Enhancing University EFL Learners' Writing Performance: The Role of AI‐ Enhanced Goal‐Setting, Feedback and Social Norm Interventions.
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 whic...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 1; pp. 1 - 31 |
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| Autor principal: | |
| Formato: | research tables/charts randomized controlled trial Journal Article |
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Wiley-Blackwell
Feb2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191181631&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191181631 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Feb2026 vid: 42 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 191181631 191181631 191181631 10.1002/jcal.70179 191181631 ppf: 1 ppct: 30 formats: tig: atl: Enhancing University EFL Learners' Writing Performance: The Role of AI‐ Enhanced Goal‐Setting, Feedback and Social Norm Interventions. aug: au: Wang, Yan affil: School of Foreign Studies, Henan University of Urban Construction, Pingdingshan, China sug: subj: Students, Undergraduate China English as a Second Language Education Writing Evaluation Academic Performance Evaluation Artificial Intelligence Learning Methods Goal-Setting Feedback Social Norms Outcomes of Education Human Randomized Controlled Trials Random Assignment Comparative Studies Descriptive Statistics Pretest-Posttest Design Social Learning Theory Chaos Theory Motivation Evaluation Self-Efficacy Evaluation Semi-Structured Interview Reflection Effect Size Confidence Intervals Summated Rating Scaling Purposive Sample Young Adult Male Female Analysis of Covariance China English Language Education Post Hoc Analysis Data Analysis Software Chi Square Test Thematic Analysis Male Female ab: 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 < 0.001, η2 = 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 ΔM = 11.01, 95% CI [10.51, 11.52] for performance; ΔM = 3.50, 95% CI [3.16, 3.83] for motivation; ΔM = 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. Lay Summary: What is currently known about this topic? ○EFL university students often struggle with academic writing, especially online.○AI tools can support feedback, goal‐setting and peer interaction in writing.○Most studies test single AI tools briefly, so comparative evidence is limited.What does this paper add? ○Compares three AI nudges with an active control in one randomised trial.○Shows AI goal‐setting nudges produce the strongest gains in EFL writing.○Links AI nudges to changes in motivation and writing self‐efficacy.Implications for practice/or policy ○Teachers can pair AI goal‐setting with guidance to boost writing outcomes.○Institutions should invest in ethical, accessible AI writing platforms.○Policies should support training to avoid overreliance and inequity. pubtype: Academic Journal doctype: research tables/charts randomized controlled trial Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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