A distance learning framework for automatic instructor replies: articulable tacit knowledge used for feedback upon request

Distance learning has many facets, ranging from technology implementations to assessment methods. The last decade has seen an increased number of tools to facilitate virtual classrooms and collaboration. However, feedback and evaluation are only partially automated in online courses. This paper largely follows knowledge management theories and artificial intelligent techniques, developing a framework to capture and manage automated responses to student replies. The instructor´s tacit knowledge plays a direct role in augmenting class participation, learning communities, and feedback evaluation. Conceptual graphs are proposed to extract tacit knowledge from instructors written responses and to assist in externalizing it for future re-use. A question answering task is presented to illustrate the relationship between mental models and conceptual graphs and the mechanism to select responses through keyword match.