Internet and Higher Education最新文献

{"title":"Teaching via LLM-enhanced simulations: Authenticity and barriers to suspension of disbelief","authors":"Longwei Zheng ,&nbsp;Fei Jiang ,&nbsp;Xiaoqing Gu ,&nbsp;Yuanyuan Li ,&nbsp;Gong Wang ,&nbsp;Haomin Zhang","doi":"10.1016/j.iheduc.2024.100990","DOIUrl":"10.1016/j.iheduc.2024.100990","url":null,"abstract":"<div><div>As an innovative method in professional training, simulation-based learning (SBL) has been introduced into teacher education, providing pre-service teacher candidates with experiential learning opportunities. This study explores the efficacy of SBL using large language models (LLMs) to enhance teacher training, focusing on learners' suspension of disbelief (SoD). As a highly advanced form of generative artificial intelligence, LLMs possess robust capabilities in simulating human behavior, which can be harnessed to create simulated students for SBL in teacher training. This instrumental case study examines the experiences of 12 pre-service teachers who participated in a session featuring an LLM-enhanced simulation. The simulation facilitated naturalistic classroom interactions between the participants and simulated students. Our research aimed to understand how pre-service teachers perceive LLM-enhanced SBL, identify factors that influence SoD, and determine the authenticity barriers. Interview data were analyzed using various coding techniques and derived themes from these codes. The findings revealed that LLM-enhanced SBL provided a realistic and engaging environment, significantly benefiting teaching skill development and learning transfer. However, challenges such as lagging responses, weak comprehension of complex contexts, inconsistencies in simulated students' cognition, and incongruent feedback were noted. The primary contribution of this study lies in demonstrating the potential of using LLMs to replace human actors, though significant technical challenges remain. The study also indicates that enhancements in LLM fine-tuning and prompt engineering are needed to improve LLMs' understanding of classroom context and students' cognitive patterns.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100990"},"PeriodicalIF":6.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142874779","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":"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":"2025-04-01","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":"The paradox of self-efficacy and technological dependence: Unraveling generative AI's impact on university students' task completion","authors":"Ling Zhang ,&nbsp;Junzhou Xu","doi":"10.1016/j.iheduc.2024.100978","DOIUrl":"10.1016/j.iheduc.2024.100978","url":null,"abstract":"<div><div>In the era of proliferating artificial intelligence (AI) technology, generative AI is reshaping educational landscapes, prompting a critical examination of its influence on students' learning processes and their self-efficacy amid concerns over growing technological dependence. This study investigates the nuanced relationship between generative AI use and university students' self-efficacy and technological dependence, illuminating the underlying paradoxes and implications for inclusive education practices. Through a survey of 348 university students, with 200 valid responses analyzed, we uncover the direct and indirect impacts of generative AI usage frequency on AI dependence. Our findings reveal a paradoxical effect: enhanced AI usage significantly amplifies students' confidence and efficiency in learning, yet simultaneously intensifies their dependence on AI. This dual impact both supports and complicates the incorporation of AI technologies into educational settings, underscoring the need for a balanced approach to leveraging AI in teaching and learning. Our study underscores the critical importance of a nuanced understanding of AI's role in education. It highlights the necessity of crafting an educational landscape where technology augments learning processes without compromising independent learning capabilities. By navigating the complex interplay between technological advancement and educational inclusivity, our findings guide the development of AI-assisted learning environments that are not only effective but also equitable and accessible.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100978"},"PeriodicalIF":6.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662551","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":"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":"2025-04-01","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}

{"title":"Scaling up online professional development through institution-initiated blended learning programs in higher education","authors":"Jingjing Zhang ,&nbsp;Yicheng Huang ,&nbsp;Fati Wu ,&nbsp;Wei Kan ,&nbsp;Xudong Zhu","doi":"10.1016/j.iheduc.2024.100988","DOIUrl":"10.1016/j.iheduc.2024.100988","url":null,"abstract":"<div><div>The impact of Covid-19 has significantly accelerated the digital transformation in higher education worldwide. This study investigates how digital transformation changes the instructional design and implementation of large-scale blended learning programs for better learner experiences. It emphasizes the significance of diverse stakeholders' engagement in institution-initiated blended programs to promote effective online professional development. Utilizing Research-Practice Partnerships (RPPs), this study adopts a case study approach, employing participatory observation, interviews, log data, and online discourses to analyze how interactions across various sectors and levels affect the transformation to blended programs and the professional development of the involved instructors. The findings reveal that the institution-initiated blended learning approach, resembling an apprenticeship model, effectively integrates teaching practice with online professional development. An in-depth analysis of two university courses shows that key events and task-oriented approaches significantly influence instructors' online engagement, enhancing their digital literacy. Teacher Handbooks, driven by real learner data, guide teaching practices effectively, while collaborative research meetings greatly enhance the use of data analytics in teaching. Although this top-down approach presents challenges, this study demonstrates that instructors can innovatively tackle these issues. Institutional support is more likely to foster collaborative learning communities across various sectors and hierarchies. This study contributes to the field by introducing a pioneering framework in the institution's innovative educational reform, creating online professional development communities for faculty members of all ages, and enabling them to quickly and easily adapt to the digital transformation of higher education.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100988"},"PeriodicalIF":6.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790122","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":"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":"2025-04-01","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":"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":"2025-04-01","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":"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":"2025-04-01","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":"Experiential learning through simulations in fully online asynchronous courses: Exploring the role of self-debriefing","authors":"David De Jong ,&nbsp;Sara Dexter","doi":"10.1016/j.iheduc.2024.100976","DOIUrl":"10.1016/j.iheduc.2024.100976","url":null,"abstract":"<div><div>Online preparation of professionals is increasing in higher education, which in educational leadership preparation programs raises the need for a means to provide authentic simulations of leadership experiences and help aspirants learn from them. This study presents a content analysis of 826 responses from 59 different school leadership students who, following each of the 14 simulations they experienced, wrote one response in an asynchronous format as a form of self-debriefing. The five themes identified map to the four phases of the experiential learning cycle (Kolb, 1984), suggesting that virtual opportunities to practice leadership in simulations may serve as grounding experiences after which developing professionals can reflect upon, integrate with new understandings, and try out alternate approaches. This study demonstrates the purpose of self-debriefing following online simulations of relevant professional experiences and how self-debriefing may propel students through the full experiential learning cycle, offering a valuable avenue for professional development in higher education.</div></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"65 ","pages":"Article 100976"},"PeriodicalIF":6.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745703","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 the influential factors of online professional learning completion of college teachers from the Global South in an international training program","authors":"Chao Wang ,&nbsp;Xiao Hu","doi":"10.1016/j.iheduc.2024.100963","DOIUrl":"10.1016/j.iheduc.2024.100963","url":null,"abstract":"<div><p>Online courses emerged as an important mode for large-scale cross-national teachers' professional learning. However, with most previous research on teacher online professional learning (TOPL) focusing on resource-rich and technology-advanced regions, little attention has been paid to the factors influencing the online learning completion of college teachers in Global South contexts. This study aimed to explore the facilitators and inhibitors of this population's online learning completion in a cross-country program. In seven courses, individual, institutional, and country-level data of 3529 teacher-learners from 99 countries were collected. Forty-two learners were further interviewed. We adopted hierarchical linear modeling to analyze the nested relationships among the individual/institutional/country-level factors and course completion. Results revealed several significant associations between individual/institutional/country-level variables and course completion, as well as several moderation effects. Interviews complemented the analytics results. This study uncovers influential factors of TOPL in Global South contexts and provides practical implications for college teachers' online professional learning.</p></div>","PeriodicalId":48186,"journal":{"name":"Internet and Higher Education","volume":"64 ","pages":"Article 100963"},"PeriodicalIF":6.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142025156","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}