GenAITEd Ghana: A First-of-Its-Kind Context-Aware and Curriculum-Aligned Conversational AI Agent for Teacher Education
- URL: http://arxiv.org/abs/2601.06093v2
- Date: Tue, 13 Jan 2026 04:47:43 GMT
- Title: GenAITEd Ghana: A First-of-Its-Kind Context-Aware and Curriculum-Aligned Conversational AI Agent for Teacher Education
- Abstract summary: GenAITEd Ghana is a context-aware, region-specific conversational AI prototype developed to support teacher education in Ghana.<n>It operates as a multi-agent, retrieval-augmented conversational AI that coordinates multiple models for curriculum-grounded dialogue, automatic speech recognition, voice synthesis, and multimedia interaction.<n> Evaluation findings show that the system effectively enacted key Responsible AI principles, including transparency, accountability, cultural responsiveness, privacy, and human oversight.
- Score: 0.040881832071648215
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Global frameworks increasingly advocate for Responsible Artificial Intelligence (AI) in education, yet they provide limited guidance on how ethical, culturally responsive, and curriculum-aligned AI can be operationalized within functioning teacher education systems, particularly in the Global South. This study addresses this gap through the design and evaluation of GenAITEd Ghana, a context-aware, region-specific conversational AI prototype developed to support teacher education in Ghana. Guided by a Design Science Research approach, the system was developed as a school-mimetic digital infrastructure aligned with the organizational logic of Ghanaian Colleges of Education and the National Council for Curriculum and Assessment (NaCCA) framework. GenAITEd Ghana operates as a multi-agent, retrieval-augmented conversational AI that coordinates multiple models for curriculum-grounded dialogue, automatic speech recognition, voice synthesis, and multimedia interaction. Two complementary prompt pathways were embedded: system-level prompts that enforce curriculum boundaries, ethical constraints, and teacher-in-the-loop oversight, and interaction-level semi-automated prompts that structure live pedagogical dialogue through clarification, confirmation, and guided response generation. Evaluation findings show that the system effectively enacted key Responsible AI principles, including transparency, accountability, cultural responsiveness, privacy, and human oversight. Human expert evaluations further indicated that GenAITEd Ghana is pedagogically appropriate for Ghanaian teacher education, promoting student engagement while preserving educators' professional authority. Identified challenges highlight the need for continued model integration, professional development, and critical AI literacy to mitigate risks of over-reliance.
Related papers
- Prompt Engineering for Responsible Generative AI Use in African Education: A Report from a Three-Day Training Series [0.0]
Generative artificial intelligence (GenAI) tools are increasingly adopted in education.<n>Yet many educators lack structured guidance on responsible and context sensitive prompt engineering.<n>This case report documents a three day online professional development programme organised by Generative AI for Education and Research in Africa.
arXiv Detail & Related papers (2026-01-04T00:18:57Z) - Human Experts' Evaluation of Generative AI for Contextualizing STEAM Education in the Global South [0.639147752530381]
STEAM education in many parts of the Global South remains abstract and weakly connected to learners sociocultural realities.<n>This study examines how human experts evaluate the capacity of Generative AI (GenAI) to contextualize STEAM instruction in these settings.
arXiv Detail & Related papers (2025-11-23T01:14:17Z) - EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus [59.693733170193944]
We present EduDial, a comprehensive multi-turn teacher-student dialogue dataset.<n>EduDial covers 345 core knowledge points and consists of 34,250 dialogue sessions generated through interactions between teacher and student agents.
arXiv Detail & Related papers (2025-10-14T18:18:43Z) - On the development of an AI performance and behavioural measures for teaching and classroom management [29.68201271068342]
This paper presents a two-year research project focused on developing AI-driven measures to analyze classroom dynamics.<n>Key outcomes include a curated audio-visual dataset, novel behavioral measures, and a proof-of-concept teaching review dashboard.
arXiv Detail & Related papers (2025-06-11T04:52:50Z) - ai.txt: A Domain-Specific Language for Guiding AI Interactions with the Internet [44.29685364907017]
We introduce ai.txt, a domain-specific language designed to regulate interactions between AI models, agents, and web content.<n>Our approach aims to aid the governance of AI-Internet interactions, promoting responsible AI use in digital ecosystems.
arXiv Detail & Related papers (2025-05-02T00:33:00Z) - Glocalizing Generative AI in Education for the Global South: The Design Case of 21st Century Teacher Educator AI for Ghana [0.7416846035207727]
The 21st Century Teacher Educator for Ghana GPT is a customized Generative AI (GenAI) tool created using OpenAI's Retrieval-Augmented Generation (RAG) and Interactive Semi-Automated Prompting Strategy (ISA)<n>This tool supports pre-service teachers in Ghana by embedding localized linguistic, cultural, and curricular content within globally aligned principles of ethical and responsible AI use.
arXiv Detail & Related papers (2025-04-09T03:28:35Z) - Transforming Teacher Education in Developing Countries: The Role of Generative AI in Bridging Theory and Practice [0.7416846035207727]
The study focuses on Ghana, where challenges such as limited pedagogical modeling, performance-based assessments, and practitioner-expertise gaps hinder progress.
GenAI has the capacity to address these issues by supporting content knowledge acquisition, a role that currently dominates teacher education programs.
The study concludes by recommending empirical research to explore these roles further and develop practical steps for integrating GenAI into teacher education systems responsibly and effectively.
arXiv Detail & Related papers (2024-11-16T06:46:09Z) - Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach [25.903775277417267]
Recent advances in generative AI (gen AI) have created excitement about the potential of new technologies to offer a personal tutor for every learner and a teaching assistant for every teacher.
We argue that this is primarily due to the difficulties with verbalising pedagogical intuitions into gen AI prompts and the lack of good evaluation practices.
Here we present our work collaborating with learners and educators to translate high level principles from learning science into a pragmatic set of seven diverse educational benchmarks.
arXiv Detail & Related papers (2024-05-21T19:27:59Z) - Scaffolding Language Learning via Multi-modal Tutoring Systems with Pedagogical Instructions [34.760230622675365]
Intelligent tutoring systems (ITSs) imitate human tutors and aim to provide customized instructions or feedback to learners.
With the emergence of generative artificial intelligence, large language models (LLMs) entitle the systems to complex and coherent conversational interactions.
We investigate how pedagogical instructions facilitate the scaffolding in ITSs, by conducting a case study on guiding children to describe images for language learning.
arXiv Detail & Related papers (2024-04-04T13:22:28Z) - White Paper: The Generative Education (GenEd) Framework [0.0]
The Generative Education (GenEd) Framework explores the transition from Large Language Models (LLMs) to Large Multimodal Models (LMMs) in education.
This paper delves into the potential of LMMs to create personalized, interactive, and emotionally-aware learning environments.
arXiv Detail & Related papers (2023-10-16T23:30:42Z) - Exploring User Perspectives on ChatGPT: Applications, Perceptions, and
Implications for AI-Integrated Education [40.38809129759498]
ChatGPT is most commonly used in the domains of higher education, K-12 education, and practical skills training.
On one hand, some users view it as a transformative tool capable of amplifying student self-efficacy and learning motivation.
On the other hand, there is a degree of apprehension among concerned users.
arXiv Detail & Related papers (2023-05-22T15:13:14Z) - AGI: Artificial General Intelligence for Education [41.45039606933712]
This position paper reviews artificial general intelligence (AGI)'s key concepts, capabilities, scope, and potential within future education.
It highlights that AGI can significantly improve intelligent tutoring systems, educational assessment, and evaluation procedures.
The paper emphasizes that AGI's capabilities extend to understanding human emotions and social interactions.
arXiv Detail & Related papers (2023-04-24T22:31:59Z) - Strategize Before Teaching: A Conversational Tutoring System with
Pedagogy Self-Distillation [35.11534904787774]
We propose a unified framework that combines teaching response generation and pedagogical strategy prediction.
Our experiments and analyses shed light on how teaching strategies affect dialog tutoring.
arXiv Detail & Related papers (2023-02-27T03:43:25Z) - Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI)
Curriculum [58.86139968005518]
The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education.
A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum.
The co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
arXiv Detail & Related papers (2021-01-19T11:26:19Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.