2026-02-10
Lingyan Guo, Margarita Lagutkina, Larisa Mamedova
The effectiveness of technical education may vary depending on the delivery method. This study compared the effects of online, face-to-face (F2F), and hybrid learning on engineering students’ academic performance. The study involved 450 second-year students pursuing an engineering degree at a technical university in China. The pre-test and post-test scores for the five core academic subjects (i.e., computer programming, further mathematics, physics, electrical engineering, and analytical mechanics) revealed a statistically significant improvement in academic performance across all subjects after use of hybrid learning ( p < 0.000). The average gains were 3.46 points in computer programming, 4.07 points in further mathematics, 3.24 points in physics, 2.5 points in electrical engineering, and 3.06 points in analytical mechanics. The online and F2F delivery groups exhibited a statistically significant improvement with respect to scores for electrical engineering ( p < 0.000) and physics ( p < 0.002) only. The one-way ANOVA and Scheffe’s test results revealed that the hybrid model had the strongest learning effects compared to online and F2F. A SWOT analysis helped to further explore students’ perceptions of the three delivery formats. The present findings, which highlighted the effectiveness of hybrid learning, can be helpful in creating adaptive learning programs for engineering students.
2026-02-10
Heejin Chang, Scott Windeatt
This study focused on procedures for creating, testing, and developing a set of reusable online resources for use in English for academic purposes programmes. The aim of the materials was to help migrants and refugees develop the linguistic and cultural skills, knowledge, and understanding they would need to engage, interact, and collaborate effectively in a multicultural context. Development of the materials involved an iterative process using a three-stage approach: Expert review: Experts in relevant fields worked through the first version of the materials and provided critical feedback, which guided initial revisions. Usability testing groups: Small groups of target users (students and teachers) used the revised materials in workshop settings, and data were gathered from observations, interviews, and written comments. Wider evaluation: Larger-scale use and evaluation of the materials (which is ongoing, beyond the scope of this paper). This article reports on the second stage.
2026-02-10
Flavio Manganello, Giuseppe Aleo
This study investigated how the community of inquiry (CoI) framework can inform digital platform design for interprofessional continuing professional development (ICPD) in healthcare. Using a three-stage comparative methodology, we analyzed technological tools from foundational CoI literature (stage 1), conducted a rapid review of current digital ICPD practices (stage 2), and synthesized findings through matrix-based comparison (stage 3). The analysis of 10 foundational CoI studies and 11 digital interprofessional education studies revealed four distinct adaptation patterns: (a) technological convergence in core communication tools (asynchronous forums, Learning Management System (LMS) platforms); (b) evolutionary divergence in collaborative technologies (video conferencing, real-time document sharing); (c) implementation gaps in reflective and scaffolding tools; and (d) professional context adaptations addressing healthcare-specific needs. While current ICPD practices have demonstrated strong alignment with CoI principles in communication and collaboration tools, significant gaps exist in structured reflection mechanisms, automated feedback systems, and adaptive facilitation features. Critically, systematic CoI framework application in authentic ICPD contexts with practicing professionals has remained largely unexplored, with studies predominantly focused on pre-licensure interprofessional education. Current implementations have used CoI retrospectively as an analytical framework rather than proactively for design guidance. These findings suggest selective rather than comprehensive CoI integration in professional continuing education contexts. The study provided preliminary theoretical guidance for enhancing digital ICPD through CoI-informed design while highlighting the urgent need for empirical validation with practicing healthcare professionals.
2026-02-10
Ekrem Bahçekapılı, Bülent Kandemir, Elif Baykal Kablan
This study investigated middle school students’ experiences with emergency remote education during the COVID-19 pandemic using natural language processing (NLP), sentiment analysis, and topic modeling techniques. A total of 2,739 valid responses from Turkish students (ages 9–15) were collected through open-ended survey questions regarding the perceived advantages and disadvantages of distance learning. Sentiment classification was performed using a semi-supervised machine learning approach, combining TF-IDF, Word2Vec, and FastText vectorization with five classification algorithms. The TF-IDF + support vector machines (SVM) combination yielded the highest performance (F1 = 0.85). Results show a total of 1,867 positive and 2,542 negative opinions, indicating that students generally adopted a more critical view of distance education. To explore the thematic structure of opinions, topic modeling was applied with six topics. Positive sentiments clustered around themes such as educational continuity, health protection, time savings, flexible scheduling, self-regulated learning, and digital literacy. Negative sentiments were dominated by themes including limited interaction, screen fatigue, perceived low quality, technical barriers, and structural inequalities. Findings suggest that while students appreciated the safety and flexibility of remote learning, they also faced significant pedagogical, physical, and technological challenges. The study contributes methodologically by demonstrating the effectiveness of AI-based text analysis and offers practical implications for designing more equitable and student-centered digital education models. These results underscore the importance of integrating NLP and machine learning tools into educational research to uncover deeper insights from student-generated content at scale.
2026-02-10
Tian Belawati
The Handbook of Open Universities Around the World , edited by Sanjaya Mishra and Santosh Panda, offers both a panoramic survey and a reflective critique of what openness truly means in higher education today. Drawing together insights from more than 100 scholars and practitioners, the editors have curated an extraordinary compilation that maps the histories, organizational structures, and innovations of 47 open universities across Africa, the Americas, Asia, Europe, and Oceania. The result is not only a celebration of institutional achievement but also an invitation to confront difficult questions about equity, sustainability, and the future of open learning. Open universities were originally conceived as democratic institutions designed to remove barriers of geography, class, gender, and prior schooling. They opened doors to learners traditionally excluded from mainstream education systems. In the current era of rapid digital transformation, when artificial intelligence (AI) and data-driven technologies are reshaping how education is delivered and experienced, the notion of openness demands fresh examination. The Handbook situates itself precisely at this critical juncture, bridging historical foundations with emerging digital realities.