TY - GEN
T1 - Fostering students' idea generation through corpus-based recommendation in online writing environment
AU - Liao, Calvin C.Y.
AU - Cheng, Hercy N.H.
AU - Chang, Wan Chen
N1 - Funding Information:
This study was financially supported by Self-determined Research Funds of Central China Normal University from the Colleges Basic Research and Operation of Ministry of Education of China (CCNU16GD003).
Publisher Copyright:
© 2018 Asia-Pacific Society for Computers in Education.
PY - 2018/11/24
Y1 - 2018/11/24
N2 - Idea generation plays an important role in the writing process. The use of natural language techniques to mine semantic relationships between vocabularies or sentences in order to provide students with more suitable contents for writing ideas. Therefore, this study developed a corpus-based Chinese writing recommendation system. This study collects, analyzes, processes, and constructs a primary school corpus with 580,000 written texts, and develops a vocabulary and sentence recommendation mechanism for writing. 37 fourth-year students are invited to participate in the evaluation. The study found that students provided 60% of the candidate vocabularies or sentences they provided, but 40% of the candidate vocabularies or sentences were not applicable. Furthermore, students had more than 60% positive attitude towards the system.
AB - Idea generation plays an important role in the writing process. The use of natural language techniques to mine semantic relationships between vocabularies or sentences in order to provide students with more suitable contents for writing ideas. Therefore, this study developed a corpus-based Chinese writing recommendation system. This study collects, analyzes, processes, and constructs a primary school corpus with 580,000 written texts, and develops a vocabulary and sentence recommendation mechanism for writing. 37 fourth-year students are invited to participate in the evaluation. The study found that students provided 60% of the candidate vocabularies or sentences they provided, but 40% of the candidate vocabularies or sentences were not applicable. Furthermore, students had more than 60% positive attitude towards the system.
KW - Idea generation
KW - Sentence similarity computation
KW - Word vector
KW - Writing recommendation
UR - http://www.scopus.com/inward/record.url?scp=85060116696&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:85060116696
T3 - ICCE 2018 - 26th International Conference on Computers in Education, Work-in-Progress Poster Proceedings
SP - 16
EP - 18
BT - ICCE 2018 - 26th International Conference on Computers in Education, Work-in-Progress Poster Proceedings
A2 - Rodrigo, Ma. Mercedes T.
A2 - Amalathas, Sagaya
A2 - Coronel, Andrei D.
A2 - Yang, Jie Chi
A2 - Song, Yanjie
A2 - Ding, Jihong
A2 - Chang, Maiga
A2 - Wong, Lung-Hsiang
PB - Asia-Pacific Society for Computers in Education
T2 - 26th International Conference on Computers in Education, ICCE 2018
Y2 - 26 November 2018 through 30 November 2018
ER -