Artificial intelligence as a policy response to teaching and learning issues in education in Ghana
This paper offers a literature synthesis on the role of artificial intelligence (AI) as a strategic policy instrument in tackling the challenges of Teaching and Learning (TL) within the Ghanaian educational context. By examining the current state and prospects of AI in education (AIEd), specifically...
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| Format: | Article |
| Language: | English |
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University of South Florida (USF) M3 Publishing
2024-12-01
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| Series: | Journal of Global Education and Research |
| Subjects: | |
| Online Access: | https://digitalcommons.usf.edu/jger/vol8/iss3/4 |
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| _version_ | 1849763134841028608 |
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| author | Joshua Osondu Emmanuel Jean Francois Jesse Strycker |
| author_facet | Joshua Osondu Emmanuel Jean Francois Jesse Strycker |
| author_sort | Joshua Osondu |
| collection | DOAJ |
| description | This paper offers a literature synthesis on the role of artificial intelligence (AI) as a strategic policy instrument in tackling the challenges of Teaching and Learning (TL) within the Ghanaian educational context. By examining the current state and prospects of AI in education (AIEd), specifically in Ghana, this study highlights how AI can address unique educational challenges faced by Ghanaian students and educators. It adopts the dual instructor (AI and Human) model as a conceptual lens to examine how AI can revolutionize TL methodologies, thereby equipping learners for an AI-centric future. Our findings suggest that AI holds considerable promise for enhancing student engagement, personalizing learning experiences, increasing educator efficiency, and improving administrative processes. However, fully harnessing AI’s potential in education requires a strategic, contextually sensitive approach that addresses Ghana’s distinct cultural, economic, and infrastructural realities. Furthermore, integrating AIEd initiatives with overarching educational objectives is essential to maximize teaching effectiveness, student involvement, and administrative productivity. By adopting a strategic, informed, and collaborative methodology and implementing the suggested recommendations, Ghana can leverage AI to significantly upgrade its educational framework, better prepare its students for future challenges, advance its educational and developmental ambitions, and ensure AI deployment is equitable, ethical, and impactful. This study contributes to the emergent discourse on AIEd in Ghana and other similar contexts, highlighting the need for strategic policy implementations. |
| format | Article |
| id | doaj-art-a3685398b6f44344a2dbca7519ea2316 |
| institution | DOAJ |
| issn | 2577-509X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | University of South Florida (USF) M3 Publishing |
| record_format | Article |
| series | Journal of Global Education and Research |
| spelling | doaj-art-a3685398b6f44344a2dbca7519ea23162025-08-20T03:05:30ZengUniversity of South Florida (USF) M3 PublishingJournal of Global Education and Research2577-509X2024-12-018310.5038/2577-509X.8.3.1361Artificial intelligence as a policy response to teaching and learning issues in education in GhanaJoshua Osondu0Emmanuel Jean Francois1Jesse Strycker2Ohio UniversityOhio UniversityOhio UniversityThis paper offers a literature synthesis on the role of artificial intelligence (AI) as a strategic policy instrument in tackling the challenges of Teaching and Learning (TL) within the Ghanaian educational context. By examining the current state and prospects of AI in education (AIEd), specifically in Ghana, this study highlights how AI can address unique educational challenges faced by Ghanaian students and educators. It adopts the dual instructor (AI and Human) model as a conceptual lens to examine how AI can revolutionize TL methodologies, thereby equipping learners for an AI-centric future. Our findings suggest that AI holds considerable promise for enhancing student engagement, personalizing learning experiences, increasing educator efficiency, and improving administrative processes. However, fully harnessing AI’s potential in education requires a strategic, contextually sensitive approach that addresses Ghana’s distinct cultural, economic, and infrastructural realities. Furthermore, integrating AIEd initiatives with overarching educational objectives is essential to maximize teaching effectiveness, student involvement, and administrative productivity. By adopting a strategic, informed, and collaborative methodology and implementing the suggested recommendations, Ghana can leverage AI to significantly upgrade its educational framework, better prepare its students for future challenges, advance its educational and developmental ambitions, and ensure AI deployment is equitable, ethical, and impactful. This study contributes to the emergent discourse on AIEd in Ghana and other similar contexts, highlighting the need for strategic policy implementations.https://digitalcommons.usf.edu/jger/vol8/iss3/4policyartificial intelligence in educationai-human modelteachinglearning |
| spellingShingle | Joshua Osondu Emmanuel Jean Francois Jesse Strycker Artificial intelligence as a policy response to teaching and learning issues in education in Ghana Journal of Global Education and Research policy artificial intelligence in education ai-human model teaching learning |
| title | Artificial intelligence as a policy response to teaching and learning issues in education in Ghana |
| title_full | Artificial intelligence as a policy response to teaching and learning issues in education in Ghana |
| title_fullStr | Artificial intelligence as a policy response to teaching and learning issues in education in Ghana |
| title_full_unstemmed | Artificial intelligence as a policy response to teaching and learning issues in education in Ghana |
| title_short | Artificial intelligence as a policy response to teaching and learning issues in education in Ghana |
| title_sort | artificial intelligence as a policy response to teaching and learning issues in education in ghana |
| topic | policy artificial intelligence in education ai-human model teaching learning |
| url | https://digitalcommons.usf.edu/jger/vol8/iss3/4 |
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