British Journal of Educational Technology最新文献

{"title":"Ending well: Values in concluding or transitioning community educational technology projects","authors":"Caroline R. Pitt","doi":"10.1111/bjet.13598","DOIUrl":"https://doi.org/10.1111/bjet.13598","url":null,"abstract":"<p>Community-partnered educational research projects exist in a complex network of stakeholders, values, time constraints and funding limitations. Many researchers are beholden to mandates around their funding, as well as the tenure clock and the ‘publish or perish’ mindset. However, building rapport and trust with communities takes time and resource investment that is not always prioritized in academia, and the ending process of a project is rarely explored. In this study, the educational technology project ecosystem and power dynamics in which researchers and participants exist is examined, drawing on the stakeholder analysis and value tensions of Value Sensitive Design to focus on the endings of such projects. Using a cross-case analysis of two long-term educational technology projects, the case study data corpus was qualitatively analysed to identify key themes involved in the ending process, based around retrospective interviews with participants from multiple stakeholder groups. This work identifies <i>types of</i> and <i>strategies for ending</i>, including individual endings and transitions, and develops recommendations for equitable ending processes in the context of educational technology projects. The study explores the dimensions and considerations in ending a project that involves a long-term partnership with a community, developing ways to understand, navigate and plan for the closing process and facilitating less extractive and more mutually beneficial community research partnerships.</p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 4","pages":"1415-1437"},"PeriodicalIF":6.7,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144273197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aligning human values and educational technologies with value-sensitive design","authors":"Luis P. Prieto,&nbsp;Olga Viberg,&nbsp;Jason C. Yip,&nbsp;Paraskevi Topali","doi":"10.1111/bjet.13602","DOIUrl":"https://doi.org/10.1111/bjet.13602","url":null,"abstract":"","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 4","pages":"1299-1310"},"PeriodicalIF":6.7,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13602","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144273373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supporting teachers' value-sensitive reflections on the cost–benefit dynamics of technology in educational practices","authors":"Davinia Hernández-Leo,&nbsp;Karina Ginoyan","doi":"10.1111/bjet.13592","DOIUrl":"https://doi.org/10.1111/bjet.13592","url":null,"abstract":"<p>This paper explores the application of a benefits versus costs reflection approach within non-university teaching environments, grounded in the principles of Value-Sensitive Design. Aimed at integrating human values systematically into the adoption of digital educational tools, this study involved 136 in-service school teachers across various workshops in Catalonia. Through the use of a structured customisable worksheet, educators critically self-evaluated their feelings about both the benefits and costs associated with the use of digital technologies in their teaching practices. The study found that the approach was meaningful to the teachers, who were able to adapt the use of the workshop to their cases. The positive reception by teachers suggests not only a satisfactory level of usability and utility of the approach but also their agreement with the need to integrate related strategies in their training, learning design and community debate processes.</p><p>\u0000 \u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 4","pages":"1350-1369"},"PeriodicalIF":6.7,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144273195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BJET Editorial Spring 2025: Reporting on AIED research and ethical considerations","authors":"Manolis Mavrikis,&nbsp;Cathy Lewin,&nbsp;Mutlu Cukurova,&nbsp;Louis Major,&nbsp;Laura Outhwaite,&nbsp;Elisa Rubegni","doi":"10.1111/bjet.13581","DOIUrl":"https://doi.org/10.1111/bjet.13581","url":null,"abstract":"","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 3","pages":"1118-1121"},"PeriodicalIF":6.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI for data generation in education: Towards learning and teaching support at scale","authors":"Mohammad Khalil,&nbsp;Qinyi Liu,&nbsp;Jelena Jovanovic","doi":"10.1111/bjet.13580","DOIUrl":"https://doi.org/10.1111/bjet.13580","url":null,"abstract":"<p>Supporting learning and teaching at scale requires access to large and high-quality content and datasets for analysis and innovation. With rapid advances in artificial intelligence (AI) and the growing demand for data, synthetic data has emerged as a potential solution for addressing these challenges. This editorial introduces the contributions of five accepted articles to the special section AI for Synthetic Data Generation in Education: Scaling Teaching and Learning. These articles explore key themes in leveraging AI-generated synthetic data to support learning and teaching as well as enhance educational practices at scale. The editorial emphasizes that hybrid strategies that leverage AI alongside human judgment are essential for scaling support for learning and teaching through synthetic data generation.</p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 3","pages":"993-998"},"PeriodicalIF":6.7,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13580","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging LLM respondents for item evaluation: A psychometric analysis","authors":"Yunting Liu,&nbsp;Shreya Bhandari,&nbsp;Zachary A. Pardos","doi":"10.1111/bjet.13570","DOIUrl":"https://doi.org/10.1111/bjet.13570","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;p&gt;Effective educational measurement relies heavily on the curation of well-designed item pools. However, item calibration is time consuming and costly, requiring a sufficient number of respondents to estimate the psychometric properties of items. In this study, we explore the potential of six different large language models (LLMs; GPT-3.5, GPT-4, Llama 2, Llama 3, Gemini-Pro and Cohere Command R Plus) to generate responses with psychometric properties comparable to those of human respondents. Results indicate that some LLMs exhibit proficiency in College Algebra that is similar to or exceeds that of college students. However, we find the LLMs used in this study to have narrow proficiency distributions, limiting their ability to fully mimic the variability observed in human respondents, but that an ensemble of LLMs can better approximate the broader ability distribution typical of college students. Utilizing item response theory, the item parameters calibrated by LLM respondents have high correlations (eg, &gt;0.8 for GPT-3.5) with their human calibrated counterparts. Several augmentation strategies are evaluated for their relative performance, with resampling methods proving most effective, enhancing the Spearman correlation from 0.89 (human only) to 0.93 (augmented human).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;h3&gt;Practitioner notes&lt;/h3&gt;\u0000 &lt;p&gt;What is already known about this topic\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;The collection of human responses to candidate test items is common practice in educational measurement when designing an assessment tool.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Large language models (LLMs) have been found to rival human abilities in a variety of subject areas, making them a low-cost option for testing the efficacy of educational assessment items.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Data augmentation using AI has been an effective strategy for enhancing machine learning model performance.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 \u0000 &lt;p&gt;What this paper adds\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;This paper provides the first psychometric analysis of the ability distribution of a variety of open-source and proprietary LLMs as compared to humans.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;The study finds that item parameters similar to those produced by 50 undergraduate respondents.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Using LLM respondents to augment human response data yields mixed results.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 \u0000 &lt;p&gt;Implications ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 3","pages":"1028-1052"},"PeriodicalIF":6.7,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13570","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ensuring privacy through synthetic data generation in education","authors":"Qinyi Liu,&nbsp;Ronas Shakya,&nbsp;Jelena Jovanovic,&nbsp;Mohammad Khalil,&nbsp;Javier de la Hoz-Ruiz","doi":"10.1111/bjet.13576","DOIUrl":"https://doi.org/10.1111/bjet.13576","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;p&gt;High-volume, high-quality and diverse datasets are crucial for advancing research in the education field. However, such datasets often contain sensitive information that poses significant privacy challenges. Traditional anonymisation techniques fail to meet the privacy standards required by regulations like GDPR, prompting the need for more robust solutions. Synthetic data have emerged as a promising privacy-preserving approach, allowing for the generation and sharing of datasets that mimic real data while ensuring privacy. Still, the application of synthetic data alone on educational datasets remains vulnerable to privacy threats such as linkage attacks. Therefore, this study explores for the first time the application of &lt;i&gt;private synthetic data&lt;/i&gt;, which combines synthetic data with differential privacy mechanisms, in the education sector. By considering the dual needs of data utility and privacy, we investigate the performance of various synthetic data generation techniques in safeguarding sensitive educational information. Our research focuses on two key questions: the capability of these techniques to prevent privacy threats and their impact on the utility of synthetic educational datasets. Through this investigation, we aim to bridge the gap in understanding the balance between privacy and utility of advanced privacy-preserving techniques within educational contexts.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;h3&gt;Practitioner notes&lt;/h3&gt;\u0000 &lt;p&gt;What is already known about this topic\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;Traditional privacy-preserving methods for educational datasets have not proven successful in ensuring a balance of data utility and privacy. Additionally, these methods often lack empirical evaluation and/or evidence of successful application in practice.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Synthetic data generation is a state-of-the-art privacy-preserving method that has been increasingly used as a substitute for real datasets for data publishing and sharing. However, recent research has demonstrated that even synthetic data are vulnerable to privacy threats.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Differential privacy (DP) is the gold standard for quantifying and mitigating privacy concerns. Its combination with synthetic data, often referred to as &lt;i&gt;private synthetic data,&lt;/i&gt; is presently the best available approach to ensuring data privacy. However, private synthetic data have not been studied in the educational domain.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 \u0000 &lt;p&gt;What this study contributes\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;The study has applied synthetic data generation methods with D","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 3","pages":"1053-1073"},"PeriodicalIF":6.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scaffolding middle school mathematics curricula with large language models","authors":"Rizwaan Malik,&nbsp;Dorna Abdi,&nbsp;Rose Wang,&nbsp;Dorottya Demszky","doi":"10.1111/bjet.13571","DOIUrl":"https://doi.org/10.1111/bjet.13571","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;p&gt;Despite well-designed curriculum materials, teachers often face challenges implementing them due to diverse classroom needs. This paper investigates whether large language models (LLMs) can support middle school math teachers by helping create high-quality curriculum scaffolds, which we define as the adaptations and supplements teachers employ to ensure all students can access and engage with the curriculum. Through cognitive task analysis with expert teachers, we identify a three-stage process for curriculum scaffolding: observation, strategy formulation and implementation. We incorporate these insights into three LLM approaches to create warmup tasks that activate students' background knowledge. The best-performing approach provides the model with the original curriculum materials and an expert-informed prompt; this approach generates warmups that are rated significantly higher than those created by expert teachers in terms of alignment to learning objectives, accessibility to students working below grade level and teacher preference. This research demonstrates the potential of LLMs to support teachers in creating effective scaffolds and provides a methodology for developing artificial intelligence-driven educational tools.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;h3&gt;Practitioner notes&lt;/h3&gt;\u0000 &lt;p&gt;What is already known about this topic\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;Scaffolding is essential for enabling students to access and engage with curriculum materials.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Large language models (LLMs) have shown promise in generating educational content and supporting teachers.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Teachers frequently need to adapt and supplement standardized curricula to meet the diverse needs of their students.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 \u0000 &lt;p&gt;What this paper adds\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;Identifies a three-stage curriculum scaffolding process (observation, strategy formulation, implementation) used by expert teachers.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Demonstrates that providing LLMs with additional context from the curriculum, such as the original warmup task, helps to ground the model and improve the quality of the generated warmup tasks.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Demonstrates that, when prompted well, LLMs can generate warmup tasks that are of similar or better quality compared to those created by expert teachers in terms of alignment to learning objectives, accessibility and teacher preference.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 \u0000 &lt;p&gt;Implications for practice and/or policy","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 3","pages":"999-1027"},"PeriodicalIF":6.7,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Value-sensitive design in the praxis of instructional design: A view of designers in situ","authors":"Victoria Abramenka-Lachheb,&nbsp;Ahmed Lachheb,&nbsp;Gamze Ozogul","doi":"10.1111/bjet.13574","DOIUrl":"https://doi.org/10.1111/bjet.13574","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;p&gt;Philosophical stances and design frameworks, such as value-sensitive design, manifest in design praxis through enacting specific design approaches and employing a variety of methods by the designers. Although it could overlap with other frameworks and approaches in the Instructional Design and Technology (IDT) field, value-sensitive design remains a largely unexplored topic in the praxis of instructional design for several reasons. As it focuses on different stakeholders and their values, and by recognizing the contested issue of universal values, we report in this paper on our empirical work that sought to describe the values that instructional designers hold/express in relation to their instructional design work for online courses. In this study, instructional designers communicated their values while discussing their design philosophies and how they manifested in designing human-computer interactions to promote online authentic learning. Through the theoretical lens of value-sensitive design, we provide a detailed account of instructional designers' values as well as describe and showcase how their values manifested in specific design artefacts. Through this investigation of instructional designers' values, we contribute to the ongoing discussion on value-sensitive design and generate implications for instructional design research and education. These implications contribute to the evolution of the instructional design field.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;h3&gt;Practitioner notes&lt;/h3&gt;\u0000 &lt;p&gt;What is already known about this topic\u0000\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;Philosophical stances and design frameworks, such as value-sensitive design (VSD), manifest in design praxis through designers enacting specific design approaches and employing a variety of methods.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;VSD overlaps with other frameworks and approaches in the Instructional Design and Technology (IDT) field and manifests through different terms/frameworks.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;VSD is a largely unexplored topic in the praxis of instructional design.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;Designers' philosophies, values and design judgements play a significant role in design practice, and they are the driving force behind the enactment of frameworks and philosophical stances such as VSD.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;The IDT field has not sufficiently addressed the role of the designer in carrying out design work.&lt;/li&gt;\u0000 &lt;/ul&gt;\u0000 &lt;p&gt;What this paper adds\u0000\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 4","pages":"1311-1349"},"PeriodicalIF":6.7,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13574","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144273225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling cognitive processes in digital reading through behavioural cues: A hybrid intelligence (HI) approach","authors":"Yoon Lee,&nbsp;Gosia Migut,&nbsp;Marcus Specht","doi":"10.1111/bjet.13551","DOIUrl":"https://doi.org/10.1111/bjet.13551","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;p&gt;Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constrained by the subjective nature of human evaluation and the challenges of maintaining consistency and scalability. The recent widespread AI technology has been applied to learning analytics (LA), aiming at a more accurate, consistent and scalable understanding of learning to compensate for challenges that human intelligence faces. However, machine intelligence has been criticized for lacking contextual understanding and difficulties dealing with complex human emotions and social cues. In this work, we aim to understand learners' internal cognitive processes based on the external behavioural cues of learners in a digital reading context, using a hybrid intelligence (HI) approach, bridging human and machine intelligence. Based on the behavioural frameworks and the insights from human experts, we scope specific behavioural cues that are known to be relevant to learners' attention regulation, which is highly relevant for learners' cognitive processes. We utilize the public WEDAR dataset with 30 subjects' video data, behaviour annotation and pre–post tests on multiple choice and summarization tasks. We apply the explainable AI (XAI) approach to train the machine learning model so that human evaluators can also understand which behavioural features were essential for predicting the usage of the cognitive processes (ie, higher-order thinking skills [HOTS] and lower-order thinking skills [LOTS]) of learners, providing insights for the next-round feature engineering and intervention design. The result indicates that the dominant use of attention regulation behaviours is a reliable indicator of low use of LOTS with 79.33% prediction accuracy, while reading speed is a valuable indicator for predicting the overall usage of HOTS and LOTS, ranging from 60.66% to 78.66% accuracy, highly surpassing random guess of 33.33%. Our study demonstrates how various combinations of behavioural features supported by HI can inform learners' cognitive processes accurately and interpretably, integrating human and machine intelligence.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;div&gt;\u0000 \u0000 &lt;h3&gt;Practitioner notes&lt;/h3&gt;\u0000 &lt;p&gt;What is already known about this topic\u0000\u0000 &lt;/p&gt;&lt;ul&gt;\u0000 \u0000 &lt;li&gt;Human attention is a cognitive process that allows us to choose and concentrate on relevant information, which leads to successful learning.&lt;/li&gt;\u0000 \u0000 &lt;li&gt;In affective computing, certain behavioural cues (eg, attention regulation behaviours) are used to indicate learners' ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 2","pages":"678-711"},"PeriodicalIF":6.7,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13551","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}