Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70090
Title: Laws of attraction : in search of document value-ness for recommendation
Authors: Tang, TY
Mccalla, GI
Issue Date: 2004
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2004, v. 3232, p. 269-280 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: 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.
Description: 8th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2004, Bath, UK, September 12-17, 2004
URI: http://hdl.handle.net/10397/70090
ISBN: 978-3-540-23013-7
978-3-540-30230-8
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-540-30230-8_25
Appears in Collections:Conference Paper

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