This paper explores the needs expectations of educational stakeholders for AI (Artificial Intelligence)-enhanced learning environments. Data was collected following two-phased participatory workshops. The first workshop outlined stakeholders’ profiles in terms of technical and pedagogical characteristics. The qualitative data collected was analysed using deductive thematic analysis with Activity Theory, explicating the user needs. The second workshop articulated expectations related to the integration of AI in education. Inductive thematic analysis of the second workshop led to the elicitation of users’ expectations. We cross-examined the needs expectations, identifying contradictions, to generate user requirements for emerging technologies. The paper provides suggestions for future design initiatives that incorporate AI in learning environments.

Recent research emphasizes the importance of Artificial Intelligence applications as supporting tools for students in higher education. Simultaneously, an intensive exchange of views has started in the public debate in the international educational community. However, for a more proper use of these applications, it is necessary to investigate the factors that explain their intention and actual use in the future. With the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, this work analyses the factors influencing students’ use and intention to use Artificial Intelligence technology. For this purpose, a sample of 197 Greek students at the School of Humanities and Social Sciences from the University of Patras participated in a survey. The findings highlight that expected performance, habit, and enjoyment of these Artificial Intelligence applications are key determinants influencing teachers’ intentions to use them. Moreover, behavioural intention, habit, and facilitating conditions explain the usage of these Artificial Intelligence applications. This study did not reveal any moderating effects. The limitations, practical implications, and proposed directions for future research based on these results are discussed.

This paper reports on the development of a novel pedagogical framework for supporting instructors in their teaching process. Specifically, it describes a reference architecture that may accommodate a series of instructional design functionalities, which integrate and are enhanced by emerging technologies such as Artificial Intelligence and Machine Learning. Much attention is paid to the description of the constituent modules of the proposed architecture, as well as to the compliance of the proposed technical solution with the requirements of contemporary instructional design. Through two use case scenarios, we demonstrate the applicability and potential of the proposed solution.

An emerging area of research is the study of factors that influence the use of e-learning systems in higher education. Previous studies have mainly focused on the factors that influence the adoption of learning management systems (LMS) from the student’s point of view, and rarely from the point of view of the university lecturers. Moodle is an open-source LMS that has been used increasingly by the higher education community worldwide in the past few years. The purpose of this study is to investigate the factors that explain the acceptance of Moodle by academic personnel (faculty members) in the Greek higher education system. The convenience sample consists of 85 lecturers from different universities in Greece. All of them reported having used Moodle. Using the technology acceptance model, the correlations between the six latent variables (perceived ease of use, perceived usefulness, behavioral intention to use, perceived self-efficacy, subjective norms, and technology complexity) were examined. Five of the eight hypotheses were supported by variance base structural equation modelling. The total explained variance of the faculty members’ behavioral intention to use Moodle was estimated to be 68.3%. Perceived usefulness and perceived ease of use had a high overall effect. Subjective norms, self-efficacy, and technological complexity influenced the teachers’ intentions to adopt Moodle. This study recommends training as well as technical support for academic personnel. In addition, stakeholders should address these factors to increase usability, awareness of new opportunities for the educational community, accessibility, and the general dissemination of the benefits of learning management systems in education.

This paper proposes a new methodological approach for assessing and leveraging student engagement in a tertiary education course that builds on recent artificial intelligence advancements and the TPACK (Technological Pedagogical Content Knowledge) model. We describe how, through the design of a course that is based on Moodle and the utilization of different pedagogical and conceptual tools, we collect and process data aiming to enhance the course with techniques that may provide students and tutors with valuable insights and recommendations towards achieving better performance.

This paper presents a novel pedagogical framework that aims to promote both basic skills and 21st century competencies by integrating emerging technologies. The proposed framework builds on the strengths of big data and learning analytics to provide different types of stakeholders with explainable recommendations for smart identification of educational resources, as well as for designing personalized learning profiles that consider individual actors’ characteristics, needs and preferences. By leveraging advancements from the fields of Pedagogical Design, Creative Pedagogy, Explainable Artificial Intelligence, and Knowledge Representation and Reasoning for instructional purposes, the framework is able to provide guidelines to stakeholders on how to address underlying educational difficulties and disabilities, shape individual learning paths, and identify cases of gifted and talented students.

This paper focuses on documenting the reflections of undergraduate students in the early childhood education programme with regard to their experience with school placement in kindergarten. Their views on the importance of school placement, the implementation of activities they design, the teaching process and the interactions developed in the classroom are studied. A review of responses indicates that most students can attribute the importance of their school placement to a number of factors related, firstly, to the acquisition of experience, but also to more complex factors relating to communication and the interaction of the students themselves with kindergarten children, as well as the link between academic knowledge and its practical application. At the same time, it is highlighted the fact that, through the process of reflection, the students are willing to revise some of their choices while planning and implementing educational activities. In conclusion, it appears that the study of student reflection is a complex “mechanism” which nevertheless appears to be quite significant in preparing future teachers and can contribute to improving the operational framework of practical work experience (school placement), with a direct impact on the feedback to the knowledge they are provided. Article visualizations: