A Syllogism for Designing Collaborative Learning Technologies in the Age of AI and Multimodal Data

Abstract

Different paradigms of research interpret the social reality in different ways and these differences are not always apparent in technology enhanced learning research. However a paradigm’s visibility and its elements’ internal consistency are fundamental to the quality of research. As a philosophical position, a paradigm guides researchers to understand the nature of reality (ontology); how we create, acquire and disseminate knowledge (epistemology); and a systematic set of research strategy (methodology). In this research paper, the relationship between ontology, epistemology, and methodology is defined within the context of designing multimodal, AI technologies for collaborative learning. Two case study examples of inductive and deductive research methodologies are presented with the purpose of clarifying their differences in research outputs. Moreover, based on a recent literature review, it is presented that most empirical research in the field (40 out of 46) falls under the inductive methodology. Although, both deductive and inductive approaches are valuable for the advancement of the field; it is argued that the apparent lack of deductive investigations may lead researchers falling into technological determinism.