Computers and Education Open最新文献

{"title":"Motivation to shape the future of education with Artificial Intelligence: An international comparison between Switzerland and China","authors":"Judit Martínez-Moreno ,&nbsp;Xinyan Zhou ,&nbsp;Dominik Petko ,&nbsp;Thomas K.F. Chiu","doi":"10.1016/j.caeo.2025.100327","DOIUrl":"10.1016/j.caeo.2025.100327","url":null,"abstract":"<div><div>As digital technologies and Artificial Intelligence (AI) continue to reshape educational environments, understanding the motivations of student teachers is critical to developing effective teacher education programmes. This study cross-culturally validates the (D) FIT-Choice (Digital Factors Influencing Teaching Choice) scale and examines motivational differences among 416 student teachers in Switzerland and China. The results offer partial validation of the (D)FIT-Choice scale, with several higher-order factors demonstrating acceptable to strong internal consistency, but limitations in model fit for some factors, indicating the need for further refinement to ensure cross-cultural applicability. When comparing the motivations of Swiss and Chinese student teachers, Swiss student teachers reported stronger social utility values and intrinsic motivations than their Chinese counterparts, suggesting a focus on personal fulfilment, social contribution and aligning career choice with personal identity, possibly shaped by Switzerland's individualistic culture and civic engagement. In contrast, Chinese student teachers showed higher perceived digital teaching competence and greater enthusiasm for integrating AI into education, differences that may reflect national educational strategies and technological infrastructures, such as China's long-standing investment in educational digitalisation and the presence of AI-focused education initiatives. These results reveal different levels of willingness to shape the future of education with AI, highlighting how cultural and systemic factors influence the motivation of student teachers. In general, this study highlights how sociocultural, economic and technological contexts shape the motivations of future teachers, emphasising the importance of adapting teacher education to local contexts to prepare future teachers to actively participate in the digital transformation of education.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100327"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978110","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":"Ethical conditions for university students’ adoption of large language models in exam preparation contexts","authors":"Antonio Pérez-Portabella ,&nbsp;Mario Arias-Oliva ,&nbsp;Graciela Padilla-Castillo ,&nbsp;Jorge de Andrés-Sánchez","doi":"10.1016/j.caeo.2025.100323","DOIUrl":"10.1016/j.caeo.2025.100323","url":null,"abstract":"<div><div>Large Language Models (LLMs), have become a disruptive force in higher education, assisting students in tasks such as summarizing content, clarifying concepts, and preparing for exams. Their rapid adoption has generated both enthusiasm and ethical concern, particularly regarding fairness and responsible use in assessment contexts. This study examines whether university students’ ethical perceptions regarding the use of LLMs for exam preparation influence their intention to use them (IU), and whether this intention, in turn, affects their actual use (USE). Data were collected from 151 undergraduate students enrolled in Spanish universities. Ethical perceptions were measured using the Multidimensional Ethics Scale (MES), which captures three normative perspectives: moral equity (ME), consequentialism (CO), and deontology (DE). The first research objective (RO1) was to determine whether a minimum threshold in each ethical dimension is required for students to form the intention to use LLMs. The second (RO2) assessed whether higher ethical evaluations lead to greater acceptance and use. Necessary Condition Analysis revealed that all three ethical dimensions are necessary conditions for IU (ME: <em>d</em> = 0.338; CO: <em>d</em> = 0.274; DE: <em>d</em> = 0.207; all <em>p</em> &lt; 0.001). Partial Least Squares-Structural Equation Modeling showed that only CO (β = 0.350, <em>p</em> &lt; 0.001) and DE (β = 0.329, <em>p</em> &lt; 0.001) exert statistically significant and sufficient effects on IU, while ME does not (β = 0.108, <em>p</em> = 0.414). Finally, IU is both a necessary (<em>d</em> = 0.325, <em>p</em> &lt; 0.001) and sufficient predictor of USE (β = 0.905, <em>p</em> &lt; 0.001). The findings highlight that ethical reasoning is central to the responsible adoption of LLMs in exam preparation, offering practical guidance for educators and institutions promoting academic integrity.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100323"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791858","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":"Sustaining innovation: Teacher perspectives on content and language integrated learning (CLIL) and digital tool integration in Albanian online education","authors":"Gerda Sula ,&nbsp;Merita Hoxha","doi":"10.1016/j.caeo.2025.100328","DOIUrl":"10.1016/j.caeo.2025.100328","url":null,"abstract":"<div><div>This study explores the perceptions and experiences of secondary school teachers in Albania who implemented Content and Language Integrated Learning (CLIL) combined with digital tools, particularly EdPuzzle, in teaching natural sciences subjects during and after the COVID-19 pandemic (online and face to face). The research focuses on understanding the long-term impact of these methodologies on teaching practices and their potential for continued use in an ever-changing educational landscape. A phenomenological approach was employed to gather in-depth insights through semi-structured interviews, capturing thirty language and natural sciences teachers' reflections on the benefits, challenges, and future possibilities of integrating CLIL with video-based learning tools. Using phenomenological approach, the findings reveal that the teachers observed significant improvements in student engagement, comprehension, and autonomy through the use of CLIL and EdPuzzle. However, they also highlighted challenges related to technological access and the need for ongoing professional development. The study concludes that while the innovative teaching methods fostered during the pandemic have the potential for sustainable use, their success hinges on continued support and adaptation to the evolving educational context in Albania. Recommendations include the integration of CLIL into broader curriculum design, the provision of resources and training for teachers, and further research into the scalability of these practices across different educational settings.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100328"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926875","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":"Emotion-aware learning analytics dashboards: Effects on metacognitive regulation, academic performance, and engagement in self-paced MOOCs","authors":"Ehsan Namaziandost","doi":"10.1016/j.caeo.2026.100385","DOIUrl":"10.1016/j.caeo.2026.100385","url":null,"abstract":"<div><div>Learning analytics dashboards are widely used in self-paced online courses, yet many still emphasize progress and activity while giving limited attention to learners’ emotional states and real-time self-regulation. This study examined whether an emotion-aware learning analytics dashboard (EALAD) could improve learners’ metacognitive regulation, academic performance, and multidimensional engagement in a self-paced massive open online course (MOOC), compared with a standard learning analytics dashboard (LAD) and a no-dashboard condition. Using a randomized controlled design, 150 undergraduate students from three Iranian universities were assigned to an emotion-aware dashboard group (EDG), a standard dashboard group (SDG), or a control group (CG). The three-month intervention was implemented in a self-paced MOOC on instructional design, and all participants were selected from the intermediate range of the Oxford Quick Placement Test (OQPT), with scores between 31 and 40. Data were collected through the Metacognitive Awareness Inventory, an academic performance test, a multidimensional engagement questionnaire, and follow-up interviews. Quantitative data were analyzed using mixed-design and one-way ANCOVAs while controlling for pretest scores. The EDG showed the strongest gains across outcomes, including metacognitive regulation, partial η² = 0.596; emotional engagement, partial η² = 0.500; cognitive engagement, partial η² = 0.463; and academic performance, partial η² = 0.417<strong>,</strong> outperforming both the SDG and CG. The interview findings further showed that the EALAD helped learners recognize emotional states, respond to difficulties more promptly, and interpret progress more holistically. Participants viewed the standard dashboard as useful for pacing and progress tracking, but less helpful for understanding engagement quality. The findings suggest that integrating real-time emotional indicators with actionable dashboard prompts can support self-regulatory decision-making, meaningful engagement, and achievement in self-paced MOOC environments.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100385"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148241231","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":"An experimental study exploring human–AI complementarity in early social-emotional learning","authors":"Doris Kristina Raave ,&nbsp;Tyler Colasante ,&nbsp;Eric Roldan Roa ,&nbsp;Juan Carlos Ramos Martinez ,&nbsp;Hongtao Li ,&nbsp;Sayan Mukherjee ,&nbsp;Tina Malti","doi":"10.1016/j.caeo.2026.100331","DOIUrl":"10.1016/j.caeo.2026.100331","url":null,"abstract":"<div><div>Many children are not receiving crucial social-emotional learning (SEL) support due to systemic constraints, such as high educator workload and training burdens. Pedagogical conversational agents (PCAs)—generative AI-powered virtual characters trained to converse with students like a teacher—offer promising solutions that could extend to SEL. However, the current affective-computing capacities of PCAs may be limiting, as SEL facilitation requires deeper emotional and relational attunement than cognition-heavy subjects (e.g., literacy, numeracy). The emotional and relational skills of human educators likely confer benefits beyond those of PCAs in SEL instruction. Despite this potential complementarity, no studies have experimentally assessed the relative performance of PCAs and educators in SEL contexts. It remains unclear if and how PCAs can help educators close the SEL gap. In this study, we used a controlled comparison to reveal complementary strengths, comparing the performance of a PCA to that of human educators when independently facilitating story-based SEL activities with a static AI child. We used a static AI child to help ensure that any performance differences could be attributed to facilitator type. The PCA (<em>n</em> = 18 simulations) and educators (<em>n</em> = 18) each delivered three SEL activities (<em>N</em> = 108 observations). Expert raters, blind to facilitator type, coded dialogue excerpts for evidence-based SEL support techniques and indicators of pedagogical quality. A mixed ANOVA and <em>t</em>-tests revealed significant differences. The PCA showed strengths in basic relational and instructional domains, maintaining respectful tone and routinely providing procedural scaffolding. Educators showed strengths in deeper SEL instruction, guiding reflection and promoting social-emotional knowledge. We discuss implications for SEL through the lens of human–AI complementarity.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100331"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978115","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":"Longitudinal insights into AI in education: Usage, ethics, and policy development in higher education","authors":"Luke Parker ,&nbsp;A. Jane Loper ,&nbsp;Christopher W. Carter ,&nbsp;Josh Hayes ,&nbsp;Alice Karakas","doi":"10.1016/j.caeo.2025.100329","DOIUrl":"10.1016/j.caeo.2025.100329","url":null,"abstract":"<div><div>Since the launch of ChatGPT in November of 2022, its role in education has been a focal point of debate, with discussions centering on whether it will revolutionize learning, prove to be a temporary trend, or mark a significant technological shift. While initial studies have explored artificial intelligence's (AI) impact on specific classes and institutions, there has been a severe lack of longitudinal research within teacher education programs. This study addresses this gap by analyzing four semesters of data on the evolving use and ethical perceptions of generative AI among students in a teacher education program at a university in the Midwestern United States. Surveys conducted with over 300 students over this time reveal the growing use of GenAI in their educational practices. The findings indicate significant growth in the use of AI for assessment preparation and studying, with usage rates rising from 57 % to 83 % and 44 % to 76 %, respectively. The study also examined the ethical considerations surrounding AI use, identifying ongoing uncertainty and a statistically significant difference in ethical perceptions between AI users and non-users. Additionally, the research highlighted how students perceived the integration of AI into teaching and its impact on academic performance. Findings emphasize the need for teacher education programs to incorporate AI training and address ethical concerns comprehensively and formally.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100329"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978114","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":"Harnessing artificial intelligence for preservice teachers’ development: A scoping review of applications, benefits, and challenges","authors":"Liu Ziying ,&nbsp;Hu Yongchun ,&nbsp;Zhang Qiaoping","doi":"10.1016/j.caeo.2026.100330","DOIUrl":"10.1016/j.caeo.2026.100330","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI) into teacher education is profoundly reshaping the professional development of preservice teachers. This scoping review examines the application of AI in this context, aiming to delineate its characteristics, benefits, and challenges. Following the PRISMA-ScR guidelines, this study conducted a systematic search of three academic databases (Web of Science, ScienceDirect, and EBSCOhost) for empirical research published between 2020 and 2025. After screening an initial pool of literature, 55 studies were included for analysis. The findings reveal a diverse landscape of AI applications, technologies, and subject distributions in preservice teacher development. The analysis indicates that AI can significantly enhance various competencies, including instructional design, subject-specific instruction, practical teaching skills, evaluation efficiency, reflective practice, critical thinking, technology integration, and pedagogical innovation. However, several challenges were identified, encompassing technical limitations, the risk of over-reliance, ethical and social concerns, and barriers to implementation. This review advocates for a proactive approach to leveraging AI’s innovative potential while reducing its associated risks. Future research should focus on the continual evaluation and adaptation of AI tools to ensure they effectively support and advance the professional development of preservice teachers.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100330"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978112","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":"Virtual learning communities as contexts for pre-service teacher learning and development: A design thinking approach","authors":"Kristin Johnson,&nbsp;Alison Hooper","doi":"10.1016/j.caeo.2026.100382","DOIUrl":"10.1016/j.caeo.2026.100382","url":null,"abstract":"<div><div>This study examines how pre-service teachers described their participation in an online teacher learning environment guided by a design thinking framework during field placements. The aim was to explore (a) how participation in a virtual Teacher Learning Community (TLC) supported social learning and connection in an online context, and (b) how pre-service teachers used design thinking to interpret and respond to instructional and classroom challenges encountered in their practicum settings. Seven pre-service teachers participated in four facilitated online sessions in which they identified practice-based dilemmas, engaged in collaborative discussion, and reflected on strategies they attempted in their placements.</div><div>A qualitative thematic analysis of session transcripts and participant reflections examined interactional patterns using the Community of Inquiry framework and traced participants’ engagement across the phases of the design thinking process. Participants described the virtual TLC as supporting social presence through emotional expression, validation, and reciprocal peer mentoring, contributing to perceived psychological safety and reduced isolation. Participants also described using the design thinking structure to organize discussion, reframe challenges, and consider instructional responses, particularly related to classroom management and instructional decision-making.</div><div>Findings suggest that intentionally designed online teacher learning communities may function as spaces for collaborative sensemaking alongside field-based learning, rather than as interventions producing direct instructional outcomes. By centering pre-service teachers’ perspectives, this study highlights how virtual environments can support reflective dialogue and practice-oriented discussion during clinical experiences and informs the design of technology-mediated supports in teacher preparation.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100382"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148177770","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 personalization in block-based programming languages using clustering and static code analysis","authors":"Tatiana Person ,&nbsp;Juan Antonio Caballero-Hernández ,&nbsp;Cristóbal Romero ,&nbsp;Iván Ruiz-Rube ,&nbsp;Juan Manuel Dodero","doi":"10.1016/j.caeo.2026.100333","DOIUrl":"10.1016/j.caeo.2026.100333","url":null,"abstract":"<div><div>Personalized learning in programming education aims at adapting instructional strategies to the diverse needs of students, particularly novice programmers. However, traditional approaches often fail to accommodate individual learning styles or emphasize clean coding practices. This study proposes a data-driven method to personalize programming education by analyzing large-scale datasets from block-based Visual Programming Language (VPL) projects created by novice programmers. Using static code analysis and machine learning, the approach examines the coverage of programming concepts and code quality metrics to identify patterns in student performance, enabling adaptive learning pathways. This approach is implemented in BlocklyMining, a tool that integrates static code analysis, quality assessment through SQALE, and machine-learning-based clustering. The study applies K-Means and Hierarchical Agglomerative Clustering to 215,244 MIT App Inventor projects, evaluating cluster quality using the Silhouette Coefficient (SC) and Davies–Bouldin Index (DBI). Results show that the clustering algorithms effectively group projects, thereby facilitating the generation of personalized learning recommendations tailored to novice programmers’ skill levels.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100333"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978113","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":"Protecting teacher agency in times of strong technology push: grounding decisions in Biesta's educational purposes","authors":"Anneke Smits ,&nbsp;Teemu Valtonen ,&nbsp;Satu Piispa-Hakala ,&nbsp;Alona Forkosh-Baruch ,&nbsp;Ferial Khaddage ,&nbsp;Thérèse Laferrière ,&nbsp;Hiroshi Ueda ,&nbsp;Shirley Yeung","doi":"10.1016/j.caeo.2026.100383","DOIUrl":"10.1016/j.caeo.2026.100383","url":null,"abstract":"<div><div>Digital technologies such as social media and artificial intelligence, and the datafication they enable, increasingly influence society and teaching and learning in schools. Where this leads to partial automation of education, teachers’ agency and student learning and development are at risk. This calls for educational paradigms that emphasize the importance of teacher agency and reorient towards core educational purposes. Drawing on Biesta's domains of qualification, socialization, and subjectification, we argue that technology should enhance learning without undermining teacher agency or the social interactions that socialization and subjectification require. In this conceptual paper, we focus on protecting teacher agency and on using Biesta's domains to guide wise technology choices for the classroom. Our aim is twofold: to show why and how to protect teacher agency regarding educational technology, and to guide educational stakeholders in prioritizing Biesta's three domains when evaluating technologies. We integrate our conceptual work into the TAPP model (Teacher Agency for Pedagogical Purpose).</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100383"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148177792","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}