Insider Action Research On AI Needs Within The EIT Innoenergy Ecosystem

This practice paper describes an ongoing insider action research within the EIT InnoEnergy ecosystem. Its goal is to inspire teaching staff from the seven EIT InnoEnergy double degree Master of Science programmes to integrate Artificial Intelligence (AI) tools and knowledge into their courses based on joint learning. This insider action research runs from 2023 to the end of 2024. In late 2022, a problem statement of ‘AI tools for Education’ was identified by EIT InnoEnergy teachers as being crucial for their future learning and teaching processes. To align the needs of teaching staff with the complexity of emerging AI tools, a decision was made to plan a hybrid insider action research method. The outcome of this research will be twofold: one resulting in an AI toolkit covering three teaching staff needs, and two getting a better understanding of the processes involved in taking up a learning innovation at different engineering partner universities spread across Europe within the EIT InnoEnergy ecosystem. This paper shares the first phases of the insider action research and an overview of the individual AI initiatives taken by teaching staff at different partner universities that is the result of a first qualitative data analysis coming from initiatives shared by the insiders (i.e., teaching staff). Action research methodology was chosen to inspire teaching staff to take an investigative and experimental attitude to the new AI technologies while allowing all actors to support each other and grow towards an AI integration in courses and curricula

Affordances and limitations of learning analytics for computer-assisted language learning: a case study of the VITAL project

Learning analytics (LA) has emerged as a field that offers promising new ways to support failing or weaker students, prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date, available research suggests that understanding language learner behaviour could provide valuable insights into task design for instructors and materials designers, as well as help students with effective learning strategies and personalised learning pathways. This paper first discusses previous research in the field of language learning and teaching based on learner tracking and the specific affordances of LA for CALL, as well as its inherent limitations and challenges. The second part of the paper analyses data arising from the European Commission (EC) funded VITAL project that adopted a bottom-up pedagogical approach to LA and implemented learner activity tracking in different blended or distance learning settings. Referring to data arising from 285 undergraduate students on a Business French course at Hasselt University which used a flipped classroom design, statistical and process-mining techniques were applied to map and visualise actual uses of online learning resources over the course of one semester. Results suggested that most students planned their self-study sessions in accordance with the flipped classroom design, both in terms of their timing of online activity and selection of contents. Other metrics measuring active online engagement – a crucial component of successful flipped learning - indicated significant differences between successful and non-successful students. Meaningful learner patterns were revealed in the data, visualising students’ paths through the online learning environment and uses of the different activity types. The research implied that valuable insights for instructors, course designers and students can be acquired based on the tracking and analysis of language learner data and the use of visualisation and process-mining tools

Language and Text-to-Speech Technologies for Highly Accessible Language & Culture Learning

This contribution presents the results of the â??Speech technology integrated learning modules for Intercultural Dialogu

Language and Text-to-Speech Technologies for Highly Accessible Language & Culture Learning

This contribution presents the results of the “Speech technology integrated learning modules for Intercultural Dialogue” project. The project objective was to increase the availability and quality of e-learning opportunities for less widely-used and less taught European languages using a user-friendly and highly accessible learning environment. The integration of new Text-to-Speech developments into web-based authoring software for tutorial CALL had a double goal: on the one hand increase the accessibility of e-learning packages, also for learners having difficulty reading (e.g. dyslexic learners) or preferring auditory learning; on the other hand exploiting some didactic possibilities of this technology

E-Learning Readiness in Organisations – Case Healthcare

e-Learning is a good opportunity for companies to up-skill their employees and to meet the demands of lifelong learning but the implementation of it needs to be well prepared and managed because it takes often high investment costs both on the financial and the organisational side. That is why it is important for a company to know if it is e-learning ready. E-readiness and e-learning readiness are already well covered in literature and several theoretical models are suggested. We developed an e-learning readiness measurement instrument based on these models. We used it as a survey instrument to conclude about the e-learning readiness of Flemish hospitals