Incorporating social opinion in content selection for an e-learning course

Acceptability of an e-learning course is influenced by various factors. Prominent amongst them is identification of appropriate learning content for the course. Such identification is benefited through the inputs from different strata of the society. Gathering and aggregating opinions from various representatives of the society is a complex task. This paper utilizes analytic hierarchy process (AHP) to design content for an online computing course by considering the opinion of various social clusters, viz. - academicians, researchers, students, alumni and industry. The preferences of these clusters on various criteria and alternatives are elicited and priority weight vectors are calculated. Appropriate weights are assigned to each of the clusters depending on the target group for which the course is designed. The collective priority vector for the alternatives is obtained by aggregating individual weights using aggregation of individual priorities (AIP) method. The e-learning courses thus designed have higher prospects of receiving approval from the society.