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This study aims to describe preservice mathematics teacher knowledge of higher order thinking skills in terms of definition, Bloom's taxonomy level, curriculum, learning, and evaluation. This research is quantitative research with a survey method. and sample consisted of 248 preservice mathematics teachers in semesters VI-VIII of the Department of Mathematics Education, Nusa Cendana University, Timor University, and Wira Wacana Sumba University. The instrument used was a questionnaire about high order thinking skill (HOTS) which consisted of 105 statements. Data analysis used Likert's summeted rating, one sample test, Mann Whitney, Kruskall-Wallis tests, multiple linear regression test, and multivariate analyisis of variance (MANOVA) test. The results showed that the knowledge level of preservice mathematics teacher was in the good category. Based on gender differences, there was no significant difference in the average knowledge of preservice mathematics teacherabout HOTS, there was a significant difference in the average knowledge of preservice mathematics teacher about HOTS which is significant based on differences in academic ability and gender differences do not significantly affect knowledge about HOTS levels in Bloom's taxonomy, curriculum, and pedagogy while academic knowledge has a significant effect on HOTS knowledge of preservice teachers in almost all aspects except for pedagogy.

Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning process. However, most of the currently used techniques for evaluating cognitive levels rely on labour-intensive and time-consuming manual coding. In this study, we explore the machine learning (ML) algorithms and taxonomy of Bloom's cognitive levels to explore features that affect learner's cognitive level in online assessments and the ability to automatically predict learner's cognitive level and thus, come up with a recommendation or pedagogical intervention to improve learner's acquisition. The analysis of 15,182 learners' assessments of a specific learning concept affirms the effectiveness of our approach. We attain an accuracy of 82.21% using ML algorithms. These results are very encouraging and have implications for how automated cognitive-level analysis tools for online learning will be developed in the future.

The present study analyses the impoliteness of criticism over social status and distance, incorporating the concept of "levels of imposition." Criticism as a fundamental speech act is commonly used by people in the modern era, either in the digital world or the real world. It usually contains impoliteness if it embodies negative behavior, conveying criticism. This study belonged to an interlanguage pragmatics study and used forty participants from English language learners having Javanese backgrounds. It also applied the role play technique to take data to be analyzed using mixed method analysis. The data showed that the criticizer performed various impoliteness strategies in criticism, considering familiar and unfamiliar relationships in different social status levels. They mainly performed bald-on-record impoliteness and adhered to other strategies such as negative, positive, and mock politeness. Besides that, delivering criticism in high intonation was also perceived as a part of impoliteness. Therefore, it suggested conducting another research concerning paralinguistics and impoliteness in various communication contexts.

Learners' acquisition of pragmatic competence in additional languages has received mounting attention since the 1990s. However, although studies on general learning strategies have proliferated since Oxford's (1990) influential inventory was published, studies on pragmatic-specific learning strategies contributing to the acquisition of this competence are rare. To fill this research gap, the current study purported to inquire into the main pragmatic learning strategies used by English language learners across gender and language learning experience. To collect the data, 145 learners were interviewed. These participants' answers were audio-taped and transcribed. These extracted strategies were organized into six groupings of memory-related, cognitive, metacognitive, compensatory, social, and affective pragmatic learning strategies based on Cohen's (2005, 2010) pragmatic-specific categorization and Oxford's (1990) general language learning strategy classification. The analysis showed that those learners with longer experience used more pragmatic learning strategies; nonetheless, gender did result in great differences in employing these strategies. This study presents a new categorization for pragmatic learning strategies, which can be used for more effective pragmatic learning strategy teaching and learning.

In this study, it was aimed to develop an achievement test taking into account the subject acquisitions of the sound and properties unit in the sixth-grade science course. In the test development phase, firstly, literature review for the study was conducted. Then, 30 multiple choice questions in align with the subject acquisition in the 2018 science curriculum. This 30-question test was presented to opinion of three academicians and a science teacher for the validity of the test. Necessary adjustments were made in line with the opinions of the experts. Subsequently, the draft test, modified according to the experts' feedback, was applied to a total of 300 seventh grade students. After the analysis, the number of questions in the test was reduced to 27. As a result of item analysis, mean difficulty index value of the test was 0.41, and item discrimination index was 0.49. The reliability analysis for the developed test was found 0.92 by calculating the KR-20 reliability coefficient value. By considering, the validity and reliability analysis results, it was concluded that the final version of the developed test, grounded in Bloom's Taxonomy, is a valid and reliable test with different difficulty levels.

Virtual reality has emerged as an influential technology in the educational landscape, offering learners and teachers immersive and interactive experiences that enhance traditional teaching methods. However, despite the increasing importance of virtual reality in education, a systematic description and classification of virtual reality use cases in education is still lacking. This limits the understanding and comparability of virtual reality use cases and highlights the need for a structured approach. This study asks the research question: How can virtual reality educational use cases, identified in the literature, be described, and classified? To classify these use cases, this study develops a state-of-the-art taxonomy. The taxonomy was developed in a combination of a conceptual-to-empirical and empirical-to-conceptual approach. The first stage to develop the taxonomy was based on a conceptual-to-empirical approach. Here, the concepts of virtual reality, use case and education serve as meta-characteristics and theoretical structure. To further detail the dimensions and characteristics, a systematic literature review was conducted by following a PRISMA-guided search and selection process. Therefore, the scientific databases Science Direct, AISel and Springer Link were used to search for studies between 2018 and 2023, obtaining a sample of 39 publications. As the conceptual-to-empirical approach did not richly describe the analysed virtual reality use cases from the studies, additional dimensions and characteristics were identified inductively. Therefore, a second iteration was conducted relating to the empirical-to-conceptual approach. This process explored the practical aspects of virtual reality scenarios and added applicable and practical characteristics to the initial theoretical foundation. The result is a comprehensive taxonomy of virtual reality use cases in education that contributes significantly to existing knowledge and provides a solid foundation for future research. The final taxonomy includes 17 dimensions and 37 characteristics. These findings can support educators to understand the nature of virtual reality use cases, enabling them to describe and implement such use cases effectively within educational settings. [Note: The publication year (2023) shown in the citation on the PDF is incorrect. The correct publication year is 2024.]

Since the mid-90s, a growing concern has emerged regarding text comprehension from a multimodal perspective. In the Chilean educational context, multimodality has been highlighted in the official programs of the Ministry of Education. The present study examines one of the official Chilean ELT school textbooks, investigating whether its reading comprehension questions align with the country's interest in developing multimodal literacy. This analysis employs Unsworth et al.'s (2019) taxonomy for classifying question types to examine 17 while-reading sections, comprising 216 questions. The findings reveal a predominant focus on questions that can be answered by reading the written text without looking at the pictures as well as a lack of images in several reading passages. These results highlight the crucial role that teachers play in complementing the school textbooks, enabling students to develop multimodal literacy as well as the necessity for textbook designers to recognize the pivotal role of images in comprehending multimodal texts.

Over the years, a sweeping interest in translanguaging practices and corrective feedback (CF) in parallel has received momentum in instructed SLA research. Whereas previous CF studies focused on CF interactions and factors affecting L2 learning, this study examined how translanguaging intertwined with CF in Arabic as a Heritage Language learning in a sixth-grade class at a K-12 school in the USA. The research data resulted from twenty hours of class observations, interviews with the class teacher, and ten randomly selected participating students. The data were coded based on Ranta and Lyster's (2007) CF types and uptake moves taxonomy. The results showed that the teacher's translanguaging practices helped learners engage in pedagogical tasks and CF interactions, leading to effective Arabic language learning. The teacher provided five CF types--explicit correction, recast, metalinguistic feedback, elicitation, and multiple feedback. Metalinguistic feedback, recast, and multiple feedback accounted for 72% of CF, where recasts received the highest uptake and repair rates (95% and 87%, respectively), and the other types of CF also led to high uptake and repair moves. This study suggests that CF can be effective when teachers employ translanguaging during CF interactions, positively address learner errors, and motivate learners' in-class participation.

Biology education plays a vital role in nurturing the understanding of learners about the intricacy of life. Various efforts have emerged to strengthen learning biological concepts but there were still studies that showed that learners have low mastery in some aspects. To determine how well students understood various biological topics, including human physiology, Concept inventory tests (CIT) were used. The concept inventory test may be able to spot students' misconceptions and ultimately lead to improved comprehension. The crafted CIT developed with the aid of a table of specifications based on Bloom's taxonomy of cognitive domain was assessed according to its validity and reliability. In validation, content validity and item analysis were considered while reliability test was employed through Cronbach's alpha. Distractor analysis was also performed to determine possible source of misconception per item. The CIT was administered to 120 senior high school STEM students (50.8% from the private schools, 37.5% in regular public schools and 11.7% from public schools with special programs in science). The results displayed high content validity with a mean of 4.83 for content validity and an average Aiken's validity coefficient of 0.98. It also highlighted that the test is moderately difficult with the test difficulty of 0.58, as well as, discriminatory with a discriminating level of 0.46. After item classification, 63 items were retained (39 accepted, 24 for revisions) and Chronbach's alpha ([alpha]=0.74) indicated good internal consistency. The concept inventory test propounds to be a good classroom test science with minor items to be revised.

This paper reports the results of a qualitative action research study conducted with children from a private Colombian institution. This study aimed to analyze the learners' cognitive and knowledge outcomes measured according to the revised Bloom's taxonomy once content and language integrated learning was implemented. Data were gathered through an interview with the learners' parents, observation, and video recordings. Results give evidence that learners develop different processes simultaneously, classified by the mentioned taxonomy. This taxonomy is a helpful approach for English learners since it allows them to perform cognitive and knowledge processes without following rigid systematic learning. As a conclusion, this implementation with children allowed participants to develop cognitive processes with greater emphasis in levels 3 and 4 (apply and analyze), whereas level 2 (understand) was developed as part of the process. Meanwhile, the factual and conceptual knowledge dimensions were strengthened. Finally, procedural, and metacognitive knowledge is developed through the implementation itself.

Classifying, naming, and identifying insects have been complicated topics among science teachers and students. This problem is due to the highly technical collection protocols, safekeeping procedures, the unavailability of appropriate learning resources, and the closure of school laboratories and facilities due to the COVID-19 pandemic. Using the remote learning setup, this study utilized Improvised Insect Traps (IITs) to provide an authentic learning experience in teaching and learning insect taxonomy at home. The study aimed to determine the effects of using IITs on students' self-efficacy beliefs and perceived levels of engagement. In this quasi-experimental study, 42 students designed and developed their improvised insect traps. Insect collection and classification were accomplished within four weeks. A 20-item validated survey questionnaire on self-efficacy and engagement levels was administered via Google Forms. Students' feedback was gathered using virtual focus group discussions and open-ended questions. Results revealed that IITs effectively improved students' self-efficacy beliefs (Z=0.033, p-value=0.022, g=0.68), while no improvement was noted in students' perceived levels of engagement (Z=0.143, p-value=0.188, g=0.07) in teaching and learning insect taxonomy. Moreover, students' feedback and responses were classified as Affordances or Constraints. Subthemes such as motivation, satisfaction, authentic learning, safety, and parental involvement were generated in the thematic analysis. Overall, this study found that the IITs activity is relevant in teaching insect taxonomy and delivering practical learning experiences among students in a distance learning modality.

A cohort of pre-service mathematics students was exposed to a teaching strategy based on retrieval practice and test-potentiated learning. The aim of the study was to determine how high and low prior topic knowledge study participants compare in terms of their procedural fluency and conceptual understanding after exposure to the teaching strategy. A pre-test and post-test repeated measures design was employed in the study to compare within groups. A revised taxonomy table based on Bloom's taxonomy was utilised to categorise test items. Findings indicate significant differences between pre-test and post-test scores within groups. Results from the independent samples t-test show a significant difference between the two groups. Outcomes confirm that the benefits of retrieval practice are greatest for unfamiliar content. Findings indicate that for low prior topic knowledge students, procedural fluency is enhanced and retained more than conceptual understanding whereas for the high prior topic knowledge students it was the reverse. The strategy was not as effective for improving conceptual understanding.

Mathematical symbols, such as those embodying quantum concepts, are indispensable for conveying complex ideas and relationships in academic writing. However, some education researchers and students keep a distance from anything mathematical: algebraic equations, geometrical reasoning, or statistical symbols. How to lower the access threshold for this type of mathematical narrative and reveal the meanings of a range of quantum conceptions to modern educators thus becomes a real problem. Using the pendulum motion equation as a reference point, I argue in this article for the advantages of academic English or French writing genres that fuse a range of mathematical symbols of quantum concepts and conceptual change. Such writings help demonstrate how incorporating the idea of probability (a) refines the debate among conceptual, verbal, and mathematical academic writing; (b) allows new conceptions that draw on the insights from quantum cognition-supported theories; (c) helps explain students' understanding of mathematical symbols; and (d) offers a new taxonomy for categorizing academic writings.

This paper presents a unified Arabic version of the English action verbs mentioned in Bloom's taxonomy (1956) that has been checked for validity and reliability by a panel of education experts. Methodologically, the Bloom's list of action verbs was first translated into Arabic by an expert professor of translation. Then, using a mixed-method approach the Arabic list was validated by three bilingual education experts working at universities in Bahrain, Qatar, and the United Arab Emirates. As part of the process, the paper established a single Bloom's taxonomy list of action verbs, based on the data provided by two reputable educational institutions that were cross-checked with a well-referenced textbook. A contextualized Arabic translation of the list was then produced and was subjected to rigorous checks by a panel of reviewers who were the education experts. The paper presents the challenges faced in translating the list into Arabic and the solutions we have adopted as well as the validity and reliability checks. The implication of this paper is in offering teacher preparation programs across the Arab world an Arabic Bloom's taxonomy list that can be used by in-service and pre-service teachers. Moreover, it contributes to teacher literacy in the correct use of Bloom's action verbs in the Arabic language.

Large introductory classes, with their expansive curriculum, demand assessment strategies that blend efficiency with reliability, prompting the consideration of multiple-choice (MC) tests as a viable option. Crafting a high-quality MC test, however, necessitates a meticulous process involving reflection on assessment format appropriateness, test blueprint design, and adherence to item-writing guidelines aligned with learning objectives and teaching strategies. This inherently time-consuming undertaking ideally requires a collaborative effort from a team of writers who possess expertise in both the subject domain and the specific course context -- an aspiration complicated by the multifaceted demands of higher education instruction. Given these challenges, educators often seek pragmatic solutions, including the adoption or adaptation of existing MC tests. However, the utility of these tests is ambiguous if the original test blueprint and the classification of questions are unknown. This paper introduces a structured four-step "reverse engineering" test blueprint process and proposes a systematic approach to identify test questions that align with the targeted learning objectives. One crucial step incorporates the Taxonomy Table (Anderson & Krathwohl, 2001) facilitating the classification of questions in the cognitive process dimension. As we delve into the intricacies of this analytical journey, we aim to provide a valuable resource for educators seeking to optimize the effectiveness and relevance of MC tests as a high-stakes assessment option.

Critical thinking, creativity, communication, teamwork, emotional intelligence, problem-solving, empathy, resilience, ambition, grit, and innovation (Heckman & Kautz, 2012). These skills, often referred to as 'soft' skills, are considered a requirement for employment and advancement for the 21st-century graduate (Carnevale & Smith, 2013). Within a Western Canadian School of Business, in an environment highly regarded for technical skill achievement in diploma and degree graduates, faculty set out to investigate the absence or inclusion of human skills in curriculum outcomes as an initial phase of investigation. There is an institutional presumption that human skill development is innately a part of the programs. The intention is that human skills (LeBusque, 2020) or power skills (PMI, 2022) naturally occur during course delivery, creating a commonality across foundational courses to reinforce the skill sets identified, developed, and refined as students complete their credentials. However, industry reports (Lapointe & Turner, 2020; RBC, 2019) and the authors' own institutional data collected from new graduates and employers indicated room for improvement in these skills. To gain a better understanding, the authors undertook an examination via document analysis of all common core courses that form the program foundation. Through the lens of dynamic skill theory (Mascolo, 2020), this evaluation involved 24 common courses, comprised of 1,442 course objectives, resulting in a range of 134 Bloom's Taxonomy verbs. In this paper, the authors begin the exploratory first phase of a broader comprehensive study with a focus on course foundations for learner development. Through this analysis, the authors present a draft framework to better understand and strengthen the learning foundations, to proceed with considerations for realignment and strategic scaffolding of both technical and human skills from entry through graduation.

Research confirms that critical thinking plays a fundamental role in decision making and problem solving, skills that are essential to function as successful adults in a complex world. Consequently, it has been a focus of educational research for decades. Faculty meetings and teacher training sessions repeatedly run sessions on ways that teachers can adapt their methodology to foster higher-level thinking. This article discusses the definition of critical thinking and the pivotal role that questioning can have in developing those skills. Out of the hundreds of questions teachers ask daily, few demand higher-level thinking. In fact, most ask for basic information or check for current learning rather than causing students to infer, analyze, evaluate, or demonstrate creativity. Further, the article includes a sampling of teaching techniques adapted from cooperative learning and other disciplines that have the potential to transform the world language classroom into a vibrant, learner-active space where students use critical thinking to solve problems.

The present study falls into the efforts to improve practices for addressing errors produced by learners in various situations involving the calculation of integrals. We attempt to clarify as precisely as possible the types of errors that secondary school students produce when using integrals in algebraic and graphical frames. Based on the synthesis of several works dealing with errors specific to integral calculus, we have been able to outline a typology of possible errors that can be produced by students in secondary school. We determine some subcategories for the three known categories of errors: conceptual, procedural, and technical. After administering a test to a random sample of secondary school students and conducting a principal component analysis, we were able to deduce that in the algebraic frame, certain conceptual and procedural subcategories dominate, with a notable advance for errors due to failure to recognize the integrand function. In the graphical frame, errors related to technical subcategories represent a major source of the erroneous productions of the students tested.

Numerous studies compared the effectiveness of various formats of video-based teaching, yet their focus has primarily been on relatively straightforward content, such as concepts and basic procedures. Research on the effectiveness of teaching complex content through different formats of videos remains limited. This study addresses this gap by conducting a well-controlled comparison between recorded video and narrated animation in the context of teaching physics problem-solving, a challenging content area with easily measurable difficulty levels. The study employed a controlled experimental design with a sample of 361 upper secondary school students who had been randomly assigned to seven classes within a selected secondary school by the school administrator. Data were collected using pre- and post-test assessments that measured students' problem-solving performance after video-based teaching. The results indicated that the effectiveness of recorded videos featuring the teacher's face was not significantly different from that of narrated animations that did not include the teacher's face, irrespective of the content's difficulty level. These findings provide valuable insights for educators in selecting appropriate teaching formats for teaching challenging content through video-based education. They contribute to our understanding of teaching strategies and have practical implications for educators seeking to optimise teaching approaches in similar contexts.

We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying the effect of Inter Stimulus Interval on these priming effects. Our model explains taxonomic priming between words by "semantic feature overlap," whereas associative priming between words is explained by Hebbian links between semantic representations derived from "co-occurrence relations" between words (or their referents). From a developmental perspective, any delay in the emergence of taxonomic priming compared to associative priming during infancy seems paradoxical since feature overlap "per se" need not be learned. We address this paradox in the model by showing that "feature overlap" itself is an emergent process. The model successfully replicates infant data related to Inter Stimulus Interval effects in priming experiments and makes testable predictions.

There is a need to conceptualize a multidimensional taxonomy for learner-AI interaction. This conceptual/perspective article shares recent work on AI learner education and further presents new conceptions for a multidimensional taxonomy for learner-AI interaction. A review of the literature is conducted (N = 11). Open coding is used to summarize an overview of work, challenges, and findings reported. The summarized work is then used to conceptualize considerations for a multidimensional taxonomy for learner-AI interaction. The contribution of this work is in identifying unforeseen limitations in characterizing human-AI interaction and presenting new conceptions for a multidimensional taxonomy for learner-AI interaction based on the synthesis of the reviewed literature. This work thus shares current findings and challenges reported by the literature and our conceptions. Four conceptions are introduced, namely the alignment between the learner and AI; diverse metrics for the learner, AI, and learner-AI interaction; feedback direction when summarizing interactions; and what works in human-AI interaction by using prior research. We find there to be challenges with the use of AI by humans. The more interaction time spent between humans and AI may not necessarily lead to enhanced learning and understanding. Humans may exploit and use AI in inappropriate ways such as plagiarism. This eminent threat begs the question to reconsider our evaluation methods in light of AI systems.

An individual competence is one of the main human resources, which enables a person to operate in everyday life. A competence profile, formally captured and described as a structured model, may enable various operations, e.g., a more precise evaluation and closure of a training gap. Such application scenarios supported by information systems are particularly compelling for the era of digitalisation, although research on adequate models capturing competence profiles is still lacking; moreover, no research was revealed synthesizing models of competence, enabling operationalisation possibilities. To fulfil this gap, current research develops a classification of competence models in the form of taxonomy, derived from operational characteristics of competence constructs. Given conceptual fuzziness of the competence term and complex, interdisciplinary scope of the study, the research method follows integrative literature review principles: results of an extensive search conducted in three iterations were critically analysed and further synthesized in the form of taxonomy. This critical analysis was performed based on an overview of twenty-four competence models with a lens of working definitions of competence framework and model concepts. As a result, all three outcomes highlight the power of competence models: (1) the overview summarises models' development methods, operationalisation, and purposes in a specific application domain, while (2) working definitions and (3) the taxonomy aim at overcoming a conceptual ambiguity of competence concepts. In addition, the presented taxonomy may serve as a knowledge base or a decision support tool on competence model selection when it comes to development of a competence management tool.

Developing immersive learning systems is challenging due to their multidisciplinary nature, involving game design, pedagogical modelling, computer science, and the application domain. The diversity of technologies, practices, and interventions makes it hard to explore solutions systematically. A new methodology called Multimodal Immersive Learning Systems Design Methodology (MILSDeM) is introduced to address these challenges. It includes a unified taxonomy, key performance indicators, and an iterative development process to foster innovation and creativity while enabling reusability and organisational learning. This article further reports on applying design-based research to design and develop MILSDeM. It also discusses the application of MILSDeM through its implementation in a real-life project conducted by the research team, which included four initiatives and eight prototypes. Moreover, the article introduces a unified taxonomy and reports on the qualitative analysis conducted to assess its components by experts from different domains.

Despite decades of research efforts, data-based instruction (DBI) for students with intensive intervention needs are not being widely used in practice as anticipated, and many educators have difficulties in implementing it. This systematic review aimed to examine what kinds of implementation drivers and strategies have been used to support educators implementing DBI and what kinds of implementation outcomes researchers have measured. Eighteen studies were synthesized using the Implementation Drivers framework and Implementation Outcomes taxonomy and were quality appraised. We found that the majority of studies primarily used competency drivers to increase teachers' DBI expertise, while a limited number of studies focused on organizational and leadership drivers. Acceptability and fidelity were frequently assessed as implementation outcomes. We discussed the implications of the findings, including the need for researchers to incorporate implementation drivers and outcomes at diverse levels to best support educators' implementation of DBI, as well as the limitations of this review, such as the limited generalizability of the findings.

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.

In its original version, control-value theory describes and explains achievement emotions. More recently, the theory has been expanded to also explain epistemic, social, and existential emotions. In this article, I outline the development of the theory, from preliminary work in the 1980s to early versions of the theory and the recent generalized control-value theory. I provide summaries of the theory's evidence-based propositions on antecedents, outcomes, and regulation of emotions, including the fundamentally important role of control and value appraisals across different types of human emotions that are relevant to education (and beyond). The theory includes descriptive taxonomies of emotions as well as propositions explaining (a) the influence of individual factors, social environments, and socio-cultural contexts on emotions; (b) the effects of emotions on learning, performance, and health; (c) reciprocal causation linking emotions, outcomes, and antecedents; (d) ways to regulate emotions; and (e) strategies for intervention. Subsequently, I outline the relevance of the theory for educational practice, including individual and large-scale assessments of emotions; students', teachers', and parents' understanding of emotions; and change of educational practices. In conclusion, I discuss strengths of the theory, open questions, and future directions.

In the rapidly evolving landscape of Industry 4.0, the demand for skilled professionals well-versed in Internet of Things (IoT) technologies is escalating. However, a significant challenge faced in educational settings is the lack of comprehensive and effective methodologies for imparting practical knowledge and skills in IoT. This paper presents an approach for designing and implementing an Internet of Things (IoT) laboratory in which students may practice and comprehend many components of an IoT environment, such as analysis of sensor data, IoT platform development, and setup of messaging protocols. The teaching methodology adopts a Cyber-Physical System (CPS) framework, which integrates teachers, classrooms, and resources to create a comprehensive learning environment. Bloom's taxonomy is employed to assess the efficacy of the suggested technique in terms of cognitive skills and knowledge acquisition. The evaluation procedure demonstrated the advantages of a hybrid learning environment, which integrated both face-to-face and remote instruction. The case study is conducted in an engineering higher education course on first year students. The findings of this paper lay the groundwork for a remotely deliverable IoT training course, contributing to the advancement of IoT education and equipping students with the necessary skills for the evolving landscape of Industry 4.0.

Despite problem posing's prominence in mathematics education research, its implementation in classrooms is limited. Therefore, teacher educators should incorporate problem posing tasks into preparation programs to help prospective teachers gain confidence in their abilities. One approach to teaching problem posing includes providing examples. The Common Core State Standards Initiative provides taxonomies with examples of one-step word problems for all four basic operations. Through this mixed-methods study, preservice teachers (N = 44) regularly identified and posed word problems within the addition and subtraction taxonomy. Before and after the intervention, the preservice teachers answered survey questions and posed problems to model given equations. The researchers analyzed the preservice teachers' abilities to pose logical word problems and to match given equations before and after instruction. They also quantitatively analyzed Likert-style survey responses on perceptions of posing the various types of word problems and integrated the results with a qualitative analysis of open-ended responses expanding on the same questions. Results showed participants' abilities to pose problems increased after the intervention. Additionally, participants felt problems with the unknown information at the beginning or middle were harder to pose than those with the unknown information at the end.

The risk of multitasking is high in online surveys. However, knowledge on the effects of multitasking on answer quality is sparse and based on suboptimal approaches. Research reports inconclusive results concerning the consequences of multitasking on task performance. However, studies suggest that especially sequential-multitasking activities are expected to be critical. Therefore, this study focusses on sequential-on-device-multitasking activities (SODM) and its consequences for data quality. Based on probability-based data, this study aims to reveal the prevalence of SODM based on the javascript function OnBlur, to reflect the its determinants and to examine the consequences for data quality. Results show that SODM was detected for 25% of all respondents and that respondent attributes and the device used to answer the survey are related to SODM. Moreover, it becomes apparent that SODM is significantly correlated to data quality measures. Therefore, I propose SODM behavior as a new instrument for researching suboptimal response behavior.

This qualitative study aims to explore how a university-level School of Marketing integrates the Sustainable Development Goals (SDGs) into curriculum, using Bloom's Taxonomy, and to develop a reflective process that could be applied within tertiary education, more broadly. The research investigates the depth of SDG integration, with marketing subject coordinators mapping the Goals within their teachings across Bloom's dimensions, then identifying and reflecting on how they are embedded. The reflective process has revealed that some subjects are directly mapped to SDGs, for example where students are required to work on an assessment task which relates to a specific Global Goal. The results also show that other subjects are indirectly mapped, such as where subject coordinators discuss topics linked to Goals or Targets but do not explicitly state this content is SDG-related. To effectively implement SDGs within teaching and learning practice, marketing subjects require an evaluation method to identify gaps and opportunities. Therefore, this reflective process enabled subject coordinators to recognize gaps in their own SDG knowledge and teaching, a process through which future marketing subject curriculum modifications can be developed, with possible applications in other disciplines.

Background: The emergence of ChatGPT in the education literature represents a transformative phase in educational technology research, marked by a surge in publications driven by initial research interest in new topics and media hype. While these publications highlight ChatGPT's potential in education, concerns arise regarding their quality, methodology, and uniqueness. Objective: Our study employs unconventional methods by combining altmetrics and bibliometrics to explore ChatGPT in education comprehensively. Methods: Two scholarly databases, Web of Science and Altmetric, were adopted to retrieve publications with citations and those mentioned on social media, respectively. We used a search query, "ChatGPT," and set the publication date between November 30th, 2022, and August 31st, 2023. Both datasets were within the education-related domains. Through a filtering process, we identified three publication categories: 49 papers with both altmetrics and citations, 60 with altmetrics only, and 66 with citations only. Descriptive statistical analysis was conducted on all three lists of papers, further dividing the entire collection into three distinct periods. All the selected papers underwent detailed coding regarding open access, paper types, subject domains, and learner levels. Furthermore, we analysed the keywords occurring and visualized clusters of the co-occurring keywords. Results and Conclusions: An intriguing finding is the significant correlation between media/social media mentions and academic citations in ChatGPT in education papers, underscoring the transformative potential of ChatGPT and the urgency of its incorporation into practice. Our keyword analysis also reveals distinctions between the themes of the papers that received both mentions and citations and those that received only citations but no mentions. Additionally, we noticed a limitation that authors' choice of keywords might be influenced by individual subjective judgements, potentially skewing results in thematic analysis based solely on author-assigned keywords such as keyword co-occurrence analysis. Henceforth, we advocate for developing a standardized keyword taxonomy in the educational technology field and integrating Large Language Models to enhance keyword analysis in altmetric and bibliometric tools. This study reveals that ChatGPT in education literature is evolving from rapid publication to rigorous research.

In the field of artificial intelligence-based fitness apps, the effective integration of behavior change techniques (BCTs) is critical for promoting physical activity and improving health outcomes. However, the specific BCTs employed by apps and their impact on user engagement and behavior change are not explored sufficiently. This study investigates the Freeletics fitness app through a mixed-methods approach to evaluate the use of BCTs. In the quantitative analysis, fifteen unique BCTs were identified based on the Behavior Change Technique Taxonomy (V1). In the qualitative analysis, user reviews (n=400) were examined to understand perspectives on the app's effectiveness in promoting behavior change. Goal setting, action planning, self-monitoring of behavior, and social support were among the most prevalent BCTs identified in the Freeletics app, and their effectiveness in enhancing user engagement and promoting behavior change was also highlighted by user reviews. Among the areas of improvement identified in the study were the need for simplifying personalization options and addressing user concerns regarding the specificity of feedback. The study underscores the importance of integrating BCTs effectively within AI-based fitness apps to drive user engagement and facilitate behavior change. It contributes valuable insights into the design and implementation of BCTs in fitness apps and offers recommendations for developers, emphasizing the significance of goal setting, feedback mechanisms, self-monitoring, and social support. By understanding the impact of specific BCTs on user behavior and addressing user concerns, developers can create more effective fitness apps, ultimately promoting healthier lifestyles and positive behavior change.

This article presents a simple, cognitive theory of science and learning. The first section of the paper develops the theory's two main propositions: (i) A wide range of scientific activities rely heavily on one type of reasoning, hypothetical thinking, and (ii) This type of reasoning is also useful to students for learning science content. The second section of the paper presents a taxonomy of multiple-choice questions that use hypothetical thinking and the third section of the paper tests the theory using data from a college biology course. As expected by the theory, student responses to 24 scientific reasoning questions were consistent with a one-dimensional psychometric construct. Student responses to the scientific reasoning questions explained 36% of the variance in exam grades. Several directions for additional research are identified, including studying the psychometric structure of scientific thinking in more detail, performing randomized, controlled experiments to demonstrate a causal relationship between scientific thinking and learning, and identifying the relative contribution of other factors to success in college.

The Integrated Course Design (ICD), using Fink's taxonomy of significant learning, popularly known as ICD/SL, is a handy way to create a better learning environment for students. It is a learner-centered approach with the desired end-product, but at the same time, it upgrades the teaching by improving the instructors' delivery mechanism. Our goal of this study was to see whether ICD/SL affects students' class participation and academic performance in the "Introduction to Bioinformatics" course offered at the Department of Biological Science, BITS Pilani, Pilani campus, India. Three class groups were chosen for this purpose: 2019-2020 (51 students), 2020-2021 (77 students), and 2021-2022 (72 students). The control group, 2019-2020, received no ICD/SL instruction; the remaining two groups, 2020-2021 and 2021-2022, received ICD/SL instruction that included revised learning goals based on Fink's taxonomy and new teaching and evaluation activities. A Likert scale was utilized to assess students' academic feedback using the Kruskal-Wallis test to determine the P-value. The findings showed that the treatment groups had higher class participation and academic performance in the summative assessment of final grades. In the experimental groups, the class participation was 23 to 27% higher compared to the control group. The absenteeism rate on the course decreased from 14% in 2019-2020 to 9% in 2020-2021 and 4% in 2021-2022. Also, in the treatment groups, 83 to 90% of students were in the High to Excellent category, compared to 74% in the control group. The failure rate of the course decreased from nearly 18 to 10% in 2021-2022 and only 6% in 2020-2021. There were significant differences between the treatment and control groups in class participation and academic performance (P < 0.05). This study has shown that the use of ICD/SL has the potential to improve students' class participation and academic performance.

This study aims to reveal the cognitive demands of senior high school English as a foreign language textbooks in China and their potential impact on students' thinking development. To achieve this, the study employed content analysis, using an analytical framework adapted from the revised Bloom's taxonomy, to examine the cognitive demands incorporated in the activities across nine target textbooks from three different publishers. The study found "Understand" to be the most common cognitive demand in the examined textbooks. However, it also identified that lower cognitive demands "Remember," "Understand," and "Apply" were less prevalent than the higher demands "Analyze," "Evaluate," and "Create." Additionally, the study observed variations in the distribution of cognitive demands within the textbooks for 10th, 11th, and 12th grades. Despite these variations, the distribution of cognitive demands across the three grade-level textbooks was found to be remarkably similar, with an increase in the occurrence frequency of cognitive demands "Apply," "Analyze," "Evaluate," and "Create," and a corresponding decrease in the occurrence frequency of cognitive demands "Understand" and "Remember." These findings indicate that senior high school English as a foreign language textbooks in China are intentionally designed to accommodate the thinking skill needs of students at each grade level and to promote the development of their thinking skills, with a particular emphasis on higher-order thinking skills. The findings hold significant implications for the design and use of language textbooks, highlighting the importance of integrating appropriate and challenging cognitive demands to effectively support students' thinking development.

One of the underrepresented aspects of pragmatic competence development is perceiving and responding to impoliteness acts. The present study reports on a quantitative and qualitative investigation of two international English language teaching (ELT) textbook series published by Oxford and Cambridge University Press; it focuses on the books highly popular among a thriving representative sample of learners of English as a foreign language (EFL) across four language proficiency levels and explores their coverage and treatment of impoliteness acts and their responses. Drawing on stringent models and taxonomies, the findings reveal that this unpleasant side of language is ignored and misrepresented in the textbooks, particularly at lower proficiency levels. We draw on our own and others' previous incivility studies and argue for the inclusion of impoliteness especially from earlier stages of language learning owing to its saliency in authentic interactions. The study concludes with implications and suggestions for language learners, instructors, textbook writers, and researchers.

The Australian Curriculum Science has "Patterns, Order and Organisation" as one of its six Key Ideas. In the biological sciences, the structural patterns revealed by observing living things are used to order and organise them in a hierarchical system of binomial nomenclature, in which living things have a generic name and a specific name, based on their morphological features. Each organism, thus described, will have its own unique name. But how does it get that name, and what happens when reputable sources have different names? This article demonstrates how science deals systematically with such disagreements by documenting a taxonomic journey into the naming of one particular zoological species, the Shark Bay pearl oyster. This scientific journey intertwines science with history and geography, as well as social, cultural, and political perspectives. It is truly a story of science as human endeavour.

This study intends to examine the reading process in Chinese of two young heritage language learners through the use of retrospective miscue analysis (RMA). Retrospective miscue analysis involves both the author and the reader in reflectively discussing the reader's oral reading miscues--responses that differ from the actual text. This study confirms the notion that reading is an active sense-making process where the graphophonic, syntactic, and semantic cues as well as translanguaging skills function interdependently to assist heritage language readers with meaning construction. Strategies of sampling, predicting, substituting, and correcting are also evident in their reading. These active but "invisible" reading behaviors are not available through asking comprehension questions. Instead, they are obtained from the reflective conversations between the researcher and the students. Retrospective miscue analysis helps readers gain a deeper understanding of the reading process and enhances their metacognitive skills. This study also includes language and reading behaviors that are unique to Chinese heritage language learners as well as implications for parents and teachers.

This paper provides a comprehensive analysis of the motivations that key policy documents have put forward as justifications for Sweden's mother-tongue instruction in immigrant and historical minority languages as a multicultural policy that has endured for nearly half a century. The diachronic development of these motivations is analysed in four periods and interpreted with the help of Ruiz's (1984) orientations in language planning. The corpus consists of 26 key policy documents making up the coordinative discourse among policy actors. Based on an innovative mix of qualitative and quantitative methods, the motivations are presented in a three-tiered taxonomy consisting of motivational units, themes and language-planning orientations. The results point to both continuity and change in how mother-tongue instruction has been justified over time. Confirming previous research, the results show that the language-as-resource orientation has played a central role in justifying both the establishment and the maintenance of mother-tongue instruction in Sweden and that language as right complemented this orientation. Furthermore, the study illustrates that the language-as-problem orientation need not always be detrimental to bilingualism and minority-language maintenance. Contrary to some claims in the literature, it is argued that language as extrinsic resource is not necessarily underpinned by neoliberalism, as there are also social liberal and conservative inroads to this orientation. The paper concludes that although the language-as-resource orientation plays an indispensable role in supporting bilingualism in education, not only the language-as-right orientation but also the language-as-problem orientation should not be neglected.

To help higher education instructors, academic support personnel, and institutional leadership better identify, encourage, incentivize, fund, support and assess pedagogical innovation, we describe herein a valid taxonomy capable of precisely characterizing the range of pedagogical innovations in higher education. The Taxonomy of Pedagogical Innovation in Higher Education probes the "Focus of Innovation," "Degree of Innovation," "Intended Outcomes," "Barriers to Adoption," "Risks of Adoption," and direct and indirect "Costs." Using two scenarios, we illustrate how to apply the taxonomy to a pedagogical innovation with different sets of contextual factors. We conclude by discussing how the taxonomy might help provide a shared vocabulary for and understanding of pedagogical innovation, align pedagogical innovation to priorities, inform investment strategy, characterize an institution's innovation culture, and help to guide efforts to assess the impact of pedagogical innovations.

The revised two-factor Study Process Questionnaire and the Approaches and Study Skills Inventory for Students are two instruments commonly used to measure student learning approach. Although they are designed to measure similar constructs, it is unclear whether the metrics they provide differ in terms of their real-world classification of learning approach. The purpose of this study is to compare outcomes of these two inventories in a study population from an undergraduate (baccalaureate) human anatomy course. The three central goals of this study are to compare the inventories in terms of 1) how students are classified, 2) the relationship between examination performance, time spent studying, and learning approach, and 3) instrument reliability. Results demonstrate that student classifications of corresponding scales of each inventory are significantly correlated, suggesting they measure similar constructs. Although the inventories had similar reliability, neither was consistently strong in predicting examination performance or study habits. Overall, these results suggest that the two inventories are comparable in terms of how they measure learning approach, but the lack of correspondence between learning approach scores and measurement outcomes questions their validity as tools that can be used universally in classrooms.

Multi-wave-cross-lagged-panel models (CLPMs) of directional ordering are a focus of much controversy in educational psychology and more generally. Extending traditional analyses, methodologists have recently argued for including random intercepts and lag2 effects between non-adjacent waves and giving more attention to controlling covariates. However, the related issues of appropriate time intervals between waves (lag1 intervals across waves) and the possibility of contemporaneous (lag0) effects within each wave are largely unresolved. Although philosophers, theologians, and scientists widely debate sequential (lagged) and simultaneous (lag0) theories of causality, CLPM researchers have mostly ignored contemporaneous effects, arguing causes "must" precede effects. In a substantive-methodological synergy, we integrated these issues and designed new structural equation models to reanalyze one of the strongest CLPM studies of academic self-concept (ASC) and achievement (five annuals of mathematics data; 3527 secondary school students). A taxonomy of models incorporating various combinations of lag0, lag1, and lag2 effects, random intercepts, and covariates consistently supported a priori reciprocal effect model (REM) predictions--medium or large reciprocal effects of ASC and achievement on each other. Consistent with self-concept theory, effects of ASC on achievement evolved over time (lag1, not lag0 effects), whereas effects of achievement on ASC effects were more contemporaneous (lag0, not lag1 effects). We argue that lag0 effects reflect proximal events occurring subsequent to the previous data wave, suggesting the need for shorter intervals but also leaving open the possibility of contemporaneous effects that are truly instantaneous. We discuss limitations and future directions but also note the broad applicability of our statistical models.

The programme outcomes are broad statements of knowledge, skills, and competencies that the students should be able to demonstrate upon graduation from a programme, while the Educational Taxonomy classifies learning objectives into different domains. The precise mapping of a course outcomes to the programme outcome and the educational taxonomy (Cognitive, Psychomotor and Affective) level is crucial to ensure Constructive Alignment at the fundamental level of a course and to ensure meaningful outcome measurements. Unfortunately, this effort is often subject to bias and human error while the use of information technologies as a mediator in this area remains unexplored. This research paper proposes an automatic learning-based advisory system for engineering curriculum to ensure constructive alignment with programme outcomes and educational taxonomy. We demonstrated the use of natural language processing and machine learning techniques to mitigate human error and bias that is often present in such classification tasks. Textual/semantic embeddings, including Term Frequency-Inverse Document Frequency (TF-IDF), Universal Sentence Encoder (USE), and Word2Vec (W2V), machine learning models (Random Forest, Support Vector Machine, Logistic Regression, and Light Gradient Boosting Machine), and their corresponding techniques for optimizing the training process are extensively investigated. In terms of accuracy, we obtained an encouraging result of 78.83%, and 78.71% for TF-IDF with Random Forest, and USE with Support Vector Machine classifier, respectively. We transformed our work into a web-based solution named the Course Outcomes Diagnostic Tool, embedded in the faculty education web platform, Edu Centre that is ubiquitously adopted by the members in the Faculty of Engineering and Technology, Tunku Abdul Rahman University of Management and Technology. The proposed solution has demonstrated great potential in reducing subjectivity, ambiguity, and human error, thereby improving the constructive alignment at the root level of course design to ensures teaching-learning activities are aligned with regulatory body expectations.

Studies have indicated that pictures in test items can impact item-solving performance, information processing (e.g., time on task) and metacognition as well as test-taking affect and motivation. The present review aims to better organize the existing and somewhat scattered research on multimedia effects in testing and problem solving while considering several potential moderators. We conducted a systematic literature search with liberal study inclusion criteria to cover the still young research field as broadly as possible. Due to the complexity and heterogeneity of the relevant studies, we present empirical findings in a narrative review style. Included studies were classified by four categories, coding the moderating function of the pictures investigated. The evaluation of 62 studies allowed for some tentative main conclusions: Decorative pictures did not appear to have a meaningful effect on test-taker performance, time on task, test-taking affect, and metacognition. Both representational and organizational pictures tended to increase performance. Representational pictures further seem to enhance test-taker enjoyment and response certainty. Regarding the contradictory effects of informational pictures on performance and time on task that we found across studies, more differentiated research is needed. Conclusions on other potential moderators at the item-level and test-taker level were often not possible due to the sparse data available. Future research should therefore increasingly incorporate potential moderators into experimental designs. Finally, we propose a simplification and extension of the functional picture taxonomy in multimedia testing, resulting in a simple hierarchical approach that incorporates several additional aspects for picture classification beyond its function.

The aim of this experiment was to investigate how glossing influences second language (L2) reading comprehension in relation to text difficulty and the two local and global meaning representations. Fifty-eight undergraduate students were asked to read three easy, moderate, and difficult texts and, following each passage, answer twenty comprehension questions targeting local and global concepts in one of the two first-language-glossed and unglossed conditions. Half of the participants in each group were supposed to think aloud while reading. The results revealed a significant difference between the performance of glossed and unglossed groups on comprehension of local concepts in all three difficulty levels. However, the impact of glossing on comprehension of global concepts was significantly influenced by text difficulty. The qualitative analysis of think-aloud protocols suggested a substantial difference in glossing functionality on fluency between the easy and the difficult texts. Furthermore, it is suggested that revisiting the glossing effect in combination with text difficulty on the reading product and underlying processes might reconcile some divergent hypotheses on glossing impact on fluency.

This paper examines visual narratology as a way of presenting qualitative primary data. The paper is an autoethnographic study with the overall goal of helping educators understand their digital literacies in a time of uncertainty and flux. The researcher deployed thematic analysis as the organising methodological framework. This performative autoethnographic method provided creative freedom and the satisfaction of a renewed perspective for the author (Jay and Johnson 2002). This primary qualitative data was given legitimacy and structure by the use of thematic analysis as a methodology. The findings support Bochner's (1994) idea that social science research can benefit from deliberately value-laden stories alongside empirical data and theories. The findings also developed the author's previous autoethnographic paper, which drew on his own social media posts as qualitative and quantitative data Atherton (2020b).