This systematic review examines Virtual Internationalisation (VI) in Higher Education (HE) by highlighting its role as a driver of pedagogical innovation. Although VI is expanding rapidly, prevailing studies remain fragmented, focusing on mobility alternatives or technological tools without synthesising how VI reshapes pedagogical innovation and academic teaching approaches. This review addresses this lacuna by systematically focusing on how academics comprehensively integrate online technological techniques to enhance pedagogical innovation, and the potential challenges that jeopardise the implementation of VI. By using the PRISMA framework, the study analysed literature retrieved from Web of Science Direct, Scopus, ERIC, Emerald Insights and JSTOR databases, whereby 411 studies and 31 articles were included in the final sample. The findings indicate that academics enhance pedagogical innovation by integrating online technological techniques through Collaborative Online International Learning (COIL), Virtual Exchange (VE), global classrooms, and Generative Artificial Intelligence (GeAI). However, implementation is constrained by technological issues, institutional policies and infrastructure, socio-cultural factors and language, equity and inclusion, quality assurance and sustainability challenges. The review concludes that the integration of digital technology approaches into HE signifies a profound pedagogical transformative shift. It is recommended that HE policies should prioritise investment in digital infrastructure, equitable internet access, and continuous professional development to strengthen VI and pedagogical innovation.
This study examines how AI literacy shapes the teaching efficiency of Higher Education Institution (HEI) teachers in Kerala, India. Responses were obtained from 380 teachers, collected through voluntary sampling, and analysed using Pearson correlation and mediation analysis. Teaching efficiency was significantly and positively correlated with AI literacy, perceived ease of use (PEOU), perceived usefulness (PU) and trust in AI tools. Demographic variables such as gender, age, qualification and subject specialisation showed no significant influence on the responses. Prior AI training and AI tool exposure significantly improved all measured variables. Mediation analysis confirmed that PEOU, PU, and trust partially mediate the relationship between AI literacy and teaching efficiency. These findings suggest institutional policy for open and distance AI learning beyond the academic sessions to improve AI literacy of the teachers.
The research investigates how college students use AI literacy skills to make ethical choices, while digital confidence serves as a linking factor, and responsible AI use acts as a regulating element. The researchers collected data from 483 students at a Philippine state university using a quantitative-correlational design with Structural Equation Modeling (SEM) analysis performed through WarpPLS (Version 8.0). The study found that AI literacy directly affects both digital confidence and ethical decision-making processes, while digital confidence serves as a partial mediator between the two variables. The results demonstrate that responsible AI use strengthens the connection between AI literacy and digital confidence, highlighting how ethical technology use affects digital trust. The study shows that AI-enabled learning environments require competence, confidence, and responsibility to work together as essential components for students to make ethical decisions. The results demonstrate that Open and Distance Learning (ODL) providers should establish three core areas, which contain AI literacy, ethical training, and confidence-building methods, to create digital learning systems that enable responsible and efficient technology operation.
This study explored how students’ experiences within social media-based digital communities support postgraduate students at the University of Ghana, where academic pressure and social isolation are common. Through semi-structured interviews with 18 students active on WhatsApp, Telegram, and LinkedIn, the research found that these platforms offer academic, informational, technical, and emotional support via resource sharing, collaborative problem-solving, networking, and peer encouragement. Participants reported improved research engagement, skill development, and reduced loneliness, particularly in relation to thesis writing, proposals, exams, and academic networking. Although limited to one institution and focused mainly on research-related activities, the findings highlight the value of low-cost, accessible digital peer networks in resource-constrained settings. The study contributes to Open and Distance Learning (ODL) by demonstrating how such communities can enhance learner retention, connectedness, and well-being, offering practical insights for strengthening informal support systems in higher education beyond the Ghanaian context.
The purpose of this study was to examine the relationship between digital competence (DC) and autonomous learning (AL) of students in online classes. Respondents were 195 students (semester II = 93 students; semester VI = 102 students) who were determined using a simple random sampling technique. Digital competence data were collected using 28 items of the Students Digital Competence Scale, while autonomous learning data were collected using 12 items of The Autonomous Learning Scale. The data of both variables were then analyzed using descriptive statistics, Mann-Whitney, and Spearman’s using Microsoft Excel and SPSS version 29. The results of the Mann-Whitney test proved that of the two variables and their indicators, only the independence of learning indicator in the AL variable showed a significant difference between the two sample groups (semester II and semester VI). Furthermore, Spearman’s test proved that DC was positively and significantly correlated with AL with a correlation value of 0.612. The indicator that has the highest correlation is: “Evaluate” with “Independence of learning” with a value of 0.582. This fact also found that all DC indicators have a better correlation value with the “Independence of learning” indicator than one other AL indicator, namely “Study habits.” Thus, to support the agenda and culture of autonomous learning through student learning behavior that is initiative and proactive, lecturers, universities, and the government simultaneously and continuously need to pay attention to, strengthen, and at the same time improve student DC.
