The internationalization of higher education increasingly involves ‘Internationalization at a Distance’ (IaD), a modality that alters how students engage with learning communities across geographical and cultural divides. Despite its growing prevalence, the complexity of fostering student engagement in transnational settings remains underexplored. This study investigates the application of the Community of Inquiry (CoI) framework—comprising teaching, cognitive and social presence—within a transnational Master of Education programme delivered jointly by an Australian university and a Chinese educational institute. Findings reveal significant challenges in achieving robust CoI elements due to geographical separation and cultural disparities, which undermine effective engagement. In response, students developed Collaborative Cell Groups, informal, peer-led communities that enhance engagement by localizing knowledge, fostering social cohesion and supplementing teaching presence. These groups illustrate both the potential and limitations of informal peer support within formal learning structures. By critically examining the interplay between formal and informal learning communities, this study offers new insights into optimizing engagement in cross-cultural distance education.
Practitioner notes
What is already known about this topic?
- The Community of Inquiry (CoI) framework has been widely recognized for structuring online learning environments by fostering cognitive, social and teaching presence to support meaningful learning experiences.
- Prior research has primarily examined the application of the CoI framework in domestic online education settings, with limited exploration of its effectiveness and challenges in cross-cultural or transnational contexts like Internationalization at a Distance (IaD).
- Existing studies suggest that while the CoI framework can provide a structured approach to enhancing engagement, its ability to fully support student participation may be hindered by factors, such as geographical separation and cultural disparities.
What this paper adds
- This study highlights the limitations of the CoI framework in fully supporting student engagement within IaD settings. Specifically, it demonstrates how cultural and geographical divides between students and instructors can hinder the effective establishment of teaching, cognitive and social presence.
Despite the growing research interest in the use of large language models for feedback provision, it still remains unknown how students perceive and use AI-generated feedback compared to instructor feedback in authentic settings. To address this gap, this study compared instructor and AI-generated feedback in a Java programming course through an experimental research design where students were randomly assigned to either condition. Both feedback providers used the same assessment rubric, and students were asked to improve their work based on the feedback. The feedback perceptions scale and students' laboratory assignment scores were compared in both conditions. Results showed that students perceived instructor feedback as significantly more useful than AI feedback. While instructor feedback was also perceived as more fair, developmental and encouraging, these differences were not statistically significant. Importantly, students receiving instructor feedback showed significantly greater improvements in their lab scores compared to those receiving AI feedback, even after controlling for their initial knowledge levels. Based on the findings, we posit that AI models potentially need to be trained on data specific to educational contexts and hybrid feedback models that combine AI's and instructors' strengths should be considered for effective feedback practices.
Practitioner notes
What is already known about this topic
- Feedback is crucial for student learning in programming education.
- Providing detailed personalised feedback is challenging for instructors.
- AI-powered solutions like ChatGPT can be effective in feedback provision.
- Existing research is limited and shows mixed results about AI-generated feedback.
What this paper adds
- The effectiveness of AI-generated feedback was compared to instructor feedback.
- Both feedback types received positive perceptions, but instructor feedback was seen as more useful.
- Instructor feedback led to greater score improvements in the programming task.
Implications for practice and/or policy
- AI should not be the sole source of feedback, as human e
Internationalization of higher education (HE) has increasingly been a subject of interest among scholars, due to developments in the field, such as increased student and staff mobility, inter-university research and teaching partnerships, and rapid technological advancements. Internationalization efforts have mainly focused on the recruitment of international students and staff to universities in the Global North, the establishment of satellite campuses overseas and research collaborations. To compete on a more even footing, countries in the Global South have increasingly invested in their HE systems and actively promoted themselves as international destinations in this changing global landscape. In this paper, we discuss the strategies and limitations of internationalization at a distance (IaD) with a specific focus on Tanzania. As an emerging destination for international students, the country's expanding HE sector is positioning itself as a global and competitive international destination through diverse efforts such as virtual mobility. This paper draws on interviews with key staff from an open and distance-learning university in Tanzania to examine and theorize the challenges relating to the provision of online distance learning (ODL) to non-mobile international students. The theoretical lens is informed by the capabilities approach and ideas of conversion factors and agency. The paper looks beyond existing limitations and proposes the idea of a responsive agency that draws on international collaborations as a way of overcoming contextual challenges through pooling and sharing resources where they exist. In this way, institutions are not independent of their affiliation with others, they belong to a community. This broadens the practice of internationalization to fostering supportive collaboration aimed at improving access to quality international HE.
Practitioner notes
What is already known about this topic
- Rising technology-supported activities have created new opportunities for universities internationalization.
- Education plays a key role in intercultural understanding.
- Internationalization of educational research and services improve quality by requiring respective higher education institutions improve academic standards.
What this paper adds
- Bring together the concepts of capabilities and third sp
This study aims to develop a comprehensive competency framework for artificial intelligence (AI) literacy, delineating essential competencies and sub-competencies. This framework and its potential variations, tailored to different learner groups (by educational level and discipline), can serve as a crucial reference for designing and implementing AI curricula. However, the research on AI literacy by target learners is still in its infancy, and the findings of several existing studies provide inconsistent guidelines for educational practices. Following the 2020 PRISMA guidelines, we searched the Web of Science, Scopus, and ScienceDirect databases to identify relevant studies published between January 2012 and October 2024. The quality of the included studies was evaluated using QualSyst. A total of 29 studies were identified, and their research findings were synthesized. Results show that at the K-12 level, the required competencies include basic AI knowledge, device usage, and AI ethics. For higher education, the focus shifts to understanding data and algorithms, problem-solving, and career-related competencies. For general workforce, emphasis is placed on the interpretation and utilization of data and AI tools for specific careers, along with error detection and AI-based decision-making. This study connects the progression of specific learning objectives, which should be intensively addressed at each stage, to propose an AI literacy education pathway. We discuss the findings, potentials, and limitations of the derived competency framework for AI literacy, including its theoretical and practical implications and future research suggestions.
Practitioner notes
What is already known about this topic
- AI literacy is becoming increasingly important as AI technologies are integrated into various aspects of life and work.
- Research on AI literacy competencies across diverse learner groups and disciplines remains fragmented and inconsistent to guide educational practices.
- Studies providing a coherent pathway for AI literacy development throughout educational and working life are lacking.
What this paper adds
- A comprehensive AI literacy competency framework consisting of 8 competencies and 18 sub-competencies.
- Variations in AI literacy competencies with tailored configurat
Mathematical stories can enhance students' motivation and interest in learning mathematics, thereby positively impacting their academic performance. However, due to resource constraints faced by the creators, generative artificial intelligence (GAI) is employed to create mathematical stories accompanied by images. This study introduces a method for automatically assessing the quality of these multimodal stories by evaluating text-image coherence and textual readability. Using GAI-generated stories for grades 3 to 5 from the US math story learning platform Read Solve Create (RSC), we extracted features related to multimodal semantics and text readability. We then analysed the correlation between these features and student engagement levels, measured by average reading time per story (behavioural engagement) and average drawing tool usage per story (cognitive engagement), derived from browsing logs and interaction metrics on the platform. Our findings reveal that textual features such as conjunctive adverbs, sentence connectors, causal connectives and simplified vocabulary positively correlate with behavioural engagement. Additionally, higher semantic similarity between text and images, as well as the number of operators in the stories, is associated with increased cognitive engagement. This study advances the application of GAI in mathematics education and offers novel insights for instructional material design.
Practitioner notes
What is already known about this topic
- Mathematical stories can enhance students' motivation and interest in mathematics, leading to improved academic performance.
- Generative artificial intelligence (GAI) has been increasingly employed to create multimodal educational content, including mathematical stories with accompanying images, to address content creators' resource constraints.
- Prior readability research has primarily focused on the analysis of text-based educational content, with less emphasis on the integration and analysis of visual elements.
What this paper adds
- Introduces a novel automated multimodal readability assessment method that evaluates the coherence between text and images and the readability of text in GAI-generated mathematical stories.
- Identifies specific story features, such as the more frequent use of three types of conjunctions (adversative conjunctions, common
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