This study explores students’ perceptions of synchronous learning during a period of rapid pedagogical transformation in higher education. Triggered by a systemic shift from traditional face-to-face instruction to online formats, institutions were compelled to redesign their teaching methods, communication channels, and assessment practices. Drawing on qualitative data from 5,154 open-ended responses in Student Evaluations of Teaching (SET) across two Israeli colleges, the research investigates how students experienced and interpreted these abrupt instructional changes. Four overarching themes emerged from the analysis: (1) the development and importance of soft skills, (2) the role of course structure, (3) perceptions of instructional professionalism, and (4) the influence of the digital platform. These findings offer insights into students’ adaptive responses to institutional change and contribute to the understanding of synchronous online learning as a complex pedagogical process.
Generative artificial intelligence (GenAI) has shown potential in supporting academic writing, yet limited research addressed the intention and actual use of this technology by foreign language students. To address this gap, the study employs an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model by integrating AI self-efficacy and AI trust to investigate the factors influencing EFL students’ intention and actual use of GenAI in academic writing. An online survey using a cross-sectional design involving 481 purposively selected EFL students from Indonesian universities was analyzed using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4. The results revealed that performance expectancy, effort expectancy, social influence, habit, and AI self-efficacy significantly shaped EFL students’ intentions to use GenAI for academic writing, while behavioral intention, habit, and AI self-efficacy significantly influence actual use. In contrast, AI trust, facilitating conditions, and hedonic motivation show no significant effect on either intention or actual use. The model demonstrated strong explanatory power, with R² values of 0.806 for behavioral intention and 0.617 for actual use. The study enhances the explanatory power of UTAUT2 in GenAI-supported academic writing and offers practical insights for pedagogy and policy to promote GenAI literacy, critical evaluation skills, and responsible use in academic writing.
As artificial intelligence (AI) continues to reshape modern society, there is an urgent need to equip K–12 educators with the skills and confidence to integrate AI tools into their instructional practice. This pilot study examined the preliminary effectiveness of an asynchronous professional development course designed to increase educators’ comfort with AI, shift their perceptions, and expand access to instructional resources. A mixed-methods approach was used to analyze data from 30 participants, including K–12 teachers, preservice educators, and others in educational roles in K–12 schools, who completed pre- and post-course surveys. Quantitative results revealed statistically significant increases in comfort with AI, perceptions of AI, access to resources, and familiarity with AI tools. Correlational analyses found strong positive relationships between perceptions, resource access, and comfort. No significant differences were observed across demographic variables; while this does not establish equivalence, it suggests the course may be broadly accessible across participant groups. Qualitative findings, including participant reflections, highlighted the transformative impact of the course, with educators reporting a shift from skepticism to enthusiasm. The course’s modular design, grounded in best practices for professional learning, was well-received and scalable. Recommendations include expanding the course to a larger and more mixed sample, integrating AI training into preservice teacher education, and updating content regularly to reflect the rapidly evolving AI landscape. This research demonstrates that thoughtfully designed, flexible professional development can build AI literacy and empower educators to adopt emerging technologies with confidence and purpose. As data collection is ongoing, these findings represent early trends that will inform future iterations and expanded implementation.
As we bring you another issue of Online Learning, (the third issue of our 30th year of publication by the way), I wanted again to include some reflections on the topic of AI and academic integrity. As noted by many journal editors, we are seeing exponential growth in the number of AI generated submissions to journals. Recently, an essay in the Chronicle of Higher Education by Mya Poe (2026) noted that the influx of AI generated papers was degrading scholarship, making it more difficult for authors of papers to attract citations who were located in the “missing middle”.
Initial cognitive structures (schemata) play a crucial role in the success of Information Systems (IS) in online learning environments, particularly in efforts to support conditions associated with learning equity. However, the IS Success Model has yet to define the role of schemata clearly. This study investigates the influence and position of schemata within the DeLone and McLean framework in the context of online learning equity, with the focus on system-related benefits that may support equitable learning conditions. While learning equity is not measured directly, the model examines perceived benefits, such as accessibility, flexibility, and participation, that are theoretically linked to fair learning opportunities. Data were collected via questionnaires administered to 252 students from two state universities, all of whom had at least one year of online learning experience. The instrument was based on the IS Success Model, which includes system quality, information quality, service quality, intention to use, user satisfaction, net benefits, and schemata. Structural Equation Modeling (SEM) was used to analyze the model. The findings show that key components of the IS Success Model are positively and significantly related to perceived system-related benefits associated with conditions that may support equitable online learning, with schemata functioning as a moderating variable. It is suggested that IS implementations should incorporate support strategies such as scaffolding, personalized guidance, and introductory content to enhance the positive impact of schemata.
