The Effect of Revision-Making of Contextualized Student-Generated Questions on University Students’ English Grammar Learning Performance

Chih Chung Lin, Fu Yun Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is a great deal of research supporting the application of student-generated questions (SGQ) to English curriculums, and recent studies have found L2 learners to benefit further from an elaborated SGQ approach — contextualized SGQ (cSGQ), which leverages the provision of a context for students to base on their generated questions. Previous research has also proved the advantages of making revision on English learner’s writing proficiency but its relevance to English grammar learning is yet to be exploited. Thus, the present study aimed to investigate the effect of cSGQ learning tasks combined with the practice of making revision of the given context on L2 learners’ English grammar learning performance. A pre- and post-test quasi-experimental research design was adopted, and 88 university students enrolling in freshman English class were invited to participate. The results showed that students in the cSGQ-revision group outperformed those not given the opportunity to make revision in both linguistic knowledge and pragmatic understanding.

Original languageEnglish
Title of host publication31st International Conference on Computers in Education, ICCE 2023 - Proceedings
EditorsJu-Ling Shih, Akihiro Kashihara, Weiqin Chen, Weiqin Chen, Hiroaki Ogata, Ryan Baker, Ben Chang, Seb Dianati, Jayakrishnan Madathil, Ahmed Mohamed Fahmy Yousef, Yuqin Yang, Hafed Zarzour
PublisherAsia-Pacific Society for Computers in Education
Pages369-374
Number of pages6
ISBN (Electronic)9786269689026
Publication statusPublished - 2023 Dec
Event31st International Conference on Computers in Education, ICCE 2023 - Matsue, Shimane, Japan
Duration: 2023 Dec 42023 Dec 8

Publication series

Name31st International Conference on Computers in Education, ICCE 2023 - Proceedings
Volume2

Conference

Conference31st International Conference on Computers in Education, ICCE 2023
Country/TerritoryJapan
CityMatsue, Shimane
Period23-12-0423-12-08

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Education

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