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Title: Learning what students want to learn
Authors: Abou-Khalil, Victoria
Flanagan, Brendan
Ogata, Hiroaki  kyouindb  KAKEN_id
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.
Rights: ここに掲載した著作物の利用に関する注意 本著作物の著作権は情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。
The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the author (s) and the IPSJ. Please be complied with Copyright Law of Japan and the Code of Ethics of the IPSJ if any users wish to reproduce, make derivative work, distribute or make available to the public any part or whole thereof. All Rights Reserved, Copyright (c) 2018 by the Information Processing Society of Japan.
URI: http://hdl.handle.net/2433/231410
Related Link: http://id.nii.ac.jp/1001/00186773/
Appears in Collections:Journal Articles

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