paper adds This study innovatively employed the fsQCA analysis method to reveal the complex phenomenon of the scientific concept learning process at a fine‐grained level. This study discussed how individual differences interact with AR and concept map strategy to influence scientific concept learning. Implications for practice and/or policy No single factor present or absent is necessary for learning outcomes, but the combinations of AR and concept map strategy always obtain satisfactory learning outcomes. There are multiple pathways to achieving good learning outcomes rather than a single optimal solution. The implementation of educational interventions should fully consider students' individual differences, such as prior knowledge, experience and attitudes. [ABSTRACT FROM AUTHOR]

Teachers who know what, how and why to teach are essential for successful student learning. However, many preservice teachers (PSTs) lack teaching experience and the ability to integrate theory and practice. To help bridge this gap, this study employed a learning‐by‐design project approach in which 22 Korean PSTs developed lesson plans for middle school English classes, constructed virtual classrooms in the metaverse based on their English lesson plans, and conducted microteaching in the virtual classrooms. The study used a qualitative research method and focused on an emic perspective with multiple data sets, including the PSTs' reflection papers and post‐interviews as primary data, and their lesson plans, virtual classrooms and recordings of microteaching as secondary data. The results showed that the project supported learning by design, and that it also helped PSTs understand learners and learning, redefine the teacher's role as a designer and facilitator, connect theories to practice and improve their teaching skills. The findings can be used as a reference for future teacher training. Practitioner notes What is already known about this topic Teachers' content, pedagogical and technological knowledge and skills are essential attributes for effective performance. Preservice teachers (PSTs) have difficulty transferring their knowledge to real classrooms because their knowledge often focuses on the ‘know‐what’ of teaching, but not on the ‘know‐how’. Microteaching in virtual environments helps PSTs connect knowledge and practice and prepare for real classroom situations. What this paper adds The study applied a learning‐by‐design approach to preservice teachers' microteaching to help them connect their pedagogical knowledge to classroom practice. The study focused on describing how the PSTs' virtual classroom design influenced the way they planned and implemented their microteaching. Implications for practice and/or policy Teacher educators can incorporate the design‐based approach into their teacher training modules to help teachers understand learner needs when planning and implementing English lessons. Teachers can develop technological literacy and positive attitudes about using technology in their classrooms. What is already known about this topic Teachers' content, pedagogical and technological knowledge and skills are essential attributes for effective performance. Preservice teachers (PSTs) have difficulty transferring their knowledge to real classrooms because their knowledge often focuses on the ‘know‐what’ of teaching, but not on the ‘know‐how’. Microteaching in virtual environments helps PSTs connect knowledge and practice and prepare for real classroom situations. What this paper adds The study applied a learning‐by‐design approach to preservice teachers' microteaching to help them connect their pedagogical knowledge to classroom practice. The study focused on describing how the PSTs' virtual classroom design influenced the way they planned and implemented their microteaching. Implications for practice and/or policy Teacher educators can incorporate the design‐based approach into their teacher training modules to help teachers understand learner needs when planning and implementing English lessons. Teachers can develop technological literacy and positive attitudes about using technology in their classrooms. [ABSTRACT FROM AUTHOR]

Video‐based learning (VBL) is popular, yet students tend to learn video material passively. Instilling teaching expectancy is a strategy to promote active processing by learners, but it is unclear how effective it will be in improving VBL. This study examined the role of teaching expectancy on VBL by comparing the learning outcomes and metacognitive monitoring of 94 learners with different expectancies (teaching, test or no expectancy). Results showed that the teaching expectancy group had better learning outcomes and no significant difference in the metacognitive monitoring of three groups. We further explored the visual behaviour patterns of learners with different expectancies by using the indicator of eye‐movement synchronization. It was found that synchronization was significantly lower in both the teaching and test expectancy groups than in the no expectancy group, and the test expectancy group was significantly lower than the teaching expectancy group. This result suggests that both teaching and test expectancy enhance the active processing of VBL. However, by sliding window analysis, we found that the teaching expectancy group used a flexible and planned attention allocation. Our findings confirmed the effectiveness of teaching expectancy in VBL. Also, this study provided evidence for the applicability of eye‐tracking techniques to assess VBL. Practitioner notes What is already known about this topic Video‐based learning has become a popular way, yet students tend to learn video material passively. When students learn with teaching expectancy, they are more likely to engage in deep processing, which has been proven in static multimedia learning. Individuals show high eye‐movement synchronization when watching the same video, and this synchronization may be reduced when they engage in top‐down processing. What this paper adds Teaching expectancy improves learning performance in Video‐based learning. Teaching expectancy enhances active cognitive processing in Video‐based learning. During the video viewing, learners with teaching expectancy not only followed the instructor's explanations but also engaged in active top‐down processing, demonstrating flexible and planned attention allocation. Implications for practice and/or policy Utilizing teaching as an intention can serve as an effective learning strategy for Video‐based learning. The use of eye‐movement intersubject correlation to analyse visual behaviour patterns provides a new way to explore how people learn from dynamic multimedia materials. What is already known about this topic Video‐based learning has become a popular way, yet students tend to learn video material passively. When students learn with teaching expectancy, they are more likely to engage in deep processing, which has been proven in static multimedia learning. Individuals show high eye‐movement synchronization when watching the same video, and this synchronization may be reduced when they engage in top‐down processing. What this paper adds Teaching expectancy improves learning performance in Video‐based learning. Teaching expectancy enhances active cognitive processing in Video‐based learning. During the video viewing, learners with teaching expectancy not only followed the instructor's explanations but also engaged in active top‐down processing, demonstrating flexible and planned attention allocation. Implications for practice and/or policy Utilizing teaching as an intention can serve as an effective learning strategy for Video‐based learning. The use of eye‐movement intersubject correlation to analyse visual behaviour patterns provides a new way to explore how people learn from dynamic multimedia materials. [ABSTRACT FROM AUTHOR]

This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student essays of varying quality. The grading scale comprised five domains: grammar, content, organization, style & expression and mechanics. The results revealed that fine‐tuned ChatGPT model demonstrated a very high level of reliability with an intraclass correlation (ICC) score of 0.972, Default ChatGPT model exhibited an ICC score of 0.947 and Bard showed a substantial level of reliability with an ICC score of 0.919. Additionally, a significant overlap was observed in certain domains when comparing the grades assigned by LLMs and human raters. In conclusion, the findings suggest that while LLMs demonstrated a notable consistency and potential for grading competency, further fine‐tuning and adjustment are needed for a more nuanced understanding of non‐objective essay criteria. The study not only offers insights into the potential use of LLMs in grading student essays but also highlights the need for continued development and research. Practitioner notes What is already known about this topic Large language models (LLMs), such as OpenAI's ChatGPT and Google's Bard, are known for their ability to generate text that mimics human‐like conversation and writing. LLMs can perform various tasks, including essay grading. Intraclass correlation (ICC) is a statistical measure used to assess the reliability of ratings given by different raters (in this case, EFL instructors and LLMs). What this paper adds The study makes a unique contribution by directly comparing the grading performance of expert EFL instructors with two LLMs—ChatGPT and Bard—using an analytical grading scale. It provides robust empirical evidence showing high reliability of LLMs in grading essays, supported by high ICC scores. It specifically highlights that the overall efficacy of LLMs extends to certain domains of essay grading. Implications for practice and/or policy The findings open up potential new avenues for utilizing LLMs in academic settings, particularly for grading student essays, thereby possibly alleviating workload of educators. The paper's insistence on the need for further fine‐tuning of LLMs underlines the continual interplay between technological advancement and its practical applications. The results lay down a footprint for future research in advancing the use of AI in essay grading. What is already known about this topic Large language models (LLMs), such as OpenAI's ChatGPT and Google's Bard, are known for their ability to generate text that mimics human‐like conversation and writing. LLMs can perform various tasks, including essay grading. Intraclass correlation (ICC) is a statistical measure used to assess the reliability of ratings given by different raters (in this case, EFL instructors and LLMs). What this paper adds The study makes a unique contribution by directly comparing the grading performance of expert EFL instructors with two LLMs—ChatGPT and Bard—using an analytical grading scale. It provides robust empirical evidence showing high reliability of LLMs in grading essays, supported by high ICC scores. It specifically highlights that the overall efficacy of LLMs extends to certain domains of essay grading. Implications for practice and/or policyThe findings open up potential new avenues for utilizing LLMs in academic settings, particularly for grading student essays, thereby possibly alleviating workload of educators.The paper's insistence on the need for further fine‐tuning of LLMs underlines the continual interplay between technological advancement and its practical applications.The results lay down a footprint for future research in advancing the use of AI in essay grading. [ABSTRACT FROM AUTHOR]

Dementia patients may have language barriers and decreased comprehension ability. Their family caregivers can feel frustrated when communicating with them. Poor communication hinders family caregivers from obtaining accurate health information about patients, and may also increase their emotional burden, affecting patient care quality. The present study developed a virtual reality‐based simulated communication training (VRSCT) system and applied it to a training course for family caregivers of dementia patients. It allowed family caregivers to simulate real‐world situations in a VR environment, experience the daily communication barriers and stress with dementia patients, and apply their acquired knowledge and skills to solve related problems. This study used a randomised control experimental design with mixed analysis methods. A total of 63 family caregivers were recruited and randomly divided into the experimental group (N = 32) learning with the VRSCT system to interact with virtual dementia patients and practice communication skills, and the control group (N = 31) using the traditional role‐playing method for practice. Quantitative data were analysed to determine participants' knowledge of dementia care, attitudes, communication confidence and skills. In addition, the qualitative method was used to analyse the participants' discussion records. The results showed that by using the VRSCT approach, participants significantly improved their knowledge of dementia care, attitudes, communication confidence and communication skills compared to the control group. In addition, participants reported that through the real‐time feedback of the VRSCT system, they could recognise their previous incorrect communication approach. As a result, they adjusted their communication strategies and increased their self‐confidence. Practitioner notes What is already known about this topic Situational simulation helps learners improve their communication skills in a safe environment. Virtual reality (VR) creates a realistic, highly interactive learning environment, allowing users to be deeply immersed in the learning experience. What this paper adds This study proposed a VR‐based simulated communication training (VRSCT) approach; moreover, seven dementia cases of different degrees of severity were designed in the VR system to enable family members to experience possible challenges of taking care of dementia patients they might encounter in their daily lives. Each case in the VRSCT system has its unique symptoms and communication barriers. The learner in the story plays a caregiver, experiencing and solving the problems and challenges posed by the system. The experimental results show that the proposed method improves learners' knowledge, attitudes, communication confidence, and communication skills related to dementia care. Implications for practice and/or policy Utilising VR training can amplify awareness and secure enhanced social support for dementia‐related challenges. Using VRSCT, as governments and institutions recognise the effectiveness of VR training, they will provide more resources and promote its widespread application. What is already known about this topic Situational simulation helps learners improve their communication skills in a safe environment. Virtual reality (VR) creates a realistic, highly interactive learning environment, allowing users to be deeply immersed in the learning experience. What this paper adds This study proposed a VR‐based simulated communication training (VRSCT) approach; moreover, seven dementia cases of different degrees of severity were designed in the VR system to enable family members to experience possible challenges of taking care of dementia patients they might encounter in their daily lives. Each case in the VRSCT system has its unique symptoms and communication barriers. The learner in the story plays a caregiver, experiencing and solving the problems and challenges posed by the system. The experimental results show that the proposed method improves learners' knowledge, attitudes, communication confidence, and communication skills related to dementia care. Implications for practice and/or policy Utilising VR training can amplify awareness and secure enhanced social support for dementia‐related challenges. Using VRSCT, as governments and institutions recognise the effectiveness of VR training, they will provide more resources and promote its widespread application. [ABSTRACT FROM AUTHOR]

Universities, significantly impacted by the shift to online learning during pandemic, must critically evaluate their teaching methods and outcomes to enhance performance in the post‐pandemic era. However, there has been a limited examination of whether students achieved comparable levels in cognition and social interaction during the pandemic compared to traditional face‐to‐face learning. Addressing this gap, this exploratory study utilized a quasi‐experimental design to analyse and compare the learning performance and outcomes of two cohorts of students (totalling 45) in a 12‐week university course delivered through the computer‐supported collaborative learning (CSCL) approach, both during and after the pandemic. Employing quantitative analysis and lag sequential analysis, the study examined students' behaviours, similarities and differences in performance within CSCL environments under two distinct social situations. Results indicated that students engaged in complete online learning with CSCL and those in face‐to‐face teaching with CSCL achieved similar levels of conceptual understanding. Additionally, a comparable distribution pattern of learning behaviours was observed. However, significant differences in behaviour sequences emerged between the two implementations, with students exhibiting a higher level of engagement in CSCL activities during the post‐pandemic period. These findings inform the design of CSCL environments should integrate student‐centred activities and include guiding scripts, prompts and scaffoldings in navigating learning endeavours effectively. Practitioner notes What is already known about this topic The CSCL environment could facilitate teacher‐student and student–student interaction in learning activities. Studies have been conducted on the impact of scripts and prompts on students' cognition and social interaction in CSCL environment. There is a crucial need for conducting more in‐depth data analysis to comprehensively explore the CSCL process within university settings. What this paper adds A well‐designed CSCL environment, coupled with effective instructional strategies, exhibits resilience, sustaining its beneficial effects on students' academic performance and interaction. Both cohorts demonstrated a proclivity for engaging in repetitive behaviours, particularly focused on reviewing and reading activities. The latter cohort displayed a preference for individual tasks over collaborative efforts, showcasing a relatively higher frequency of individual work as opposed to group activities. Notably absent in both groups were crucial behavioural sequences, namely VR‐IA and VC‐IA, underscoring potential areas for CSCL improvement. Implications for practice and/or policy In the CSCL environment, a variety of activities rooted in student‐centred pedagogy (ie, self‐regulated learning, inquiry‐based learning and peer feedback) should be seamlessly integrated. It is recommended to furnish students with scripts, prompts and scaffoldings to bolster their navigation through collaborative and independent learning endeavours within CSCL environment. Students are encouraged to bridge their newly acquired knowledge with their existing understanding, for enhancing engagement and promoting deeper comprehension. What is already known about this topic The CSCL environment could facilitate teacher‐student and student–student interaction in learning activities. Studies have been conducted on the impact of scripts and prompts on students' cognition and social interaction in CSCL environment. There is a crucial need for conducting more in‐depth data analysis to comprehensively explore the CSCL process within university settings. What this paper adds A well‐designed CSCL environment, coupled with effective instructional strategies, exhibits resilience, sustaining its beneficial effects on students' academic performance and interaction. Both cohorts demonstrated a proclivity for engaging in repetitive behaviours, particularly focused on reviewing and reading activities. The latter cohort displayed a preference for individual tasks over collaborative efforts, showcasing a relatively higher frequency of individual work as opposed to group activities. Notably absent in both groups were crucial behavioural sequences, namely VR‐IA and VC‐IA, underscoring potential areas for CSCL improvement. Implications for practice and/or policy In the CSCL environment, a variety of activities rooted in student‐centred pedagogy (ie, self‐regulated learning, inquiry‐based learning and peer feedback) should be seamlessly integrated. It is recommended to furnish students with scripts, prompts and scaffoldings to bolster their navigation through collaborative and independent learning endeavours within CSCL environment. Students are encouraged to bridge their newly acquired knowledge with their existing understanding, for enhancing engagement and promoting deeper comprehension. [ABSTRACT FROM AUTHOR]

Authentic dialogue demands that we respond, interpret and sometimes disagree with others' ideas—a key component of participation in a democratic society. Yet the sharing and uptake of different ideas can be hampered by traditional online platforms which divide students into isolated threads. To tackle this issue, we introduce two novel online forums designed to foster engagement and idea exchange: a linear chat, akin to SMS, and a collaborative writing forum we call CREW. Seventy‐three graduate students, divided into 18 small groups, tested these forums. We used discourse analysis to measure idea uptake and other dialogic features. From this analysis, seven discussions emerged as particularly interactive and engaging, exhibiting a high uptake‐to‐turn ratio. We noticed linear chat encouraged a high proportion of uptake, but also produced ‘tangles’—breaks in related post chains. CREW discussions sparked similar engagement but resolved most tangles since they required a collaborative written response. This study offers fresh insights in both research and teaching for improving online discussions. Practitioner notes What is already known about this topic A vital practice for scholarly dialogue and democratic discourse is uptake: building on what others have written or said. Instead of encouraging uptake of others' words and ideas, typical online discussions in Learning Management Systems (LMSs) can inadvertently isolate students in separate threads. What this paper adds We introduce and analyse two new, innovative types of online discussions that may encourage more uptake of others' words and ideas. To eliminate isolation and encourage uptake, a linear chat forum makes all posts visible, but may produce interruptions, or ‘tangles’. A forum that includes collaborative responsive writing requires participants to converge on a collective response, encouraging dialogue and overcoming tangles. Implications for practice/policy Teachers and other stakeholders might consider how discussion forum designs in LMSs can support or limit authentic dialogue. Practitioners might consider how to incorporate deliberation about a shared focus into online discussions. Instructors might avoid tangles by aligning assignment purposes with dialogic principles: posing authentic questions that invite multiple interpretations and require uptake of others' responses. What is already known about this topic A vital practice for scholarly dialogue and democratic discourse is uptake: building on what others have written or said. Instead of encouraging uptake of others' words and ideas, typical online discussions in Learning Management Systems (LMSs) can inadvertently isolate students in separate threads. What this paper adds We introduce and analyse two new, innovative types of online discussions that may encourage more uptake of others' words and ideas. To eliminate isolation and encourage uptake, a linear chat forum makes all posts visible, but may produce interruptions, or ‘tangles’. A forum that includes collaborative responsive writing requires participants to converge on a collective response, encouraging dialogue and overcoming tangles. Implications for practice/policy Teachers and other stakeholders might consider how discussion forum designs in LMSs can support or limit authentic dialogue. Practitioners might consider how to incorporate deliberation about a shared focus into online discussions. Instructors might avoid tangles by aligning assignment purposes with dialogic principles: posing authentic questions that invite multiple interpretations and require uptake of others' responses. [ABSTRACT FROM AUTHOR]

In order for teachers to successfully gain new knowledge during professional development (PD), courses must be of high quality and stimulate active involvement from participants. More and more PD courses are taking place online, without clear evidence of whether face‐to‐face and online courses differ in terms of their quality or level of participants' engagement. The present study investigates differences between face‐to‐face and online PD with respect to certain quality characteristics: clarity and structure, cognitive activation, collaboration and practical relevance, as well as participants' behavioural, cognitive and affective engagement. The study is based on 2210 teachers from Germany who participated in 1 of 137 face‐to‐face or 54 online PD courses. Although participants rated face‐to‐face and online courses very positively regarding all quality characteristics and engagement dimensions, they evaluated online courses slightly less favourably compared to face‐to‐face courses. Implications for practice and research are derived to help ensure high‐quality PD offerings in the future. Practitioner notes What is already known about this topic Face‐to‐face and online PD have the potential to be similarly effective. PD quality and participants' engagement can be assumed to be predictors of PD effectiveness. PD quality contains clarity and structure, cognitive activation, collaboration and practical relevance. Engagement is a three‐dimensional construct composed of behavioural, cognitive and affective components. What this paper adds PD quality was rated very positively for online and face‐to‐face courses. Participants rated the quality of online PD lower compared to face‐to‐face PD. Participants rated their engagement in online PD lower compared to face‐to‐face PD. Implications for practice and/or policy PD format should always be chosen with which a higher benefit can be achieved. Quality assurance should take place before PD is conducted. What is already known about this topic Face‐to‐face and online PD have the potential to be similarly effective. PD quality and participants' engagement can be assumed to be predictors of PD effectiveness. PD quality contains clarity and structure, cognitive activation, collaboration and practical relevance. Engagement is a three‐dimensional construct composed of behavioural, cognitive and affective components. What this paper adds PD quality was rated very positively for online and face‐to‐face courses. Participants rated the quality of online PD lower compared to face‐to‐face PD. Participants rated their engagement in online PD lower compared to face‐to‐face PD. Implications for practice and/or policy PD format should always be chosen with which a higher benefit can be achieved. Quality assurance should take place before PD is conducted. [ABSTRACT FROM AUTHOR]

Teaching and learning in higher education have increasingly become digitalized and associated with innovative pedagogical methodologies over the past decades. Following the sudden onset of the pandemic in March 2020, several studies tended to focus on traditional students' experiences with emergency remote education while literature is scarce on non‐traditional students (or adult learners) pedagogical experiences in Distance Education contexts. Using a qualitative case study approach, this study explored how digital technologies mediated instructors' and adult learners' educational experiences during COVID‐19 and their first‐time experiences with blended learning. Between October 2021 and July 2022, semi‐structured interviews were conducted with 40 adult learners and 20 instructors in three selected public higher education institutions (HEIs) in Ghana. Data analysis followed Braun and Clarke's (2012) thematic analysis approach. The results showed that the transition to blended learning was supported by the adoption and integration of varied virtual online technologies. The themes highlight the positive and negative impacts of technology in mediating the educational experiences of instructors and adult learners in blended learning environments. The themes which reflected both instructors' and adult learners' experiences were enhanced course delivery and pedagogy, competency development, technological issues and poor‐quality pedagogy. Blended learning facilitated by technology could be the ‘new normal learning’ post‐pandemic for adult learners pursuing Distance Education in Ghana. The study recommends the implementation of agile strategies and policies by HEIs to ensure sustainable quality education in distance learning. Practitioner notes What is already known about this topic The COVID‐19 pandemic necessitated the adoption of innovative pedagogical approaches in higher education contexts. Technological transformations in information and communication technology (ICT) have enhanced remote teaching in higher education institutions globally. The educational experiences of educators and learners differ in blended learning contexts. What this paper adds Instructors and adult learners' positive experiences with navigating a variety of web‐based technologies during the educational process are negatively impacted by technological difficulties during online instruction. Participants' experiences of blended learning are mixed with a preference for face‐to‐face dimension of blended learning instead of the online dimension. The paper identifies four themes that characterize instructors and adult learners' experiences with technology‐enhanced learning including enhanced course delivery and pedagogy, competency development, technological issues and poor‐quality pedagogy. Implications for practice and/or policy The study provides evidence‐based information on the relevance of digitizing distance education for sustainable development and promotion of lifelong learning opportunities for distance education students. The research recommends that higher education institutions (HEIs) implement agile policies to facilitate a seamless shift to distance learning. HEIs may adopt open distance learning frameworks to streamline 21st century pedagogical and learning practices in distance‐blended learning environments for quality course instruction. The study highlights the potential distance learning modalities that HEIs can consider for Distance Education students to sustain effective quality teaching and learning. What is already known about this topic The COVID‐19 pandemic necessitated the adoption of innovative pedagogical approaches in higher education contexts. Technological transformations in information and communication technology (ICT) have enhanced remote teaching in higher education institutions globally. The educational experiences of educators and learners differ in blended learning contexts. What this paper adds Instructors and adult learners' positive experiences with navigating a variety of web‐based technologies during the educational process are negatively impacted by technological difficulties during online instruction. Participants' experiences of blended learning are mixed with a preference for face‐to‐face dimension of blended learning instead of the online dimension. The paper identifies four themes that characterize instructors and adult learners' experiences with technology‐enhanced learning including enhanced course delivery and pedagogy, competency development, technological issues and poor‐quality pedagogy. Implications for practice and/or policy The study provides evidence‐based information on the relevance of digitizing distance education for sustainable development and promotion of lifelong learning opportunities for distance education students. The research recommends that higher education institutions (HEIs) implement agile policies to facilitate a seamless shift to distance learning. HEIs may adopt open distance learning frameworks to streamline 21st century pedagogical and learning practices in distance‐blended learning environments for quality course instruction. The study highlights the potential distance learning modalities that HEIs can consider for Distance Education students to sustain effective quality teaching and learning. [ABSTRACT FROM AUTHOR]

The HyFlex course has been widely adopted in higher education settings. However, there is a paucity of empirical studies examining students' acceptance of large‐scale HyFlex courses, as well as factors influencing their acceptance. To fill this research gap, the present study investigated students' acceptance of a large‐scale HyFlex course and the variations in their acceptance according to different participation modes (ie, on‐site, synchronously online and mixed attendance), based on a total of 160 valid samples from a large‐scale HyFlex course at a normal university in central China during the fall semester of 2022. The results indicated that students' overall HyFlex course acceptance was generally high, and the students who alternately engaged in on‐site and synchronously online learning had the highest level of acceptance. Furthermore, this study employed structural equation modelling to validate a model integrating the unified theory of acceptance and use of technology with connected classroom climate (CCC). The findings showed that performance expectancy (PE), effort expectancy, facilitating conditions and CCC directly influenced students' acceptance, with performance expectancy having the strongest direct effect. However, social influence only had an indirect effect on students' acceptance, while CCC had both direct and indirect effects. This study carries substantial theoretical and practical implications, enhancing our understanding of students' acceptance of the HyFlex learning approach.Practitioner notesWhat is already known about this topic The adoption of the HyFlex course, especially in the context of large‐scale courses, is prevalent in higher education settings. Existing studies have predominately focused on assessing the impact of HyFlex course on student engagement and learning outcomes, the development and implementation of HyFlex course structures, and educators' perspectives and experiences with HyFlex courses. Although some research has delved into students' satisfaction with HyFlex courses, particularly in small class settings, our understanding of students' acceptance of large‐scale HyFlex course remains limited. There has been a noticeable gap in investigations exploring distinctions among students who opt for varying HyFlex course delivery modes, such as on‐site, synchronously online and mixed attendance formats. What this paper adds This study reveals that students generally displayed a high level of acceptance towards the large‐scale HyFlex course. Notably, students who participated in alternating on‐site and synchronously online learning exhibited a significantly higher level of acceptance towards the HyFlex course compared to their counterparts. A novel approach was employed in this study by integrating the UTAUT model with the concept of connected classroom climate (CCC) to comprehensively explore the key influencing factors and their interrelationships regarding students' acceptance of a large‐scale HyFlex course. The study found that performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and CCC were all significant factors that positively influenced students' acceptance of the HyFlex course. Particularly, PE emerged as the factor with the strongest direct impact on HyFlex course acceptance (ACP). Interestingly, social influence (SI) did not exhibit a significant direct effect on students' ACP. However, it had a significant and positive indirect effect on students' ACP through the mediation of PE. Furthermore, CCC was shown to have both direct and indirect effects on students' acceptance of the HyFlex course, with the indirect effect of CCC on ACP accounted for nearly half of the total effect. Implications for practice and/or policy Instructors should prioritize emphasizing the advantages and benefits of HyFlex courses to enhance students' motivation and willingness to participate actively in these courses. This may involve showcasing how HyFlex course offer flexibility, convenience and varied learning opportunities. When implementing HyFlex courses, instructors should work to mitigate students' perceived EE. This could be achieved through streamlining course navigation, ensuring user‐friendly technology tools and providing clear guidelines for participation. Simultaneously, efforts should be made to enhance perceived learning support to facilitate students' engagement and acceptance of HyFlex courses. Instructors in HyFlex course settings should place a strong emphasis on creating a supportive and collaborative learning environment. This involves fostering interactions among students, encouraging peer‐to‐peer support and providing resources and guidance to help students navigate the challenges and opportunities presented by HyFlex course formats. Building a sense of community and connectedness among students can significantly impact their acceptance and success in such courses. What is already known about this topic The adoption of the HyFlex course, especially in the context of large‐scale courses, is prevalent in higher education settings. Existing studies have predominately focused on assessing the impact of HyFlex course on student engagement and learning outcomes, the development and implementation of HyFlex course structures, and educators' perspectives and experiences with HyFlex courses. Although some research has delved into students' satisfaction with HyFlex courses, particularly in small class settings, our understanding of students' acceptance of large‐scale HyFlex course remains limited. There has been a noticeable gap in investigations exploring distinctions among students who opt for varying HyFlex course delivery modes, such as on‐site, synchronously online and mixed attendance formats. What this paper adds This study reveals that students generally displayed a high level of acceptance towards the large‐scale HyFlex course. Notably, students who participated in alternating on‐site and synchronously online learning exhibited a significantly higher level of acceptance towards the HyFlex course compared to their counterparts. A novel approach was employed in this study by integrating the UTAUT model with the concept of connected classroom climate (CCC) to comprehensively explore the key influencing factors and their interrelationships regarding students' acceptance of a large‐scale HyFlex course. The study found that performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and CCC were all significant factors that positively influenced students' acceptance of the HyFlex course. Particularly, PE emerged as the factor with the strongest direct impact on HyFlex course acceptance (ACP). Interestingly, social influence (SI) did not exhibit a significant direct effect on students' ACP. However, it had a significant and positive indirect effect on students' ACP through the mediation of PE. Furthermore, CCC was shown to have both direct and indirect effects on students' acceptance of the HyFlex course, with the indirect effect of CCC on ACP accounted for nearly half of the total effect. Implications for practice and/or policy Instructors should prioritize emphasizing the advantages and benefits of HyFlex courses to enhance students' motivation and willingness to participate actively in these courses. This may involve showcasing how HyFlex course offer flexibility, convenience and varied learning opportunities. When implementing HyFlex courses, instructors should work to mitigate students' perceived EE. This could be achieved through streamlining course navigation, ensuring user‐friendly technology tools and providing clear guidelines for participation. Simultaneously, efforts should be made to enhance perceived learning support to facilitate students' engagement and acceptance of HyFlex courses. Instructors in HyFlex course settings should place a strong emphasis on creating a supportive and collaborative learning environment. This involves fostering interactions among students, encouraging peer‐to‐peer support and providing resources and guidance to help students navigate the challenges and opportunities presented by HyFlex course formats. Building a sense of community and connectedness among students can significantly impact their acceptance and success in such courses. [ABSTRACT FROM AUTHOR]

In the ever‐evolving AI‐driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre‐service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers' willingness to integrate AI (WIAI), especially from the perspective of pre‐service STEM teachers' attitudes towards the application of AI in teaching. In the study, a comprehensive survey was conducted among 239 pre‐service STEM teachers, examining the influences and interconnectedness of Technological Pedagogical Content Knowledge (TPACK), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Self‐Efficacy (SE) on WIAI. Structural Equation Modeling (SEM) was employed for data analysis. The findings illuminated direct influences of TPACK, PU, PE, and SE on WIAI. TPACK was found to directly affect PE, PU, and SE, while PE and PU also directly influenced SE. Further analysis revealed significant mediating roles of PE, PU, and SE in the relationship between TPACK and WIAI, highlighting the presence of a chain mediation effect. In light of these insights, the study offers several recommendations on promoting pre‐service STEM teachers' willingness to integrate AI into their teaching practices. Practitioner notes What is already known about this topic? The potential of AI technologies to enrich learning experiences and improve outcomes in STEM education has been recognized. Pre‐service teachers' willingness to integrate AI into teaching practice is crucial for shaping the future learning environment. The TAM and TPACK frameworks are used to analyse teacher factors in technology‐supported learning environments. Few studies have been conducted for examining factors of pre‐service teachers' willingness to integrate AI into teaching practices in the context of STEM education. What this paper adds? A survey was designed and developed for exploring pre‐service STEM teachers' WIAI and its relationships with factors including TPACK, PE, PU, and SE. TPACK, SE, PU, and PE have direct impact on pre‐service STEM teachers' WIAI. SE, PU, and PE have been identified as mediating variables in the relationship between TPACK and WIAI. Two sequential mediation effects, TPACK → PE → SE → WIAI and TPACK → PU → SE → WIAI, among pre‐service STEM teachers were further identified. Implications of this study for practice and/or policy Pre‐service STEM teachers are encouraged to explore and utilize AI technology to enhance their confidence and self‐efficacy in integrating AI into teaching practices. Showcasing successful cases and practical experiences is essential for fostering awareness of AI integration in STEM education. It is recommended to introduce AI education courses in teacher training programs. Offering internship and practicum opportunities related to AI technologies can enhance their practical skills in integrating AI into education. What is already known about this topic? The potential of AI technologies to enrich learning experiences and improve outcomes in STEM education has been recognized. Pre‐service teachers' willingness to integrate AI into teaching practice is crucial for shaping the future learning environment. The TAM and TPACK frameworks are used to analyse teacher factors in technology‐supported learning environments. Few studies have been conducted for examining factors of pre‐service teachers' willingness to integrate AI into teaching practices in the context of STEM education. What this paper adds? A survey was designed and developed for exploring pre‐service STEM teachers' WIAI and its relationships with factors including TPACK, PE, PU, and SE. TPACK, SE, PU, and PE have direct impact on pre‐service STEM teachers' WIAI. SE, PU, and PE have been identified as mediating variables in the relationship between TPACK and WIAI. Two sequential mediation effects, TPACK → PE → SE → WIAI and TPACK → PU → SE → WIAI, among pre‐service STEM teachers were further identified. Implications of this study for practice and/or policy Pre‐service STEM teachers are encouraged to explore and utilize AI technology to enhance their confidence and self‐efficacy in integrating AI into teaching practices. Showcasing successful cases and practical experiences is essential for fostering awareness of AI integration in STEM education. It is recommended to introduce AI education courses in teacher training programs. Offering internship and practicum opportunities related to AI technologies can enhance their practical skills in integrating AI into education. [ABSTRACT FROM AUTHOR]

Digital games (DGs) have the potential to immerse learners in simulated real‐world environments that foster contextualised and active learning experiences. These also offer opportunities for performance assessments by providing an environment for students to carry out tasks requiring the application of knowledge and skills learned in the classroom. Although widely used for teaching and learning, there are challenges in using digital game applications for assessment. Designing assessments around tasks in complex learning environments like DGs is not always easy, particularly for educators new to using these technologies for teaching. This paper presents a game‐based assessment framework (GBAF) that is designed to be educator‐friendly and useful for the design of assessments for immersive learning environments. The application of the framework to the design of embedded and external (multiple‐choice questions) assessments is also presented. The GBAF offered an easy and structured basis for the design of two distinct assessments for a computer game. It provides educators with useful guidelines for designing assessments around pre‐existing games. Practitioner notesWhat is already known about this topicImmersive technologies are increasingly being used for teaching and learning due to their benefits to knowledge and skills acquisition. However, for educators interested in using these tools for formal classroom teaching, there is a lack of resources and guidance on assessment designs and implementations. The most commonly used assessment design framework, the evidence‐centred design (ECD), is complicated to use, requiring advanced machine learning skills to implement. This has so far limited its use to large‐scale computerised and game‐based testing.What this paper addsThis paper presents a framework developed to guide educators through the design and implementation of assessments when teaching with immersive learning applications. Grounded in the constructive alignment principles and the ECD framework, the game‐based assessment framework is designed to help educators align assessment tasks to game tasks and the intended learning outcomes. It also provides step‐by‐step guidelines for the identification of appropriate immersive applications. It shows the practical application of the framework to the design of embedded (in‐game) assessments and external (multiple‐choice tests) assessments.Implications for practice and/or policyThe framework presented in this paper provides a structured and pedagogically sound basis for the design of assessments when measuring performance, or skills and knowledge acquisition with immersive learning applications. [ABSTRACT FROM AUTHOR]

This paper provides an experience report on a co‐design approach with teachers to co‐create learning analytics‐based technology to support problem‐based learning in middle school science classrooms. We have mapped out a workflow for such applications and developed design narratives to investigate the implementation, modifications and temporal roles of the participants in the design process. Our results provide precedent knowledge on co‐designing with experienced and novice teachers and co‐constructing actionable insight that can help teachers engage more effectively with their students' learning and problem‐solving processes during classroom PBL implementations. Practitioner notesWhat is already known about this topic Success of educational technology depends in large part on the technology's alignment with teachers' goals for their students, teaching strategies and classroom context.Teacher and researcher co‐design of educational technology and supporting curricula has proven to be an effective way for integrating teacher insight and supporting their implementation needs.Co‐designing learning analytics and support technologies with teachers is difficult due to differences in design and development goals, workplace norms, and AI‐literacy and learning analytics background of teachers.What this paper adds We provide a co‐design workflow for middle school teachers that centres on co‐designing and developing actionable insights to support problem‐based learning (PBL) by systematic development of responsive teaching practices using AI‐generated learning analytics.We adapt established human‐computer interaction (HCI) methods to tackle the complex task of classroom PBL implementation, working with experienced and novice teachers to create a learning analytics dashboard for a PBL curriculum.We demonstrate researcher and teacher roles and needs in ensuring co‐design collaboration and the co‐construction of actionable insight to support middle school PBL.Implications for practice and/or policy Learning analytics researchers will be able to use the workflow as a tool to support their PBL co‐design processes.Learning analytics researchers will be able to apply adapted HCI methods for effective co‐design processes.Co‐design teams will be able to pre‐emptively prepare for the difficulties and needs of teachers when integrating middle school teacher feedback during the co‐design process in support of PBL technologies. [ABSTRACT FROM AUTHOR]

This paper describes a Human‐Centred Learning Analytics (HCLA) design approach for developing learning analytics (LA) dashboards for K‐12 classrooms that maintain both contextual relevance and scalability—two goals that are often in competition. Using mixed methods, we collected observational and interview data from teacher partners and assessment data from their students' engagement with the lesson materials. This DBR‐based, human‐centred design process resulted in a dashboard that supported teachers in addressing their students' learning needs. To develop the dashboard features that could support teachers, we found that a design refinement process that drew on the insights of teachers with varying teaching experience, philosophies and teaching contexts strengthened the resulting outcome. The versatile nature of the approach, in terms of student learning outcomes, makes it useful for HCLA design efforts across diverse K‐12 educational contexts. Practitioner notesWhat is already known about this topic Learning analytics that are aligned to both a learning theory and learning design support student learning.LA dashboards that support users to understand the associated learning analytics data provide actionable insight.Design‐based research is a promising methodology for Human‐Centred Learning Analytics design, particularly in the K‐12 educational context.What this paper adds Leveraging a longstanding, yet fluid, research‐practice partnership is an effective design‐based research adaptation for addressing the high variation in instructional practices that characterize K‐12 education.Using both quantitative and qualitative data that reflects students' developing knowledge effectively supports teachers' inquiry into student learning.Teachers' use of learning analytics dashboards is heavily influenced by their perspectives on teaching and learning.Implications for practice and/or policy Impact on student learning outcomes, alongside usability and feasibility, should be included as a necessary metric for the effectiveness of LA design.LA dashboard developers should both leverage learning data that reflect students' developing knowledge and position teachers to take responsive pedagogical action to support student learning.LA researchers and developers should utilize a long‐term, yet fluid, research‐practice partnership to form a multi‐stakeholder, multidisciplinary design team for Human‐Centred Learning Analytics design. [ABSTRACT FROM AUTHOR]

Several studies have indicated that stakeholder engagement could ensure the successful adoption of learning analytics (LA). Considering that researchers and tech developers may not be aware of how LA tools can derive meaningful and actionable information for everyday use, these studies suggest that participatory approaches based on human‐centred design can provide stakeholders with the opportunity to influence decision‐making during tool development. So far, there is a growing consensus about the importance of identifying stakeholders' needs and expectations in early stages, so researchers and developers can design systems that resonate with their users. However, human‐centred LA is a growing sub‐field, so further empirical work is needed to understand how stakeholders can contribute effectively to the design process and the adoption strategy of analytical tools. To illustrate mechanisms to engage various stakeholders throughout different phases of a design process, this paper presents a multiple case study conducted in different Latin American universities. A series of studies inform the development of an analytical tool to support continuous curriculum improvement, aiming to improve student learning and programme quality. Yet, these studies differ in scope and design stage, so they use different mechanisms to engage students, course instructors and institutional administrators. By cross analysing the findings of these three cases, three conclusions emerged for each design phase of a CA tool, presenting mechanisms to ensure stakeholder adoption after tool development. Further implications of this multiple case study are discussed from a theoretical and methodological perspective. Practitioner notesWhat is already known about this topic? Human‐centred learning analytics (LA) has accommodated different configurations of stakeholder engagement, including co‐design and participatory design.Participatory design provides developers with a wide variety of techniques to engage a particular group in a mutual learning process.Most studies mainly focus on engaging stakeholders to identify needs in the early stages of the design process.More empirical works are needed to unveil the effectiveness of human centredness during LA design and after tool development.What this paper adds? Provides a multiple case study to illustrate mechanisms to engage various stakeholders in different design phases of a curriculum analytics (CA) tool.Summarises different assertions based on case study findings regarding needs for analytical tool, its early evaluation and its potential use after development.Provides empirical evidence on how to promote stakeholder engagement at a specific design stage and for a specific purpose.The implications for practitioners LA researchers and developers can use assertions based on evidence as a starting point to drive the design process of CA solutions.Researchers and practitioners will have a set of protocols to implement participatory techniques in different design phases of a CA tool. [ABSTRACT FROM AUTHOR]

Gamification, characterized by the integration of game design elements into non‐game environments, has gained popularity in classrooms due to its potential for increased engagement and enjoyment compared to traditional lecture‐based teaching methods. While students generally exhibit positive attitudes towards gamification, its impact on academic achievement remains a subject of debate. This study employed a meta‐analysis approach to examine the overall influence of gamification on students' academic performance. The sample comprised 22 experimental studies conducted between 2008 and 2023, comparing the effects of gamified and non‐gamified classes. Utilizing a random effects model, the results revealed a moderately positive effect of gamification on student academic performance (Hedges's g = 0.782, p < 0.05). The paper further discussed the outcomes of various moderator analyses, providing valuable insights into the selection and utilization of game design elements, as well as considerations specific to different educational stages.Practitioner notesWhat is already known about this topic Most research has consistently demonstrated that gamification has a positive impact on students' achievement. The current state of review research is not sufficiently comprehensive. There is a lack of meta‐analyses exploring the diverse impacts of gamification. What this paper adds The effect of factors such as geographical regions, education levels, learning environments, subjects and game elements on gamification was examined. The study revealed a significant and positive impact of gamification on students' achievement across various factors, including geographical regions, education levels, learning environments, subjects and game elements. Implications for practice and/or policy Gamification represents a prudent choice for teachers seeking to enhance students' achievement. Teachers are suggested to adopt and employ appropriate game elements in their instructional approaches. Future research could focus on investigating the impact of feedback as a game element in teaching and learning. Most research has consistently demonstrated that gamification has a positive impact on students' achievement. The current state of review research is not sufficiently comprehensive. There is a lack of meta‐analyses exploring the diverse impacts of gamification. The effect of factors such as geographical regions, education levels, learning environments, subjects and game elements on gamification was examined. The study revealed a significant and positive impact of gamification on students' achievement across various factors, including geographical regions, education levels, learning environments, subjects and game elements. Gamification represents a prudent choice for teachers seeking to enhance students' achievement. Teachers are suggested to adopt and employ appropriate game elements in their instructional approaches. Future research could focus on investigating the impact of feedback as a game element in teaching and learning. [ABSTRACT FROM AUTHOR]

Previous research has demonstrated the effectiveness of executive functions (EFs) training, both in computer‐based and school‐based formats. However, there is limited research on the combined effects of these training modalities. This study aims to assess the feasibility and preliminary efficacy of an EFs training programme for primary school children. The programme includes computerized training sessions for home use and school activities with metacognitive elements. The study included a sample of 53 second‐grade children, with 21 children in the training group and 32 children in the control group. Feasibility questionnaires were completed by children, parents and teachers. The children also underwent an EFs evaluation. The results indicate that the training was enjoyable for children and feasible for parents and teachers. Furthermore, preliminary efficacy analysis revealed significant improvements in working memory. These findings suggest that the training model holds promise for enhancing EFs in children in the school context. Practitioner notes What is already known about this topic Individual differences in executive functions influence acquisitions, behaviours and competencies in several specific domains from infancy to adulthood. Enhancing executive functions during school‐age years can contribute to reducing or preventing academic, behavioural and social difficulties. Among interventions targeting executive functions in school‐aged children, school‐based interventions have shown the highest effectiveness, followed by metacognitive interventions and computer‐based interventions. What this paper adds This paper presents the implementation of an innovative school‐based training programme designed to improve executive functions (EFs). The programme combines metacognitive sessions conducted at school with computer‐based sessions carried out at home. The goal was to enhance the effectiveness and generalizability of the training. The training programme was found to be enjoyable for children and feasible for both parents and teachers. Preliminary efficacy data indicate promising results, suggesting that the training programme is effective in achieving its intended goals. Implications for practice and/or policy Integrating school‐based metacognitive training with computerized sessions delivered at home can provide a high‐intensity training programme that may not be achievable in the school context alone. The school activities, conducted in group settings with teachers and peers, were found to be the most appreciated by the children, indicating that computer sessions alone cannot replace the value of metacognitive sessions at school, within a meaningful social context for the child. It is crucial to actively involve families in the training process to ensure good adherence. Additionally, the availability of technological resources in each family should be evaluated before implementing the training programme. What is already known about this topic Individual differences in executive functions influence acquisitions, behaviours and competencies in several specific domains from infancy to adulthood. Enhancing executive functions during school‐age years can contribute to reducing or preventing academic, behavioural and social difficulties. Among interventions targeting executive functions in school‐aged children, school‐based interventions have shown the highest effectiveness, followed by metacognitive interventions and computer‐based interventions. What this paper adds This paper presents the implementation of an innovative school‐based training programme designed to improve executive functions (EFs). The programme combines metacognitive sessions conducted at school with computer‐based sessions carried out at home. The goal was to enhance the effectiveness and generalizability of the training. The training programme was found to be enjoyable for children and feasible for both parents and teachers. Preliminary efficacy data indicate promising results, suggesting that the training programme is effective in achieving its intended goals. Implications for practice and/or policy Integrating school‐based metacognitive training with computerized sessions delivered at home can provide a high‐intensity training programme that may not be achievable in the school context alone. The school activities, conducted in group settings with teachers and peers, were found to be the most appreciated by the children, indicating that computer sessions alone cannot replace the value of metacognitive sessions at school, within a meaningful social context for the child. It is crucial to actively involve families in the training process to ensure good adherence. Additionally, the availability of technological resources in each family should be evaluated before implementing the training programme. [ABSTRACT FROM AUTHOR]

Deep neural networks are increasingly employed to model classroom dialogue and provide teachers with prompt and valuable feedback on their teaching practices. However, these deep learning models often have intricate structures with numerous unknown parameters, functioning as black boxes. The lack of clear explanations regarding their classroom dialogue analysis likely leads teachers to distrust and underutilize these AI‐powered models. To tackle this issue, we leveraged explainable AI to unravel classroom dialogue analysis and conducted an experiment to evaluate the effects of explanations. Fifty‐nine pre‐service teachers were recruited and randomly assigned to either a treatment (n = 30) or control (n = 29) group. Initially, both groups learned to analyse classroom dialogue using AI‐powered models without explanations. Subsequently, the treatment group received both AI analysis and explanations, while the control group continued to receive only AI predictions. The results demonstrated that teachers in the treatment group exhibited significantly higher levels of trust in and technology acceptance of AI‐powered models for classroom dialogue analysis compared to those in the control group. Notably, there were no significant differences in cognitive load between the two groups. Furthermore, teachers in the treatment group expressed high satisfaction with the explanations. During interviews, they also elucidated how the explanations changed their perceptions of model features and attitudes towards the models. This study is among the pioneering works to propose and validate the use of explainable AI to address interpretability challenges within deep learning‐based models in the context of classroom dialogue analysis.Practitioner notesWhat is already known about this topic Classroom dialogue is recognized as a crucial element in the teaching and learning process. Researchers have increasingly utilized AI techniques, particularly deep learning methods, to analyse classroom dialogue. Deep learning‐based models, characterized by their intricate structures, often function as black boxes, lacking the ability to provide transparent explanations regarding their analysis. This limitation can result in teachers harbouring distrust and underutilizing these models. What this paper adds This paper highlights the importance of incorporating explainable AI approaches to tackle the interpretability issues associated with deep learning‐based models utilized for classroom dialogue analysis. Through an experimental study, this paper demonstrates that providing model explanations enhances teachers' trust in and technology acceptance of AI‐powered classroom dialogue models, without increasing their cognitive load. Teachers express satisfaction with the model explanations provided by explainable AI. Implications for practice and/or policy The integration of explainable AI can effectively address the challenge of interpretability in complex AI‐powered models used for analysing classroom dialogue. Intelligent teaching systems designed for classroom dialogue can benefit from advanced AI models and explainable AI approaches, which offer users both automated analysis and clear explanations. By enabling users to understand the underlying rationale behind the analysis, the explanations can contribute to fostering trust and acceptance of the AI models among users. Classroom dialogue is recognized as a crucial element in the teaching and learning process. Researchers have increasingly utilized AI techniques, particularly deep learning methods, to analyse classroom dialogue. Deep learning‐based models, characterized by their intricate structures, often function as black boxes, lacking the ability to provide transparent explanations regarding their analysis. This limitation can result in teachers harbouring distrust and underutilizing these models. This paper highlights the importance of incorporating explainable AI approaches to tackle the interpretability issues associated with deep learning‐based models utilized for classroom dialogue analysis. Through an experimental study, this paper demonstrates that providing model explanations enhances teachers' trust in and technology acceptance of AI‐powered classroom dialogue models, without increasing their cognitive load. Teachers express satisfaction with the model explanations provided by explainable AI. The integration of explainable AI can effectively address the challenge of interpretability in complex AI‐powered models used for analysing classroom dialogue. Intelligent teaching systems designed for classroom dialogue can benefit from advanced AI models and explainable AI approaches, which offer users both automated analysis and clear explanations. By enabling users to understand the underlying rationale behind the analysis, the explanations can contribute to fostering trust and acceptance of the AI models among users. [ABSTRACT FROM AUTHOR]

This study addresses the need for inclusive AI education by focusing on marginalized female students who historically lack access to learning opportunities in computing. It applies the theoretical framework of intersectionality to understand how gender, race and ethnicity intersect to shape these students' learning experiences and outcomes. Specifically, this study investigated 27 high‐school students' cognitive engagement in machine learning practices. We conducted the Wilcoxon–Mann–Whitney test to explore differences in cognitive engagement between marginalized female students and their peers, employed comparative content analysis to delve into significant differences and analysed interview data thematically to gain deeper insights into students' machine learning model development processes. The findings indicated that, when engaging in machine learning practices requiring drawing diverse cultural perspectives, marginalized female students demonstrated significantly higher performance compared to their peers. In particular, marginalized female students exhibited strengths in holistic language analysis, paying attention to writers' intentions and recognizing cultural nuances in language. This study suggests that integrating language analysis and machine learning across subjects has the potential to empower marginalized female students and amplify their perspectives. Furthermore, it calls for a strengths‐based approach to reshape the narrative of underrepresentation and promote equitable participation in machine learning and AI. Practitioner notes What is already known about this topic Female students, particularly those from underrepresented groups such as African American and Latina students, often experience low levels of cognitive engagement in computing. Marginalized female students possess unique strengths that, when nurtured, have the potential to not only transform their own learning experiences but also contribute to the advancement of the computing field. It is critical to empower marginalized female students in K‐12 AI (ie, a subfield of computing) education, seeking to bridge the gender and racial disparity in AI. What this paper adds Marginalized female students outperformed their peers in responding to machine learning questions related to feature analysis and feature distribution interpretation. When responding to these questions, they demonstrated a holistic approach to analysing language by considering interactions between features and writers' intentions. They drew on knowledge about how language was used to convey meaning in different cultural contexts. Implications for practice and/or policy Educators should design learning environments that encourage students to draw upon their cultural backgrounds, linguistic insights and diverse experiences to enhance their engagement and performance in AI‐related activities. Educators should strategically integrate language analysis and machine learning across different subjects to create interdisciplinary learning experiences that support students' exploration of the interplay among language, culture and AI. Educational institutions and policy initiatives should adopt a strengths‐based approach that focuses on empowering marginalized female students by acknowledging their inherent abilities and diverse backgrounds. What is already known about this topic Female students, particularly those from underrepresented groups such as African American and Latina students, often experience low levels of cognitive engagement in computing. Marginalized female students possess unique strengths that, when nurtured, have the potential to not only transform their own learning experiences but also contribute to the advancement of the computing field. It is critical to empower marginalized female students in K‐12 AI (ie, a subfield of computing) education, seeking to bridge the gender and racial disparity in AI. What this paper adds Marginalized female students outperformed their peers in responding to machine learning questions related to feature analysis and feature distribution interpretation. When responding to these questions, they demonstrated a holistic approach to analysing language by considering interactions between features and writers' intentions. They drew on knowledge about how language was used to convey meaning in different cultural contexts. Implications for practice and/or policy Educators should design learning environments that encourage students to draw upon their cultural backgrounds, linguistic insights and diverse experiences to enhance their engagement and performance in AI‐related activities. Educators should strategically integrate language analysis and machine learning across different subjects to create interdisciplinary learning experiences that support students' exploration of the interplay among language, culture and AI. Educational institutions and policy initiatives should adopt a strengths‐based approach that focuses on empowering marginalized female students by acknowledging their inherent abilities and diverse backgrounds. [ABSTRACT FROM AUTHOR]

Well‐designed online educational games can improve students' math knowledge, skills and engagement; however, more research is needed to understand how to formatively assess components of students' mathematical understanding and learning as students solve problems in online educational games. In this study, we examined how 7th‐grade students' (N = 760) in‐game performance (ie, strategy efficiency, mathematical validity of the first action, mathematical errors) and help‐seeking behaviours (ie, hint requests) correlated with their algebraic knowledge in an online mathematics game. The k‐means cluster analysis identified four groups of students based on their in‐game metrics, and some variabilities in their in‐game performance were found. Although hint requests were available, only a few students showed a high percentage of hint requests during their gameplay. The regression analysis revealed that students' in‐game performance and help‐seeking behavioural patterns explained a significant amount of variance in students' algebraic knowledge above and beyond their prior knowledge. Our results suggest that how students interact with the online learning game is related to their later math performance, and qualitative aspects of student behaviours captured using log data provide meaningful information to students' algebraic understanding. Practitioner notes What is already known about this topic Well‐designed online educational games can improve students' math knowledge, skills, and engagement. Several studies found that some in‐game metrics, such as in‐game progress or correctness of tasks, are positively associated with learning outcomes. However, many studies used simple metrics like the correctness of each task or the number of problems completed to measure students' performance in the game. Few studies measured more in the moment or qualitative aspects of student in‐game performance, for example, how efficiently students solved problems in the game. What this paper adds In‐game metrics measuring more in the moment and qualitative aspects of students' problem‐solving explained a significant amount of variance in students' algebraic knowledge above and beyond students' prior knowledge. Students' strategy efficiency and strategic planning were positively associated with students' math problem‐solving performance. Although hints were available for almost all problems, only a few students exhibited a high level of help‐seeking behaviours, and the students with the lowest in‐game performance who needed help the most showed low help‐seeking behaviours. Implications for practice and/or policy Classifying students into profiles could provide ways to identify students with different levels of problem‐solving skills and help teachers provide more personalized instruction. Teachers could use this information as a formative assessment to identify the core areas of intervention needed, particularly for students struggling with math concepts taught in the game. Instructional strategies that make hints more appealing or engaging to students might be needed. What is already known about this topic Well‐designed online educational games can improve students' math knowledge, skills, and engagement. Several studies found that some in‐game metrics, such as in‐game progress or correctness of tasks, are positively associated with learning outcomes. However, many studies used simple metrics like the correctness of each task or the number of problems completed to measure students' performance in the game. Few studies measured more in the moment or qualitative aspects of student in‐game performance, for example, how efficiently students solved problems in the game. What this paper adds In‐game metrics measuring more in the moment and qualitative aspects of students' problem‐solving explained a significant amount of variance in students' algebraic knowledge above and beyond students' prior knowledge. Students' strategy efficiency and strategic planning were positively associated with students' math problem‐solving performance. Although hints were available for almost all problems, only a few students exhibited a high level of help‐seeking behaviours, and the students with the lowest in‐game performance who needed help the most showed low help‐seeking behaviours. Implications for practice and/or policy Classifying students into profiles could provide ways to identify students with different levels of problem‐solving skills and help teachers provide more personalized instruction. Teachers could use this information as a formative assessment to identify the core areas of intervention needed, particularly for students struggling with math concepts taught in the game. Instructional strategies that make hints more appealing or engaging to students might be needed. [ABSTRACT FROM AUTHOR]

Spatial perspective‐taking (SPT) ability positively influences performance in STEM fields. While limited research studies have been done with school students, they have yielded inconclusive findings and, hence, here we report findings from our study with an augmented reality (AR) enhanced learning environment (ARELE), GeoSolvAR, on middle‐school students' SPT ability. We conducted a sequential explanatory mixed‐method study with 90 students to test GeoSolvAR's twin features of augmented systems and inquiry‐based activities. The study had one experimental (n = 30) and two control groups (n = 30 × 2), where students were individually administered an online pre‐ and posttest to measure their SPT ability. The experimental group worked with both the features of GeoSolvAR, while the control group worked with only the AR feature or had no intervention. Our findings reveal that the experimental group showed significant improvement in SPT ability while students in the control groups showed non‐significant improvement or no change. Furthermore, we found that all experimental group students used certain body movements and imagined shifts in spatial positions while solving the activity questions. Thus, we conjecture that GeoSolvAR affords thinking and imagining with the body which makes it a potent tool for improving students' SPT ability. Practitioner notes What is already known about this topic Spatial perspective taking (SPT) belongs to a set of spatial abilities that have been shown to positively influence academic success and career success in STEM fields. Augmented reality systems with their ability to augment 2D images into 3D forms are being explored mostly in college and above levels to improve SPT ability. Limited research investigating the improvement of SPT in school students has used VR digital games or robots. These have either yielded inconclusive findings or not found any improvement in school students' SPT abilities. What this paper adds Conclusive evidence for improving SPT ability in middle‐school students. Empirical evidence for a design to effectively combine augmenting abilities of AR systems with inquiry‐based learning scaffolds to improve the SPT ability of middle‐school students. A conjecture about the mechanism by which middle‐school children's spatial perspective taking improves when scaffolded with an Augmented Reality Enhanced Learning Environment (ARELE) tool. Implications for practice and policy Practitioners such as teachers may directly use GeoSolvAR (the ARELE tool) to help middle‐school students improve their spatial perspective‐taking abilities. Researchers from the fields of both technology‐enhanced learning and science education may use the findings to design improved AR tools and test their impact on students' SPT ability. This work can serve as the basis for further investigating the effect of improved SPT ability on students' performance in STEM subjects. Our work provides support for embodied cognition being used as a strategy for solving SPT tasks. The identification of specific head and hand movements (gestures) can be further probed to understand the exact mechanism of how the ARELE mediates students' performance on the SPT tasks. What is already known about this topic Spatial perspective taking (SPT) belongs to a set of spatial abilities that have been shown to positively influence academic success and career success in STEM fields. Augmented reality systems with their ability to augment 2D images into 3D forms are being explored mostly in college and above levels to improve SPT ability. Limited research investigating the improvement of SPT in school students has used VR digital games or robots. These have either yielded inconclusive findings or not found any improvement in school students' SPT abilities. What this paper adds Conclusive evidence for improving SPT ability in middle‐school students. Empirical evidence for a design to effectively combine augmenting abilities of AR systems with inquiry‐based learning scaffolds to improve the SPT ability of middle‐school students. A conjecture about the mechanism by which middle‐school children's spatial perspective taking improves when scaffolded with an Augmented Reality Enhanced Learning Environment (ARELE) tool. Implications for practice and policy Practitioners such as teachers may directly use GeoSolvAR (the ARELE tool) to help middle‐school students improve their spatial perspective‐taking abilities. Researchers from the fields of both technology‐enhanced learning and science education may use the findings to design improved AR tools and test their impact on students' SPT ability. This work can serve as the basis for further investigating the effect of improved SPT ability on students' performance in STEM subjects. Our work provides support for embodied cognition being used as a strategy for solving SPT tasks. The identification of specific head and hand movements (gestures) can be further probed to understand the exact mechanism of how the ARELE mediates students' performance on the SPT tasks. [ABSTRACT FROM AUTHOR]

The number of scientific publications about serious games has exponentially increased, often surpassing human limitations in processing such a large volume of information. Consequently, the importance of frameworks for summarising such fast‐expanding literature has also grown. This paper draws a panorama of serious game research streams, focusing on higher education in engineering and management. The research design involves a systematic review using PRISMA guidelines, along with bibliometric and content analyses. The sample comprises 701 documents collected from both Scopus and Web of Science databases. For supporting bibliometric analyses, Bibliometrix and Biblioshiny tools are employed. In addition, a coding schema is developed for in‐depth analysis of 701 documents selected according to the inclusion criteria. In short, the literature on serious games for engineering and management education grows more rapidly than modern science, following a globalised, collaborative and context‐based trajectory. The results reveal five main research streams: game design guidelines, game design cases, game experiment guidelines, game experiment cases and generalists. These streams are summarised in a proposed framework. Cross‐tabulation and statistical analyses conducted in SPSS Statistics identify the key relationships amongst the research streams. Finally, opportunities to investigate serious games for sustainable development education arise, and there is a need for future efforts to formalise the framework classification algorithm. Practitioner notesWhat is already known about this topic Scientific production related to Serious Games (SGs) has grown exponentially in a globalised manner. It reflects the interest from various domains, particularly the field of sustainability in management.Literature reviews on SGs have emphasised various topics, including the acceptance of simulations and games as effective methods of teaching and learning. The role of technology‐enhanced games and simulations in the context of digital transformation in education and the emergence of sustainability as a promising field for future SGs research are also highlighted.The literature has introduced three categories for empirical research on SGs: (1) game presentation, (2) game evaluation and (3) game effectiveness. It has also highlighted methodological rigour as a common challenge across studies.What this paper adds Scientific research on SGs in Engineering and Management Higher Education (EMHE) experiences exponential and significantly faster growth compared to modern science in a globalised and collaborative manner. This growth reveals the scarcity of experts in this area and attracts the attention of various fields, particularly in the realm of sustainability.Thematic trajectories indicate a decline in discussions regarding users' perceptions of SGs and their validity as educational tools. They also demonstrate consistency in discussions about SGs design, and the potential of sustainability emerges as a promising area for future SGs in EMHE.A comprehensive framework composed by five primary research streams connects game design cases and guidelines, game experiment cases and guidelines and generalists. This framework can serve as a lens for future context‐based literature reviews, and the relationships amongst its streams reinforce the idea that the field can benefit from increased methodological rigour in experiments.Implications for practice and/or policy This review offers categorised supplementary material in which educators can discover a variety of artefacts for application in their specific educational contexts. Designers can access guidelines for enhancing the design of innovative games. Researchers can access guidelines for more effective evaluation of their artefacts across various contexts. Finally, policymakers can explore numerous experiments to inform decisions related to technology‐enhanced innovations in the classroom. [ABSTRACT FROM AUTHOR]

Although the utilization of mobile technologies has recently emerged in various educational settings, limited research has focused on cognitive load detection in the pen‐based learning process. This research conducted two experimental studies to investigate what and how multimodal data can be used to measure and classify learners' real‐time cognitive load. The results found that it was a promising method to predict learners' cognitive load by analysing their handwriting, touch gestural and eye‐tracking data individually and conjunctively. The machine learning approach used in this research achieved a prediction accuracy of 0.86 area under the receiver operating characteristic curve (AUC) and 0.85/0.86 sensitivity/specificity by only using handwriting data, 0.93 AUC and 0.93/0.94 sensitivity/specificity by only using touch gestural data, and 0.94 AUC and 0.94/0.95 sensitivity/specificity by using both the touch gestural and eye‐tracking data. The results can contribute to the optimization of cognitive load and the development of adaptive learning systems for pen‐based mobile learning. Practitioner notesWhat is already known about this topic Pen‐based mobile learning systems allow natural ways of handwriting and gestural touching, which can facilitate learners' cognitive processes in mobile learning.Behavioural and physiological multimodal data are helpful in detecting learners' real‐time cognitive load in mobile learning.The effectiveness of behavioural and physiological multimodal data for measuring cognitive load in pen‐based mobile learning is limited investigated.What this paper adds This paper confirms the effectiveness of handwriting and touch gestural multimodal data for measuring pen‐based learning cognitive load, in terms of their stroke‐, path‐ and time‐based features.This paper explores the potential of eye‐tracking data in measuring pen‐based learning cognitive load.A combination of behavioural and physiological multimodal data is reported to increase the prediction accuracy for cognitive load measurement.Implications for practice and/or policy Practitioners are suggested to use behavioural and physiological multimodal data individually or conjunctively for measuring cognitive load in pen‐based learning.The results provide guides for developing adaptive pen‐based learning systems by optimizing the real‐time cognitive load. [ABSTRACT FROM AUTHOR]

Learning analytics (LA) is an emerging area that has had extensive development in higher education in recent years, focused both on the learning process of students within subjects and on monitoring their trajectories in training programmes. However, most of the developments remain in the pilot phase without reaching institutional adoption. This paper reports the results of a systematic review of the literature carried out with the aim of identifying the factors that influence the adoption of LA, as well as the existing strategies that facilitate such adoption in higher education institutions. The results show that factors for LA adoption are situated in multiple dimensions, including stakeholders at different levels, institutional and pedagogical processes, technical limitations and ethical considerations. This work contributes with a consolidated list of 14 critical factors to be considered to effectively adopt LA tools, addressing planning, strong leadership, collaboration and prioritizing senior management commitment, goal setting, cross‐organizational design, educational process redesign, system integration and legacy system linkage. On the other hand, a variety of frameworks, models and approaches are distinguished in the literature to help the adoption of LA, however, none of them cover all the factors involved in such adoption. Therefore, we provide a compilation of strategies that have been used in the literature to reduce the gaps associated with the different factors described. Practitioner notesWhat is already known about this topic LA is a field of research that has had a lot of interest and a wide variety of tools have been developed. Still, it is criticized that they originate more from data availability than from the needs of students, teachers and decision makers.LA tools are mostly evaluated on their usability aspects and to a lesser extent on their usefulness to impact learning processes.The adoption processes of LA in higher education are oriented to specific aspects such as the relevance of the visualizations in the different contexts of application, but they do not address extensively other important aspects involved in such adoption.What this paper adds This article seeks to synthesize what has been investigated in the literature regarding the factors that affect the adoption of LA by higher education institutions.Describe the 14 critical factors identified from the literature to address adoption of multiple dimensions that include stakeholders at different levels, institutional contexts and ethical considerations.A compilation of strategies that have been used in the literature to reduce the gaps associated with the different factors are described, and the aspects or dimensions that are not addressed are highlighted.Implications for practice and/or policy The synthesis of LA adoption factors and the approach strategies present in the literature allow practitioners to focus their efforts on the key aspects to consider in their LA adoption processes.Future work could shift from a pure design perspective to strengthen an engineering perspective in the adoption practices.From the point of view of the policies associated with the adoption of LA in higher education institutions, it is concluded that it is necessary to approach the process from a comprehensive perspective considering all the dimensions involved. [ABSTRACT FROM AUTHOR]

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are concerns regarding the practicality and ethicality of these innovations. Such concerns may hinder future research and the adoption of LLMs‐based innovations in authentic educational contexts. To address this, we conducted a systematic scoping review of 118 peer‐reviewed papers published since 2017 to pinpoint the current state of research on using LLMs to automate and support educational tasks. The findings revealed 53 use cases for LLMs in automating education tasks, categorised into nine main categories: profiling/labelling, detection, grading, teaching support, prediction, knowledge representation, feedback, content generation, and recommendation. Additionally, we also identified several practical and ethical challenges, including low technological readiness, lack of replicability and transparency and insufficient privacy and beneficence considerations. The findings were summarised into three recommendations for future studies, including updating existing innovations with state‐of‐the‐art models (eg, GPT‐3/4), embracing the initiative of open‐sourcing models/systems, and adopting a human‐centred approach throughout the developmental process. As the intersection of AI and education is continuously evolving, the findings of this study can serve as an essential reference point for researchers, allowing them to leverage the strengths, learn from the limitations, and uncover potential research opportunities enabled by ChatGPT and other generative AI models. Practitioner notesWhat is currently known about this topic Generating and analysing text‐based content are time‐consuming and laborious tasks.Large language models are capable of efficiently analysing an unprecedented amount of textual content and completing complex natural language processing and generation tasks.Large language models have been increasingly used to develop educational technologies that aim to automate the generation and analysis of textual content, such as automated question generation and essay scoring.What this paper adds A comprehensive list of different educational tasks that could potentially benefit from LLMs‐based innovations through automation.A structured assessment of the practicality and ethicality of existing LLMs‐based innovations from seven important aspects using established frameworks.Three recommendations that could potentially support future studies to develop LLMs‐based innovations that are practical and ethical to implement in authentic educational contexts.Implications for practice and/or policy Updating existing innovations with state‐of‐the‐art models may further reduce the amount of manual effort required for adapting existing models to different educational tasks.The reporting standards of empirical research that aims to develop educational technologies using large language models need to be improved.Adopting a human‐centred approach throughout the developmental process could contribute to resolving the practical and ethical challenges of large language models in education. [ABSTRACT FROM AUTHOR]

In the last two decades, there has been a global movement towards pedagogies that create more inclusive school environments in order to meet the needs of diverse learners. One such approach is Universal Design for Learning (UDL), which foregrounds the design of flexible and accessible learning experiences for all, regardless of learner characteristics. Technology is a key enabler in this. To date, much of the research on UDL has focused on its impact in higher education, with less evidence available on the use of UDL within second‐level education. This systematic literature review of n = 15 empirical studies selected from a wide‐ranging search that returned an initial result of n = 1253 explores how the affordances of digital technology have been harnessed for UDL enactment at second level. The findings show that, to date, empirical research at second level has focused mostly on the easy wins within the UDL principle of Representation, where educators offer choice about how learners access content. However, there is a clear gap in UDL research on the use of technologies to support the Engagement and Action & Expression principles of UDL, supporting student self‐regulation and self‐assessment, and on technology‐mediated communication and collaboration. The paper highlights the potential for future cross‐pollination of research in educational technology with UDL. Practitioner NotesWhat is already known about this topicUniversal Design for Learning has been extensively researched in higher education and special education contexts but much less so at K‐12, in particular at second level.Technology offers many affordances that can provide choice and variation in the learning process, which can be harnessed in a UDL approach.The transformative potential of technology in educational contexts was not fully realised pre‐COVID.The COVID pandemic saw an acceleration in technology adoption for learning, but it remains to be seen whether technology is being deployed to complement or transform existing practices.What this paper addsThis paper clearly identifies which affordances of technology are commonly deployed in UDL implementations, particularly noting the provision of choice through multi‐media options for Representation and expression.There is a clear gap in UDL research on the use of technologies to support self‐regulation and self‐assessment, (eg, peer, teacher and automated feedback tools) and on technology‐mediated communication and collaboration.The UDL literature does not address the potential negative impacts of technology within the learning context or the short‐lived nature of positive impacts (novelty effect).Implications for practice and/or policyWhile technology affords great opportunities for choice and Engagement, the design of the learning experience must take priority, availing of technology as needed.There are great opportunities for cross‐pollination of research at the forefront of educational technology and universal design to address any gaps in technology use in UDL implementations. [ABSTRACT FROM AUTHOR]

As online education continues to proliferate that there is a need to understand how institutions can better support faculty in the transition to online education. Building on work that has suggested the importance of learning spaces for faculty to engage in discussion and reflection on their move to online education, this paper employs Bakhtin's notion of ideological becoming to provide a theoretically grounded understanding of how the design of such spaces can better facilitate this move. The paper reveals how learning spaces designed to develop critical awareness empower faculty to navigate discourses of online education, enabling them to build on their existing knowledge and skills as educators. The findings reveal how engaging faculty in critical dialogue can enable a cumulative shift in thinking from discussions dominated by authoritative discourses of online education that create an initial confusion between performance and pedagogy to the development of critical awareness that enables them to challenge dominant discourses and reconnect with the self as an experienced educator. The paper provides an important insight into an approach that might enable institutions to better support faculty buy‐in and acceptance of online education. Practitioner NotesWhat is already known about this topicInstitutions struggle to understand how best to engage faculty in the transition to online education.A number of frameworks and models have been proposed to facilitate the transition, but these mostly take a managerial perspective.The transition to online teaching is most effective when supported by opportunities for faculty to engage in critical reflection and discussion.Less is known about how opportunities for critical reflection support the transition process and there is a need to theoretically ground such understanding.What this paper addsThe paper draws on Bakhtin's notion of ideological becoming to explore how learning spaces for educator discussion and reflection can be used to facilitate the transition process.The findings show how learning spaces can be designed to enable faculty to develop the skills to navigate and challenge dominant discourses of online learning.The development of critical awareness among educators can also facilitate the development of educational practices for both classroom and online teaching.Implications for practice and/or policyThe transition to online education is not an individual activity, but a collaborative and dialogical process.Faculty need time and space to critically challenge dominant discourses of online education and to re‐establish their existing skills and experience within an online context.This should not be a one‐off event but an ongoing process and conversation in a constantly changing and evolving higher education context.At the policy level, we should not expect online educational practice to be based on one approach or model, but to celebrate individuality and innovation. [ABSTRACT FROM AUTHOR]