The Impact of AI-Enabled Prompt Engineering Intervention on Sixth-Grade Students’ Academic Achievement, Motivation, and Engagement
Keywords:
Artificial Intelligence in Education, Prompt Engineering, Self-Determination Theory (SDT), Agentic Engagement, Academic Motivation, Academic AchievementAbstract
The present study aimed to investigate the effectiveness of an AI-enabled prompt engineering intervention on sixth-grade students’ academic achievement, academic motivation, and multidimensional engagement in science learning. This study employed a quasi-experimental pretest–posttest design with a non-equivalent control group. The sample consisted of 30 sixth-grade female students who were assigned to an experimental group (n = 15) and a control group (n = 15). The experimental group participated in an eight-session AI-supported science learning program in which prompt engineering techniques were used to position the AI system as a Socratic and facilitative tutor rather than a direct provider of answers. Data collection instruments included the Academic Motivation Scale (AMS), a multidimensional engagement questionnaire based on Reeve’s model, and a researcher-developed science achievement test. The intervention was implemented over four weeks with two 45-minute sessions per week. Data were analyzed using descriptive statistics and Analysis of Covariance (ANCOVA) in SPSS at a significance level of 0.05. The ANCOVA findings demonstrated a statistically significant effect of the AI-based intervention on all dependent variables (p < .001). The intervention explained 67% of the variance in academic achievement (Partial η² = .67), 61% of the variance in academic motivation (Partial η² = .61), and 64% of the variance in total academic engagement (Partial η² = .64). The experimental group showed significantly higher posttest scores compared with the control group across all dimensions of engagement. The strongest effect was observed in agentic engagement, where students demonstrated greater proactive participation, questioning behavior, and instructional agency. Significant improvements were also observed in affective, cognitive, and behavioral engagement dimensions, indicating that AI-assisted instruction enhanced students’ emotional involvement, strategic thinking, and persistence in learning activities. The findings provide strong empirical evidence that AI-enabled prompt engineering interventions can substantially improve academic achievement, motivation, and engagement among primary school students.
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