In this paper we explore the uniqueness of paper recommendation for e-learning systems through a human-subject study. Experiment results showed that the majority of learners have struggled to reach a 'harmony' between their interest and educational goal: they admit that in order to acquire new knowledge, they are willing to read not-interesting-yet-pedagogically-useful papers. In other words, learners seem to be more tolerant than users in commercial recommender systems. Nevertheless, as educators, we should still maintain a balance of recommending interesting papers and pedagogically helpful ones in order to retain learners and continuously engage them throughout the learning process. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Tang, T. Y., & McCalla, G. (2004). Laws of attraction: In search of document value-ness for recommendation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3232, 269–280. https://doi.org/10.1007/978-3-540-30230-8_25
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