User Control and Serendipitous Recommendations in Learning Environments
Author(s) -
Ahmad Hassan Afridi
Publication year - 2018
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2018.04.032
Subject(s) - serendipity , recommender system , computer science , collaborative filtering , control (management) , focus (optics) , interface (matter) , world wide web , multimedia , artificial intelligence , physics , epistemology , bubble , maximum bubble pressure method , parallel computing , optics , philosophy
This paper reports about the study of serendipitous recommendations generation by recommender systems in educational environments. The recommender system provides students with serendipity slider to express desired serendipity and accuracy of recommendations. The recommender uses interface level processing of randomization of recommendations list. The increasing serendipity results in changing score/values of accuracy of recommendations. This was tested by deploying a study material recommender system based on collaborative filtering techniques. The recommender system was used by 60 students in a focus group setting. In conclusion, the research suggests that serendipitous recommendations can be archived using user controlled recommenders in learning environment.
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