AI-Powered Self-Assessment: Supercharging Future Teachers' Lesson Planning During Teaching Practice

Authors

  • Maimoona Naeem PhD Education Lecturer, Division of Education, University of Education Lahore.
  • Javaid Iqbal Punjab Higher Education Commission, Lahore
  • Ayman Sahar Division of Education, University of Education Lahore

Abstract

The advancement of artificial intelligence (AI) has introduced innovative approaches to professional learning in teacher education. Lesson planning is a fundamental teaching skill however; many future teachers face challenges in preparing effective and well-organised lesson plans during teaching practice. This study investigated the effect of AI-based self-assessment on future teachers’ lesson planning during teaching practice at the secondary school. The study employed a pre-test and post-test single-group experimental action research design. A sample of twenty future teachers enrolled in a teacher education program participated in the study. The participants prepared Grade 8 science lesson plans. A holistic lesson planning rubric was used to evaluate lesson plans, with each lesson plan carrying a total score of twenty.  Pre-test lesson plans were assessed before the intervention. The participants then used AI-based self-assessment to review and improve their lesson plans through structured, criterion-based feedback. After revision, post-test lesson plans were evaluated using the same rubric. The findings revealed that pre-test lesson plans demonstrated average to below-average lesson planning skills, particularly in writing clear objectives, aligning instructional activities with objectives, organizing lesson sequence, and planning assessment strategies. Post-test results showed noticeable improvement in overall lesson planning quality. The use of AI-based self-assessment enhanced planning practices. The study concludes that AI-based self-assessment is an effective supportive tool for improving lesson planning skills of future teachers. It promotes reflective practice, self-regulated learning, and professional development. The study recommends integrating AI-based self-assessment tools into teacher education programs to enhance lesson planning quality during teaching practice.

Keywords: Artificial Intelligence, Self-Assessment, Lesson Planning, Teaching Practice, Future Teachers

https://doi.org/10.5281/zenodo.19206537

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Published

2026-03-24

How to Cite

Maimoona Naeem, Javaid Iqbal, & Ayman Sahar. (2026). AI-Powered Self-Assessment: Supercharging Future Teachers’ Lesson Planning During Teaching Practice. `, 5(01), 2393–2409. Retrieved from https://assajournal.com/index.php/36/article/view/1540