Classroom dialogue is crucial for effective teaching and learning, prompting many professional development (PD) programs to focus on dialogic pedagogy. Traditionally, these programs rely on manual analysis of classroom practices, which limits timely feedback to teachers. To address this, artificial intelligence (AI) has been employed for rapid dialogue analysis. However, practical applications of AI models remain limited, often prioritising state-of-the-art performance over educational impact. This study explores whether higher accuracy in AI models correlates with better educational outcomes. We evaluated the performance of two language models—BERT and Llama3—in dialogic analysis and assessed the impact of their performance differences on teachers' learning within a PD program. By fine-tuning BERT and engineering prompts for Llama3, we found that BERT exhibited substantially higher accuracy in analysing dialogic moves. Sixty preservice teachers were randomly assigned to either the BERT or Llama3 group, both participating in a workshop on the academically productive talk (APT) framework. The BERT group utilized the fine-tuned BERT model to facilitate their learning, while the Llama3 group employed the Llama3 model. Statistical analysis showed significant improvements in both groups' knowledge and motivation to learn the APT framework, with high levels of satisfaction reported. Notably, no significant differences were found between the two groups in posttest knowledge, motivation, and satisfaction. Interviews further elucidated how both models facilitated teachers' learning of the APT framework. This study validates the use of AI in teacher training and is among the first to investigate the relationship between AI accuracy and educational outcomes.
{"title":"Evaluating the use of BERT and Llama to analyse classroom dialogue for teachers' learning of dialogic pedagogy","authors":"Deliang Wang, Gaowei Chen","doi":"10.1111/bjet.13604","DOIUrl":"https://doi.org/10.1111/bjet.13604","url":null,"abstract":"<p>Classroom dialogue is crucial for effective teaching and learning, prompting many professional development (PD) programs to focus on dialogic pedagogy. Traditionally, these programs rely on manual analysis of classroom practices, which limits timely feedback to teachers. To address this, artificial intelligence (AI) has been employed for rapid dialogue analysis. However, practical applications of AI models remain limited, often prioritising state-of-the-art performance over educational impact. This study explores whether higher accuracy in AI models correlates with better educational outcomes. We evaluated the performance of two language models—BERT and Llama3—in dialogic analysis and assessed the impact of their performance differences on teachers' learning within a PD program. By fine-tuning BERT and engineering prompts for Llama3, we found that BERT exhibited substantially higher accuracy in analysing dialogic moves. Sixty preservice teachers were randomly assigned to either the BERT or Llama3 group, both participating in a workshop on the academically productive talk (APT) framework. The BERT group utilized the fine-tuned BERT model to facilitate their learning, while the Llama3 group employed the Llama3 model. Statistical analysis showed significant improvements in both groups' knowledge and motivation to learn the APT framework, with high levels of satisfaction reported. Notably, no significant differences were found between the two groups in posttest knowledge, motivation, and satisfaction. Interviews further elucidated how both models facilitated teachers' learning of the APT framework. This study validates the use of AI in teacher training and is among the first to investigate the relationship between AI accuracy and educational outcomes.</p><p>\u0000 \u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 6","pages":"2671-2704"},"PeriodicalIF":8.1,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bera-journals.onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248638","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}
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 types of and strategies for ending, 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.
{"title":"Ending well: Values in concluding or transitioning community educational technology projects","authors":"Caroline R. Pitt","doi":"10.1111/bjet.13598","DOIUrl":"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":8.1,"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}
Luis P. Prieto, Olga Viberg, Jason C. Yip, Paraskevi Topali
{"title":"Aligning human values and educational technologies with value-sensitive design","authors":"Luis P. Prieto, Olga Viberg, Jason C. Yip, Paraskevi Topali","doi":"10.1111/bjet.13602","DOIUrl":"10.1111/bjet.13602","url":null,"abstract":"","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 4","pages":"1299-1310"},"PeriodicalIF":8.1,"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}
Wonjoon Cha, Minxuan Hong, Michael Glassman, Eric M. Anderman, Tzu-Jung Lin
<div> <section> <p>Despite the growing use of learning technology in classrooms, factors predicting young students' engagement in contexts fully or partially mediated by technology remain understudied. This study investigated how fourth and fifth grade students' technology self-efficacy (ie, confidence in utilizing learning management systems) and networking agency (ie, comfort in collaborating and communicating with others online) predicted students' engagement in technology-mediated instruction in online and face-to-face environments. Hierarchical regression and moderation analyses were employed to examine the independent and joint effects of technology self-efficacy and networking agency in two cohorts of public elementary school students from a Midwestern US city. For Cohort 1 students primarily receiving synchronous online instruction in 2020–2021, higher networking agency predicted greater engagement in online learning. For Cohort 2 students primarily receiving face-to-face instruction in 2021–2022, only technology efficacy significantly predicted student engagement. As for task-specific engagement in small group activities, however, which involved heavier use of the learning management systems and applications, networking agency was a significant moderator. Notably, as students felt less comfortable with online collaboration/communication (ie, lower networking agency), technology self-efficacy had a stronger association with students' engagement. These findings suggest that while technology self-efficacy is crucial, it alone does not ensure engagement. Educators should cultivate both technical skills and a supportive, collaborative online environment to enhance engagement across technology-mediated learning contexts.</p> </section> <section> <div> <div> <h3>Practitioner notes</h3> <p>What is already known about this topic </p><ul> <li>Technology (self-)efficacy, or students' confidence in using online learning tools, is crucial for their engagement in technology-mediated learning.</li> <li>Student engagement in technology-mediated learning varies between online and face-to-face environments.</li> </ul> <p>What this paper adds </p><ul> <li>In online environments, networking agency or comfort in online collaboration and communication predicts engagement more strongly than technology efficacy.</li> <li>Technology efficacy consistently predicts young learners' engagement in technology-mediated learning in face-to-face classroom
{"title":"The roles of technology efficacy and networking agency in elementary students' engagement in online and face-to-face technology-mediated learning","authors":"Wonjoon Cha, Minxuan Hong, Michael Glassman, Eric M. Anderman, Tzu-Jung Lin","doi":"10.1111/bjet.13597","DOIUrl":"https://doi.org/10.1111/bjet.13597","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Despite the growing use of learning technology in classrooms, factors predicting young students' engagement in contexts fully or partially mediated by technology remain understudied. This study investigated how fourth and fifth grade students' technology self-efficacy (ie, confidence in utilizing learning management systems) and networking agency (ie, comfort in collaborating and communicating with others online) predicted students' engagement in technology-mediated instruction in online and face-to-face environments. Hierarchical regression and moderation analyses were employed to examine the independent and joint effects of technology self-efficacy and networking agency in two cohorts of public elementary school students from a Midwestern US city. For Cohort 1 students primarily receiving synchronous online instruction in 2020–2021, higher networking agency predicted greater engagement in online learning. For Cohort 2 students primarily receiving face-to-face instruction in 2021–2022, only technology efficacy significantly predicted student engagement. As for task-specific engagement in small group activities, however, which involved heavier use of the learning management systems and applications, networking agency was a significant moderator. Notably, as students felt less comfortable with online collaboration/communication (ie, lower networking agency), technology self-efficacy had a stronger association with students' engagement. These findings suggest that while technology self-efficacy is crucial, it alone does not ensure engagement. Educators should cultivate both technical skills and a supportive, collaborative online environment to enhance engagement across technology-mediated learning contexts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Technology (self-)efficacy, or students' confidence in using online learning tools, is crucial for their engagement in technology-mediated learning.</li>\u0000 \u0000 <li>Student engagement in technology-mediated learning varies between online and face-to-face environments.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>In online environments, networking agency or comfort in online collaboration and communication predicts engagement more strongly than technology efficacy.</li>\u0000 \u0000 <li>Technology efficacy consistently predicts young learners' engagement in technology-mediated learning in face-to-face classroom","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 6","pages":"2623-2646"},"PeriodicalIF":8.1,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bera-journals.onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248520","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}
Xiaoqing Xu, Lifang Qiao, Nuo Cheng, Hongxia Liu, Wei Zhao
<div> <section> <p>The rapid development of generative artificial intelligence (GenAI) has brought opportunities and new challenges to higher education. Students need a high level of self-regulated learning to adapt to this change. However, it is difficult for students to persist in self-regulation without guidance. Metacognitive support has a significant advantage in enhancing self-regulated learning, but fewer studies have explored the effects of its role in GenAI environments. The purpose of this study was to investigate the impacts of metacognitive support on college students' self-regulated learning and learning experiences in a GenAI environment. A quasi-experiment was designed in which 68 college students were divided into two groups. The experimental group (<i>N</i> = 35) received explicit metacognitive support, while the control group (<i>N</i> = 33) did not receive any metacognitive prompts. The experiment lasted 4 weeks. The study measured students' academic performance, self-regulated learning ability and learning experiences (including cognitive load and technology acceptance). The results indicate that in the GenAI environment, metacognitive support, while not producing significant between-group differences in achievement, enhances students' self-regulated learning abilities particularly in terms of task strategy and self-evaluation, as well as optimizing their learning experience. The study also found that students were at risk of decreasing their level of self-regulated learning if they lacked metacognitive support in the GenAI environment. The conclusion points out that GenAI supports learners to accomplish learning tasks while potentially reducing self-regulated learning effectiveness, and that metacognitive support is key to supporting effective regulation in learners' GenAI environments. This study provides an important theoretical and practical basis for how to better support learners' learning in GenAI environments.</p> </section> <section> <div> <div> <h3>Practitioner notes</h3> <p>What is already known about this topic </p><ul> <li>SRL is vital for effective learning in digital environments.</li> <li>Generative AI tools, like ChatGPT, can enhance learning but require support.</li> <li>Learners often struggle to apply SRL strategies without guidance.</li> </ul> <p>What this paper adds </p><ul> <li>Metacognitive support improves SRL in Generative AI environments.</li> <li>It reduces cognitive load and increases the perceived usefulness of AI tools.</li>
{"title":"Enhancing self-regulated learning and learning experience in generative AI environments: The critical role of metacognitive support","authors":"Xiaoqing Xu, Lifang Qiao, Nuo Cheng, Hongxia Liu, Wei Zhao","doi":"10.1111/bjet.13599","DOIUrl":"10.1111/bjet.13599","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <p>The rapid development of generative artificial intelligence (GenAI) has brought opportunities and new challenges to higher education. Students need a high level of self-regulated learning to adapt to this change. However, it is difficult for students to persist in self-regulation without guidance. Metacognitive support has a significant advantage in enhancing self-regulated learning, but fewer studies have explored the effects of its role in GenAI environments. The purpose of this study was to investigate the impacts of metacognitive support on college students' self-regulated learning and learning experiences in a GenAI environment. A quasi-experiment was designed in which 68 college students were divided into two groups. The experimental group (<i>N</i> = 35) received explicit metacognitive support, while the control group (<i>N</i> = 33) did not receive any metacognitive prompts. The experiment lasted 4 weeks. The study measured students' academic performance, self-regulated learning ability and learning experiences (including cognitive load and technology acceptance). The results indicate that in the GenAI environment, metacognitive support, while not producing significant between-group differences in achievement, enhances students' self-regulated learning abilities particularly in terms of task strategy and self-evaluation, as well as optimizing their learning experience. The study also found that students were at risk of decreasing their level of self-regulated learning if they lacked metacognitive support in the GenAI environment. The conclusion points out that GenAI supports learners to accomplish learning tasks while potentially reducing self-regulated learning effectiveness, and that metacognitive support is key to supporting effective regulation in learners' GenAI environments. This study provides an important theoretical and practical basis for how to better support learners' learning in GenAI environments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>SRL is vital for effective learning in digital environments.</li>\u0000 \u0000 <li>Generative AI tools, like ChatGPT, can enhance learning but require support.</li>\u0000 \u0000 <li>Learners often struggle to apply SRL strategies without guidance.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>Metacognitive support improves SRL in Generative AI environments.</li>\u0000 \u0000 <li>It reduces cognitive load and increases the perceived usefulness of AI tools.</li>\u0000 ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 5","pages":"1842-1863"},"PeriodicalIF":8.1,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811293","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}
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.
{"title":"Supporting teachers' value-sensitive reflections on the cost–benefit dynamics of technology in educational practices","authors":"Davinia Hernández-Leo, Karina Ginoyan","doi":"10.1111/bjet.13592","DOIUrl":"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":8.1,"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}
The affinity space framework has proven useful for explaining and understanding teacher activity on social media platforms. In this study, we explore the ‘dark side’ of teacher affinity spaces by documenting a partisan teachers' group on an alternative social media platform. We used a mix of a priori and emergent coding to analyse screenshots of posts and comments from a public teachers' group and group administrators' activity on the broader platform. Findings indicate that although the group administrators began with a focus on teachers, most participants were non-teachers with political (rather than professional) concerns about US education. Furthermore, administrators both freely engaged with political talking points in their activity outside the teachers' group and allowed the broader platform culture—including conspiratorial thinking, explicit racism and out-group villainization—to seep in. We conclude by describing how these findings correspond with the key characteristics of an affinity space, including an overlapping of affinities, a lack of concern for professional qualifications, and influence from the broader platform. These findings provide an illustrative example of how teacher affinity spaces can drift from their stated intention within the larger platform context.
Practitioner notes
What is already known about this topic
Social media spaces have been conceptualized as affinity spaces for educators.
Most studies provide optimistic accounts of teacher professional learning on social media.
Most research has analysed teachers' use of mainstream platforms.
What this paper adds
We offer a detailed analysis of a partisan US teacher group on an alternative platform.
Initial efforts to focus on teaching devolved into in-group identification and out-group villainization.
This study highlights how the characteristics of affinity spaces can be detrimental to teacher professional learning.
Implications for practice and/or policy
Administrators of online groups should recognize their important role in ensuring group purposes are enacted.
Educators should assess whether the larger platform is conducive to cultivatin
{"title":"The dark side of affinity spaces for teacher professional learning","authors":"Daniel G. Krutka, Spencer P. Greenhalgh","doi":"10.1111/bjet.13593","DOIUrl":"https://doi.org/10.1111/bjet.13593","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <p>The affinity space framework has proven useful for explaining and understanding teacher activity on social media platforms. In this study, we explore the ‘dark side’ of teacher affinity spaces by documenting a partisan teachers' group on an alternative social media platform. We used a mix of a priori and emergent coding to analyse screenshots of posts and comments from a public teachers' group and group administrators' activity on the broader platform. Findings indicate that although the group administrators began with a focus on teachers, most participants were non-teachers with political (rather than professional) concerns about US education. Furthermore, administrators both freely engaged with political talking points in their activity outside the teachers' group and allowed the broader platform culture—including conspiratorial thinking, explicit racism and out-group villainization—to seep in. We conclude by describing how these findings correspond with the key characteristics of an affinity space, including an overlapping of affinities, a lack of concern for professional qualifications, and influence from the broader platform. These findings provide an illustrative example of how teacher affinity spaces can drift from their stated intention within the larger platform context.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Social media spaces have been conceptualized as affinity spaces for educators.</li>\u0000 \u0000 <li>Most studies provide optimistic accounts of teacher professional learning on social media.</li>\u0000 \u0000 <li>Most research has analysed teachers' use of mainstream platforms.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>We offer a detailed analysis of a partisan US teacher group on an alternative platform.</li>\u0000 \u0000 <li>Initial efforts to focus on teaching devolved into in-group identification and out-group villainization.</li>\u0000 \u0000 <li>This study highlights how the characteristics of affinity spaces can be detrimental to teacher professional learning.</li>\u0000 </ul>\u0000 <p>Implications for practice and/or policy\u0000\u0000 </p><ul>\u0000 \u0000 <li>Administrators of online groups should recognize their important role in ensuring group purposes are enacted.</li>\u0000 \u0000 <li>Educators should assess whether the larger platform is conducive to cultivatin","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 6","pages":"2573-2594"},"PeriodicalIF":8.1,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248710","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}
Given the significant and unique contributions of both in-class and out-of-class learning, pedagogical initiatives that connect learners' experiences across these two learning spheres would bolster language development. Technology can catalyse the integration. Whether and how teachers utilize this potential of technology to engage in digital bridging initiatives, initiatives that support the connection of students' in-class and out-of-class learning experiences with digital resources, deserve attention. Thematic analysis of 13 interview responses and exploratory and confirmatory factor analyses of 1101 survey responses of primary and secondary school Chinese EFL teachers unravelled two dimensions of digital bridging initiatives: inward bridging practices and outward bridging practices. SEM analysis of the survey responses further revealed various determinants of teachers' bridging initiatives, underscoring the strong and direct influence of teachers' awareness of students' out-of-class digital behaviours and the mediated influence of school culture. The study further highlighted the prominence of teacher internal factors, such as educator-oriented identity belief, awareness of students' out-of-class digital behaviours, and TPACK, for outward bridging. The study advocates attention to the nuances of teachers' digital bridging initiatives and influencing factors across contexts.
{"title":"Teachers' digital initiatives to bridge students' in-class and out-of-class language learning and the influencing factors","authors":"Chun Lai, Zhan Shi","doi":"10.1111/bjet.13595","DOIUrl":"https://doi.org/10.1111/bjet.13595","url":null,"abstract":"<p>Given the significant and unique contributions of both in-class and out-of-class learning, pedagogical initiatives that connect learners' experiences across these two learning spheres would bolster language development. Technology can catalyse the integration. Whether and how teachers utilize this potential of technology to engage in digital bridging initiatives, initiatives that support the connection of students' in-class and out-of-class learning experiences with digital resources, deserve attention. Thematic analysis of 13 interview responses and exploratory and confirmatory factor analyses of 1101 survey responses of primary and secondary school Chinese EFL teachers unravelled two dimensions of digital bridging initiatives: inward bridging practices and outward bridging practices. SEM analysis of the survey responses further revealed various determinants of teachers' bridging initiatives, underscoring the strong and direct influence of teachers' awareness of students' out-of-class digital behaviours and the mediated influence of school culture. The study further highlighted the prominence of teacher internal factors, such as educator-oriented identity belief, awareness of students' out-of-class digital behaviours, and TPACK, for outward bridging. The study advocates attention to the nuances of teachers' digital bridging initiatives and influencing factors across contexts.</p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 6","pages":"2595-2622"},"PeriodicalIF":8.1,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bera-journals.onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13595","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248709","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}
Chia-Jung Li, Gwo-Jen Hwang, Ching-Yi Chang, Hui-Chi Su
In professional training, developing critical thinking is essential for professionals to analyse problem situations and respond effectively to emergencies. Conventional professional training typically employs multimedia materials combined with progressive prompting (PP) to support trainees in constructing knowledge and solving problems on their own. However, for those trainees who have insufficient knowledge or experience, it could be challenging for them to understand and utilise the prompts for finding solutions to the problems to be dealt with. To provide a personalised advisor during the progressive prompting-based training process, this study proposed a generative artificial intelligence (GenAI)-supported PP (GenAI-PP) learning approach by employing GenAI to facilitate discussions with individual trainees regarding the prompts, thereby encouraging deeper thinking and critical analysis at each stage. This study adopted a quasi-experimental design to compare the effects of GenAI-PP and the conventional PP (C-PP) approach on students' learning outcomes. The participants were 62 newly qualified nurses with less than one year of clinical experience in Taiwan, who needed to learn to interpret electrocardiograms (ECGs) as part of their professional training. Results showed that the GenAI-PP group significantly outperformed the C-PP group on test scores (p < 0.01) and critical thinking (p < 0.01). Moreover, the GenAI-PP group experienced significantly lower extraneous cognitive load compared to the C-PP group (p < 0.001). These findings suggest the potential of GenAI-PP in professional training; that is, GenAI could serve as a learning partner to discuss with trainees the prompts provided by the instructor to help them master core concepts and develop key career competencies, especially for training programs that require in-depth analysis and decision-making.
{"title":"Generative AI-supported progressive prompting for professional training: Effects on learning achievement, critical thinking, and cognitive load","authors":"Chia-Jung Li, Gwo-Jen Hwang, Ching-Yi Chang, Hui-Chi Su","doi":"10.1111/bjet.13594","DOIUrl":"https://doi.org/10.1111/bjet.13594","url":null,"abstract":"<p>In professional training, developing critical thinking is essential for professionals to analyse problem situations and respond effectively to emergencies. Conventional professional training typically employs multimedia materials combined with progressive prompting (PP) to support trainees in constructing knowledge and solving problems on their own. However, for those trainees who have insufficient knowledge or experience, it could be challenging for them to understand and utilise the prompts for finding solutions to the problems to be dealt with. To provide a personalised advisor during the progressive prompting-based training process, this study proposed a generative artificial intelligence (GenAI)-supported PP (GenAI-PP) learning approach by employing GenAI to facilitate discussions with individual trainees regarding the prompts, thereby encouraging deeper thinking and critical analysis at each stage. This study adopted a quasi-experimental design to compare the effects of GenAI-PP and the conventional PP (C-PP) approach on students' learning outcomes. The participants were 62 newly qualified nurses with less than one year of clinical experience in Taiwan, who needed to learn to interpret electrocardiograms (ECGs) as part of their professional training. Results showed that the GenAI-PP group significantly outperformed the C-PP group on test scores (<i>p</i> < 0.01) and critical thinking (<i>p</i> < 0.01). Moreover, the GenAI-PP group experienced significantly lower extraneous cognitive load compared to the C-PP group (<i>p</i> < 0.001). These findings suggest the potential of GenAI-PP in professional training; that is, GenAI could serve as a learning partner to discuss with trainees the prompts provided by the instructor to help them master core concepts and develop key career competencies, especially for training programs that require in-depth analysis and decision-making.</p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 6","pages":"2550-2572"},"PeriodicalIF":8.1,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248509","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}
Longwei Zheng, Anna He, Changyong Qi, Haomin Zhang, Xiaoqing Gu
<div> <section> <p>In the field of education, the think-aloud protocol is commonly used to encourage learners to articulate their thoughts during the learning process, providing observers with valuable insights into learners' cognitive processes beyond the final learning outcomes. However, the implementation of think-aloud protocols faces challenges such as task interference and limitations in completeness and authenticity of verbal reports. This study proposes a method called Cognitive Echo, which leverages large language models (LLMs) trained with simulated student experiences to enhance the completeness and authenticity of think-aloud verbalizations. LLMs have been demonstrated to simulate human-like behaviour more effectively by memorizing experiences. In this work, we introduce specific learner roles and train the LLMs to act as distinct learners. Our method involves integrating transaction data from learners' interactions with a tutoring system and the tutor's content to create interactive experiences between learners and teachers, thereby training the model to become simulated students with learning experiences. To investigate the effectiveness of this approach, we designed a test playground based on the retrospective think-aloud protocol and examined how LLM-trained simulated students improve cognitive process transparency and generalization of learning strategies. The study found that Cognitive Echo not only reveals what simulated students genuinely think about their learning experiences but also enables them to transfer their different cognitive strategies to new tasks. By training simulated students on real learning behaviour data to ensure their cognitive processes reflect authentic learner experiences, this approach will extend think-aloud protocols to more practice-oriented applications.</p> </section> <section> <div> <div> <h3>Practitioner notes</h3> <p>What is already known about this topic </p><ul> <li>Think-aloud protocols are widely used in educational settings to explore students' cognitive processes by asking them to verbalize their thoughts while solving problems, but they are prone to issues like task interference and incomplete data reporting.</li> <li>Existed applications of simulating student cognition in educational research are rigid and less adaptive to individual learner characteristics.</li> <li>Artificial intelligences, especially large language models, have shown promise in educational contexts, particularly for simulating human-like behaviours.</li> </ul> <p>What this paper adds </p><ul>
{"title":"Cognitive Echo: Enhancing think-aloud protocols with LLM-based simulated students","authors":"Longwei Zheng, Anna He, Changyong Qi, Haomin Zhang, Xiaoqing Gu","doi":"10.1111/bjet.13590","DOIUrl":"10.1111/bjet.13590","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <p>In the field of education, the think-aloud protocol is commonly used to encourage learners to articulate their thoughts during the learning process, providing observers with valuable insights into learners' cognitive processes beyond the final learning outcomes. However, the implementation of think-aloud protocols faces challenges such as task interference and limitations in completeness and authenticity of verbal reports. This study proposes a method called Cognitive Echo, which leverages large language models (LLMs) trained with simulated student experiences to enhance the completeness and authenticity of think-aloud verbalizations. LLMs have been demonstrated to simulate human-like behaviour more effectively by memorizing experiences. In this work, we introduce specific learner roles and train the LLMs to act as distinct learners. Our method involves integrating transaction data from learners' interactions with a tutoring system and the tutor's content to create interactive experiences between learners and teachers, thereby training the model to become simulated students with learning experiences. To investigate the effectiveness of this approach, we designed a test playground based on the retrospective think-aloud protocol and examined how LLM-trained simulated students improve cognitive process transparency and generalization of learning strategies. The study found that Cognitive Echo not only reveals what simulated students genuinely think about their learning experiences but also enables them to transfer their different cognitive strategies to new tasks. By training simulated students on real learning behaviour data to ensure their cognitive processes reflect authentic learner experiences, this approach will extend think-aloud protocols to more practice-oriented applications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <div>\u0000 \u0000 <div>\u0000 \u0000 <h3>Practitioner notes</h3>\u0000 <p>What is already known about this topic\u0000\u0000 </p><ul>\u0000 \u0000 <li>Think-aloud protocols are widely used in educational settings to explore students' cognitive processes by asking them to verbalize their thoughts while solving problems, but they are prone to issues like task interference and incomplete data reporting.</li>\u0000 \u0000 <li>Existed applications of simulating student cognition in educational research are rigid and less adaptive to individual learner characteristics.</li>\u0000 \u0000 <li>Artificial intelligences, especially large language models, have shown promise in educational contexts, particularly for simulating human-like behaviours.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":"56 5","pages":"2019-2042"},"PeriodicalIF":8.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811128","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}
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