The integration of Generative Artificial Intelligence (GenAI) into second language (L2) writing has attracted growing interest, yet its value in primary education remains unclear. Lu et al. (2026) used a mixed-methods design with 301 Grade 5 and Grade 6 students from a primary school in Eastern China. Eight classes were randomly assigned to a GenAI-supported writing group or a conventional writing control group. Writing motivation, engagement, and performance were measured at pre-test (Week 1) and post-test (Week 9), and 12 experimental-group students were interviewed.
MANCOVA showed significant multivariate group effects on writing motivation (F(3, 294) = 3.067, p = .028, partial η² = 0.030), engagement (F(4, 292) = 8.392, p < .001, partial η² = 0.103) and performance (F(3, 294) = 2.841, p = .038, partial η² = 0.028). The experimental group scored higher on ideal L2 writing self, academic buoyancy, behavioral and emotional engagement, and language use, while opinion and content was only marginal (p = .054). There were no group differences in growth mindset, cognitive or metacognitive engagement, organization, or total scores. Paired t-tests showed small gains in the experimental group for ideal L2 writing self (d = 0.26), academic buoyancy (d = 0.24), behavioral engagement (d = 0.22), emotional engagement (d = 0.24), language use (d = 0.27) and overall writing performance (d = 0.28), but not cognitive (d = 0.12) or metacognitive (d = 0.07) engagement. The control group showed no significant gains after Bonferroni correction. Interviews highlighted GenAI’s multifaceted roles in shaping these outcomes. Although effect sizes were small, the study suggests GenAI can support motivation, engagement, and performance in primary-level L2 writing.
Teachers should position GenAI as a supportive tool rather than a substitute for students’ thinking, using activities that emphasize challenge, effort, and reflection to reduce over-reliance. Given the limited gains in cognitive and metacognitive engagement, explicit instruction in self-regulated writing strategies (planning, monitoring, and revision) is needed, supported by teacher modeling and student reflection. Collaborative GenAI activities should be structured so that students generate ideas independently, critically evaluate AI suggestions, and decide how to use them.
Source (Open Access): Lu, Q., Wang, M., Yao, Y., Zhu, X., Xiao, L., & Yin, H. (2026). Exploring the impact of a GenAI-supported writing program on primary students’ writing motivation, engagement, and performance: A mixed methods study. Learning and Instruction, 106, 102451.