Internet and Higher Education最新文献

{"title":"Empowering ChatGPT adoption in higher education: A comprehensive analysis of university students' intention to adopt artificial intelligence using self-determination and technology-to-performance chain theories","authors":"Yaser Hasan Al-Mamary,&nbsp;Aliyu Alhaji Abubakar","doi":"10.1016/j.iheduc.2025.101015","DOIUrl":"10.1016/j.iheduc.2025.101015","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI), particularly ChatGPT, in higher education is rapidly expanding, offering new avenues for enhancing the learning experience. Despite its potential, the adoption of ChatGPT remains in need of further study, especially in regions like Saudi Arabia. Previous studies have focused on general e-learning tools, but more research needs to examine the specific factors influencing university students' adoption of AI technologies. This study aims to investigate the adoption of ChatGPT among university students in Saudi Arabia, focusing on the mediating role of Technology-to-Performance Chain (TPC) theory between Self-Determination Theory (SDT) constructs (autonomy, competence, and relatedness) and students' intentions to adopt ChatGPT. It also seeks to identify which SDT factors most significantly affect the adoption process. Using a quantitative approach, this study collected data from 253 university students in Saudi Arabia. Structural equation modelling was used to analyze the collected data and determine the relationship between self-determination theory (SDT), technology-to-performance chain theory (TPC) and ChatGPT adoption. Findings reveal that the perceived autonomy and relatedness significantly affect TTF and ChatGPT utilisation, whereas perceived competence has no effect. In addition, TTF and utilisation are the main predictors of intention to adopt ChatGPT. These findings can be useful for educational policy makers and researchers because they indicate that to enhance university students' adoption of AI technologies, focus should be given to their psychological needs. The results also show that enhancing students' self-determination and their perceived connection with technology can significantly affect their decision to adopt such technologies. This research also presents a new model wherein SDT is integrated with TPC with regard to AI in higher education, specifically in the context of Saudi Arabia. This work contributes to the current literature on AI in education with emphasis on cultural specificities of adoption processes.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"66 ","pages":"Article 101015"},"PeriodicalIF":6.4,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of generative AI by students with disabilities in higher education","authors":"Xin Zhao ,&nbsp;Andrew Cox ,&nbsp;Xuanning Chen","doi":"10.1016/j.iheduc.2025.101014","DOIUrl":"10.1016/j.iheduc.2025.101014","url":null,"abstract":"<div><div>The use of generative AI is controversial in education largely because of its potential impact on academic integrity. Yet some scholars have suggested it could be particularly beneficial for students with disabilities. To date there has been no empirical research to discover how these students use generative AI in academic writing. Informed by a prior interview study and AI-literacy model, we surveyed students regarding their use of generative AI, and gained 124 valid responses from students with disabilities. We identified primary conditions affecting writing such as ADHD, dyslexia, dyspraxia, and autism. The main generative AI used were chatbots, particularly ChatGPT, and rewriting applications. They were used in a wide range of academic writing tasks. Key concerns students with disabilities had included the inaccuracy of AI answers, risks to academic integrity, and subscription cost barriers. Students expressed a strong desire to participate in AI policymaking and for universities to provide generative AI training. The paper concludes with recommendations to address educational disparities and foster inclusivity.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"66 ","pages":"Article 101014"},"PeriodicalIF":6.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-staged SEM-ANN approach to predict learning presence in online foreign language education: The role of teaching presence and online interaction","authors":"Nuoen Li,&nbsp;Kit-Ling Lau","doi":"10.1016/j.iheduc.2025.101012","DOIUrl":"10.1016/j.iheduc.2025.101012","url":null,"abstract":"<div><div>While the theoretical value of the Community of Inquiry (CoI) framework in comprehending online learning experiences has been acknowledged, the newly introduced CoI element—learning presence—has received insufficient attention in the field of foreign language (FL) education. Drawing on the constructivist stimulus-mediation-response approach, this study investigated the predicting effects of teaching presence and online interaction on learning presence. Data were collected from 460 college-level online Chinese as a Foreign Language (CFL) learners at seven Chinese higher education institutions. Partial least squares structural equation modeling (PLS-SEM) was used to explore the linear relationships, followed by the artificial neural network (ANN) technique to assess the relative importance of predictors based on the nonlinear relationships between variables in the research model. The results support most of the predictive effects of teaching presence and online interaction on learning presence variables (self-efficacy, metacognitive self-regulation, and metacognitive co-regulation). Teaching presence, learner-instructor interaction, and learner-learner interaction were the most influential predictors of self-efficacy, metacognitive self-regulation, and metacognitive co-regulation, respectively. Furthermore, the mediating role of online interaction between teaching presence and learning presence was partially supported. The findings highlight the critical roles of teaching presence and online interaction in fostering online FL learners' active and responsible learning while offering valuable insights into the design of online language courses.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"66 ","pages":"Article 101012"},"PeriodicalIF":6.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring human and AI collaboration in inclusive STEM teacher training: A synergistic approach based on self-determination theory","authors":"Tingting Li,&nbsp;Zehui Zhan,&nbsp;Yu Ji,&nbsp;Tongde Li","doi":"10.1016/j.iheduc.2025.101003","DOIUrl":"10.1016/j.iheduc.2025.101003","url":null,"abstract":"<div><div>Inclusive STEM teacher training plays a critical role in shaping the future of STEM teaching practices and improving educational outcomes for all students, particularly those from marginalized and underrepresented backgrounds. This study investigates the inclusive collaborative learning framework for enhancing STEM teaching among student teachers, focusing on interpersonal and human-machine (generative artificial intelligence) collaboration. Employing a Self-Determination Theory guided approach, two rounds of exploratory studies were conducted. Study 1 compared the effects of interpersonal collaboration (TSPL: in-Service Teacher-Student Teacher Pair Learning) and human-machine collaboration (CSPL: ChatGPT-Student Teacher Pair Learning). Building on Study 1, Study 2 employed a hybrid inclusive collaborative learning model (iHMCL: integrated Human-Machine Collaborative Learning) with expanded participant demographics, blended course formats, and integrated peer, expert, and AI feedback mechanisms. The two-year iterative empirical research revealed differences in the impact of the three collaborative learning approaches on student teachers' learning. CSPL and iHMCL groups outperformed TSPL in STEM teaching knowledge and cognitive load, while TSPL and iHMCL excelled in STEM teaching ability compared to CSPL. The SDT-based inclusive collaborative learning framework for STEM teacher training proved effective, with noted implications. In the future, the integration of generative artificial intelligence and cross boundary learning in inclusive STEM teacher education will require educators to redefine their roles, emphasizing emotional support, critical thinking, and creativity, ensuring that AI complements rather than replaces hands-on, reality-based learning.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 101003"},"PeriodicalIF":6.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What should I know? Analysing behaviour and feedback from student use of a virtual assistant to share information about disabilities","authors":"Tim Coughlan ,&nbsp;Francisco Iniesto","doi":"10.1016/j.iheduc.2025.101002","DOIUrl":"10.1016/j.iheduc.2025.101002","url":null,"abstract":"<div><div>Administrative burden is a recognised cause of inequities for disabled students. Experiences of sharing information about disabilities and arranging adjustments can be demoralising and present barriers to success. To explore how Artificial Intelligence technologies could improve this situation, a virtual assistant (VA) was iteratively developed and deployed to support the initial steps of the process through which students share information. Here we describe findings from an eight-month trial where this was made available for students to use as an alternative to completing a form when declaring disabilities. 544 students tried using the assistant during this period. We analyse 351 questions asked of the VA by students, and a feedback survey with 129 responses. Results indicate the types of support expected while interacting with a VA and provide feedback on aspects of the design, the relationship with wider processes and experience of use. Overall, most participants wanted to continue using a VA in these processes, with positive perceptions across disability categories. We identify 12 themes showing a broad range of questions asked of the assistant. Given recent advances in AI, we discuss the opportunities and challenges to build on this and develop further inclusive innovations. Future work should focus on enabling context-informed answers to questions, enabling students to learn and contribute through the conversation, managing expectations according to VA capabilities, enhancing and monitoring inclusivity and integrating the VA with wider processes.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"66 ","pages":"Article 101002"},"PeriodicalIF":6.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating perceived fairness of AI prediction system for math learning: A mixed-methods study with college students","authors":"Yukyeong Song ,&nbsp;Chenglu Li ,&nbsp;Wanli Xing ,&nbsp;Bailing Lyu ,&nbsp;Wangda Zhu","doi":"10.1016/j.iheduc.2025.101000","DOIUrl":"10.1016/j.iheduc.2025.101000","url":null,"abstract":"<div><div>Entities such as governments and universities have begun using AI for algorithmic decision-making that impacts people's lives. Despite their known benefits, such as efficiency, the public has raised concerns about the fairness of AI's decision-making. Here, the concept of perceived fairness, defined as people's emotional, cognitive, and behavioral responses toward the justice of the AI system, has been widely discussed as one of the important factors in determining technology acceptance. In the field of AI in education, students are among the biggest stakeholders; thus, it is important to consider students' perceived fairness of AI decision-making systems to gauge technology acceptance. This study adopted an explanatory sequential mixed-method research design involving 428 college students to investigate the factors that impact students' perceived fairness of AI's pass-or-fail prediction decisions in the context of math learning and suggest ways to improve the perceived fairness based on students' voices. The findings suggest that students who received a favorable prediction outcome (i.e., pass), who were presented with a system that had a lower algorithmic bias and higher transparency, who major(ed) in STEM (vs. non-STEM), who have higher math anxiety, and who received the outcome that matches their math knowledge level (i.e., accurate) tend to report a higher level of perceived fairness for the AI's prediction decisions. Interesting interaction effects were also found regarding decision-making, students' math anxiety and knowledge, and the outcome's favorability on students' perceived fairness. Qualitative thematic analysis revealed students' strong desire for transparency with guidance, explainability, and interactive communication with the AI system, as well as constructive feedback and emotional support. This study contributes to the development of a justice theory in the era of AI and suggests practical design implications for AI systems and communication strategies with AI systems in education.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 101000"},"PeriodicalIF":6.4,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming online learning research: Leveraging GPT large language models for automated content analysis of cognitive presence","authors":"Daniela Castellanos-Reyes ,&nbsp;Larisa Olesova ,&nbsp;Ayesha Sadaf","doi":"10.1016/j.iheduc.2025.101001","DOIUrl":"10.1016/j.iheduc.2025.101001","url":null,"abstract":"<div><div>The last two decades of online learning research vastly flourished by examining discussion board text data through content analysis based on constructs like cognitive presence (CP) with the Practical Inquiry Model (PIM). The PIM sets a footprint for how cognitive development unfolds in collaborative inquiry in online learning experiences. Ironically, content analysis is a resource-intensive endeavor in terms of time and expertise, making researchers look for ways to automate text classification through ensemble machine-learning algorithms. We leveraged large language models (LLMs) through OpenAI's Generative Pre-Trained Transformer (GPT) models in the public API to automate the content analysis of students' text data based on PIM indicators and assess the reliability and efficiency of automated content analysis compared to human analysis. Using the seven steps of the Large Language Model Content Analysis (LACA) approach, we proposed an AI-adapted CP codebook leveraging prompt engineering techniques (i.e., role, chain-of-thought, one-shot, few-shot) for the automated content analysis of CP. We found that a fine-tuned model with a one-shot prompt achieved moderate interrater reliability with researchers. The models were more reliable when classifying students' discussion board text in the Integration phase of the PIM. A cost comparison showed an obvious cost advantage of LACA approaches in online learning research in terms of efficiency. Nevertheless, practitioners still need considerable data literacy skills to deploy LACA at a scale. We offer theoretical suggestions for simplifying the CP codebook and improving the IRR with LLM. Implications for practice are discussed, and future research that includes instructional advice is recommended.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 101001"},"PeriodicalIF":6.4,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Awareness, perception, and adoption of ChatGPT in African HEIs: A multi-dimensional analysis","authors":"Olugbenga Ayo Ojubanire ,&nbsp;Sunday Adewale Olaleye ,&nbsp;Mohamed Amine Marhraoui ,&nbsp;Mesiet William Kamihanda ,&nbsp;Oluwatosin Ifedayo Oke ,&nbsp;Oluwaseun Abigail Ojubanire","doi":"10.1016/j.iheduc.2025.100999","DOIUrl":"10.1016/j.iheduc.2025.100999","url":null,"abstract":"<div><div>The adoption of artificial intelligence (AI), particularly Large Language Models like ChatGPT, has gained significant traction in the education sector, offering numerous benefits for students and educators alike. This study focuses on the triggers and drivers of ChatGPT adoption within African higher education institutions (HEIs). Utilizing the Technology Acceptance Model (TAM) and the Diffusion of Innovations Theory (DIT) as theoretical frameworks, the research proposes a conceptual model to explore the impact of ChatGPT on perceived usefulness and awareness. Additionally, the study examines how ChatGPT awareness influences perceived usefulness through the intermediary role of ChatGPT knowledge. A quantitative methodology was employed, with data collected from higher education institutions in Morocco, Nigeria, and Tanzania. The Partial Least Squares Structural Equation Modelling (PLS-SEM) technique was used to analyze the data. The findings emphasize the positive impact of triggers on both the perceived usefulness and awareness of ChatGPT. Furthermore, the study highlights the significant effect of ChatGPT awareness on perceived usefulness, mediated by knowledge. The research contributes to the existing literature by providing empirical insights into the adoption of ChatGPT in African HEIs and underscores the importance of awareness and knowledge in enhancing perceived usefulness. The study also offers practical recommendations for educators and policymakers to facilitate the effective integration of AI tools in education, considering regional and demographic variations.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100999"},"PeriodicalIF":6.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Humanizing college online instruction: The effects of professional development on faculty perceptions and instructional practices","authors":"Di Xu ,&nbsp;Yujia Liu ,&nbsp;Zhiling Meng Shea ,&nbsp;Kimberly Vincent-Layton ,&nbsp;Jeffrey White ,&nbsp;Michelle Pacansky-Brock","doi":"10.1016/j.iheduc.2025.100998","DOIUrl":"10.1016/j.iheduc.2025.100998","url":null,"abstract":"<div><div>The rapid growth of online learning has raised concerns about quality and equity in virtual education. This study introduces the Humanizing Online STEM Academy, a six-week professional development program designed specifically to promote humanizing and inclusive teaching within STEM college online courses. We document in detail the Academy's design and instructional approach, and examine its impact on the perceptions and instructional practices of 79 faculty participants from eight California institutions, using pre- and post-Academy surveys and in-depth interviews. Results indicate that participants found the humanizing elements covered in the Academy highly beneficial for building trust with students. Post-Academy, instructors reported increased confidence in online teaching, stronger belief in their ability to address equity gaps, and enhanced support for diverse student backgrounds. Their instructional approaches also evolved to prioritize interpersonal interactions and individual student needs. Interviews revealed heightened awareness of student diversity and intentional efforts to accommodate it.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100998"},"PeriodicalIF":6.4,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the relationship between collaborative design, online learning and educator integrated professional development","authors":"Vasiliki Papageorgiou ,&nbsp;Edgar Meyer ,&nbsp;Iro Ntonia","doi":"10.1016/j.iheduc.2025.100997","DOIUrl":"10.1016/j.iheduc.2025.100997","url":null,"abstract":"<div><div>The global expansion of university-level online programmes has heightened the demand for educators to design and facilitate meaningful learning experiences. However, many educators lack the necessary expertise and experience, highlighting the urgency for contextually relevant professional development opportunities. This paper investigates the collaborative design processes of novice online educators and digital learning professionals when designing online learning and the conditions promoting educators’ development. A multiple case study methodology was employed, recruiting six interdisciplinary design teams from five UK-based universities. Data collection involved two phases of semi-structured interviews and design meeting observations. Findings evidence three key processes: (1) framing the design inquiry, (2) sharing and integrating insider knowledge and expertise, and (3) anticipating the future. Emotional support, skilled facilitation and valuing diverse perspectives acted as enabling conditions. We propose network-enabled and boundary-crossing capabilities as novel dimensions of educators’ development. This paper emphasises the need for purposeful collaborative design initiatives for integrated professional development.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100997"},"PeriodicalIF":6.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}