INVITATION:
The Dean, School of Education under the College of Education and External Studies (CEES), cordially invites you to the PhD Public Defense of the following candidate:
Name of the Candidate: Mr. Louis Kakinda Teresphorus
Title of Thesis:
Developing a Pedagogical Framework for Pres-Service Teachers’ Integration of AI-Chatbots in Competency-Based Local Language Grammar Instruction: A case of Luganda
Date: Wednesday 18th December 2025.
Time: 9:00am – 12:00pm
ABSTRACT
The effective implementation of Uganda's competence-based curriculum calls for innovative approaches to indigenous language teacher preparation, particularly in promoting communicative competence in Luganda. Despite the potential of AI technologies like ChatGPT to enhance language teaching, this potential remains underutilized in Luganda preservice teacher training. This study aimed to develop and validate a pedagogical framework for preservice teachers' integration of AI-chatbots in Luganda grammar instruction. The research employed Design-Based Research methodology within constructivist and interpretivist paradigms, integrating Systemic Functional Linguistics and Genre Theory, Focus-on-Form principles, and AI-TPACK. Twenty-six preservice teachers participated across two implementation cycles. Data were collected through pre-post AI-TPACK surveys, interviews, focus groups, observations, reflective journals, and analysis of lesson plans and ChatGPT interaction logs. Thematic analysis employed deductive and inductive coding with triangulation for credibility. Results demonstrated substantial AI-TPACK development across seven domains and overall competence increase. Fifteen empirically validated design principles emerged across six clusters. These principles coalesce into a four-phase operational framework termed Plan-Generate-Verify-Adapt (PGVA) which positions teachers as cultural-guardians who systematically validate AI outputs against indigenous community standards while leveraging AI's affordances for material generation and pedagogical scaffolding. The study concludes that successful AI integration in indigenous language teacher education requires systematic attention to cultural-linguistic integrity, explicit genre-based scaffolding, progressive competence development, and operational workflow structures rather than assuming technology alone transforms practice. Recommendations include institutional adoption of the framework in teacher preparation programs, policy support for AI infrastructure in indigenous language contexts, curriculum embedding of AI-TPACK competencies and PGVA workflow training, and extension to other Ugandan indigenous languages.
Supervisors
- Assoc. Prof. Mulumba Bwanika Mathias
- Prof. Fred Masagazi Masaazi
Your presence and participation will be highly appreciated as we support the student in this important academic milestone.