{"title":"Exploring STEM educators’ perspectives on the integration of AI-enabled technologies in teaching and learning","authors":"Hulya Avci , Stephanie J. Lunn , Zahra Hazari","doi":"10.1016/j.caeo.2025.100304","DOIUrl":"10.1016/j.caeo.2025.100304","url":null,"abstract":"<div><div>The innovation and proliferation of artificial intelligence (AI) technologies are transforming Science, Technology, Engineering, and Mathematics (STEM) disciplines and pedagogical practices, making it essential to prepare educators for this evolving landscape. This qualitative study explores STEM educators’ perceptions of how they developed proficiency with AI-enabled technologies, what motivated their adoption, and the challenges they faced in classroom integration. Using a cross-sectional survey design, we collected open-ended responses from 27 in-service secondary STEM educators in the United States and analyzed the data through the reflexive thematic analysis. Our findings revealed that STEM educators recognized AI as a cognitive scaffold that can support student understanding of complex content and a socio-affective tool that can help enhance teacher–student relationships. The participants highlighted that by streamlining routine tasks, AI allowed them to reclaim time for meaningful student interactions and responsive instruction. The participants also reported developing their AI proficiency through self-directed learning, peer support, and professional networks, driven by motivations to enhance instructional efficiency, support personalized learning, and prepare students for AI-driven futures. However, the participants emphasized several significant challenges, including lack of institutional support, the overwhelming abundance of AI tools, concerns about affordability, and students’ growing overreliance on AI systems. These insights highlight the need for structured, discipline-specific professional development for in-service educators to promote effective and human-centered integration of AI in STEM education. This study contributes to a growing body of research by centering STEM educators’ perspectives and offering novel insights into how to support their effective integration of AI technologies into STEM teaching and learning.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100304"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A review of reviews on TPACK research: is there any focus?","authors":"Febe Fontyn , Jo Tondeur , Jan Sermeus","doi":"10.1016/j.caeo.2025.100285","DOIUrl":"10.1016/j.caeo.2025.100285","url":null,"abstract":"<div><div>The TPACK framework describes what knowledge educators need to effectively integrate technology into teaching specific content. This integrated knowledge is specific to the domains that TPACK combines, i.e. to the content that is taught, the pedagogical approaches chosen and the technology used. Given that there is a substantial body of research literature on TPACK, it seems useful to focus review-studies on one domain. For example, a review might summarize what is known about teachers’ TPACK using a specific technology, comparing and combining the literature across content domains or pedagogical approaches. Inversely a review could also focus on specific content or on a specific pedagogical approach. In this review of reviews we investigate to what extent review research on TPACK focuses on specific domains (technology, pedagogy or content) or their related knowledge components in the TPACK-framework. Based on a systematic literature review of 32 review studies we find that few reviews focus their research questions, selection criteria or results on specific domains or knowledge components. This could be due to a lack of clarity regarding the interpretation of the model (analytic or holistic), about which only six reviews were explicit. We call on the field to clarify the interpretation of TPACK and to decide on which research would be needed to test the model. We argue that focused review studies could be one way to significantly advance the TPACK research field.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100285"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Pérez-Arteaga , E. Letón , J. Pérez-Martín , E.M. Molanes-López , A. Rodriguez-Ascaso
{"title":"Assessment of captions’ quality by students of a MOOC on accessibility of digital materials","authors":"J. Pérez-Arteaga , E. Letón , J. Pérez-Martín , E.M. Molanes-López , A. Rodriguez-Ascaso","doi":"10.1016/j.caeo.2025.100279","DOIUrl":"10.1016/j.caeo.2025.100279","url":null,"abstract":"<div><div>Captions constitute one of the fundamental components of audiovisual accessibility. Ensuring that captions comply with applicable accessibility standards is an important and complex task that requires dedication and specific knowledge. It goes beyond checking whether or not the video has captions. This work aims to evaluate whether students can adequately assess the quality of captions for the deaf or hard of hearing. It analyses data from an activity of a MOOC on accessibility of digital materials, in which they assessed the quality of captions. It was a voluntary task within the course delivered through an Open edX platform. At the time of enrollment, the students were randomly divided into two groups (AB and BA) so that the cohort AB watched the well-captioned video first and then the poorly-captioned video (with identified errors only in relation to 11 requirements of the UNE 153010:2012 standard), and the cohort BA watched them the other way round. After watching each of the videos, 87 students responded to a survey of 18 items with a 5-point Likert scale. The experimental design was a randomized, triple-blind, crossover AB/BA study. The data were analyzed using a multilevel multiple ordinal regression model. The main conclusions are: (1) basic training on accessibility of multimedia learning materials enables students to perform a preliminary assessment of the accessibility of captions; (2) qualitative guidelines present fewer problems than quantitative ones when identifying accessibility problems; (3) novice evaluators tend to underscore some of the items in non-accessible captions, compared to accessible captions.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100279"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144841445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The impact of generative AI on essay revisions and student engagement","authors":"Noble Lo , Alan Wong , Sumie Chan","doi":"10.1016/j.caeo.2025.100249","DOIUrl":"10.1016/j.caeo.2025.100249","url":null,"abstract":"<div><div>This study investigates the effect of AI-generated feedback on university students’ essay writing proficiency in Hong Kong. By integrating generative AI into the revision process, the research examines how automated feedback influences the quality of students’ written work, as well as their engagement, motivation, and emotional responses during revision. The study employs a randomized controlled design, comparing students who received AI feedback on their essays with those who did not. Both quantitative and qualitative data were collected to assess the impact of AI feedback on writing improvement and student experiences. Quantitative analysis shows significant improvements in essay quality for students who utilized AI feedback, while qualitative findings highlight increased engagement and motivation, though students exhibited mixed emotional responses to the revision process. The results suggest that generative AI has considerable potential to enhance writing skills in higher education by providing timely, individualized feedback. This research contributes to ongoing discussions on the role of AI in education, particularly in supporting language instruction and student development.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100249"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Moderating effects of student heterogeneity on community of inquiry affective outcomes: A multigroup analysis","authors":"Teng Seng Choo , Hazri Jamil , Lei Mee Thien","doi":"10.1016/j.caeo.2025.100276","DOIUrl":"10.1016/j.caeo.2025.100276","url":null,"abstract":"<div><div>This study examines the influence of student background attributes on the relationships between Community of Inquiry (CoI) presences and affective learning outcomes in online courses. Using partial least squares structural equation modeling (PLS-SEM) and multigroup analysis, the study investigated how gender, prior online course experience, and degree level moderate the effects of teaching, cognitive, social, and metacognitive presence on perceived learning and satisfaction. Data were collected from 479 students at a Malaysian public university. Results show that gender and prior experience moderate some relationships between CoI presences and perceived learning, but not perceived satisfaction. Specifically, male students perceive greater learning benefits from metacognitive presence compared with females, while females perceive higher learning from cognitive presence. Students with prior online course experience report significantly higher perceived learning from metacognitive presence compared with inexperienced students. Degree level (undergraduate vs. postgraduate) does not significantly moderate most relationships, though measurement invariance issues were found for teaching presence across degree levels. The findings highlight the importance of considering student subgroup heterogeneity in online education research and practice. The result suggests tailored instructional strategies that consider gender differences and prior online learning experience. This study contributes to a more nuanced understanding of how diverse learners experience and benefit from different aspects of the online learning environment, with implications for course design and delivery.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100276"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Path to intelligent evaluation: Utilizing power BI for enhanced performance insights","authors":"Xiaojun Li, Yueke Dong, Zhi Ai","doi":"10.1016/j.caeo.2025.100271","DOIUrl":"10.1016/j.caeo.2025.100271","url":null,"abstract":"<div><div>This paper aims to enhance the performance evaluation process for university faculty by tackling the shortcomings of current assessment methods, including the “one-size-fits-all” approach, the excessive focus on research over teaching, and the absence of automated and intelligent data analysis. The study utilizes performance data from 869 faculty members and employs Microsoft Power BI along with its various components to facilitate comprehensive and categorical assessments, improving both the intelligence of the evaluation process and the visualization of the assessment results.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100271"},"PeriodicalIF":4.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring the association between digital storytelling and self-regulated learning: a review of claims","authors":"Dinaol Urgessa Gita , Bekalu Ferede , Jo Tondeur","doi":"10.1016/j.caeo.2025.100267","DOIUrl":"10.1016/j.caeo.2025.100267","url":null,"abstract":"<div><div>Following the advancement of digital technology, digital storytelling has increasingly evolved in fostering various aspects of students' learning, including self-regulated learning. However, there is a deficiency in studies regarding how digital storytelling is related to self-regulated learning and its specific domains. This review of claims explored the association between digital storytelling and self-regulated learning. Systematic searches in Scopus, Web of Science, and Google Scholar databases were employed. After utilizing inclusion-exclusion criteria, 28 studies were selected for review. A qualitative conceptual review design was employed. Claims were carefully collected from each study. Thematic analysis was employed to analyze data. Our analysis reveals that digital storytelling enhances (meta-) cognitive, motivational, emotional, and behavioral regulations of students, though some domains received little attention. Moreover, to create digital storytelling successfully, students’ use of the (meta-) cognitive strategies such as planning, goal setting, researching, imagination, and reflection contribute vital role. In conclusion, while it's clear that digital storytelling and self-regulated learning are associated, this association is rudimentary; more research is needed to explore how digital storytelling improves all domains of self-regulated learning and how self-regulated learning also influences digital storytelling.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100267"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"User perception and anatomical understanding from use of 3D anatomy technology by exercise science students: A pilot study","authors":"Leesa Anne Grier , Anthony Leicht","doi":"10.1016/j.caeo.2025.100295","DOIUrl":"10.1016/j.caeo.2025.100295","url":null,"abstract":"<div><div>Understanding anatomy poses a significant challenge for non-medical university students, particularly those without prior science knowledge, such as exercise science students. Technology-Enhanced Learning (TEL) resources, including 3D anatomy platforms, have been explored to support student engagement and improve academic outcomes with variable results.</div><div>Objectives: This pilot study investigated the potential of the Complete Anatomy (CA) 3DTEL resource, combined with traditional blended learning methods, to enhance anatomy knowledge of first-year, undergraduate exercise science students.</div><div>Design: Cohort observational study.</div><div>Methods: The study followed 36 participants (46 % female, 54 % male) across two 13-week units. Guided implementation of CA was introduced during unit 1, while students engaged with the resource independently during unit 2. User satisfaction was assessed via surveys, and academic performance evaluated by comparing final unit grades with a 2022 cohort that did not use the resource.</div><div>Results: Results indicated stable student satisfaction and a significantly different academic performance for the 2023 cohort, with median grades increasing from a Pass (50.0–64.9 %) to a Credit (65.0–74.9 %).</div><div>Conclusion: These findings suggest that integrating 3DTEL resources with blended learning can positively support anatomy learning for science-naïve students.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100295"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Social media discussions on educators: Selecting and appraisal of recent research using TF-IDF","authors":"Mateo R. Borbon Jr. , Ryan A. Ebardo","doi":"10.1016/j.caeo.2025.100293","DOIUrl":"10.1016/j.caeo.2025.100293","url":null,"abstract":"<div><div>This systematic literature review, analyzing 36 peer-reviewed publications from 2019 to February of 2025, addresses a critical gap by examining the use of social media analytics (SMA) for faculty evaluation. Employing a novel methodological approach that combines machine learning-assisted screening (ASReview) with TF-IDF, the study finds that platforms like Twitter and Facebook are increasingly analyzed using sentiment analysis, machine learning, and text mining. These techniques provide real-time, unfiltered student feedback on teaching effectiveness, complementing traditional evaluation instruments and helping to monitor institutional reputation. While SMA offers valuable insights, the review highlights significant challenges, including data quality and credibility, algorithmic bias, ethical concerns, and generalizability. Effectively leveraging SMA's potential requires addressing these issues through robust theoretical frameworks, balanced institutional policies, and enhanced digital literacy to improve teaching practices while safeguarding academic integrity.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100293"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learning in hybrid times: Comparing student experiences in traditional and GenAI-supported instruction","authors":"Meital Amzalag , Dizza Beimel , Rina Zviel-Girshin","doi":"10.1016/j.caeo.2025.100313","DOIUrl":"10.1016/j.caeo.2025.100313","url":null,"abstract":"<div><div>The emergence of generative artificial intelligence (GenAI) tools, such as ChatGPT, is reshaping the landscape of higher education by introducing new opportunities for learner autonomy, flexibility, and engagement. While extensive research has explored GenAI’s technical capabilities and ethical implications, limited attention has been paid to students’ subjective learning experiences with AI-supported instruction. This study investigates how undergraduate students perceive and experience two instructional modes in a database management course: traditional lecturer-led instruction and GenAI-supported self-regulated learning. Sixty-eight second-year engineering students participated in the study, providing qualitative insights through open-ended survey responses. The findings reveal key cognitive, emotional, and strategic differences between the two approaches: traditional instruction fostered structure, immediate feedback, and emotional reassurance, while GenAI-supported learning promoted autonomy and exploration but raised concerns regarding reliability and critical thinking. Importantly, students did not view these modes as mutually exclusive, but rather as complementary components of a broader “learning puzzle,” balancing the stability of face-to-face instruction with the adaptability of GenAI to support diverse learning needs. This study contributes to a deeper understanding of hybrid learning environments and underscores the importance of nuanced, learner-centered integration of AI technologies in higher education.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100313"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}