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Title:
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CLOSENESS ANALYSIS OF STUDENTS' WORD-USAGE
LOCATED IN A HIGH-DIMENSIONAL SPACE |
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Author(s):
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Toshiro Minami and Yoko Ohura |
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ISBN:
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978-989-8704-37-5 |
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Editors:
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Miguel Baptista Nunes, Pedro Isaías and Philip Powell |
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Year:
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2022 |
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Edition:
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Single |
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Keywords:
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Educational Data Mining (EDM), Natural Language Processing (NLP), Word-Usage Analysis, Graph Drawing, Simplicial
Complex, High-Dimensional Euclidean Space |
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First Page:
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115 |
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Last Page:
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122 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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As a part of our studies in investigating the relations between university students' performances and their attitudes to
learning, we propose a new method of representing word-usage profiles of students by embedding the word-usage vectors
into a high-dimensional Euclidean space in this paper. The original source of data are the answer texts of students for a
term-end evaluation questionnaire in a university class. By analyzing the relations in a couple of layouts of the word-vectors
that are supposed to represent a kind of attitudes of students, we intend to find some kinds of relations between word-usages
and academic achievements of students. The major achievements of this paper include (1) to investigate the relations of
students' word-usages themselves as well as (2) to develop new methods that clarify the differences of students in terms of
their viewpoint in comparison with their achievements through these layouts. |
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