Computers and Education Open最新文献_第2页

Learning personalization in block-based programming languages using clustering and static code analysis 使用聚类和静态代码分析学习基于块的编程语言中的个性化

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2026-01-14 DOI: 10.1016/j.caeo.2026.100333

Tatiana Person , Juan Antonio Caballero-Hernández , Cristóbal Romero , Iván Ruiz-Rube , Juan Manuel Dodero

{"title":"Learning personalization in block-based programming languages using clustering and static code analysis","authors":"Tatiana Person , Juan Antonio Caballero-Hernández , Cristóbal Romero , Iván Ruiz-Rube , 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}

引用次数: 0

Perceived utility moderates motivational intervention effects in learning to teach responsibly with GenAI 感知效用调节了GenAI负责任教学的动机干预效果

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2025-12-13 DOI: 10.1016/j.caeo.2025.100324

Jana Boos , Thérése Eder , Andreas Lachner

{"title":"Perceived utility moderates motivational intervention effects in learning to teach responsibly with GenAI","authors":"Jana Boos , Thérése Eder , Andreas Lachner","doi":"10.1016/j.caeo.2025.100324","DOIUrl":"10.1016/j.caeo.2025.100324","url":null,"abstract":"<div><div>Making responsible decisions when integrating artificial intelligence (AI) into teaching requires educators to simultaneously consider technological, pedagogical, and ethical knowledge. However, pre-service teachers often lack this integrated understanding, limiting their ability to reason responsibly in AI-supported educational contexts. Prior research has shown that motivational interventions, particularly those enhancing the utility-value of learning content, can support knowledge integration processes during learning. However, their potential effects on knowledge acquisition remain limited. In this experimental field study (<em>N</em> = 158), we investigated the effects of a scaffolded utility-value intervention on pre-service teachers’ knowledge integration and knowledge acquisition. Additionally, we explored potential aptitude-treatment interaction effects, as utility-value interventions are regarded as especially beneficial for learners with initial low perceived utility-value. Using a one-factorial experimental design with three conditions, participants were assigned to either a utility-value intervention without scaffolds, a scaffolded utility-value intervention, or a control condition before engaging with a digital learning environment that addressed technical, pedagogical, and ethical issues related to AI use in teaching. Overall, the analyses revealed no general effects of the interventions. However, exploratory moderation analyses suggested that the utility-value intervention was detrimental to the knowledge integration of pre-service teachers with high initial perceived utility-value. These findings highlight the importance of tailoring motivational support to learners’ individual prerequisites to foster the development of professional knowledge for the responsible integration of AI in teaching.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100324"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978111","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}

引用次数: 0

Design and validation of a questionnaire on teachers' uses of generative artificial intelligence 教师使用生成式人工智能问卷的设计与验证

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2026-01-08 DOI: 10.1016/j.caeo.2026.100332

Héctor Pérez-Montesdeoca , Daniel Rodríguez-Rodríguez , David Stendardi , Aitana Fernández-Sogorb

{"title":"Design and validation of a questionnaire on teachers' uses of generative artificial intelligence","authors":"Héctor Pérez-Montesdeoca , Daniel Rodríguez-Rodríguez , David Stendardi , Aitana Fernández-Sogorb","doi":"10.1016/j.caeo.2026.100332","DOIUrl":"10.1016/j.caeo.2026.100332","url":null,"abstract":"<div><div>The use of generative artificial intelligence (GAI) in secondary education is transforming teaching practices and students' learning experiences. This study presents the design and validation of a questionnaire to assess the various educational uses of GAI by secondary school teachers. An initial pool of items was developed based on a comprehensive review of recent literature and validated through expert judgment. The preliminary version of the instrument was administered to a sample of 486 secondary school teachers in Spain. Confirmatory factor analyses supported a six-dimension structure: teacher management, creation of teaching materials, student assessment, student empowerment, attention to diversity, and student motivation. The questionnaire demonstrated high internal consistency and adequate convergent and discriminant validity. The results show that teachers use GAI both to optimize their professional performance and to enrich students' learning experiences. Practical implications of the instrument for teacher training, institutional decision-making, and future research directions are discussed.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100332"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978109","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}

引用次数: 0

Designing effective AI professional development: A framework grounded in intelligent-TPACK 设计有效的AI专业发展：基于intelligent-TPACK的框架

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2026-02-09 DOI: 10.1016/j.caeo.2026.100337

Selçuk Dogan

{"title":"Designing effective AI professional development: A framework grounded in intelligent-TPACK","authors":"Selçuk Dogan","doi":"10.1016/j.caeo.2026.100337","DOIUrl":"10.1016/j.caeo.2026.100337","url":null,"abstract":"<div><div>The increasing presence of artificial intelligence (AI) in education requires teachers to develop not only technological proficiency but also pedagogical and ethical fluency in AI use. Responding to this need, this study employs a Conceptual Framework Development model to develop the Intelligent-Technological Pedagogical Content Knowledge-based Professional Development (i-TPACK-based PD) Framework, a research-informed, integrated model that aligns the five knowledge domains of i-TPACK (i.e., i-TK, i-TCK, i-TPK, i-TPACK, and AI Ethics) with four evidence-based AI PD pathways: active learning, use of models and examples, coaching and expert support, and feedback and reflection. Drawing from 40 systematic reviews and empirical studies, the framework interweaves these five i-TPACK domains and four AI PD pathways to create a cohesive structure that fosters teachers’ AI-specific pedagogical reasoning, technological fluency, content-based applications, and ethical decision-making. The paper provides a detailed mapping of i-TPACK domains to AI PD pathways, a sample scenario that illustrates the practical implementation across the phases of teacher learning, and design principles to support PD developers. Additionally, it outlines recommendations for research and practice while critically addressing limitations related to program duration, delivery format, outcome evaluation, and ethical integration. This model offers actionable guidance for designing, implementing, and evaluating AI PD that is pedagogically grounded, ethically responsive, and adaptable across educational contexts.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100337"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188599","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}

引用次数: 0

Unveiling the blended learning factors that affect English as a foreign language learning students’ writing 揭示影响英语作为外语学习学生写作的混合学习因素

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2026-01-14 DOI: 10.1016/j.caeo.2026.100334

Phe Quang Chu , Raqib Chowdhury , Le Thi Thanh Thu

{"title":"Unveiling the blended learning factors that affect English as a foreign language learning students’ writing","authors":"Phe Quang Chu , Raqib Chowdhury , Le Thi Thanh Thu","doi":"10.1016/j.caeo.2026.100334","DOIUrl":"10.1016/j.caeo.2026.100334","url":null,"abstract":"<div><div>While numerous studies targeted the effects of blended learning (BL) on English as a foreign language (EFL) students’ written products, a study to determine the mechanism of what factors in the BL environment impact EFL writing performance is under-researched. In response, the authors drew on Bandura’s triadic reciprocal determinism and Venkatesh et al.’s unified theory of acceptance and use of technology to navigate the hypothesized research model in an exploratory sequential mixed methods design. The sample included six participants in the initial qualitative phase and 148 respondents in the later quantitative phase. The findings based on the statistical analysis of measurement and structural models indicate that BL improves students’ global aspects of writing (task fulfillment, organization) more than their local matters (vocabulary, grammar). In the BL environment, environmental factors and students’ personal factors significantly influence their behaviors, which powerfully predict their writing performance. In the indirect relation, writing performance is impacted almost equally by the BL environmental factors and students’ personal factors. The study suggests some conclusions on the roles of individual, environmental, and behavioral factors in affecting writing performance and implications for promoting the BL prospect in the EFL writing context.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100334"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188120","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}

引用次数: 0

Generative AI in higher education: Ethical and behavioral factors influencing students’ intentions to use ChatGPT 高等教育中的生成式人工智能：影响学生使用ChatGPT意愿的伦理和行为因素

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2026-02-07 DOI: 10.1016/j.caeo.2026.100336

Nina Rizun , Ovidiu Niculae Bordean , Anastasija Nikiforova , Ioana Natalia Beleiu , Aleksandra Revina

{"title":"Generative AI in higher education: Ethical and behavioral factors influencing students’ intentions to use ChatGPT","authors":"Nina Rizun , Ovidiu Niculae Bordean , Anastasija Nikiforova , Ioana Natalia Beleiu , Aleksandra Revina","doi":"10.1016/j.caeo.2026.100336","DOIUrl":"10.1016/j.caeo.2026.100336","url":null,"abstract":"<div><div>This study investigates the behavioral and ethical considerations shaping students’ adoption of ChatGPT for academic tasks, emphasizing the broader implications of Generative AI in higher education. By integrating the Fairness, Accountability, Transparency & Ethics in AI (FATE), the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT), we developed and tested an integrated model using survey data from 344 students across four European countries, Estonia, Germany, Poland, and Romania, selected to capture diverse educational and digital contexts in Northern, Western, Central, and Eastern Europe. Our findings highlight that while ethical concerns shape trust, social influence and students' perceived control over their ability to use ChatGPT are stronger predictors of actual usage. We revealed that explainability and privacy are the strongest predictors of trust in ChatGPT, yet trust does not directly influence students’ intention to use it. Instead, trust significantly impacts perceived performance, suggesting that students evaluate ChatGPT’s reliability through its effectiveness rather than as a factor in adoption. From a behavioral perspective, social influence from university professors and perceived behavioral control emerges as key drivers of ChatGPT adoption. Finally, this research provides practical insights for educators and policymakers on promoting the adoption of generative AI tools in higher education by addressing opportunities, considering associated risks, and determining typical usage patterns among students.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100336"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188600","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}

引用次数: 0

Pre-service teachers’ agency during their interactions with generative AI while designing for learning – a process view on Intelligent-TPACK 职前教师在设计学习过程中与生成式人工智能互动中的能动性——基于Intelligent-TPACK的过程观

IF 5.7

Computers and Education Open Pub Date : 2026-06-01 Epub Date: 2025-12-13 DOI: 10.1016/j.caeo.2025.100325

Kristina Krushinskaia, Jan Elen, Annelies Raes

{"title":"Pre-service teachers’ agency during their interactions with generative AI while designing for learning – a process view on Intelligent-TPACK","authors":"Kristina Krushinskaia, Jan Elen, Annelies Raes","doi":"10.1016/j.caeo.2025.100325","DOIUrl":"10.1016/j.caeo.2025.100325","url":null,"abstract":"<div><div>Agency is considered a core societal value, yet it remains unknown how human agency is affected in human-AI interactions. This study is among the first to use process-level indicators to examine teacher agency during interactions with generative AI (GenAI) in the context of instructional design. While instructional design is regarded as a key teacher role, research shows that teachers often avoid this cognitively demanding task. Today, GenAI offers new opportunities to support teachers in the design process. One approach involves using expert bots customized with one instructional design model, which scaffold the design process and offer ready-made components (e.g., learning goals). However, it is unclear how interactions with an expert bot versus basic ChatGPT influence teacher agency. In this research, we analyzed process data and qualitative feedback from an experiment involving 78 pre-service teachers randomly assigned to one of two conditions: (1) the expert bot condition, where participants interacted with a custom GenAI bot; and (2) the ChatGPT condition, where participants could request any type of support. Three indicators of agency were examined: (1) length of interaction, (2) ownership, and (3) collaborative problem-solving behaviors. The first two indicators suggested higher agency in the expert bot condition, as participants interacted longer and used significantly more self-generated prompts. However, the third indicator revealed reduced agency in both conditions. Instead of providing meaningful feedback on the bot’s suggestions, participants in the expert bot condition often agreed with its output. This suggests that the material contexts of ChatGPT and the expert bot both have unique constraints on teachers’ agency.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"10 ","pages":"Article 100325"},"PeriodicalIF":5.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791899","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}

引用次数: 0

The chain mediating effect of academic anxiety and performance expectations between academic self-efficacy and generative AI reliance 学业焦虑、成绩期望在学业自我效能感与生成人工智能依赖之间的链式中介作用

IF 5.7

Computers and Education Open Pub Date : 2025-12-01 Epub Date: 2025-07-31 DOI: 10.1016/j.caeo.2025.100275

Ting Huang , Chenze Wu

{"title":"The chain mediating effect of academic anxiety and performance expectations between academic self-efficacy and generative AI reliance","authors":"Ting Huang , Chenze Wu","doi":"10.1016/j.caeo.2025.100275","DOIUrl":"10.1016/j.caeo.2025.100275","url":null,"abstract":"<div><div>While Generative Artificial Intelligence (GenAI) tools have been used by an increasing number of students, many teachers and researchers recognized that excessive use of these tools may have adverse impacts on students’ academic development. However, the underlying mechanisms driving GenAI reliance and its consequences remain underexplored. This study aimed to address these gaps by investigating the relationships among academic self-efficacy, academic anxiety, performance expectations, and GenAI reliance, as well as examining the consequences of GenAI reliance and coping strategies to mitigate these issues. Data were collected from 337 university students in a Chinese university and analyzed using Pearson correlation, chain mediation effect, and thematic analysis. The results indicated no significant direct relationship between academic self-efficacy and GenAI reliance. However, academic anxiety and performance expectations were found to mediate this relationship. The most salient consequences of GenAI reliance were decreased independent thinking ability, reduced innovative thinking ability, restricted self-reflection, and limited critical thinking ability. Additionally, students’ self-initiated and expected teacher-initiated strategies to alleviate these consequences were recognized. This study contributes to the limited understanding of GenAI reliance and provides valuable insights for educators and academic institutions in directing students toward the appropriate and critical utilization of GenAI tools.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100275"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144756856","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}

引用次数: 0

How do teachers use digital technology in classrooms? Characterizing mathematics teachers’ teaching practices 教师如何在课堂上使用数字技术？数学教师教学实践的特征

IF 5.7

Computers and Education Open Pub Date : 2025-12-01 Epub Date: 2025-11-17 DOI: 10.1016/j.caeo.2025.100310

Alina Kadluba , Frank Reinhold , Andreas Obersteiner

{"title":"How do teachers use digital technology in classrooms? Characterizing mathematics teachers’ teaching practices","authors":"Alina Kadluba , Frank Reinhold , Andreas Obersteiner","doi":"10.1016/j.caeo.2025.100310","DOIUrl":"10.1016/j.caeo.2025.100310","url":null,"abstract":"<div><div>Digital technology has the potential to improve student learning, especially in mathematics. However, the extent to which students benefit from technology largely depends on how it is integrated into instruction. Nevertheless, little is known about how teachers implement digital technology in the classroom. This study examines how 14 in-service teachers use a digital tool for teaching fractions in 15–20 lessons. We used classroom observation to identify teaching practices, and cluster analysis to group them into teaching approaches. Four main approaches of teaching with digital technology emerged: (i) <em>Practicing</em>, where teachers used various features of the tool to make students practice the learning content, (ii) <em>Presenting</em>, where teachers used the tool predominantly to present the learning content but did not utilize many features, (iii) <em>Motivating Students</em>, where the tool and especially its game-like features were used as a reward for students, and (iv) <em>Low-Guidance</em>, where the teacher did not provide guidance for students how to use the tool. Teaching practices varied between these approaches in several dimensions, for example in how teachers explained the learning content, how they implemented rules, and which learning materials they selected. The findings highlight large variation in integrating even one and the same digital tool in the mathematics classroom. We identified teaching approaches for technology-enhanced learning settings that can inform future research investigating how technology implementation influences student learning. These approaches may also guide the design of professional development programs that support teachers in developing effective strategies for integrating digital technology into their instruction.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100310"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736677","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}

引用次数: 0

Intelligent‑TPACK in practice: design and evidence from a three‑week teacher preparation module 智能TPACK在实践中：设计和证据从一个为期三周的教师准备模块

IF 5.7

Computers and Education Open Pub Date : 2025-12-01 Epub Date: 2025-11-08 DOI: 10.1016/j.caeo.2025.100306

Tugce Aldemir , Selcuk Kilinc , Ali Bicer , Patricia Grant , Trina Davis , Noelle Wall Sweany

{"title":"Intelligent‑TPACK in practice: design and evidence from a three‑week teacher preparation module","authors":"Tugce Aldemir , Selcuk Kilinc , Ali Bicer , Patricia Grant , Trina Davis , Noelle Wall Sweany","doi":"10.1016/j.caeo.2025.100306","DOIUrl":"10.1016/j.caeo.2025.100306","url":null,"abstract":"<div><div>Rapid advances in generative AI sharpen the need for teachers to develop pedagogical and ethical capacities for AI‑integrated instruction. While Technological Pedagogical Content Knowledge (TPACK) provides a valuable framework for technology integration, it does not fully capture AI’s unique complexities. This study presents an integrated i‑TPACK approach that extends Intelligent‑TPACK by adding AI‑as‑content (i‑CK) and AI‑for‑professional development (i‑PD) and by threading a five‑stage AI‑literacy progression (Know→ Use→ Evaluate→ Ethics→ Create) within each domain, treating ethics as distributed and iterative. We designed and examined a three-week professional development module for preservice teachers using a convergent mixed-methods design. Pre–post surveys (<em>n</em> = 25 matched pairs) with a six‑subscale Integrated i‑TPACK instrument showed statistically significant gains across all domains (Wilcoxon, Holm‑adjusted; medium‑to‑large effects). Qualitative analyses of lesson artifacts, decision logs, reflections, and micro-teaching documented instances of layered ethical decision-making (privacy/data governance, bias/fairness, transparency/provenance/accountability), progression along the AI literacy stages, and discipline-aligned pedagogical designs. Embedding an ethical decision‑making checkpoint across performance‑based activities made ethics visible in teacher work and coincided with more explicit safeguards and verification steps in lesson artifacts and micro‑teaching within the module. By detailing this empirically grounded model, our study offers theoretical and practical insights for teacher educators seeking to cultivate principled GenAI-supported instruction.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100306"},"PeriodicalIF":5.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519158","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}

引用次数: 0