Serendipitous Recommenders for Teachers in Higher Education

Abstract

Currently, most of the recommender systems that are in a prototype or deployed stage are primarily accuracy oriented. This chapter focuses on teacher preferences for designing serendipity-oriented recommender systems for academic activities. Reports on relevant literature about serendipitous recommenders and fac ulty empowerment with such tools, a focus group study of teachers for some industrial recommender system platforms, and a use case on instructor use of recommenders to inform and support recommendations for lectures are covered. Further, a survey of students to explore the feasibility of student-teacher serendipitous activities and operations are also reported. The results from all three studies show that serendipity has a major role to play in the future. The author surveyed the literature on standard digital libraries and used questionnaire-based data collection and standard statistical methods to evaluate the responses.