Indicators of the Learning Context for Supporting Personalized and Adaptive Learning Environments

Hemmler, Yvonne M.

doi:10.1109/icalt55010.2022.00026

Cited by 7 publications

(2 citation statements)

References 17 publications

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“…Following those two surveys, we find the next survey that focuses on the pedagogical implications of defining the contextual factors in the work of Hemmler and Ifenthaler (2022). The authors revisit the role of empirical-pedagogical research in shaping the design of PALE and in generating meaningful, context-aware, recommendations.…”

Section: Related Workmentioning

confidence: 99%

“…In the surveyed literature, we investigate a range of contextual factors, as well as their frequent use in the proposed solutions and approaches. Factors that we identify, and those identified in other valuable research, as in Caponera and Losito (2016), , Lallemand and Koenig (2020), Hilkenmeier et al (2021), and Hemmler and Ifenthaler (2022), are addressed with different frequencies in the literature. Reasons for a factor to be a "commonly used" one are related to: (1) the origin of that factor, i.e., pedagogical, technical, or both.…”

Section: Context Capturing and Contextual Factorsmentioning

confidence: 99%

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Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations – a pedagogical and technical perspective

Abu-Rasheed,

Weber,

Fathi

2023

Front. Educ.

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Learning personalization has proven its effectiveness in enhancing learner performance. Therefore, modern digital learning platforms have been increasingly depending on recommendation systems to offer learners personalized suggestions of learning materials. Learners can utilize those recommendations to acquire certain skills for the labor market or for their formal education. Personalization can be based on several factors, such as personal preference, social connections or learning context. In an educational environment, the learning context plays an important role in generating sound recommendations, which not only fulfill the preferences of the learner, but also correspond to the pedagogical goals of the learning process. This is because a learning context describes the actual situation of the learner at the moment of requesting a learning recommendation. It provides information about the learner’s current state of knowledge, goal orientation, motivation, needs, available time, and other factors that reflect their status and may influence how learning recommendations are perceived and utilized. Context-aware recommender systems have the potential to reflect the logic that a learning expert may follow in recommending materials to students with respect to their status and needs. During the last decade, several approaches have emerged in the literature to define the learning context and the factors that may capture it. Those approaches led to different definitions of contextualized learner-profiles. In this paper, we review the state-of-the-art approaches for defining a user’s learning-context. We provide an overview of the definitions available, as well as the different factors that are considered when defining a context. Moreover, we further investigate the links between those factors and their pedagogical foundations in learning theories. We aim to provide a comprehensive understanding of contextualized learning from both pedagogical and technical points of view. By combining those two viewpoints, we aim to bridge a gap between both domains, in terms of contextualizing learning recommendations.

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Section: Related Workmentioning

confidence: 99%