How to Make Computer‐Based Feedback More Effective: The Benefits of Allowing Learners to Choose Feedback Types

ABSTRACT Background Prior studies in computer‐based feedback predominantly concentrated on feedback assigned by the program to learners, in which case learners only received feedback passively, without consideration for their preferences or autonomy. It remains unclear whether allowing learners to choose feedback types of varying complexity can improve learning. Objectives The current study examined the effects of self‐selected feedback on emotions, motivation, and learning performance. Methods We implemented a single‐factor between‐subjects design, involving 310 middle school students tasked with completing 10 multiple‐choice items on the topic of quadratic radicals. Learners either passively received program‐provided feedback with different complexities (Knowledge of Correct Response [KCR], Cue Feedback, and Explanation Feedback) or chose between any of these three feedback types after responses. Results and Conclusions The results showed that: (a) learners in self‐selected feedback condition reported higher decisional autonomy than those in the program‐provided feedback conditions; (b) learners in self‐selected feedback condition experienced more positive emotions than those in the program‐provided KCR or cue feedback conditions, and reported stronger motivation than those in the program‐provided KCR; (c) learners in self‐selected feedback condition also outperformed those in the program‐provided KCR condition; (d) in the program‐provided feedback condition, more detailed information resulted in better learning performance (explanation > cue > KCR). Implications These findings underscored the significance of allowing learners to choose feedback type to improve learning in computer‐based learning environments and provided empirical evidence to support more learner‐centered approaches to feedback design.

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Publication Details

Journal
Journal of Computer Assisted Learning
Published
2026-06-17
DOI
https://doi.org/10.1002/jcal.70273
Primary Topic
Student Assessment and Feedback
Type
article
Field-Weighted Citation Impact
0.00

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article

How to Make Computer‐Based Feedback More Effective: The Benefits of Allowing Learners to Choose Feedback Types

Shaoying Gong, Jiangnan Guo, Yanqing Wang, Zhen Wang et al.
Journal of Computer Assisted Learning
Student Assessment and Feedback
article

How to Make Computer‐Based Feedback More Effective: The Benefits of Allowing Learners to Choose Feedback Types

Shaoying Gong, Jiangnan Guo, Yanqing Wang, Zhen Wang, Yi-Xiang Wang
article en

Abstract

ABSTRACT Background Prior studies in computer‐based feedback predominantly concentrated on feedback assigned by the program to learners, in which case learners only received feedback passively, without consideration for their preferences or autonomy. It remains unclear whether allowing learners to choose feedback types of varying complexity can improve learning. Objectives The current study examined the effects of self‐selected feedback on emotions, motivation, and learning performance. Methods We implemented a single‐factor between‐subjects design, involving 310 middle school students tasked with completing 10 multiple‐choice items on the topic of quadratic radicals. Learners either passively received program‐provided feedback with different complexities (Knowledge of Correct Response [KCR], Cue Feedback, and Explanation Feedback) or chose between any of these three feedback types after responses. Results and Conclusions The results showed that: (a) learners in self‐selected feedback condition reported higher decisional autonomy than those in the program‐provided feedback conditions; (b) learners in self‐selected feedback condition experienced more positive emotions than those in the program‐provided KCR or cue feedback conditions, and reported stronger motivation than those in the program‐provided KCR; (c) learners in self‐selected feedback condition also outperformed those in the program‐provided KCR condition; (d) in the program‐provided feedback condition, more detailed information resulted in better learning performance (explanation > cue > KCR). Implications These findings underscored the significance of allowing learners to choose feedback type to improve learning in computer‐based learning environments and provided empirical evidence to support more learner‐centered approaches to feedback design.

Journal of Computer Assisted LearningVol. 42(4)
Fuyang Normal University (CN), Henan University (CN), Central China Normal University (CN), Ministry of Education (BN), Hebei Normal University (CN)
National Natural Science Foundation of China, Humanities and Social Science Fund of Ministry of Education of China
Quality Education
Openalex Percentile: Top 3%
Student Assessment and Feedback
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