Student‐generated content in college teaching: content quality, behavioural pattern and learning performance
Abstract
This study investigates the quality of course content, behavioural patterns of students and learning performance in teaching of student‐generated content (SGC). A total of 49 third‐year university students in educational technology participated in this study. By combining the methods of questionnaire, lag sequence analysis and interview, the study found that (1) SGC quality was acceptable, (2) SGC process has 14 significant behavioural sequences, and (3) students developed their knowledge and capability and were satisfied with SGC‐based teaching approach. In addition, this study revealed problems and proposed suggestions for SGC‐based course teaching. Finally, implications for course teaching in colleges, the limitations and future research plan were presented.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
DBL is more effective than traditional learning because learners work on real problems in teams and pursue their own ideas, leading to higher engagement and better learning outcomes.
“DBL is more effective than traditional learning because learners work on real problems in teams and are allowed to pursue their own ideas and approaches, which in turn leads to higher engagement and thus better learning outcomes [18,34,35].”
From Students as Designers of Augmented Reality: Impact on Learning and Motivation in Computer Science (2021) · cites this paper as [34]
Cites
Effective peer assessment processes: Research findings and future directions
van Zundert, M., Sluijsmans, D., & van Merriënboer, J. (2010) · Learning and Instruction · doi:10.1016/j.learninstruc.2009.08.004 · Cited by 536 · see citing works
Generative learning processes of the brain
Wittrock, M. C. (1992) · Educational Psychologist · doi:10.1207/s15326985ep2704_8 · Cited by 343 · see citing works
Will massive open online courses change how we teach?
Martin, F. G. (2012) · Communications of the ACM · doi:10.1145/2240236.2240246 · Cited by 324 · see citing works
Decentralization in wikipedia governance.
Forte, A., Larco, V., & Bruckman, A. (2009) · Journal of Management Information Systems · doi:10.2753/mis0742-1222260103 · Cited by 300 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Students as Designers of Augmented Reality: Impact on Learning and Motivation in Computer Science
Buchner, J., & Kerres, M. (2021) · Multimodal Technologies and Interaction · doi:10.3390/mti5080041 · Cited by 23 · see citing works
Robosourcing Educational Resources -- Leveraging Large Language Models for Learnersourcing
Denny, P., Sarsa, S., Hellas, A., & Leinonen, J. (2022) · arXiv · doi:10.48550/arxiv.2211.04715 · Cited by 21 · see citing works
Aladsani (2024) · doi:10.1186/s41239-024-00454-5 · Cited by 5 · see citing works
- Authors
- Yang, X., Guo, X., & Yu, S.
- Affiliations
- Jiangsu Normal University (CN)
- Beijing Normal University (CN)
- Corresponding author
- Yang, X.
- Venue
- Journal of Computer Assisted Learning
- Publisher
- Wiley
- Published
- 2015-10-07
- Volume
- 32
- Issue
- 1
- Pages
- 1-15
- ISSN
- 0266-4909 (ISSN-L)
- 1365-2729
- OpenAlex
- W1930726950
- Cited by
- 38
- References
- 4
- Citations by year
- 2026: 2 · 2024: 6 · 2023: 4 · 2022: 6 · 2021: 4 · 2020: 4 · 2019: 6 · 2018: 3 · 2017: 2 · 2016: 1
- FWCI
- 4.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computer Assisted Learning (publishedVersion)
- Funders
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- Qing Lan Project
- National Social Science Foundation of China for the Youth Scholars of Education (CCA130134)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Innovative Teaching Methods
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Keywords
- student-generated content, course content quality, student behavior, learning performance, educational technology students, student satisfaction, university teaching
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
