The recent emergence of generative AI (GenAI) tools such as ChatGPT, Midjourney, and Gemini have introduced revolutionary capabilities that are predicted to transform numerous facets of society fundamentally. In higher education (HE), the advent of GenAI presents a pivotal moment that may profoundly alter learning and teaching practices in aspects such as inaccuracy, bias, overreliance on technology and algorithms, and limited access to educational AI resources that require in-depth investigation. To evaluate the implications of adopting GenAI in HE, a team of academics and field experts have co-authored this paper, which analyzes the potential for the responsible integration of GenAI into HE and provides recommendations about this integration. This paper recommends strategies for integrating GenAI into HE to create the following positive outcomes: raise awareness about disruptive change, train faculty, change teaching and assessment practices, partner with students, impart AI learning literacies, bridge the digital divide, and conduct applied research. Finally, we propose four preliminary scale levels of a GenAI adoption for faculty. At each level, we suggest courses of action to facilitate progress to the next stage in the adoption of GenAI. This study offers a valuable set of recommendations to decision-makers and faculty, enabling them to prepare for the responsible and judicious integration of GenAI into HE.

Innovation models are key to fostering technology-focused entrepreneurship in higher education institutions (HEIs). These models create dynamic environments that encourage collaboration, creativity, and problem-solving skills among students and faculty. HEIs face several challenges in fostering entrepreneurship, including allocating sufficient financial and human resources, integrating entrepreneurship education across disciplines, and managing intellectual property. Overcoming these challenges requires HEIs to cultivate an entrepreneurial culture and establish strong partnerships with industry stakeholders. To achieve these goals, HEIs must adopt successful innovation models proven to work. This article presents an international case study highlighting such models and the factors contributing to their success. This study explores the implementation and impact of innovation models, specifically IDEATION and DEETECHTIVE, within HEIs to foster technology-focused entrepreneurship. By implementing numerous actions focusing on online education integration and the Quintuple Helix Innovation Model, these models support shifting engineering students’ mindsets toward entrepreneurship. This research highlights the importance of academia–industry collaboration, international partnerships, and the integration of entrepreneurship education in technology-focused disciplines. This study presents two models. The first, IDEATION, focuses on open innovation and sharing economy aspects. This model underwent rigorous testing and refinement, evolving into the second model, DEETECHTIVE, which is more comprehensive and deep tech-focused. These models have been validated as effective frameworks for fostering entrepreneurship and innovation within HEIs. This study’s findings underscore the potential of these models to enhance innovation capacity, foster an entrepreneurial culture, and create ecosystems rich in creativity and advancement. Practical implications include the establishment of open innovation-oriented structures and mechanisms, the development of specialized curriculum components, and the creation of enhanced collaboration platforms.

This paper presents two complementary quantitative studies examining the integration of generative AI (GenAI) tools into programming courses in higher education. Study 1 investigated undergraduate students’ perceptions of GenAI tools, focusing on usefulness in coursework, creativity enhancement, behavioral intention to use, and concerns and critiques. Study 2 evaluated undergraduate students’ performance in correcting code generated by large language models (LLMs) during programming exams, comparing this performance to their results on instructor-designed programming tasks. Findings from Study 1 revealed generally favorable student perceptions of GenAI. Participants reported medium-to-high levels of perceived usefulness, particularly emphasizing GenAI’s potential to enhance learning efficiency and support creative problem-solving. Students also expressed strong intentions to continue using GenAI tools in their studies, while reported concerns were relatively low and centered primarily on the risk of over-reliance. Findings from Study 2 showed that students encountered significantly greater difficulty when correcting LLM-generated code compared to traditional exam tasks, highlighting the unique challenges posed by AI-generated outputs in assessment contexts. Taken together, the results suggest that while students recognize the value of GenAI tools in supporting learning and creative exploration, programming education must also focus on developing students’ skills in critically evaluating and correcting AI-generated content to ensure effective and responsible integration.

Integrating remote Internet of Things (IoT) laboratories into project-based learning (PBL) in higher education institutions (HEIs) while exploiting the approach of technology-enhanced learning (TEL) is a challenging yet pivotal endeavor. Our proposed approach enables students to interact with an IoT-equipped lab locally and remotely, thereby bridging theoretical knowledge with practical application, creating a more immersive, adaptable, and effective learning experience. This study underscores the significance of combining hardware, software, and coding skills in PBL, emphasizing how IoTRemoteLab (the remote lab we developed) supports a customized educational experience that promotes innovation and safety. Moreover, we explore the potential of IoTRemoteLab as a TEL, facilitating and supporting the understanding and definition of the requirements of remote learning. Furthermore, we demonstrate how we incorporate generative artificial intelligence into IoTRemoteLab’s settings, enabling personalized recommendations for students leveraging the lab locally or remotely. Our approach serves as a model for educators and researchers aiming to equip students with essential skills for the digital age while addressing broader issues related to access, engagement, and sustainability in HEIs. The practical findings following an in-class experiment reinforce the value of IoTRemoteLab and its features in preparing students for future technological demands and fostering a more inclusive, safe, and effective educational environment.

Nowadays, teachers and students utilize different ICT devices for conducting innovative and educational activities from anywhere at any time. The enactment of these activities relies on robust communication and computational infrastructures used for supporting technological devices enabling better accessibility to educational resources and pedagogical scaffolds, wherever and whenever necessary. In this paper, we present EDU.Tube: an interactive environment that relies on web and mobile solutions offered to teachers and students for authoring and incorporating educational interactions at specific moments along the time line of occasional YouTube video-clips. The teachers and students could later experience these authored artefacts while interacting from their stationary or mobile devices. We describe our efforts related to the design, deployment and evaluation of an educational activity supported by the EDU.Tube environment. Furthermore, we illustrate the specific teachers’ and students’ efforts practiced along the different phases of this educational activity. The evaluation of this activity and results are presented, followed by a discussion of these findings, as well as some recommendations for future research efforts further elaborating on EDU.Tube’s aspects in relation to learning analytics.

In the present paper, we explore the integration of Generative Artificial Intelligence (GenAI) into the teaching, learning and research practices within the Faculty of Instructional Technologies undergraduate programme at the Holon Institute of Technology (HIT), Israel. Our goal is to examine how GenAI has supported transitions in various courses across three study clusters: core topics related to learning and training, user experience and user interface design (UX/UI), and technological development. Through five case studies from these clusters, we demonstrate how the incorporation of GenAI has enhanced student practices as they conceptualise, design, and create technology-enhanced learning (TEL) tools, systems, and architectures designed to meet realworld needs. In this context, we demonstrate how GenAI integration influences the interrelationship among the three study clusters, thereby facilitating a cohesive approach essential for students developing their capstone projects, which require the integration of knowledge and skills from all courses. This paper situates these efforts within the intelligent-technological pedagogical content knowledge (TPACK) framework, illustrating GenAI’s role in TEL. We conclude with recommendations for researchers and practitioners considering the adoption of GenAI to enhance their capabilities in deploying next-generation TEL environments.