Optimizing the pedagogical impact of learning modality-based learning objects using artificial intelligence

Abtar Kaur Darshan Singh, Jeremy Dunning, Ansary Ahmed and Mansor Fadzil
Open University Malaysia
Malaysia

Learning modality-based learning objects have been created in the form of instructional templates using appropriate pedagogical and learning style orientations and some of these include: time-revealed scenarios, case studies and the intelligent paragraph. Some of the more important pedagogical orientations that have been considered include: determining the prior or available knowledge of a learner; presenting material in a logical, motivating and contiguous manner; allowing learners to have the ability to repeatedly practice what has been learnt; providing feedback on a learning interaction; supporting learners with memory techniques; and continuously adapting the content to learning styles. While most of the above-mentioned pedagogical orientations could be achieved when preparing the first or introductory set of learning objects, the statement does not hold true for subsequent learning if some form of artificial intelligence is not incorporated into the learning objects. Use of artificial intelligence allows for better management of the learning processes and outcomes for a learner vis-à-vis the learner's dominant learning style.

In this presentation, we will discuss some concepts related to pedagogy and learning styles, learning objects, the role of artificial intelligence in achieving these, and provide samples of learning objects that have been created to achieve the stated contentions.