Computers and Education Artificial Intelligence最新文献

Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education

Computers and Education Artificial Intelligence Pub Date : 2025-02-10 DOI: 10.1016/j.caeai.2025.100380

Ashish Garg, K. Nisumba Soodhani, Ramkumar Rajendran

{"title":"Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education","authors":"Ashish Garg, K. Nisumba Soodhani, Ramkumar Rajendran","doi":"10.1016/j.caeai.2025.100380","DOIUrl":"10.1016/j.caeai.2025.100380","url":null,"abstract":"<div><div>The advent of Generative Artificial Intelligence (GenAI) and large language models like LLama, Palm2, GPT, Gemini, and Claude has revolutionized education by generating human-like text and contextually relevant responses. Our research investigates the impact of structured prompt training on students' learning in data analysis and programming. We experimented with 157 first-year engineering students divided into three groups: a control group (internet access, no GenAI), an experimental group 1 (internet and GenAI without prompt training), and an experimental group 2 (internet and GenAI with prompt training). The prompt training session included techniques like few-shot prompting, chain prompting, and the CLEAR framework. We assessed participants' performance in data analysis tasks using Python, with pre-tests and post-tests measuring their skills in programming across three Bloom's taxonomy levels (understanding, application, and analysis). ANOVA on post-test scores showed significant differences among the groups, with G3 (with prompt training) outperforming G2 (without prompt training) and the control group across all three levels, evidenced by higher mean scores (G3: 6.60, G2: 4.94, Control: 4.28), similar pattern observed in task completion also. These results underscore the effectiveness of structured prompt training in enhancing students' data analysis and programming skills. Our study highlights the potential of GenAI and structured prompt training to transform educational practices and suggests future research directions, including integrating prompt engineering within human-AI collaboration.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100380"},"PeriodicalIF":0.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding the practices, perceptions, and (dis)trust of generative AI among instructors: A mixed-methods study in the U.S. higher education

Computers and Education Artificial Intelligence Pub Date : 2025-02-10 DOI: 10.1016/j.caeai.2025.100383

Wenhan Lyu , Shuang Zhang , Tingting Chung Rachel , Yifan Sun , Yixuan Zhang

{"title":"Understanding the practices, perceptions, and (dis)trust of generative AI among instructors: A mixed-methods study in the U.S. higher education","authors":"Wenhan Lyu , Shuang Zhang , Tingting Chung Rachel , Yifan Sun , Yixuan Zhang","doi":"10.1016/j.caeai.2025.100383","DOIUrl":"10.1016/j.caeai.2025.100383","url":null,"abstract":"<div><div>Generative AI (GenAI) has brought opportunities and challenges for higher education as it integrates into teaching and learning environments. As instructors navigate this new landscape, understanding their engagement with and attitudes toward GenAI is crucial. We surveyed 178 instructors from a single U.S. university to examine their current practices, perceptions, trust, and distrust of GenAI in higher education in March 2024. While most surveyed instructors reported moderate to high familiarity with GenAI-related concepts, their actual use of GenAI tools for direct instructional tasks remained limited. Our quantitative results show that trust and distrust in GenAI are related yet distinct; high trust does not necessarily imply low distrust, and vice versa. We also found significant differences in surveyed instructors' familiarity with GenAI across different trust and distrust groups. Our qualitative results show nuanced manifestations of trust and distrust among surveyed instructors and various approaches to support calibrated trust in GenAI. We discuss practical implications focused on (dis)trust calibration among instructors.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100383"},"PeriodicalIF":0.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Technological self-efficacy and sense of coherence: Key drivers in teachers' AI acceptance and adoption

Computers and Education Artificial Intelligence Pub Date : 2025-02-05 DOI: 10.1016/j.caeai.2025.100377

Asmahan Masry Herzallah , Rania Makaldy

{"title":"Technological self-efficacy and sense of coherence: Key drivers in teachers' AI acceptance and adoption","authors":"Asmahan Masry Herzallah , Rania Makaldy","doi":"10.1016/j.caeai.2025.100377","DOIUrl":"10.1016/j.caeai.2025.100377","url":null,"abstract":"<div><div>This study investigates the factors influencing teachers within the Israeli education system toward the adaptations of artificial intelligence (AI) in teaching by examining the roles of technological self-efficacy (TSE) and a sense of coherence (SOC). Drawing on the Technology Acceptance Model (TAM), a sample of 200 Arab and Jewish teachers in Israel completed online questionnaires. The findings indicated a positive attitude towards AI among teachers. We found a significant positive correlation between perceived usefulness, perceived ease of use, and positive attitude towards AI. TSE fully mediated the relationship between attitude towards AI and adoption intentions AI, while a SOC partially mediated the relationship between TSE and teachers' attitude towards AI. The findings underscore the importance of developing TSE and fostering a SOC among teachers as part of the AI implementation process in the education system.</div><div>The findings offer a new understanding of AI technology adoption processes in education by incorporating psychological variables into the TAM framework and providing practical insights for decision-makers in the Israeli education system and beyond.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100377"},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The influence of AI literacy on complex problem-solving skills through systematic thinking skills and intuition thinking skills: An empirical study in Thai gen Z accounting students

Computers and Education Artificial Intelligence Pub Date : 2025-02-05 DOI: 10.1016/j.caeai.2025.100382

Watcharawat Promma , Narinthon Imjai , Berto Usman , Somnuk Aujirapongpan

{"title":"The influence of AI literacy on complex problem-solving skills through systematic thinking skills and intuition thinking skills: An empirical study in Thai gen Z accounting students","authors":"Watcharawat Promma , Narinthon Imjai , Berto Usman , Somnuk Aujirapongpan","doi":"10.1016/j.caeai.2025.100382","DOIUrl":"10.1016/j.caeai.2025.100382","url":null,"abstract":"<div><div>The rapid integration of artificial intelligence (AI) into various sectors has heightened the need for understanding its impact on cognitive and problem-solving skills. This study investigates the influence of AI literacy (AIL) on complex problem-solving skills (CPS) by examining the mediating roles of systematic thinking skills (STS) and intuitive thinking skills (ITS) among Generation Z accounting students in Thailand. Utilizing structural equation modeling (SEM) to analyze the relationships between these constructs, the research draws on a sample of 420 final-year undergraduate accounting students from both public and private universities, selected through convenience sampling. The findings reveal that AIL significantly enhances both STS and ITS, which in turn play a crucial mediating role in the development of CPS. These results underscore the importance of integrating AIL into educational curricula, particularly to foster deeper cognitive abilities that are essential for effective problem-solving in the context of AI technology. Moreover, the study advocates for the implementation of training programs designed to cultivate these skills within the workforce, thereby preparing individuals to navigate the challenges of the digital era where technology is increasingly pivotal. The implications of this research extend to the formulation of educational policies, the design of training initiatives, and the development of human resource strategies aimed at enhancing the nation's competitive advantage on a global scale.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100382"},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Psychometrics of an Elo-based large-scale online learning system

Computers and Education Artificial Intelligence Pub Date : 2025-02-04 DOI: 10.1016/j.caeai.2025.100376

Hanke Vermeiren , Joost Kruis , Maria Bolsinova , Han L.J. van der Maas , Abe D. Hofman

{"title":"Psychometrics of an Elo-based large-scale online learning system","authors":"Hanke Vermeiren , Joost Kruis , Maria Bolsinova , Han L.J. van der Maas , Abe D. Hofman","doi":"10.1016/j.caeai.2025.100376","DOIUrl":"10.1016/j.caeai.2025.100376","url":null,"abstract":"<div><div>The Elo rating system (ERS), an intuitive and computationally efficient algorithm, offers a means to effectively update estimates of item difficulties and learner abilities as they evolve. This method proves to be highly advantageous in online learning environments. Computerized adaptive practice (CAP) endeavors to present learners with items that are well-suited to their individual ability levels, with the ultimate goal of enhancing motivation and optimizing learning outcomes. The objective of this paper is to outline common challenges that arise in an Elo-based CAP system and to present the psychometric enhancements implemented in the Prowise Learn environments to address these concerns. More specifically, we focus on three main aspects; 1) the development of a new scoring rule balancing response time and accuracy, 2) a way to fix the item scale to deal with item drift, and 3) an improved adaptive K-factor algorithm to speed up convergence in estimation. Using data from the Prowise Learn environment, analyses were done to illustrate the effect of the enhancements. Results show that these enhancements result in more dynamic tracking of the ratings, solve the issue of item drift, and capture the speed-accuracy trade-off more accurately.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100376"},"PeriodicalIF":0.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143311058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extending the technology acceptance model: The role of subjective norms, ethics, and trust in AI tool adoption among students

Computers and Education Artificial Intelligence Pub Date : 2025-02-04 DOI: 10.1016/j.caeai.2025.100379

Rochman Hadi Mustofa , Trian Gigih Kuncoro , Dwi Atmono , Hardika Dwi Hermawan , Sukirman

{"title":"Extending the technology acceptance model: The role of subjective norms, ethics, and trust in AI tool adoption among students","authors":"Rochman Hadi Mustofa , Trian Gigih Kuncoro , Dwi Atmono , Hardika Dwi Hermawan , Sukirman","doi":"10.1016/j.caeai.2025.100379","DOIUrl":"10.1016/j.caeai.2025.100379","url":null,"abstract":"<div><div>This study extends the Technology Acceptance Model (TAM) to investigate the adoption of AI tools among university students, incorporating Ethics and Trust as moderating variables and Subjective Norms as a quadratic variable. Structural Equation Modeling (SEM) on a sample of 437 students’ reveals that Perceived Usefulness (PU) significantly influences Attitude Toward Using (ATU), while Perceived Ease of Use (PU) significantly influences Attitude Toward Using (ATU), while Perceived Ease of Use (PEoU) does not, suggesting familiarity with technology reduces the role of ease of use. Ethics positively impacts ATU, highlighting its importance in shaping attitudes. However, Ethics and Trust do not moderate the ATU-Actual Use (AU) relationship, and the hypothesized quadratic effect of Subjective Norms is unsupported, confirming a linear relationship. These findings underscore the direct influence of Ethics and Trust in AI adoption and suggest that educational policies should prioritize ethical AI usage and trust-building to enhance acceptance.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100379"},"PeriodicalIF":0.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The mediating role of academic stress, critical thinking and performance expectations in the influence of academic self-efficacy on AI dependence: Case study in college students

Computers and Education Artificial Intelligence Pub Date : 2025-02-04 DOI: 10.1016/j.caeai.2025.100381

Benicio Gonzalo Acosta-Enriquez , Marco Agustín Arbulú Ballesteros , Maria de los Angeles Guzman Valle , Jahaira Eulalia Morales Angaspilco , Janet del Rosario Aquino Lalupú , Jessie Leila Bravo Jaico , Nilton César Germán Reyes , Roger Ernesto Alarcón García , Walter Esteban Janampa Castillo

{"title":"The mediating role of academic stress, critical thinking and performance expectations in the influence of academic self-efficacy on AI dependence: Case study in college students","authors":"Benicio Gonzalo Acosta-Enriquez , Marco Agustín Arbulú Ballesteros , Maria de los Angeles Guzman Valle , Jahaira Eulalia Morales Angaspilco , Janet del Rosario Aquino Lalupú , Jessie Leila Bravo Jaico , Nilton César Germán Reyes , Roger Ernesto Alarcón García , Walter Esteban Janampa Castillo","doi":"10.1016/j.caeai.2025.100381","DOIUrl":"10.1016/j.caeai.2025.100381","url":null,"abstract":"<div><div>This study investigated the mediating roles of academic stress, critical thinking, and performance expectations in the relationship between academic self-efficacy and AI dependency among university students. Data were collected via validated instruments and analyzed via structural equation modeling (PLS-SEM) in a cross-sectional study that included 676 students from six universities in northern Peru. The findings indicated that the relationship between academic self-efficacy and AI dependency was substantially mediated by academic stress (β = 0.398, p < 0.001). Furthermore, this relationship is serially mediated by academic stress and performance expectations (β = 0.325, p < 0.001). Academic self-efficacy also had a direct and significant effect on AI dependency (β = 0.444, p < 0.001). Paths that utilized critical thinking as a mediator were not statistically significant, contrary to expectations. The model accounted for 58.9% of the variance in AI dependency. These results indicate that students' levels of AI dependency are significantly influenced by psychological factors, including academic stress and performance expectations. This research contributes to the comprehension of the psychological processes that underlie the adoption of AI in higher education. It also offers valuable insights for the development of interventions that foster balanced AI use while enhancing academic self-efficacy.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100381"},"PeriodicalIF":0.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching

Computers and Education Artificial Intelligence Pub Date : 2025-02-03 DOI: 10.1016/j.caeai.2025.100378

Biao Kong , Che He

引用次数: 0

Towards the implementation of automated scoring in international large-scale assessments: Scalability and quality control

Computers and Education Artificial Intelligence Pub Date : 2025-01-27 DOI: 10.1016/j.caeai.2025.100375

Ji Yoon Jung, Lillian Tyack, Matthias von Davier

{"title":"Towards the implementation of automated scoring in international large-scale assessments: Scalability and quality control","authors":"Ji Yoon Jung, Lillian Tyack, Matthias von Davier","doi":"10.1016/j.caeai.2025.100375","DOIUrl":"10.1016/j.caeai.2025.100375","url":null,"abstract":"<div><div>Even before the age of artificial intelligence, automated scoring received considerable attention in educational measurement. However, its application to constructed response (CR) items in international large-scale assessments (ILSAs) has remained a challenge, primarily due to the difficulty of handling multilingual responses spanning many languages. This study addresses this challenge by investigating two machine learning approaches — supervised and unsupervised learning — for scoring multilingual responses. We explored various scoring methods to assess three science CR items from TIMSS 2023 across all participating countries and 42 languages. The results showed that the supervised learning approach, particularly combining multiple machine translations with artificial neural networks (MMT_ANNs), showed comparable performance to human scoring. The MMT_ANN model demonstrated impressive accuracy, correctly classifying up to 94.88% of responses across all languages and countries. This remarkable performance can be attributed to MMT_ANNs providing more suitable translations at both individual response and language levels. Furthermore, MMT_ANNs consistently generated accurate scores for identical or borderline responses within and across countries. These findings indicate the potential of automated scoring as an accurate and cost-effective measure for quality control in ILSAs, reducing the need to hire additional human raters to ensure scoring reliability.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100375"},"PeriodicalIF":0.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Opportunities, challenges and school strategies for integrating generative AI in education

Computers and Education Artificial Intelligence Pub Date : 2025-01-25 DOI: 10.1016/j.caeai.2025.100373

Davy Tsz Kit Ng , Eagle Kai Chi Chan , Chung Kwan Lo

{"title":"Opportunities, challenges and school strategies for integrating generative AI in education","authors":"Davy Tsz Kit Ng , Eagle Kai Chi Chan , Chung Kwan Lo","doi":"10.1016/j.caeai.2025.100373","DOIUrl":"10.1016/j.caeai.2025.100373","url":null,"abstract":"<div><div>The increasing accessibility of Generative Artificial Intelligence (GenAI) tools has led to their exploration and adoption in education. This qualitative study investigates the opportunities and challenges associated with integrating GenAI in education, and the strategies that encourage teachers and students to embrace GenAI in school settings. We recruited 76 educators in Canada to participate in a professional training seminar about GenAI and expressed their views through online surveys. Through written reflections, an optimistic outlook on GenAI's role in education was identified among the teachers, and some discipline-specific ideas were proposed. Thematic analysis reveals three key practices of AI implementation: teaching/learning, administration and assessments. However, three major challenges are also identified: school's readiness, teachers' AI competencies, and students' AI literacy and ethics. Teachers suggest several strategies to motivate GenAI integration, including professional development, clear guidelines, and access to AI software and technical support. Finally, Singh's Teach AI Global Initiative Guidance and Socio-ecological Model are adapted and proposed to support schools in becoming AI-ready by addressing teachers' and students' needs, facilitating organizational learning, and promoting improvement and transformation to foster their literacy development. Recommendations were provided for developing effective strategies to embrace GenAI in education.</div></div>","PeriodicalId":34469,"journal":{"name":"Computers and Education Artificial Intelligence","volume":"8 ","pages":"Article 100373"},"PeriodicalIF":0.0,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0