Holding learners' attention is challenging, especially when they are asked to listen to long passages. High-immersion virtual reality (VR) can immerse learners in listening tasks, even in such complex languages as Chinese. This exploratory study examined the effect of VR on 43 Chinese language learners' listening comprehension, enjoyment, sense of presence, and cognitive load. Participants were self-selected into two groups without knowing the purpose of the study or the details of their activity. The experimental group (n1 = 23) experienced an interactive multimedia story in VR, and the comparison group (n2 = 20) watched a screencast video recording of the same story. Multivariate analysis of covariance (MANCOVA) indicated that VR may have a positive effect on the development of listening skills. Compared with the video group, the VR group had significantly higher listening comprehension scores, reported significantly more enjoyment and sense of presence, and reported experiencing less cognitive load. Thus, the findings suggest that VR could be used as a pedagogical tool to enhance foreign language listening skills.
{"title":"An exploratory study on practising listening comprehension skills in high-immersion virtual reality","authors":"Yongluan Ye, Regina Kaplan-Rakowski","doi":"10.1111/bjet.13481","DOIUrl":"10.1111/bjet.13481","url":null,"abstract":"<p>Holding learners' attention is challenging, especially when they are asked to listen to long passages. High-immersion virtual reality (VR) can immerse learners in listening tasks, even in such complex languages as Chinese. This exploratory study examined the effect of VR on 43 Chinese language learners' listening comprehension, enjoyment, sense of presence, and cognitive load. Participants were self-selected into two groups without knowing the purpose of the study or the details of their activity. The experimental group (<i>n</i><sub>1</sub> = 23) experienced an interactive multimedia story in VR, and the comparison group (<i>n</i><sub>2</sub> = 20) watched a screencast video recording of the same story. Multivariate analysis of covariance (MANCOVA) indicated that VR may have a positive effect on the development of listening skills. Compared with the video group, the VR group had significantly higher listening comprehension scores, reported significantly more enjoyment and sense of presence, and reported experiencing less cognitive load. Thus, the findings suggest that VR could be used as a pedagogical tool to enhance foreign language listening skills.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937712","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}
The HyFlex course has been widely adopted in higher education settings. However, there is a paucity of empirical studies examining students' acceptance of large‐scale HyFlex courses, as well as factors influencing their acceptance. To fill this research gap, the present study investigated students' acceptance of a large‐scale HyFlex course and the variations in their acceptance according to different participation modes (ie, on‐site, synchronously online and mixed attendance), based on a total of 160 valid samples from a large‐scale HyFlex course at a normal university in central China during the fall semester of 2022. The results indicated that students' overall HyFlex course acceptance was generally high, and the students who alternately engaged in on‐site and synchronously online learning had the highest level of acceptance. Furthermore, this study employed structural equation modelling to validate a model integrating the unified theory of acceptance and use of technology with connected classroom climate (CCC). The findings showed that performance expectancy (PE), effort expectancy, facilitating conditions and CCC directly influenced students' acceptance, with performance expectancy having the strongest direct effect. However, social influence only had an indirect effect on students' acceptance, while CCC had both direct and indirect effects. This study carries substantial theoretical and practical implications, enhancing our understanding of students' acceptance of the HyFlex learning approach.Practitioner notesWhat is already known about this topic The adoption of the HyFlex course, especially in the context of large‐scale courses, is prevalent in higher education settings.Existing studies have predominately focused on assessing the impact of HyFlex course on student engagement and learning outcomes, the development and implementation of HyFlex course structures, and educators' perspectives and experiences with HyFlex courses.Although some research has delved into students' satisfaction with HyFlex courses, particularly in small class settings, our understanding of students' acceptance of large‐scale HyFlex course remains limited.There has been a noticeable gap in investigations exploring distinctions among students who opt for varying HyFlex course delivery modes, such as on‐site, synchronously online and mixed attendance formats.What this paper adds This study reveals that students generally displayed a high level of acceptance towards the large‐scale HyFlex course.Notably, students who participated in alternating on‐site and synchronously online learning exhibited a significantly higher level of accept
{"title":"Examining students' acceptance of the large‐scale HyFlex course: An empirical study","authors":"Harrison Hao Yang, Zhongyue Yin, Sha Zhu","doi":"10.1111/bjet.13477","DOIUrl":"https://doi.org/10.1111/bjet.13477","url":null,"abstract":"The HyFlex course has been widely adopted in higher education settings. However, there is a paucity of empirical studies examining students' acceptance of large‐scale HyFlex courses, as well as factors influencing their acceptance. To fill this research gap, the present study investigated students' acceptance of a large‐scale HyFlex course and the variations in their acceptance according to different participation modes (ie, on‐site, synchronously online and mixed attendance), based on a total of 160 valid samples from a large‐scale HyFlex course at a normal university in central China during the fall semester of 2022. The results indicated that students' overall HyFlex course acceptance was generally high, and the students who alternately engaged in on‐site and synchronously online learning had the highest level of acceptance. Furthermore, this study employed structural equation modelling to validate a model integrating the unified theory of acceptance and use of technology with connected classroom climate (CCC). The findings showed that performance expectancy (PE), effort expectancy, facilitating conditions and CCC directly influenced students' acceptance, with performance expectancy having the strongest direct effect. However, social influence only had an indirect effect on students' acceptance, while CCC had both direct and indirect effects. This study carries substantial theoretical and practical implications, enhancing our understanding of students' acceptance of the HyFlex learning approach.<jats:boxed-text content-type=\"box\" position=\"anchor\"><jats:caption>Practitioner notes</jats:caption>What is already known about this topic <jats:list list-type=\"bullet\"> <jats:list-item>The adoption of the HyFlex course, especially in the context of large‐scale courses, is prevalent in higher education settings.</jats:list-item> <jats:list-item>Existing studies have predominately focused on assessing the impact of HyFlex course on student engagement and learning outcomes, the development and implementation of HyFlex course structures, and educators' perspectives and experiences with HyFlex courses.</jats:list-item> <jats:list-item>Although some research has delved into students' satisfaction with HyFlex courses, particularly in small class settings, our understanding of students' acceptance of large‐scale HyFlex course remains limited.</jats:list-item> <jats:list-item>There has been a noticeable gap in investigations exploring distinctions among students who opt for varying HyFlex course delivery modes, such as on‐site, synchronously online and mixed attendance formats.</jats:list-item> </jats:list>What this paper adds <jats:list list-type=\"bullet\"> <jats:list-item>This study reveals that students generally displayed a high level of acceptance towards the large‐scale HyFlex course.</jats:list-item> <jats:list-item>Notably, students who participated in alternating on‐site and synchronously online learning exhibited a significantly higher level of accept","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937605","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}
Collaborative learning, driven by knowledge co-construction and meaning negotiation, is a pivotal aspect of educational contexts. While gesture's importance in conveying shared meaning is recognized, its role in collaborative group settings remains understudied. This gap hinders accurate and equitable assessment and instruction, particularly for linguistically diverse students. Advancements in multimodal learning analytics, leveraging sensor technologies, offer innovative solutions for capturing and analysing body movements. This study employs these novel approaches to demonstrate how learners' machine-detected body movements during the learning process relate to their verbal and nonverbal contributions to the co-construction of embodied math knowledge. These findings substantiate the feasibility of utilizing learners' machine-detected body movements as a valid indicator for inferring their engagement with the collaborative knowledge construction process. In addition, we empirically validate that these inferred different levels of learner engagement indeed impact the desired learning outcomes of the intervention. This study contributes to our scientific understanding of multimodal approaches to knowledge expression and assessment in learning, teaching, and collaboration.
{"title":"Your body tells how you engage in collaboration: Machine-detected body movements as indicators of engagement in collaborative math knowledge building","authors":"Hanall Sung, Mitchell J. Nathan","doi":"10.1111/bjet.13473","DOIUrl":"10.1111/bjet.13473","url":null,"abstract":"<p>Collaborative learning, driven by knowledge co-construction and meaning negotiation, is a pivotal aspect of educational contexts. While gesture's importance in conveying shared meaning is recognized, its role in collaborative group settings remains understudied. This gap hinders accurate and equitable assessment and instruction, particularly for linguistically diverse students. Advancements in multimodal learning analytics, leveraging sensor technologies, offer innovative solutions for capturing and analysing body movements. This study employs these novel approaches to demonstrate how learners' machine-detected body movements during the learning process relate to their verbal and nonverbal contributions to the co-construction of embodied math knowledge. These findings substantiate the feasibility of utilizing learners' machine-detected body movements as a valid indicator for inferring their engagement with the collaborative knowledge construction process. In addition, we empirically validate that these inferred different levels of learner engagement indeed impact the desired learning outcomes of the intervention. This study contributes to our scientific understanding of multimodal approaches to knowledge expression and assessment in learning, teaching, and collaboration.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13473","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937662","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}
<div> <section> <p>Teaching and learning in higher education have increasingly become digitalized and associated with innovative pedagogical methodologies over the past decades. Following the sudden onset of the pandemic in March 2020, several studies tended to focus on traditional students' experiences with emergency remote education while literature is scarce on non-traditional students (or adult learners) pedagogical experiences in Distance Education contexts. Using a qualitative case study approach, this study explored how digital technologies mediated instructors' and adult learners' educational experiences during COVID-19 and their first-time experiences with blended learning. Between October 2021 and July 2022, semi-structured interviews were conducted with 40 adult learners and 20 instructors in three selected public higher education institutions (HEIs) in Ghana. Data analysis followed Braun and Clarke's (2012) thematic analysis approach. The results showed that the transition to blended learning was supported by the adoption and integration of varied virtual online technologies. The themes highlight the positive and negative impacts of technology in mediating the educational experiences of instructors and adult learners in blended learning environments. The themes which reflected both instructors' and adult learners' experiences were enhanced course delivery and pedagogy, competency development, technological issues and poor-quality pedagogy. Blended learning facilitated by technology could be the ‘new normal learning’ post-pandemic for adult learners pursuing Distance Education in Ghana. The study recommends the implementation of agile strategies and policies by HEIs to ensure sustainable quality education in distance learning.</p> </section> <section> <div> <div> <h3>Practitioner notes</h3> <p>What is already known about this topic </p><ul> <li>The COVID-19 pandemic necessitated the adoption of innovative pedagogical approaches in higher education contexts.</li> <li>Technological transformations in information and communication technology (ICT) have enhanced remote teaching in higher education institutions globally.</li> <li>The educational experiences of educators and learners differ in blended learning contexts.</li> </ul> <p>What this paper adds </p><ul> <li>Instructors and adult learners' positive experiences with navigating a variety of web-based technologies during the educational process are negatively impacted by technological difficulties during online instruction.</li>
{"title":"Transitioning to blended learning during COVID-19: Exploring instructors and adult learners' experiences in three Ghanaian universities","authors":"Esinam Afi Kayi","doi":"10.1111/bjet.13475","DOIUrl":"10.1111/bjet.13475","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Teaching and learning in higher education have increasingly become digitalized and associated with innovative pedagogical methodologies over the past decades. Following the sudden onset of the pandemic in March 2020, several studies tended to focus on traditional students' experiences with emergency remote education while literature is scarce on non-traditional students (or adult learners) pedagogical experiences in Distance Education contexts. Using a qualitative case study approach, this study explored how digital technologies mediated instructors' and adult learners' educational experiences during COVID-19 and their first-time experiences with blended learning. Between October 2021 and July 2022, semi-structured interviews were conducted with 40 adult learners and 20 instructors in three selected public higher education institutions (HEIs) in Ghana. Data analysis followed Braun and Clarke's (2012) thematic analysis approach. The results showed that the transition to blended learning was supported by the adoption and integration of varied virtual online technologies. The themes highlight the positive and negative impacts of technology in mediating the educational experiences of instructors and adult learners in blended learning environments. The themes which reflected both instructors' and adult learners' experiences were enhanced course delivery and pedagogy, competency development, technological issues and poor-quality pedagogy. Blended learning facilitated by technology could be the ‘new normal learning’ post-pandemic for adult learners pursuing Distance Education in Ghana. The study recommends the implementation of agile strategies and policies by HEIs to ensure sustainable quality education in distance learning.</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>The COVID-19 pandemic necessitated the adoption of innovative pedagogical approaches in higher education contexts.</li>\u0000 \u0000 <li>Technological transformations in information and communication technology (ICT) have enhanced remote teaching in higher education institutions globally.</li>\u0000 \u0000 <li>The educational experiences of educators and learners differ in blended learning contexts.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>Instructors and adult learners' positive experiences with navigating a variety of web-based technologies during the educational process are negatively impacted by technological difficulties during online instruction.</li>\u0000 ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937603","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}
The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In this paper, we explore the magnitude of the country and language divide in the leading open-source and proprietary LLMs with respect to knowledge of K-12 taxonomies in a variety of countries and their performance on tagging problem content with the appropriate skill from a taxonomy, an important task for aligning open educational resources and tutoring content with state curricula. We also experiment with approaches to narrowing the performance divide by enhancing LLM skill tagging performance across four countries (the USA, Ireland, South Korea and India–Maharashtra) for more equitable outcomes. We observe considerable performance disparities not only with non-English languages but with English and non-US taxonomies. Our findings demonstrate that fine-tuning GPT-3.5 with a few labelled examples can improve its proficiency in tagging problems with relevant skills or standards, even for countries and languages that are underrepresented during training. Furthermore, the fine-tuning results show the potential viability of GPT as a multilingual skill classifier. Using both an open-source model, Llama2-13B, and a closed-source model, GPT-3.5, we also observe large disparities in tagging performance between the two and find that fine-tuning and skill information in the prompt improve both, but the closed-source model improves to a much greater extent. Our study contributes to the first empirical results on mitigating disparities across countries and languages with LLMs in an educational context.
Practitioner notes
What is already known about this topic
Recent advances in generative AI have led to increased applications of LLMs in education, offering diverse opportunities.
LLMs excel predominantly in English and exhibit a bias towards the US context.
Automated content tagging has been studied using English-language content and taxonomies.
What this paper adds
Investigates the country and language disparities in LLMs concerning knowledge of educational taxonomies and their performance in tagging content.
{"title":"Bridging large language model disparities: Skill tagging of multilingual educational content","authors":"Yerin Kwak, Zachary A. Pardos","doi":"10.1111/bjet.13465","DOIUrl":"10.1111/bjet.13465","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>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.</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>Recent advances in generative AI have led to increased applications of LLMs in education, offering diverse opportunities.</li>\u0000 \u0000 <li>LLMs excel predominantly in English and exhibit a bias towards the US context.</li>\u0000 \u0000 <li>Automated content tagging has been studied using English-language content and taxonomies.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>Investigates the country and language disparities in LLMs concerning knowledge of educational taxonomies and their performance in tagging content.</li>\u0000 \u0000 <li>Presents the firs","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13465","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937667","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}
Mohammad Khalil, Jacqueline Wong, Barbara Wasson, Fred Paas
A core focus of self-regulated learning (SRL) research lies in uncovering methods to empower learners within digital learning environments. As digital technologies continue to evolve during the current hype of artificial intelligence (AI) in education, the theoretical, empirical and methodological nuances to support SRL are emerging and offering new ways for adaptive support and guidance for learners. Such affordances offer a unique opportunity for personalised learning experiences, including adaptive interventions. Exploring the application of adaptivity to enhance SRL is an important and emerging area of research that requires further attention. This editorial introduces the contributions of seven papers for the special section on adaptive support for SRL within digital learning environments. These papers explore various themes related to enhancing SRL strategies through technological interventions, offering valuable insights and paving the way for future advancements in this dynamic area.
{"title":"Adaptive support for self-regulated learning in digital learning environments","authors":"Mohammad Khalil, Jacqueline Wong, Barbara Wasson, Fred Paas","doi":"10.1111/bjet.13479","DOIUrl":"10.1111/bjet.13479","url":null,"abstract":"<p>A core focus of self-regulated learning (SRL) research lies in uncovering methods to empower learners within digital learning environments. As digital technologies continue to evolve during the current hype of artificial intelligence (AI) in education, the theoretical, empirical and methodological nuances to support SRL are emerging and offering new ways for adaptive support and guidance for learners. Such affordances offer a unique opportunity for personalised learning experiences, including adaptive interventions. Exploring the application of adaptivity to enhance SRL is an important and emerging area of research that requires further attention. This editorial introduces the contributions of seven papers for the special section on adaptive support for SRL within digital learning environments. These papers explore various themes related to enhancing SRL strategies through technological interventions, offering valuable insights and paving the way for future advancements in this dynamic area.</p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13479","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887474","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}
Fengyao Sun, Peiyao Tian, Daner Sun, Yanhua Fan, Yuqin Yang
<div> <section> <p>In the ever-evolving AI-driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre-service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers' willingness to integrate AI (WIAI), especially from the perspective of pre-service STEM teachers' attitudes towards the application of AI in teaching. In the study, a comprehensive survey was conducted among 239 pre-service STEM teachers, examining the influences and interconnectedness of Technological Pedagogical Content Knowledge (TPACK), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Self-Efficacy (SE) on WIAI. Structural Equation Modeling (SEM) was employed for data analysis. The findings illuminated direct influences of TPACK, PU, PE, and SE on WIAI. TPACK was found to directly affect PE, PU, and SE, while PE and PU also directly influenced SE. Further analysis revealed significant mediating roles of PE, PU, and SE in the relationship between TPACK and WIAI, highlighting the presence of a chain mediation effect. In light of these insights, the study offers several recommendations on promoting pre-service STEM teachers' willingness to integrate AI into their teaching practices.</p> </section> <section> <div> <div> <h3>Practitioner notes</h3> <p>What is already known about this topic? </p><ul> <li>The potential of AI technologies to enrich learning experiences and improve outcomes in STEM education has been recognized.</li> <li>Pre-service teachers' willingness to integrate AI into teaching practice is crucial for shaping the future learning environment.</li> <li>The TAM and TPACK frameworks are used to analyse teacher factors in technology-supported learning environments.</li> <li>Few studies have been conducted for examining factors of pre-service teachers' willingness to integrate AI into teaching practices in the context of STEM education.</li> </ul> <p>What this paper adds? </p><ul> <li>A survey was designed and developed for exploring pre-service STEM teachers' WIAI and its relationships with factors including TPACK, PE, PU, and SE.</li> <li>TPACK, SE, PU, and PE have direct impact on pre-service STEM teachers' WIAI.</li> <li>SE, PU, and PE have been identified as mediating variables in the relationship
在不断发展的人工智能驱动的教育中，将人工智能技术融入教学实践对于有抱负的 STEM 教育工作者来说已变得越来越必要。然而，关于职前 STEM 教师是否准备好将人工智能融入教学实践的研究仍然十分匮乏。本研究探讨了影响教师融入人工智能意愿（WIAI）的因素，特别是从职前 STEM 教师对在教学中应用人工智能的态度角度进行了研究。研究对 239 名职前 STEM 教师进行了全面调查，考察了技术教学内容知识（TPACK）、感知有用性（PU）、感知易用性（PE）和自我效能感（SE）对 WIAI 的影响和相互联系。数据分析采用了结构方程模型（SEM）。研究结果表明了 TPACK、PU、PE 和 SE 对 WIAI 的直接影响。发现 TPACK 直接影响 PE、PU 和 SE，而 PE 和 PU 也直接影响 SE。进一步的分析表明，在 TPACK 与 WIAI 的关系中，PE、PU 和 SE 起着重要的中介作用，突出了连锁中介效应的存在。鉴于这些见解，本研究就促进职前 STEM 教师将人工智能融入教学实践的意愿提出了若干建议。 人工智能技术在丰富 STEM 教育的学习体验和提高成果方面的潜力已得到认可。职前教师将人工智能融入教学实践的意愿对于塑造未来的学习环境至关重要。TAM和TPACK框架被用来分析教师在技术支持的学习环境中的因素。在 STEM 教育背景下，很少有研究探讨职前教师将人工智能融入教学实践的意愿因素。本文有何新意？ 本文设计并编制了一份调查问卷，以探讨职前 STEM 教师的 WIAI 及其与 TPACK、PE、PU 和 SE 等因素的关系。TPACK、SE、PU和PE对职前STEM教师的WIAI有直接影响。在 TPACK 与 WIAI 的关系中，SE、PU 和 PE 被认为是中介变量。研究还发现了两个连续的中介效应，即 TPACK → PE → SE → WIAI 和 TPACK → PU → SE → WIAI。本研究对实践和/或政策的启示 鼓励职前 STEM 教师探索和利用人工智能技术，增强他们将人工智能融入教学实践的信心和自我效能感。展示成功案例和实践经验对于培养将人工智能融入 STEM 教育的意识至关重要。建议在教师培训课程中引入人工智能教育课程。提供与人工智能技术相关的实习和实践机会，可以提高他们将人工智能融入教育的实践技能。
{"title":"Pre-service teachers' inclination to integrate AI into STEM education: Analysis of influencing factors","authors":"Fengyao Sun, Peiyao Tian, Daner Sun, Yanhua Fan, Yuqin Yang","doi":"10.1111/bjet.13469","DOIUrl":"10.1111/bjet.13469","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>In the ever-evolving AI-driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre-service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers' willingness to integrate AI (WIAI), especially from the perspective of pre-service STEM teachers' attitudes towards the application of AI in teaching. In the study, a comprehensive survey was conducted among 239 pre-service STEM teachers, examining the influences and interconnectedness of Technological Pedagogical Content Knowledge (TPACK), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Self-Efficacy (SE) on WIAI. Structural Equation Modeling (SEM) was employed for data analysis. The findings illuminated direct influences of TPACK, PU, PE, and SE on WIAI. TPACK was found to directly affect PE, PU, and SE, while PE and PU also directly influenced SE. Further analysis revealed significant mediating roles of PE, PU, and SE in the relationship between TPACK and WIAI, highlighting the presence of a chain mediation effect. In light of these insights, the study offers several recommendations on promoting pre-service STEM teachers' willingness to integrate AI into their teaching practices.</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>The potential of AI technologies to enrich learning experiences and improve outcomes in STEM education has been recognized.</li>\u0000 \u0000 <li>Pre-service teachers' willingness to integrate AI into teaching practice is crucial for shaping the future learning environment.</li>\u0000 \u0000 <li>The TAM and TPACK frameworks are used to analyse teacher factors in technology-supported learning environments.</li>\u0000 \u0000 <li>Few studies have been conducted for examining factors of pre-service teachers' willingness to integrate AI into teaching practices in the context of STEM education.</li>\u0000 </ul>\u0000 <p>What this paper adds?\u0000\u0000 </p><ul>\u0000 \u0000 <li>A survey was designed and developed for exploring pre-service STEM teachers' WIAI and its relationships with factors including TPACK, PE, PU, and SE.</li>\u0000 \u0000 <li>TPACK, SE, PU, and PE have direct impact on pre-service STEM teachers' WIAI.</li>\u0000 \u0000 <li>SE, PU, and PE have been identified as mediating variables in the relationship ","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140837388","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}
There is a global trend in the increased adoption of e-assessment in school classrooms to enhance learning. Teachers, as classroom-based assessment designers and implementers, play a vital role in such assessment change. However, little is known about school teachers' classroom-based e-assessment practices and the underlying reasons. To address this research gap, this study identified the factors influencing Hong Kong primary school teachers' e-assessment practices underpinned by the theory of planned behaviour (TPB). A large-scale survey was issued to 878 teachers via Qualtrics. Structural equation modelling (SEM) analysis shows that primary school teachers' intentions of using e-assessment and perceived behavioural control of it were the two strongest factors predicting their e-assessment practices in a general way. Specifically, teachers' intentions outweighed perceived behavioural control in determining their use of alternative e-assessment tasks and e-feedback, but this reversed for e-tests/exercises. The impact of perceived behavioural control was consistent across the three types of e-assessment practices. Furthermore, teachers' attitudes significantly influenced their intentions to use alternative e-assessment tasks, while subject norms primarily predicted their intentions to use e-feedback. The findings have implications for primary schools to take countermeasures to facilitate the successful implementation of e-assessment at the classroom level.
{"title":"Primary school teachers' classroom-based e-assessment practices: Insights from the theory of planned behaviour","authors":"Ying Zhan, Daner Sun, Ho Man Kong, Ye Zeng","doi":"10.1111/bjet.13478","DOIUrl":"10.1111/bjet.13478","url":null,"abstract":"<p>There is a global trend in the increased adoption of e-assessment in school classrooms to enhance learning. Teachers, as classroom-based assessment designers and implementers, play a vital role in such assessment change. However, little is known about school teachers' classroom-based e-assessment practices and the underlying reasons. To address this research gap, this study identified the factors influencing Hong Kong primary school teachers' e-assessment practices underpinned by the theory of planned behaviour (TPB). A large-scale survey was issued to 878 teachers via Qualtrics. Structural equation modelling (SEM) analysis shows that primary school teachers' intentions of using e-assessment and perceived behavioural control of it were the two strongest factors predicting their e-assessment practices in a general way. Specifically, teachers' intentions outweighed perceived behavioural control in determining their use of alternative e-assessment tasks and e-feedback, but this reversed for e-tests/exercises. The impact of perceived behavioural control was consistent across the three types of e-assessment practices. Furthermore, teachers' attitudes significantly influenced their intentions to use alternative e-assessment tasks, while subject norms primarily predicted their intentions to use e-feedback. The findings have implications for primary schools to take countermeasures to facilitate the successful implementation of e-assessment at the classroom level.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bjet.13478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141015211","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}
Robert D. Plumley, Matthew L. Bernacki, Jeffrey A. Greene, Shelbi Kuhlmann, Mladen Raković, Christopher J. Urban, Kelly A. Hogan, Chaewon Lee, Abigail T. Panter, Kathleen M. Gates
Even highly motivated undergraduates drift off their STEM career pathways. In large introductory STEM classes, instructors struggle to identify and support these students. To address these issues, we developed co-redesign methods in partnership with disciplinary experts to create high-structure STEM courses that better support students and produce informative digital event data. To those data, we applied theory- and context-relevant labels to reflect active and self-regulated learning processes involving LMS-hosted course materials, formative assessments, and help-seeking tools. We illustrate the predictive benefits of this process across two cycles of model creation and reapplication. In cycle 1, we used theory-relevant features from 3 weeks of data to inform a prediction model that accurately identified struggling students and sustained its accuracy when reapplied in future semesters. In cycle 2, we refit a model with temporally contextualized features that achieved superior accuracy using data from just two class meetings. This modelling approach can produce durable learning analytics solutions that afford scaled and sustained prediction and intervention opportunities that involve explainable artificial intelligence products. Those same products that inform prediction can also guide intervention approaches and inform future instructional design and delivery.
{"title":"Co-designing enduring learning analytics prediction and support tools in undergraduate biology courses","authors":"Robert D. Plumley, Matthew L. Bernacki, Jeffrey A. Greene, Shelbi Kuhlmann, Mladen Raković, Christopher J. Urban, Kelly A. Hogan, Chaewon Lee, Abigail T. Panter, Kathleen M. Gates","doi":"10.1111/bjet.13472","DOIUrl":"10.1111/bjet.13472","url":null,"abstract":"<p>Even highly motivated undergraduates drift off their STEM career pathways. In large introductory STEM classes, instructors struggle to identify and support these students. To address these issues, we developed co-redesign methods in partnership with disciplinary experts to create high-structure STEM courses that better support students and produce informative digital event data. To those data, we applied theory- and context-relevant labels to reflect active and self-regulated learning processes involving LMS-hosted course materials, formative assessments, and help-seeking tools. We illustrate the predictive benefits of this process across two cycles of model creation and reapplication. In cycle 1, we used theory-relevant features from 3 weeks of data to inform a prediction model that accurately identified struggling students and sustained its accuracy when reapplied in future semesters. In cycle 2, we refit a model with temporally contextualized features that achieved superior accuracy using data from just two class meetings. This modelling approach can produce durable learning analytics solutions that afford scaled and sustained prediction and intervention opportunities that involve explainable artificial intelligence products. Those same products that inform prediction can also guide intervention approaches and inform future instructional design and delivery.\u0000 </p>","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141015020","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}
Despite the importance of academic counselling for student success, providing timely and personalized guidance can be challenging for higher education institutions. In this study, we investigate the impact of counselling instances supported by a learning analytics (LA) tool, called TrAC, which provides specific data about the curriculum and grades of each student. To evaluate the tool, we measured changes in students' performance ranking position over 3 years and compared the performance of students who received counselling with and without the tool. Our results show that using the tool is related to an improvement in cohort ranking. We further investigated the characteristics of counselled students using cluster analyses. The findings highlight the potential beneficial influence on academic outcomes arising from the provision of guidance to students regarding their course load decisions via TrAC-mediated counselling. This study contributes to the field of LA by providing evidence of the impact of counselling supported by an LA tool in a real-world setting over a long period of time. Our results suggest that incorporating LA into academic counselling practices can improve student success.
Practitioner notes
What is already known about this topic
By analysing student performance, teaching strategies and resource impact, learning analytics (LA) empowers institutions to make informed changes in curriculum design, resource allocation and educational policies.
Through insights into academic progress, engagement and behaviour, LA counselling tools enable the identification of at-risk students and those needing additional support.
In the related literature, there are areas for further exploration such as understanding the scalability and long-term effects of interventions on student success and retention.
What this paper adds
Through rigorous data analysis, the paper establishes a connection between LA utilization and enhanced student performance, offering concrete evidence of the effectiveness of LA interventions.
By examining various factors such as academic stage and course load, the research offers valuable insights into the contextual nuances that optimize the outcomes of LA tool-based support.
It adds to the growing body of evidence that supports the efficacy of data-driven interventio
尽管学业辅导对学生的成功非常重要，但对于高等教育机构来说，提供及时和个性化的指导可能具有挑战性。在本研究中，我们调查了由名为 TrAC 的学习分析（LA）工具支持的辅导实例的影响，该工具可提供有关每个学生的课程和成绩的具体数据。为了对该工具进行评估，我们测量了三年来学生成绩排名位置的变化，并比较了接受和未接受该工具辅导的学生的成绩。我们的结果表明，使用该工具与学生成绩排名的提高有关。我们还利用聚类分析进一步调查了接受辅导的学生的特点。研究结果凸显了通过以 TrAC 为媒介的辅导为学生的课程负担决策提供指导对学业成绩产生的潜在有利影响。本研究通过提供证据，证明了在现实世界环境中，通过LA工具支持的辅导在很长一段时间内产生的影响，从而为LA领域做出了贡献。通过分析学生成绩、教学策略和资源影响，学习分析（LA）使教育机构能够在课程设计、资源分配和教育政策方面做出明智的改变。通过对学业进展、参与度和行为的深入了解，LA 辅导工具能够识别高危学生和需要额外支持的学生。在相关文献中，还有一些需要进一步探索的领域，如了解干预措施对学生成功率和保留率的可扩展性和长期影响。本文的补充 通过严谨的数据分析，本文建立了使用 "LA "与提高学生成绩之间的联系，为 "LA "干预措施的有效性提供了具体证据。通过对学术阶段和课程负担等各种因素的研究，该研究对优化基于洛杉矶工具的支持结果的环境细微差别提供了有价值的见解。该研究补充了越来越多的证据，这些证据支持以数据为导向的教育干预措施的有效性，促进了一种更加知情和以证据为基础的学生支持和成功方法。对实践和政策的影响 加强学生支持策略：通过根据已确定的有效条件调整辅导干预措施，教育工作者可以积极主动地满足学生的个人需求，从而提高学习成绩和保留率。知情决策：已证明的积极影响凸显了类似的数据驱动措施在促进学生成功方面的潜力。政策制定者可以考虑在机构层面激励采用此类干预措施。未来的研究方向：通过确定影响LA干预措施效果的背景因素，鼓励进一步探索如何针对特定条件优化其他LA干预措施。这将为今后制定更精确、更有效的学生支持策略提供指导。
{"title":"The impact of an academic counselling learning analytics tool: Evidence from 3 years of use","authors":"Valeria Henríquez, Julio Guerra, Eliana Scheihing","doi":"10.1111/bjet.13474","DOIUrl":"10.1111/bjet.13474","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Despite the importance of academic counselling for student success, providing timely and personalized guidance can be challenging for higher education institutions. In this study, we investigate the impact of counselling instances supported by a learning analytics (LA) tool, called TrAC, which provides specific data about the curriculum and grades of each student. To evaluate the tool, we measured changes in students' performance ranking position over 3 years and compared the performance of students who received counselling with and without the tool. Our results show that using the tool is related to an improvement in cohort ranking. We further investigated the characteristics of counselled students using cluster analyses. The findings highlight the potential beneficial influence on academic outcomes arising from the provision of guidance to students regarding their course load decisions via TrAC-mediated counselling. This study contributes to the field of LA by providing evidence of the impact of counselling supported by an LA tool in a real-world setting over a long period of time. Our results suggest that incorporating LA into academic counselling practices can improve student success.</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>By analysing student performance, teaching strategies and resource impact, learning analytics (LA) empowers institutions to make informed changes in curriculum design, resource allocation and educational policies.</li>\u0000 \u0000 <li>Through insights into academic progress, engagement and behaviour, LA counselling tools enable the identification of at-risk students and those needing additional support.</li>\u0000 \u0000 <li>In the related literature, there are areas for further exploration such as understanding the scalability and long-term effects of interventions on student success and retention.</li>\u0000 </ul>\u0000 <p>What this paper adds\u0000\u0000 </p><ul>\u0000 \u0000 <li>Through rigorous data analysis, the paper establishes a connection between LA utilization and enhanced student performance, offering concrete evidence of the effectiveness of LA interventions.</li>\u0000 \u0000 <li>By examining various factors such as academic stage and course load, the research offers valuable insights into the contextual nuances that optimize the outcomes of LA tool-based support.</li>\u0000 \u0000 <li>It adds to the growing body of evidence that supports the efficacy of data-driven interventio","PeriodicalId":48315,"journal":{"name":"British Journal of Educational Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140812299","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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