Culturally-based Adaptive Learning and Concept Analytics to Guide Educational Website Content Integration
Torsten Reiners, University of Hamburg, Germany ; Heinz Dreher, Curtin University of Technology, Australia
JITE-Research Volume 8, Number 1, ISSN 1539-3585 Publisher: Informing Science Institute
In modern learning environments, the lecturer or educational designer is often confronted with multi-national student cohorts, requiring special consideration regarding language, cultural norms and taboos, religion, and ethics. Through a somewhat provocative example we demonstrate that taking such factors into account can be essential to avoid embarrassment and harm to individual learners’ cultural sensibilities and, thus, provide the motivation for finding a solution using a specially designed feature, known as adaptive learning paths, for implementation in Learning Management Systems (LMS). Managing cultural conflicts is achievable by a twofold process. First, a learner profile must be created, in which the specific cultural parameters can be recorded. According to the learner profile, a set of content filter tags can be assigned to the learning path for the relevant students. Example content filter tags may be “no sex” or “nudity ok, but not combined with religion”. Second, the LMS must have the functionality to select and present content based on the content filter tags. The design of learning material is presented via a meta-data based repository of learning objects that permits the adaptation of learning paths according to learner profiles, which include the cultural sensibilities in addition to prior knowledge and learning and categorized learning content – a detailed example is given. The drawback of using static or predefined meta-data elements is discussed, suggesting a further refinement via the introduction of dynamic concept analysis to be applied to both learner profiles and learning objects (restricted to text at this stage). An automated method of generating the content filter tags is achieved through the use of the Normalised Word Vector algorithm first developed for Automated Essay Grading system known as MarkIT (R. Williams, 2006). An automated method reduces human effort and ensures consistency. Sophisticated fine-grained dynamic learning path adaptivity is achieved through a detailed design given in the article, helping ensure that learners from a variety of cultural backgrounds can be treated appropriately and fairly and are not disadvantaged or offended by inappropriate learning content and examples.
Reiners, T. & Dreher, H. (2009). Culturally-based Adaptive Learning and Concept Analytics to Guide Educational Website Content Integration. Journal of Information Technology Education: Research, 8(1), 125-139. Informing Science Institute.
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