Teacher-AI Collaboration in Content Recommendation for Digital Personalised Learning among Pre-primary Learners in Kenya

Research on teacher-AI collaboration is limited despite AI's growing role in education, especially in low- and middle-income countries (LMICs). To address this gap, this study investigates how teacher agency in a digital personalised learning (DPL) tool can affect behavioural changes and learning outcomes in Kenya. Teachers in the experimental group could apply their pedagogical judgement to override system-generated content for learners to practise, whereas teachers in the control group were limited to system-generated content. Teacher agency was assessed by measuring the diversity of unique choices made and the frequency of changes in their choices. The nine-week A/B test involved 562 learners from 45 pre-primary classes, each led by a different teacher, with classes randomly assigned to a control or an experimental group. The results demonstrate that teacher agency in content recommendation significantly impacted learner device usage, but not teacher usage of digitised lesson plans. Learners in the experimental group achieved significantly higher digital scores on learning units than the control group. Additional analysis of the experimental group revealed that the degree of teacher agency significantly influenced learner device usage, but not lesson plan usage or digital scores. The study highlights the importance of further research to enhance teachers-AI synergy, to improve learning outcomes in LMICs and beyond.