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Title:
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TOWARDS GENERATING EXERCISE QUESTIONS WITH LOD FOR WEB-BASED INVESTIGATIVE LEARNING |
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Author(s):
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Rei Saito, Yoshiki Sato, Miki Hagiwara, Koichi Ota and Akihiro Kashihara |
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ISBN:
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978-989-8533-93-7 |
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Editors:
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Demetrios G. Sampson, Dirk Ifenthaler, Pedro Isaías and Maria Lidia Mascia |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Web-Based Investigative Learning, Linked Open Data, Exercise Questions |
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Type:
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Full Paper |
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First Page:
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117 |
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Last Page:
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124 |
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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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Web allows learners to investigate any question to learn with a large number of Web resources. In such investigative
learning, leaners are expected to investigate the question by navigating Web resources/pages to construct their knowledge
and decomposing the question into sub-questions. In acquiring skills in such investigative learning, learners need to
practice with exercise questions. However, it is hard to define correct knowledge to be constructed for the questions since
Web-based investigative learning could result in diverse knowledge as correct one for the same question. Towards this
issue, this paper proposes the method with Linked Open Data (LOD) for generating exercise questions, which includes an
initial question and sub-questions to be decomposed from an initial question. These sub-questions are extracted and
selected as keywords with LOD and Word2vec. This paper also reports a case study with the generation method. The
results suggest that it is effective as scaffolding particularly for novice learners. |
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