Enhancing University <scp>EFL</scp> Learners' Writing Performance: The Role of <scp>AI</scp> ‐ Enhanced Goal‐Setting, Feedback and Social Norm Interventions

ABSTRACT Background English as a Foreign Language (EFL) learners often struggle to develop robust academic writing, especially in online settings with limited feedback and interaction. Existing AI writing tools show promise but are often tested in brief, isolated interventions, so little is known about which AI‐supported strategies are most effective. Objectives In a four‐arm randomised controlled trial ( N = 383), three AI‐enhanced nudges (goal‐setting, feedback, social norm) were compared with an active control across 18 × 90‐min sessions (total dose = 27 h). Posttest group differences were large (Welch's F (3, 188.454) = 1447.280, p &lt; 0.001, η 2 = 0.895), with the goal‐setting nudge yielding the highest writing performance ( M = 20.24/25, 81.0% of maximum). Methods University EFL students were randomly assigned to three AI‐enhanced nudge conditions (goal‐setting, feedback, social norm) or an active control in a pretest–posttest design. Interventions drew on social cognitive theory (SCT) and nonlinear dynamic language learning theory (NDLLT) and were delivered over 18 × 90‐min sessions. Writing performance, motivation and self‐efficacy were assessed with validated instruments, complemented by interviews and reflective essays. Results and Conclusions Goal‐setting nudges produced the largest gains in writing performance, motivation and self‐efficacy, with feedback and social norm nudges also outperforming the active control. Effect sizes were large: goal‐setting versus control Δ M = 11.01, 95% CI [10.51, 11.52] for performance; Δ M = 3.50, 95% CI [3.16, 3.83] for motivation; Δ M = 3.22, 95% CI [2.95, 3.49] for self‐efficacy. Students described AI‐enhanced goal‐setting as making tasks more manageable and progress more visible, while AI feedback and peer comparisons supported revision and engagement. Overall, the findings suggest that carefully designed, instructor‐mediated AI nudges can substantially enhance EFL academic writing when used to supplement, rather than replace, human teaching. Centring on three research questions, RQ1 tested differential effects of the three nudges versus control on writing performance, motivation and self‐efficacy; RQ2 examined learners' perceived effectiveness and experiences across modalities; RQ3 explored the correspondence between quantitative performance gains and qualitative learner insights.

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Publication Details

Journal
Journal of Computer Assisted Learning
Published
2026-01-02
DOI
https://doi.org/10.1002/jcal.70179
Primary Topic
Writing and Handwriting Education
Type
article
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article

Enhancing University EFL Learners' Writing Performance: The Role of AI ‐ Enhanced Goal‐Setting, Feedback and Social Norm Interventions

Y. Wang
Journal of Computer Assisted Learning
Writing and Handwriting Education
article

Enhancing University EFL Learners' Writing Performance: The Role of AI ‐ Enhanced Goal‐Setting, Feedback and Social Norm Interventions

Y. Wang
article en

Abstract

ABSTRACT Background English as a Foreign Language (EFL) learners often struggle to develop robust academic writing, especially in online settings with limited feedback and interaction. Existing AI writing tools show promise but are often tested in brief, isolated interventions, so little is known about which AI‐supported strategies are most effective. Objectives In a four‐arm randomised controlled trial ( N = 383), three AI‐enhanced nudges (goal‐setting, feedback, social norm) were compared with an active control across 18 × 90‐min sessions (total dose = 27 h). Posttest group differences were large (Welch's F (3, 188.454) = 1447.280, p &lt; 0.001, η 2 = 0.895), with the goal‐setting nudge yielding the highest writing performance ( M = 20.24/25, 81.0% of maximum). Methods University EFL students were randomly assigned to three AI‐enhanced nudge conditions (goal‐setting, feedback, social norm) or an active control in a pretest–posttest design. Interventions drew on social cognitive theory (SCT) and nonlinear dynamic language learning theory (NDLLT) and were delivered over 18 × 90‐min sessions. Writing performance, motivation and self‐efficacy were assessed with validated instruments, complemented by interviews and reflective essays. Results and Conclusions Goal‐setting nudges produced the largest gains in writing performance, motivation and self‐efficacy, with feedback and social norm nudges also outperforming the active control. Effect sizes were large: goal‐setting versus control Δ M = 11.01, 95% CI [10.51, 11.52] for performance; Δ M = 3.50, 95% CI [3.16, 3.83] for motivation; Δ M = 3.22, 95% CI [2.95, 3.49] for self‐efficacy. Students described AI‐enhanced goal‐setting as making tasks more manageable and progress more visible, while AI feedback and peer comparisons supported revision and engagement. Overall, the findings suggest that carefully designed, instructor‐mediated AI nudges can substantially enhance EFL academic writing when used to supplement, rather than replace, human teaching. Centring on three research questions, RQ1 tested differential effects of the three nudges versus control on writing performance, motivation and self‐efficacy; RQ2 examined learners' perceived effectiveness and experiences across modalities; RQ3 explored the correspondence between quantitative performance gains and qualitative learner insights.

Journal of Computer Assisted LearningVol. 42(1)
University of the Cordilleras (PH), Henan University of Urban Construction (CN)
Quality Education
Openalex Percentile: Top 99%
Writing and Handwriting Education
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