Learning Technologies

ILSP has been a pioneer and a champion in Learning Technologies in Greece since its foundation, embracing mainly two subject areas, language learning and digital literacy. Both areas are today at the forefront of the European research agendas. Technologies for better human learning and teaching are among the main objectives of the Horizon 2020 work programme 2014-1015, highlighting the need for more effective and efficient (digital) human learning, through innovative solutions that promote adaptive learning with augmented cognition technologies and game-based learning, and solutions that make better use of educational cloud, mobile technology, learning analytics and big data. Digital literacy and skills development and inclusion that are among the seven key domains of intervention according to the European Commission’s Digital Agenda Scorecard for 2013, which  highlights the need for spurring innovative web-based solutions and ventures for the development and promotion of digital skills.

On the front of language learning technologies, ILSP research teams are constantly seeking to promote research in the field of language learning by setting up consistent and reliable methodologies for language education that are grounded on a cross-fertilization of linguistic theories, findings in language acquisition research, language pedagogy and ICT, the latter providing a valuable impetus for the design of a comprehensive approach to language learning. This blending serves as a basis for a host of efficient activities in the field of language development, such as assessment of children’s and adults’ language proficiency, Technology-Enhanced Language Learning (TELL), independent evaluation of language learning interventions, design of language policies, etc. In recent years focus has been placed on the early assessment of speech and language disorders in children, aiming at providing a smooth integration of these children in the educational system. Moreover, basic and applied research is directed towards (i) investigating how to maximize the effectiveness and efficiency of tools and technologies in language education and (ii) implementing highly interactive TEL applications compliant with learner needs and fostering learner autonomy.

In parallel with language learning technologies, ILSP has contributed to progress in the domain of digital and professional skills development.   In practice, professional skills development is rarely contained within a single formal education course. Instead, in most cases, it is delivered through vocational Education and Training (VET). Experiential learning through on-the-job training (OJT) is an effective training approach in practice-oriented disciplines. However, setting up an OJT environment and training program for diverse professional skills development is costly and cannot be afforded by most organizations. Imitation of OJT through augmented reality (AR) is a practical alternative (Nakajima and Itho 2003) (Haritos and Macchiarella 2005). Yet, AR is applicable mostly to specialized training. Besides, the development and implementation of the training scenarios, as well as the necessary software and hardware infrastructure for the human-machine interfaces is itself also rather costly.

Learning technologies can support asynchronous training in a cost-efficient way. With virtual learning environments, trainees can choose the training pace, the course subjects and self-assessment tests that fit their needs (Emmanouilidis 2009) (Emmanouilidis and Spais, 2010). Training can become ubiquitous through mobile learning (Mierlus-Mazilu 2010, Hung and Zhang 2011). The spread of use of social networking tools has also brought attention to the contribution of social and groupware learning (Casagranda et al. 2011, Westerhout et al. 2011). Individually targeted learning can be delivered through personalization. Assessment methods may vary according to different learning styles that lead to better results for engineering students when combined with concept maps (Martínez Cartas 2012). Combining social and cloud-based e-learning with personalization to create a mash up in a personalized learning environment (PLE) is a step towards establishing groupware or collaborative learning (Ko et al. 2011)(Westerhout et al., 2011). A further advancement in this direction is the combination of context-awareness in an ambient intelligence environment, in order to convey context-adaptive learning (Garcia et al. 2011). Focusing on professional and industrial training, current e-learning applications are also directed in training through virtual environments (El-Chaar et al. 2011).