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Title: Learning what students want to learn
Authors: Abou-Khalil, Victoria
Flanagan, Brendan
Ogata, Hiroaki  kyouindb  KAKEN_id  orcid (unconfirmed)
Author's alias: 緒方, 広明
Keywords: Learning Analytics
Ubiquitous learning
Polysemous words
Computer Supported Language Learning
Issue Date: 21-Mar-2018
Publisher: Information Processing Society of Japan (IPSJ)
Journal title: IPSJ SIG Technical Reports
Volume: 2018-CLE-24
Issue: 13
Start page: 1
End page: 6
Abstract: Polysemous words are words that have different meanings in different contexts. This type of word is confusing for language students. In order to be able to provide the language learners with the right translation in the right context, it is important to understand the meaning intended by the student. This paper proposes a method to predict the meaning intended by the student based on students' past learned words, current location and time. The method proposed uses records from the SCROLL system (System for Capturing and Reminding Of Learning Log) to analyze the activity of students. We assume that the uploaded vocabulary of a student can be used to predict the meaning intended by the student when looking up a polysemous word. The identification of the intended meaning in the student's current context could be then used to provide the student with the appropriate translation possibly improving the learning.
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