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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]

Augmented reality (AR) games offer significant potential to enhance learning experiences, yet the impact of when these games are introduced during the educational process remains underexplored. This study explored how the timing of providing the AR game influenced learners' achievement, satisfaction and acceptance. Using a quasi‐experimental design, 68 second‐graders engaged with the AR game AR Easy Sign Language: Grams and Kilograms, either before class or in class. Additionally, perspectives from eight students, one teacher and 24 parents (from the before‐class group) were collected. Results indicated that providing the AR game in class significantly improved learners' achievement and acceptance compared to providing it before class. While overall satisfaction was unaffected by timing, students' cognitive focus differed: in‐class participants emphasised the game's educational value, whereas those using it before class viewed it more as an entertaining tool with educational functionality. Both the teacher and parents acknowledged the educational value of AR games but expressed concerns regarding the cost and potential health issues. This study contributes to theoretical understanding and practical implementation strategies for AR games in education, particularly in optimising their timing for maximal impact. Practitioner notes What is already known about this topic AR games integrate the advantages of augmented reality and games, enabling learners to interact with virtual and physical objects in a fun way, bringing a new dynamic to education. Prior research has shown that AR games contribute to the improved learning process and learning outcomes. However, applying technologies such as AR games to authentic educational contexts is still challenging, as it involves many decision‐making issues to be investigated. One key issue that remains unresolved is determining the optimal timing of providing AR games. What this paper adds Providing AR games in class significantly enhanced students' learning achievement and acceptance, emphasising the need to carefully time such interventions. The timing of providing AR games influenced students' cognition, with in‐class use promoting a focus on learning, while before‐class use emphasised entertainment. Teachers and parents acknowledged the educational value of AR games for students, but they had concerns regarding potential visual health risks and the associated costs. Implications for practice and/or policy Educators should determine the timing of providing AR games depending on the desired goal. Providing AR games before class allows students to focus more on the game experience while providing AR games in class allows for a focus on learning through the game and enhancing learning achievement. Students' cognition of technology may influence their usage and outcomes. Developers should design AR games with mechanisms that guide learners' cognition of educational content, while researchers should explore the effectiveness of such designs to achieve better learning outcomes. Educational institutions should select devices with built‐in eye protection features and enforce screen time limits to mitigate visual health risks, addressing concerns raised by teachers and parents. AR games incorporating sign language have the potential to improve students' learning achievement, holding promise for applications in special education. What is already known about this topic AR games integrate the advantages of augmented reality and games, enabling learners to interact with virtual and physical objects in a fun way, bringing a new dynamic to education. Prior research has shown that AR games contribute to the improved learning process and learning outcomes. However, applying technologies such as AR games to authentic educational contexts is still challenging, as it involves many decision‐making issues to be investigated. One key issue that remains unresolved is determining the optimal timing of providing AR games. What this paper adds Providing AR games in class significantly enhanced students' learning achievement and acceptance, emphasising the need to carefully time such interventions. The timing of providing AR games influenced students' cognition, with in‐class use promoting a focus on learning, while before‐class use emphasised entertainment. Teachers and parents acknowledged the educational value of AR games for students, but they had concerns regarding potential visual health risks and the associated costs. Implications for practice and/or policy Educators should determine the timing of providing AR games depending on the desired goal. Providing AR games before class allows students to focus more on the game experience while providing AR games in class allows for a focus on learning through the game and enhancing learning achievement. Students' cognition of technology may influence their usage and outcomes. Developers should design AR games with mechanisms that guide learners' cognition of educational content, while researchers should explore the effectiveness of such designs to achieve better learning outcomes. Educational institutions should select devices with built‐in eye protection features and enforce screen time limits to mitigate visual health risks, addressing concerns raised by teachers and parents. AR games incorporating sign language have the potential to improve students' learning achievement, holding promise for applications in special education. [ABSTRACT FROM AUTHOR]

High dropout rates in online courses, caused by potential factors such as financial issues, low motivation and poor self‐regulation among learners, pose a significant challenge to the sustainable development of online education. Therefore, continuance of online courses has become a critical topic in both the academic and practical fields. By combining the Community of Inquiry framework (CoI) with Expectation‐Confirmation Theory, this study introduces three new constructs—confirmed teaching presence (CTP), confirmed cognitive presence (CCP) and confirmed social presence (CSP)—into the research model to understand how confirmed expectations towards CoI determine online learners' course continuance intention. Utilizing a mixed‐methods approach, the study conducted quantitative analysis on 409 learner surveys using partial least squares (PLS), followed by semi‐structured interviews, which revealed the depth and breadth of the confirmed CoI expectations on learners' willingness to continue learning. Specifically, the quantitative results uncovered the differential effects of CTP, CCP and CSP on learners' course continuance intentions by elucidating the internal mechanisms. The interviews provided deeper insights by illuminating online learners' initial expectations as well as their pre‐course and post‐course expectations. The findings of the study not only provide evidence of the crucial role of confirmed expectations in shaping online learners' course continuance intention but also offer actionable recommendations for improving online course design and fostering lifelong learning. Practitioner notes What is already known about this topic Online courses have expanded in scale and attracted a large number of learners in recent years, the large base of online learners has brought tremendous and unprecedented challenges to online course development. A high dropout rate is especially considered as a severe issue for online course development. The issue of learners' continuance intention was often explored from a technological perspective and at the platform level by using Information system (IS) theories. The community of inquiry (CoI) framework was extensively utilized as a theoretical basis for understanding online learning experiences and its three elements—teaching, cognitive and social presences—have long been deemed as major antecedents that influence learners' online learning behaviours and intentions. What this paper adds This paper integrated the community of inquiry (CoI) framework with Expectation confirmation theory and proposed three new variables: confirmed teaching presence (CTP), confirmed cognitive presence (CCP) and confirmed social presence (CSP). The study reveals the internal mechanisms by which the three confirmed expectations impact online learners' courses continuance intention. This implies that different confirmed expectations may have varying effects on online learners' learning behaviour. This research collects data from multiple sources to comprehensively explore online learners' expectations and perceptions. It also sheds light on the importance of learners' actual participation in the learning process for predicting their behavioural intentions. Implications for practice and/or policy The finding that learners' confirmed expectations impact their online course continuance intention conveys an important message to course practitioners: exaggerated or false claims for the online course must be avoided to prevent students from forming unrealistic expectations. Improving online learners' course completion rate cannot be hinged upon simply and blindly fostering and extending the three presences. Instead, knowing learners' confirmed expectations of the three presences allows course practitioners to reconsider and organize the important course elements. The research reveals the distinct role that each confirmed presence plays in promoting online learners' course continuance intention and, meanwhile, expands the understanding of learners' learning needs and experiences. Practitioners could make timely and appropriate strategies based on these to better motivate course learners' engagement and retention. What is already known about this topic Online courses have expanded in scale and attracted a large number of learners in recent years, the large base of online learners has brought tremendous and unprecedented challenges to online course development. A high dropout rate is especially considered as a severe issue for online course development. The issue of learners' continuance intention was often explored from a technological perspective and at the platform level by using Information system (IS) theories. The community of inquiry (CoI) framework was extensively utilized as a theoretical basis for understanding online learning experiences and its three elements—teaching, cognitive and social presences—have long been deemed as major antecedents that influence learners' online learning behaviours and intentions. What this paper adds This paper integrated the community of inquiry (CoI) framework with Expectation confirmation theory and proposed three new variables: confirmed teaching presence (CTP), confirmed cognitive presence (CCP) and confirmed social presence (CSP). The study reveals the internal mechanisms by which the three confirmed expectations impact online learners' courses continuance intention. This implies that different confirmed expectations may have varying effects on online learners' learning behaviour. This research collects data from multiple sources to comprehensively explore online learners' expectations and perceptions. It also sheds light on the importance of learners' actual participation in the learning process for predicting their behavioural intentions. Implications for practice and/or policy The finding that learners' confirmed expectations impact their online course continuance intention conveys an important message to course practitioners: exaggerated or false claims for the online course must be avoided to prevent students from forming unrealistic expectations. Improving online learners' course completion rate cannot be hinged upon simply and blindly fostering and extending the three presences. Instead, knowing learners' confirmed expectations of the three presences allows course practitioners to reconsider and organize the important course elements. The research reveals the distinct role that each confirmed presence plays in promoting online learners' course continuance intention and, meanwhile, expands the understanding of learners' learning needs and experiences. Practitioners could make timely and appropriate strategies based on these to better motivate course learners' engagement and retention. [ABSTRACT FROM AUTHOR]

Secondary school students (N = 269) participated in a daylong visual programming course held in a stimulating environment for start‐up enterprises. The tasks were application‐oriented and partly creative. For example, a wearable device with light‐emitting diodes, (ie, LEDs) could be applied to a T‐shirt and used for optical messages. Our research questions related to the control‐value model of achievement emotions. We measured experienced enjoyment four times and examined the dependence of enjoyment on the individual tasks. Experience of enjoyment was also tested for the prediction of students' self‐efficacy for programming. The results showed that momentary enjoyment was not significantly dependent on the task situation, but it was dependent on the general enjoyment of programming. However, students with lower enjoyment scores showed higher increases in enjoyment during the final tasks than those with higher initial scores. The emotion score of the girls increased more than those of the boys but the girls' overall enjoyment scores were lower than those of the boys. Students' self‐efficacy beliefs of both genders increased over the course, and some of the differences in beliefs can be explained by the enjoyment of the course. In conclusion, our teaching approach seemed beneficial for the motivation to learn programming, particularly among girls. Practitioner notes What is already known about this topic Lower secondary students often report a lack of self‐efficacy beliefs for visual programming, especially girls whose confidence in their abilities seems to be missing. Activities that show how programming can be used in everyday life or at work promote interest and enjoyment, especially among girls. What this paper adds Experiencing enjoyment did not depend on individual task types (more structured vs. more open), but proved to be stable across all tasks. The experience of positive emotions in our computer science course had an impact on the secondary school students' self‐efficacy beliefs. Implications for practice and/or policy The combination of smart textiles and programming was viewed as a motivating learning experience with the potential to foster secondary school students' confidence and problem‐solving skills in computer science. A guided sequence of learning to debug can provide a self‐enhancing foundation for the students' own activities with following tasks that are more open and creative approaches. What is already known about this topic Lower secondary students often report a lack of self‐efficacy beliefs for visual programming, especially girls whose confidence in their abilities seems to be missing. Activities that show how programming can be used in everyday life or at work promote interest and enjoyment, especially among girls. What this paper adds Experiencing enjoyment did not depend on individual task types (more structured vs. more open), but proved to be stable across all tasks. The experience of positive emotions in our computer science course had an impact on the secondary school students' self‐efficacy beliefs. Implications for practice and/or policy The combination of smart textiles and programming was viewed as a motivating learning experience with the potential to foster secondary school students' confidence and problem‐solving skills in computer science. A guided sequence of learning to debug can provide a self‐enhancing foundation for the students' own activities with following tasks that are more open and creative approaches. [ABSTRACT FROM AUTHOR]

Recent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open‐ended environments. AI systems are known to underperform humans in (1) interpreting students' emotions in learning contexts, (2) grasping the nuances of social interactions and (3) understanding domain‐specific information that was not well‐represented in the training data. As such, combined human and AI (ie, hybrid) approaches are needed to overcome the current limitations of AI systems. In this paper, we take a first step towards investigating how a human‐AI collaboration between teachers and researchers using an AI‐generated multimodal timeline can guide and support teachers' feedback while addressing students' STEM+C difficulties as they work collaboratively to build computational models and solve problems. In doing so, we present a framework characterizing the human component of our human‐AI partnership as a collaboration between teachers and researchers. To evaluate our approach, we present our timeline to a high school teacher and discuss the key insights gleaned from our discussions. Our case study analysis reveals the effectiveness of an iterative approach to using human‐AI collaboration to address students' STEM+C challenges: the teacher can use the AI‐generated timeline to guide formative feedback for students, and the researchers can leverage the teacher's feedback to help improve the multimodal timeline. Additionally, we characterize our findings with respect to two events of interest to the teacher: (1) when the students cross a difficulty threshold, and (2) the point of intervention, that is, when the teacher (or system) should intervene to provide effective feedback. It is important to note that the teacher explained that there should be a lag between (1) and (2) to give students a chance to resolve their own difficulties. Typically, such a lag is not implemented in computer‐based learning environments that provide feedback. Practitioner notes What is already known about this topic Collaborative, open‐ended learning environments enhance students' STEM+C conceptual understanding and practice, but they introduce additional complexities when students learn concepts spanning multiple domains. Recent advances in generative AI and MMLA allow for integrating multiple datastreams to derive holistic views of students' states, which can support more informed feedback mechanisms to address students' difficulties in complex STEM+C environments. Hybrid human‐AI approaches can help address collaborating students' STEM+C difficulties by combining the domain knowledge, emotional intelligence and social awareness of human experts with the general knowledge and efficiency of AI. What this paper adds We extend a previous human‐AI collaboration framework using a hybrid intelligence approach to characterize the human component of the partnership as a researcher‐teacher partnership and present our approach as a teacher‐researcher‐AI collaboration. We adapt an AI‐generated multimodal timeline to actualize our human‐AI collaboration by pairing the timeline with videos of students encountering difficulties, engaging in active discussions with a high school teacher while watching the videos to discern the timeline's utility in the classroom. From our discussions with the teacher, we define two types of inflection points to address students' STEM+C difficulties—the difficulty threshold and the intervention point—and discuss how the feedback latency interval separating them can inform educator interventions. We discuss two ways in which our teacher‐researcher‐AI collaboration can help teachers support students encountering STEM+C difficulties: (1) teachers using the multimodal timeline to guide feedback for students, and (2) researchers using teachers' input to iteratively refine the multimodal timeline. Implications for practice and/or policy Our case study suggests that timeline gaps (ie, disengaged behaviour identified by off‐screen students, pauses in discourse and lulls in environment actions) are particularly important for identifying inflection points and formulating formative feedback. Human‐AI collaboration exists on a dynamic spectrum and requires varying degrees of human control and AI automation depending on the context of the learning task and students' work in the environment. Our analysis of this human‐AI collaboration using a multimodal timeline can be extended in the future to support students and teachers in additional ways, for example, designing pedagogical agents that interact directly with students, developing intervention and reflection tools for teachers, helping teachers craft daily lesson plans and aiding teachers and administrators in designing curricula. What is already known about this topic Collaborative, open‐ended learning environments enhance students' STEM+C conceptual understanding and practice, but they introduce additional complexities when students learn concepts spanning multiple domains. Recent advances in generative AI and MMLA allow for integrating multiple datastreams to derive holistic views of students' states, which can support more informed feedback mechanisms to address students' difficulties in complex STEM+C environments. Hybrid human‐AI approaches can help address collaborating students' STEM+C difficulties by combining the domain knowledge, emotional intelligence and social awareness of human experts with the general knowledge and efficiency of AI. What this paper adds We extend a previous human‐AI collaboration framework using a hybrid intelligence approach to characterize the human component of the partnership as a researcher‐teacher partnership and present our approach as a teacher‐researcher‐AI collaboration. We adapt an AI‐generated multimodal timeline to actualize our human‐AI collaboration by pairing the timeline with videos of students encountering difficulties, engaging in active discussions with a high school teacher while watching the videos to discern the timeline's utility in the classroom. From our discussions with the teacher, we define two types of inflection points to address students' STEM+C difficulties—the difficulty threshold and the intervention point—and discuss how the feedback latency interval separating them can inform educator interventions. We discuss two ways in which our teacher‐researcher‐AI collaboration can help teachers support students encountering STEM+C difficulties: (1) teachers using the multimodal timeline to guide feedback for students, and (2) researchers using teachers' input to iteratively refine the multimodal timeline. Implications for practice and/or policy Our case study suggests that timeline gaps (ie, disengaged behaviour identified by off‐screen students, pauses in discourse and lulls in environment actions) are particularly important for identifying inflection points and formulating formative feedback. Human‐AI collaboration exists on a dynamic spectrum and requires varying degrees of human control and AI automation depending on the context of the learning task and students' work in the environment. Our analysis of this human‐AI collaboration using a multimodal timeline can be extended in the future to support students and teachers in additional ways, for example, designing pedagogical agents that interact directly with students, developing intervention and reflection tools for teachers, helping teachers craft daily lesson plans and aiding teachers and administrators in designing curricula. [ABSTRACT FROM AUTHOR]

Although education is framed as a future‐oriented enterprise, we often fail to serve the diverse futurities of youth, particularly in formal learning environments. The cultural norms of formal learning environments are rooted in dominant ways of being and knowing and this shapes how learning environments and learning technologies can be designed. As a result, the futures youth can envision for themselves in these spaces are often static and limited by the dominant culture. As a move toward supporting youths' diverse cultural backgrounds and experiences, we ask how youth develop relationship with culture through creating culturally centred multimedia projects. Guided by a case study approach, we collected thirty‐six remixing multimedia projects from twelve sixth graders, who created these projects for three culturally centred learning activities over a school year. Findings share one case from each learning activity to demonstrate how students represent their relationships with culture through three forms of symbolising. Implications from this work reject the settled expectations of dominant culture in formal learning environments and, instead, invite youths' knowledges and experiences through remixing with multimedia. Practitioner notes What is already known about this topic Formal learning environments are shaped by norms rooted in the dominant culture but are often assumed to be acultural spaces. Multimedia technologies have been leveraged to engage youth with culture in the classroom. Remixing is a sociocultural learning process that allows youth to reimagine their lived experiences. What this paper adds Sixth graders' relationships with culture were mediated by remixing with multimedia resources in a series of culturally centred multimedia projects. Forms of symbolising in students' remixing works reveal diverse relationships with their own culture and other cultures. Culturally centred multimedia projects afford the development of intertwined and reciprocal relationships with one's own culture and other cultures. Implications for practice Formal learning environments and embedded learning activities often operate on static or limited relationships between youth and their diverse range of cultural experiences. Engaging with multimedia projects can develop students' relationships with their own culture and other cultures in a reciprocal way. Supporting the development of diverse relationships with culture is crucial to designing a culturally centred learning environment. What is already known about this topic Formal learning environments are shaped by norms rooted in the dominant culture but are often assumed to be acultural spaces. Multimedia technologies have been leveraged to engage youth with culture in the classroom. Remixing is a sociocultural learning process that allows youth to reimagine their lived experiences. What this paper adds Sixth graders' relationships with culture were mediated by remixing with multimedia resources in a series of culturally centred multimedia projects. Forms of symbolising in students' remixing works reveal diverse relationships with their own culture and other cultures. Culturally centred multimedia projects afford the development of intertwined and reciprocal relationships with one's own culture and other cultures. Implications for practice Formal learning environments and embedded learning activities often operate on static or limited relationships between youth and their diverse range of cultural experiences. Engaging with multimedia projects can develop students' relationships with their own culture and other cultures in a reciprocal way. Supporting the development of diverse relationships with culture is crucial to designing a culturally centred learning environment. [ABSTRACT FROM AUTHOR]

Social media has been shown to be an efficient way to engage in networked participatory scholarship (NPS), which is defined as the use of online social networks to share and further develop scholarship. As leaders in the field, educational technology scholars should be at the forefront of this practice. We used social network analysis (SNA) to examine the structure and characteristics of the #TPACK Twitter network and to determine whether and how the users were engaging in value‐added NPS. Our findings revealed that the #TPACK Twitter network was loosely organized, and users were not very well connected outside of their clusters. Our findings also revealed that #TPACK tweets largely did not represent value‐added NPS. The majority of posts lacked useful context, were limited to merely sharing links to resources and did not establish meaningful interactions among users. The implications of this study provide a new direction for educational technology researchers and PK‐12 practitioners to approach social media from a value‐added standpoint and to apply value‐added NPS to improve their use of social media to advance research, enhance professional learning and forge closer ties between researchers and practitioners. Practitioner notes What is already known about this topic Publication in high‐impact academic journals and measuring research impact through citations and journal indexing is still the dominant practice in research dissemination; however, there is growth in the use of alternative methods and the use of altmetrics to measure the impact of these methods. Scholars struggle with using social media in ways that align with networked participatory scholarship (NPS). Social network analysis (SNA) is the study of the structure and characteristics of the relationships that form in social networks, and can be used to fanalyze an online social network. What this paper adds Value‐added social learning theory and NPS can be used in SNA to both evaluate and inform scholars' social media practices. Educational technology scholars and practitioners struggle with using social media for value‐added NPS. Lost opportunities for value‐added NPS that were documented in this study include lack of engagement with the wider network, not sharing the role of spreading ideas and not making value‐added contributions. Implications for practice and policy Education scholars should use SNA as a tool to evaluate the level of value‐added NPS in the social media networks around areas of study they care about so that they can develop both personal and systemic plans for implementing value‐added NPS to create more dynamic learning spaces on these platforms. Institutions should investigate ways they can remove barriers and incentivize value‐added NPS. Innovations in the dissemination of scholarship should involve helping scholars to develop the skills needed for successful value‐added NPS. What is already known about this topic Publication in high‐impact academic journals and measuring research impact through citations and journal indexing is still the dominant practice in research dissemination; however, there is growth in the use of alternative methods and the use of altmetrics to measure the impact of these methods. Scholars struggle with using social media in ways that align with networked participatory scholarship (NPS). Social network analysis (SNA) is the study of the structure and characteristics of the relationships that form in social networks, and can be used to fanalyze an online social network. What this paper adds Value‐added social learning theory and NPS can be used in SNA to both evaluate and inform scholars' social media practices. Educational technology scholars and practitioners struggle with using social media for value‐added NPS. Lost opportunities for value‐added NPS that were documented in this study include lack of engagement with the wider network, not sharing the role of spreading ideas and not making value‐added contributions. Implications for practice and policy Education scholars should use SNA as a tool to evaluate the level of value‐added NPS in the social media networks around areas of study they care about so that they can develop both personal and systemic plans for implementing value‐added NPS to create more dynamic learning spaces on these platforms. Institutions should investigate ways they can remove barriers and incentivize value‐added NPS. Innovations in the dissemination of scholarship should involve helping scholars to develop the skills needed for successful value‐added NPS. [ABSTRACT FROM AUTHOR]

The escape room game is an example of digital game‐based learning that has become a popular learning tool in recent years. However, not enough is known about enthusiasm for and promising reports of the use of escape rooms in education. The purpose of this study was to investigate the effects of escape room game‐based civics education on eighth grade students' learning motivation, critical thinking and flow experience. To explore the effects, a quasi‐experimental pretest–posttest with a control group design method was employed. The participants were 76 eighth grade students. The subjects were divided into two groups: the experimental group, which used an escape room game, and the control group which used the Google classroom digital platform. The results of the study indicated that there was a significant difference between the two groups in favour of the experimental group in terms of learning motivation. There was a significant difference between the two groups' critical thinking in favour of the experimental group for the ‘assumption’ and ‘interpretation’ subscales of the critical thinking test. Regarding flow experience, the experimental group performed significantly better than the control group. Finally, based on the research results, suggestions are made for the future use of escape room games for teaching and for future research. Practitioner notes What is already known about this topic Escape room games have substantial potential for enhancing learning, motivation and critical thinking. Studies promoting mental flow, integrating complex skills and using multiple strategies in a game context are limited. What this paper adds Students' mind flow experience and critical thinking were enhanced through escape room games. The escape room game made the learning process more varied, triggered students' interest, and improved their learning motivation. This study compared the effect of escape room game‐based learning with the Google Classroom platform, not the traditional teaching approach. Implications for practice and/or policy Escape room games offer learners innovative opportunities to develop critical thinking skills. Using an appropriately designed escape room as a game‐based learning environment is an effective and motivating game‐based learning approach. The realistic and interactive nature of escape room games is an important factor that influences learners' mind‐flow experiences. What is already known about this topic Escape room games have substantial potential for enhancing learning, motivation and critical thinking. Studies promoting mental flow, integrating complex skills and using multiple strategies in a game context are limited. What this paper adds Students' mind flow experience and critical thinking were enhanced through escape room games. The escape room game made the learning process more varied, triggered students' interest, and improved their learning motivation. This study compared the effect of escape room game‐based learning with the Google Classroom platform, not the traditional teaching approach. Implications for practice and/or policy Escape room games offer learners innovative opportunities to develop critical thinking skills. Using an appropriately designed escape room as a game‐based learning environment is an effective and motivating game‐based learning approach. The realistic and interactive nature of escape room games is an important factor that influences learners' mind‐flow experiences. [ABSTRACT FROM AUTHOR]

Preparing preservice teachers (PSTs) to be able to notice, interpret, respond to and orchestrate student ideas—the core practices of responsive teaching—is a key goal for contemporary science and mathematics teacher education. This mixed‐methods study, employing a virtual reality (VR)‐supported simulation integrated with artificial intelligence (AI)‐powered virtual students, explored the frequent patterns of PSTs' talk moves as they attempted to orchestrate a responsive discussion, as well as the affordances and challenges of leveraging AI‐supported virtual simulation to enhance PSTs' responsive teaching skills. Sequential analysis of the talk moves of both PSTs (n = 24) and virtual students indicated that although PSTs did employ responsive talk moves, they encountered difficulties in transitioning from the authoritative, teacher‐centred teaching approach to a responsive way of teaching. The qualitative analysis with triangulated dialogue transcripts, observational field notes and semi‐structured interviews revealed participants' engagement in (1) orchestrating discussion by leveraging the design features of AI‐supported simulation, (2) iterative rehearsals through naturalistic and contextualized interactions and (3) exploring realism and boundaries in AI‐powered virtual students. The study findings provide insights into the potential of leveraging AI‐supported virtual simulation to improve PSTs' responsive teaching skills. The study also underscores the need for PSTs to engage in well‐designed pedagogical practices with adaptive and in situ support. Practitioner notes What is already known about this topic Developing the teaching capacity of responsive teaching is an important goal for preservice teacher (PST) education. PSTs need systematic opportunities to build fluency in this approach. Virtual simulations can provide PSTs with the opportunities to practice interactive teaching and have been shown to improve their teaching skills. Artificial intelligence (AI)‐powered virtual students can be integrated into virtual simulations to enable interactive and authentic practice of teaching. What this paper adds AI‐supported simulation has the potential to support PSTs' responsive teaching skills. While PSTs enact responsive teaching talk moves, they struggle to enact those talk moves in challenging teaching scenarios due to limited epistemic and pedagogical resources. AI‐supported simulation affords iterative and contextualized opportunities for PSTs to practice responsive teaching talk moves; it challenges teachers to analyse student discourse and respond in real time. Implications for practice and/or policy PSTs should build a teaching repertoire with both basic and advanced responsive talk moves. The learning module should adapt to PSTs' prior experience and provide PSTs with in situ learning support to navigate challenging teaching scenarios. Integrating interaction features and AI‐based virtual students into the simulation can facilitate PSTs' active participation. What is already known about this topic Developing the teaching capacity of responsive teaching is an important goal for preservice teacher (PST) education. PSTs need systematic opportunities to build fluency in this approach. Virtual simulations can provide PSTs with the opportunities to practice interactive teaching and have been shown to improve their teaching skills. Artificial intelligence (AI)‐powered virtual students can be integrated into virtual simulations to enable interactive and authentic practice of teaching. What this paper adds AI‐supported simulation has the potential to support PSTs' responsive teaching skills. While PSTs enact responsive teaching talk moves, they struggle to enact those talk moves in challenging teaching scenarios due to limited epistemic and pedagogical resources. AI‐supported simulation affords iterative and contextualized opportunities for PSTs to practice responsive teaching talk moves; it challenges teachers to analyse student discourse and respond in real time. Implications for practice and/or policy PSTs should build a teaching repertoire with both basic and advanced responsive talk moves. The learning module should adapt to PSTs' prior experience and provide PSTs with in situ learning support to navigate challenging teaching scenarios. Integrating interaction features and AI‐based virtual students into the simulation can facilitate PSTs' active participation. [ABSTRACT FROM AUTHOR]

Previous literature has associated math literacy with linguistic factors such as verbal ability and phonological skills. However, few studies have investigated linguistic synchrony, shown in mathematical discussions. This study modelled math literacy and examined the relationship of math literacy with linguistic synchrony between students and facilitators. We retrieved data from 20,776 online mathematical discussion threads at a secondary school level. First, we assessed students' math literacy based on their discussions and classified them into high‐ and low‐math literacy groups. Then, we conducted Cross‐Recurrence Quantification Analysis (CRQA) to calculate linguistic synchrony within each thread. The result implies that students with high math literacy are more likely to share common words (eg, mathematical terms) with facilitators. At the same time, they would paraphrase the facilitators' words rather than blindly mimic them as the exact sentences or phrases. On the other hand, students with low math literacy tend to use overlapping words with facilitators less frequently and are more likely to repeat the exact same phrases from the facilitators. The findings provide an empirical data analysis and insights into mathematical discussions and linguistic synchrony. In addition, this paper implies the directions to improve online mathematical discussions and foster math literacy. Practitioner notesWhat is already known about this topic Mathematical discussions are known to be an effective way to promote math literacy.Math literacy and linguistic skills have a strong link.Linguistic synchrony is related to better collaboration and common knowledge building.What this paper adds Reveals the relationship between math literacy and linguistic synchrony and deepens the understanding of digital communication in online learning environments.Provides empirical analysis of natural language data in group discussions using CRQA.Conceptualizes linguistic synchrony with three sub‐concepts: linguistic concurrence, predictability, and complexity.Implications for practice and/or policy Educators and practitioners could utilize the automatic formative assessment of math literacy based on the student's language use in mathematical discussions.Educational technology researchers and designers could include CRQA indices and recurrence plots in the dashboard design to provide information to support teachers and learners.Teachers would be able to provide real‐time interventions to promote effective mathematical communication and foster math literacy throughout mathematical discussions. [ABSTRACT FROM AUTHOR]

In this crossover experiment, we investigated the impact of a statement bank, enabling the reuse of previously written feedback (SA condition), on 45 math teachers' feedback for 60 completed linear equation tests, compared to traditional pen‐and‐paper feedback (PP condition). In the SA condition, teachers were encouraged to use atomic feedback, a set of formulation requirements that makes feedback items significantly more reusable. A previous study found that significantly more feedback was written in the SA condition but did not investigate the content of the feedback. To address this gap, we employed a novel approach of combining text mining with qualitative methods. Results indicate similar wording and sentiments in both conditions. However, SA feedback was more elaborate yet general, focusing on major and minor strengths and deficits, while PP feedback was shorter but more concrete, emphasising main issues. Despite low feedback quality in both conditions, the statement bank led to less effective diagnostic activities, implying that teachers' careless use of statement banks, although convenient, might lead to lower‐quality feedback. Practitioner notesWhat is already known about this topic High‐quality feedback should strike a balance between the volume and focus on the main issues, as more feedback does not necessarily equate to better feedback. Feedback should analyse a student's solution whenever possible: interpreting mistakes and communicating that interpretation as feedback.Text mining identifies meaningful patterns and new insights in text using computer algorithms.When teachers can reuse already given feedback using a software tool (statement bank), they tend to write more feedback instead of saving time.What this paper adds Feedback is compared when teachers could use a tool to reuse already given feedback (referred to as 'statement banks') versus a scenario without such a tool. Both approaches observed similar word frequencies, sentiments and amounts of erroneous, descriptive and corrective feedback. However, feedback with a statement bank tended to be more elaborate yet less specific to individual student solutions. In contrast, feedback without the tool was shorter but more concrete, focusing on main issues. Overall, the tool for reusing feedback directed teachers towards less effective diagnostic activities.The paper introduces a novel methodological approach by combining text mining with qualitative techniques in educational research. While text mining provides an overall understanding of differences and similarities in feedback approaches, qualitative methods are essential for in‐depth analysis of content characteristics and feedback quality.Implications for practice and/or policy Statement banks can support teachers by giving more feedback, but in order to improve feedback quality, further measures are necessary (eg, improving pedagogical content knowledge).Teachers may not confuse handiness with quality: statement banks can help, but when used carelessly, teachers tend to describe and correct students' work instead of analysing underlying (mis‐)conceptions using it. Continued attention to feedback quality remains necessary when using such tools. [ABSTRACT FROM AUTHOR]

Educational outcomes from traditionally underrepresented groups are generally worse than for their more advantaged peers. This problem is typically known as the awarding gap (we use the term awarding gap over 'attainment gap' as attainment places the responsibility on students to attain at equal levels) and continues to pose a challenge for educational systems across the world. While Learning Analytics (LA) dashboards help identify patterns contributing to the awarding gap, they often lack stakeholder involvement, offering very little support to institutional Equality, Diversity and Inclusion (EDI) leads or educators to pinpoint and address these gaps. This paper introduces an innovative EDI LA dashboard, co‐created with diverse stakeholders. Rigorously evaluated, the dashboard provides fine‐grained insights and course‐level analysis, empowering institutions to effectively address awarding gaps and contribute to a diverse and inclusive higher education landscape. Practitioners notesWhat is already known about this topic Traditionally underrepresented groups face educational disparities, commonly known as the awarding gap.Underachievement is a complex multi‐dimensional problem and cannot be solely attributable to individual student deficiencies.LA dashboards targeting this specific problem are often not public, there is little research about them, and are frequently designed with little involvement of educational stakeholders.What this paper adds Pioneers the introduction of a dashboard specifically designed to address the awarding gap problem.Emphasises the significant data needs of educational stakeholders in tackling awarding gaps.Expands the design dimensions of Learning Analytics (LA) by introducing a specific design approach rooted in established user experience (UX) design methods.Implications for practice and/or policy Insights from this study will guide practitioners, designers, and developers in creating AI‐based educational systems to effectively target the awarding gap problem. [ABSTRACT FROM AUTHOR]

A key goal of educational institutions around the world is to provide inclusive, equitable quality education and lifelong learning opportunities for all learners. Achieving this requires contextualized approaches to accommodate diverse global values and promote learning opportunities that best meet the needs and goals of all learners as individuals and members of different communities. Advances in learning analytics (LA), natural language processes (NLP), and artificial intelligence (AI), especially generative AI technologies, offer potential to aid educational decision making by supporting analytic insights and personalized recommendations. However, these technologies also raise serious risks for reinforcing or exacerbating existing inequalities; these dangers arise from multiple factors including biases represented in training datasets, the technologies' abilities to take autonomous decisions, and processes for tool development that do not centre the needs and concerns of historically marginalized groups. To ensure that Educational Decision Support Systems (EDSS), particularly AI‐powered ones, are equipped to promote equity, they must be created and evaluated holistically, considering their potential for both targeted and systemic impacts on all learners, especially members of historically marginalized groups. Adopting a socio‐technical and cultural perspective is crucial for designing, deploying, and evaluating AI‐EDSS that truly advance educational equity and inclusion. This editorial introduces the contributions of five papers for the special section on advancing equity and inclusion in educational practices with AI‐EDSS. These papers focus on (i) a review of biases in large language models (LLMs) applications offers practical guidelines for their evaluation to promote educational equity, (ii) techniques to mitigate disparities across countries and languages in LLMs representation of educationally relevant knowledge, (iii) implementing equitable and intersectionality‐aware machine learning applications in education, (iv) introducing a LA dashboard that aims to promote institutional equality, diversity, and inclusion, and (v) vulnerable student digital well‐being in AI‐EDSS. Together, these contributions underscore the importance of an interdisciplinary approach in developing and utilizing AI‐EDSS to not only foster a more inclusive and equitable educational landscape worldwide but also reveal a critical need for a broader contextualization of equity that incorporates the socio‐technical questions of what kinds of decisions AI is being used to support, for what purposes, and whose goals are prioritized in this process. [ABSTRACT FROM AUTHOR]

This article discusses the field of Learning Analytics and the need for practical applications and evidence of its effectiveness in real learning environments. The article presents six papers that cover a range of academic disciplines and utilize different types of data. The first group of papers focuses on traditional data sources and aims to identify students who need assistance and provide guidance to improve their learning processes. The second group of papers utilizes data from various sources, such as physical and physiological signals, to enhance the understanding and improvement of interactions during collaborative work and learning. The article concludes by stating that this special section provides a starting point for those interested in reproducible ideas and validated tools in the field of Learning Analytics. [Extracted from the article]

Despite the importance of academic counselling for student success, providing timely and personalized guidance can be challenging for higher education institutions. In this study, we investigate the impact of counselling instances supported by a learning analytics (LA) tool, called TrAC, which provides specific data about the curriculum and grades of each student. To evaluate the tool, we measured changes in students' performance ranking position over 3 years and compared the performance of students who received counselling with and without the tool. Our results show that using the tool is related to an improvement in cohort ranking. We further investigated the characteristics of counselled students using cluster analyses. The findings highlight the potential beneficial influence on academic outcomes arising from the provision of guidance to students regarding their course load decisions via TrAC‐mediated counselling. This study contributes to the field of LA by providing evidence of the impact of counselling supported by an LA tool in a real‐world setting over a long period of time. Our results suggest that incorporating LA into academic counselling practices can improve student success. Practitioner notesWhat is already known about this topic By analysing student performance, teaching strategies and resource impact, learning analytics (LA) empowers institutions to make informed changes in curriculum design, resource allocation and educational policies.Through insights into academic progress, engagement and behaviour, LA counselling tools enable the identification of at‐risk students and those needing additional support.In the related literature, there are areas for further exploration such as understanding the scalability and long‐term effects of interventions on student success and retention.What this paper adds Through rigorous data analysis, the paper establishes a connection between LA utilization and enhanced student performance, offering concrete evidence of the effectiveness of LA interventions.By examining various factors such as academic stage and course load, the research offers valuable insights into the contextual nuances that optimize the outcomes of LA tool‐based support.It adds to the growing body of evidence that supports the efficacy of data‐driven interventions in education, fostering a more informed and evidence‐based approach to student support and success.Implications for practice and policy Enhanced student support strategies: By tailoring counselling interventions to align with the identified effective conditions, educators can proactively address individual student needs, improving academic outcomes and retention rates.Informed decision making: The demonstrated positive impact highlights the potential of similar data‐driven initiatives to foster student success. Policymakers can consider incentivizing the adoption of such interventions at institutional levels.Future directions for research: By identifying contextual factors that influence the efficacy of LA interventions, it encourages further exploration into how other LA interventions can be optimized for specific conditions. This can guide the development of more precise and effective student support strategies in the future. [ABSTRACT FROM AUTHOR]

Collaborative learning, driven by knowledge co‐construction and meaning negotiation, is a pivotal aspect of educational contexts. While gesture's importance in conveying shared meaning is recognized, its role in collaborative group settings remains understudied. This gap hinders accurate and equitable assessment and instruction, particularly for linguistically diverse students. Advancements in multimodal learning analytics, leveraging sensor technologies, offer innovative solutions for capturing and analysing body movements. This study employs these novel approaches to demonstrate how learners' machine‐detected body movements during the learning process relate to their verbal and nonverbal contributions to the co‐construction of embodied math knowledge. These findings substantiate the feasibility of utilizing learners' machine‐detected body movements as a valid indicator for inferring their engagement with the collaborative knowledge construction process. In addition, we empirically validate that these inferred different levels of learner engagement indeed impact the desired learning outcomes of the intervention. This study contributes to our scientific understanding of multimodal approaches to knowledge expression and assessment in learning, teaching, and collaboration.Practitioner notesWhat is already known about this topicPrevious research emphasizes the importance of gestures as essential tools for constructing common ground and reflecting shared meaning‐making in learning and teaching contexts.The prior studies in multimodal learning analytics (MMLA) suggest that certain forms of body movements and postures can be differentiated based on the automatic detection of upper body joint locations.Empirical observations indicate that co‐thought gestures typically involve smaller hand or arms movement that are closer to the gesturer's body than co‐speech gestures used in interpersonal communication.What this paper addsThis paper fills the research gap by examining the use of gestures in collaborative learning, offering insights into how individuals contribute verbally and nonverbally to collaborative knowledge construction.This paper introduces the concept of using machine‐detected body movements as a viable proxy for inferring learners' engagement in collaborative knowledge‐building activities.Leverages sensor technologies for automatic detection of body movements, the innovative approach in this work seeks to overcome the time‐intensive and laborious process of manually coding gestures.Implications for practice and/or policyBy recognizing the potential significance of learners' body movements in indicating engagement levels with collaborative knowledge‐building activities, instructors can set up computer‐supported collaborative learning (CSCL) environments to enable capturing these movements.Given the crucial role of gestures in learning, teaching, and collaboration, educators can create more equitable formative assessment practices for linguistically diverse students by developing strategies that align with multimodal forms of knowledge expression.Research can expand beyond mathematics to explore the transferability of these findings to other subjects, helping educators create comprehensive pedagogical approaches that leverage multimodal interactions across disciplines. [ABSTRACT FROM AUTHOR]

The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In this paper, we explore the magnitude of the country and language divide in the leading open‐source and proprietary LLMs with respect to knowledge of K‐12 taxonomies in a variety of countries and their performance on tagging problem content with the appropriate skill from a taxonomy, an important task for aligning open educational resources and tutoring content with state curricula. We also experiment with approaches to narrowing the performance divide by enhancing LLM skill tagging performance across four countries (the USA, Ireland, South Korea and India–Maharashtra) for more equitable outcomes. We observe considerable performance disparities not only with non‐English languages but with English and non‐US taxonomies. Our findings demonstrate that fine‐tuning GPT‐3.5 with a few labelled examples can improve its proficiency in tagging problems with relevant skills or standards, even for countries and languages that are underrepresented during training. Furthermore, the fine‐tuning results show the potential viability of GPT as a multilingual skill classifier. Using both an open‐source model, Llama2‐13B, and a closed‐source model, GPT‐3.5, we also observe large disparities in tagging performance between the two and find that fine‐tuning and skill information in the prompt improve both, but the closed‐source model improves to a much greater extent. Our study contributes to the first empirical results on mitigating disparities across countries and languages with LLMs in an educational context. Practitioner notesWhat is already known about this topic Recent advances in generative AI have led to increased applications of LLMs in education, offering diverse opportunities.LLMs excel predominantly in English and exhibit a bias towards the US context.Automated content tagging has been studied using English‐language content and taxonomies.What this paper adds Investigates the country and language disparities in LLMs concerning knowledge of educational taxonomies and their performance in tagging content.Presents the first empirical findings on addressing disparities in LLM performance across countries and languages within an educational context.Improves GPT‐3.5's tagging accuracy through fine‐tuning, even for non‐US countries, starting from zero accuracy.Extends automated content tagging to non‐English languages using both open‐source and closed‐source LLMs.Implications for practice and/or policy Underscores the importance of considering the performance generalizability of LLMs to languages other than English.Highlights the potential viability of ChatGPT as a skill tagging classifier across countries. [ABSTRACT FROM AUTHOR]

This study investigated the added value of real‐time adaptive feedback on seventh graders' performances in tablet‐based geometry learning. To isolate the effects of the medium (ie, tablet) from those of the feedback, three groups were compared: paper‐and‐pencil, pen‐based tablet without feedback and pen‐based tablet with feedback. The feedback was provided by a tutoring system based on an artificial intelligence that automatically interpreted students' pen strokes on the screen. A total of 85 French students drew three geometric shapes, either on paper or on a tablet, and then performed a transfer task on paper. Results showed that using a tablet without feedback did not improve learning but seemed to enhance interest in the task compared to the paper‐and‐pencil group. Students in the tablet with feedback group performed significantly better than the other two groups on learning, as well as on transfer. This study was the first to combine media comparison and added‐value approaches to test the effects on students' geometry performances of using a new educational app on a pen‐based tablet in a naturalistic classroom environment. Results showed that it was not the medium used but the intelligent tutoring system‐based feedback that improved students' performance. Our data therefore indicate that artificial intelligence is a promising way of providing learners with real‐time adaptive feedback in order to improve their performances. Practitioner notesWhat is already known about this topic Previous meta‐analyses have investigated the effects of tablet‐based learning.Tablet computers have been proven to increase students' motivation.Yet, the influence of tablet computers on learning outcomes remains inconclusive.Other studies show that certain features of environments, such as feedback, have positive effects on learning.What this paper adds Most of the previous studies adopted a media comparison approach (paper‐ vs. tablet‐based instruction).We combine this approach with an added‐value approach by adding or not real‐time AI‐based feedback.Results showed that tablet use increased children's interest but not their learning outcomes.Feedback improved children's performance in a training task and a later transfer paper task.Implications for practice and/or policy Tablet computers can promote students' interest in the task during geometry instruction.App features play a critical role in improving students' learning.Specifically, IA‐based adaptive feedback helps children to perform better on a geometry task. [ABSTRACT FROM AUTHOR]

This study explored the influence of the dynamic assessment of human–computer interactive games on children's language potential. Thirty‐seven special children aged 3–7 years were selected to participate in the study. They were divided into three groups according to their scores on the Autism Behaviour Checklist: (1) a non‐autism group, (2) a suspected autism group and (3) an autism group. In two stages of static and dynamic assessment, all three groups of children completed language tests under the conditions of no mediated prompt and mediated prompts, and the data generated in the game interactions were processed and analysed. The findings suggest the following: (1) static assessment may ignore children's language potential, while dynamic assessment can measure and differentiate children's potential language development ability; (2) children with ASD need more mediation prompts and are more likely to complete tasks with explicit mediation prompts; (3) children with ASD have weaker language potential, and children with suspected ASD or non‐ASD children have homogeneous language potential; and (4) assessors should pay timely attention to and maintain children's learning status and psychological changes. This study demonstrates the importance of human–computer interactive games as a dynamic assessment tool to tap into children's language potential and to determine their proximal developmental zone, which has important implications for teachers in understanding groups with different language abilities. Practitioner notesWhat is already known about the topic? The traditional language assessment paradigm (static assessment) can only evaluate the learners' current language development ability, while the short‐term development potential may not be observed.Different prompts in the mediation strategy can be used as a quantitative assessment paradigm in dynamic assessment.Much of the dynamic assessment in children with ASD focuses on language vocabulary learning outcomes and lacks measurement or quantification of language potential.What this paper adds? Presents a method for the dynamic assessment of a human–computer interactive language game suitable for children aged 3–7 years with ASD.Quantifies the potential level of language skills in children with varying degrees of ASD.Objectively and dynamically compares differences in language development potential between different groups.In dynamic assessment, children's learning status and psychological changes should be paid attention to and maintained in time.Implications for practice, research or policy This paper provides a concrete example of how human–computer interactive games can be used to dynamically assess the language potential of children with ASD.These findings highlight the importance of progressive scaffolds (mediated prompts) in children's language learning, which can help children identify and solve problems in a timely manner.For educational developers, language intervention materials should be prepared in a way that encompasses the different levels of language skills of children with different disabilities, that is, within the individual's zone of proximal development. [ABSTRACT FROM AUTHOR]

Previous studies have substantiated the pivotal role of emotions and teachers in student learning, but the underlying mechanism of teachers and emotions on academic engagement remains underexplored. The present study examined the mediating role of teacher support in the relationship between foreign language learning anxiety (FLLA) and academic engagement in online classrooms. Participants were 415 Chinese university students who completed an online questionnaire. The findings of structural equation modelling indicated that teacher support had a partial mediation effect between FLLA and academic engagement. FLLA exhibited a significant negative impact on academic engagement, both directly and indirectly via perceived teacher support. Through both direct and indirect effects, FLLA could explain 44.8% of the variation in academic engagement and the mediation effect accounted for 47.3% of the total effect. The practical implication is that foreign language teachers should extend more support for learners during online learning, and provide learners with feedback adapted to their emotions. Practitioner notesWhat is already known about this topic Emotions have a significant impact on learners' engagement, and positive academic emotions facilitate students' engagement in the class.Students will be more engaged in learning when they perceive support from their teachers.Teacher support was an influential external predictor of students' mood swings.What this paper adds The structural equation modelling shows that teacher support served as a partial mediator between foreign language learning anxiety and academic engagement.Students' social engagement and perceived emotional support were found to have a greater impact on online foreign language learning.This paper further corroborates the relationship among the presences in the CoI framework.Implications for practice and/or policy Mitigating foreign language learning anxiety and improving teacher support are necessary for effective foreign language learning in future online classes.Teachers need to ensure continued intellectual support and provide more emotional support for learners.Teachers are recommended to deliver feedback that aligns with students' emotional state. [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]

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]

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]

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]

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]

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]

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]

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]

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]

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 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]

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]