L.I.M.E. A recommendation model for informal and formal learning, engaged

Abstract

-In current eLearning models and implementations (e.g. Learning Management Systems-LMS) there is a lack of engagement between formal and informal activities. Furthermore, the online methodology focuses on a standard set of units of learning and learning objects, along with pre-defined tests, and collateral resources like, i.e. discussion fora and message wall. They miss the huge potential of learning via the interlacement of social networks, LMS and external sources. Thanks to user behaviour, user interaction, and personalised counselling by a tutor, learning performance can be improved. We design and develop an adaptation eLearning model for restricted social networks, which supports this approach. In addition, we build an eLearning module that implements this conceptual model in a real application case, and present the preliminary analysis and positive results.

A Hybrid Trust-Based Recommender System for Online Communities of Practice

“…In informal learning environments, although learners can take full control of their own learning and some knowledgeable experts can be identified via interactions, not all learners are able to overcome the barriers of metacognition and bounded rationality [20], [21]. This implies that the development of artificial intelligence tools should be more focused on informal learning environments.…”

Casos de estudio innovadores en la educación formal en Palestina: resumen, retos y perspectivas de futuro

“…Lastly, informal learning complements lesson plans and, on top of that, the network of users to allow for group progress. Most of these resources can be used, reused, shared, and embedded with formal learning (Burgos, 2013;Corbi & Burgos, 2017) under a number of licensing frameworks (Stracke et al, 2019): 'free-mium', free but registered, low-cost fee, pay per use, fixed price, free of charge during a specific period, open, universal, and free (such as the OUF code) (Burgos, 2020). In doing so, any educational system, school, university, student, parent, teacher, tutor, or academic manager can face this adversity with a bigger guarantee of success.…”

Towards a novel and LMS-free Pervasive Learning System exploiting the Experience API

“…The LIME project includes a recommender system based upon previous activities of the user [25], but it is not made clear, whether the recommendation is interactive based upon the specific user's activities. Moreover, it seems completely tight to the LMS [5] and rules in LIME cannot operate upon individual LRS records, but only upon averages and aggregated data, 'which offer a more equalized view of the learner situation' [25], [26]. The Mobler Cards App [16] introduces an application with flashing cards that incorporates an LRS and bases its decisions upon previous activities of the user.…”