Abstract:

This paper describes the design and early use of Lesson Plan Evaluator Chatbot (LPE-Chatbot within a primary level Initial Teacher Education (ITE) programme in an Irish University. The LPE-Chatbot was trialed within a Science education module with pre-service teachers.

The study follows a two-phase design. In the first phase, two Science education lecturers graded and appraised a set of lesson plans authored by pre-service teachers against shared criteria (clarity of intentions, task–assessment alignment, and appropriate progression of science pedagogy and conceptual learning). In the second phase a Dig Tech lecturer used the LPE-Chatbot to independently grade and appraise the same set of lesson plans against the same shared criteria. This involves co-use of human and AI evaluation: each student submits a science lesson plan, which is first graded and given written qualitative feedback by the science lecturers, and then evaluated by a custom-built chatbot trained on TPACK, Irish Science Primary Curriculum (1999), Irish STEM Curriculum (2025), inquiry-based pedagogy, and the university’s lesson planning rubric.

The dataset consists of preservice science teachers’ lesson plans, each evaluated under four conditions:
(1) lecturer-assigned grade,
(2) chatbot-assigned grade,
(3) lecturer written qualitative feedback, and
(4) chatbot written qualitative feedback.

The dataset will be systematically evaluated to compare grading consistency, feedback depth, pedagogical accuracy, and alignment within and between human and AI evaluators.

The purpose of the research was to see whether a curriculum-aligned generative-AI workflow combining criterion-referenced feedback on uploaded lesson plans with a student-simulation mode for rehearsal can genuinely strengthen preservice teachers’ planning quality and anticipatory reasoning about misconceptions, while keeping professional judgement firmly in charge.

The findings will be shared with relevance to other educational disciplines and practices with a view to enhance pre-service teachers’ support in lesson planning.

Keywords:

AI, education, teacher training, science, STEM, assessment, education, development.