Exploring Pre-Service Teachers’ Perceptions of ChatGPT Integration into Physical Sciences Teaching: A Case Study at a Rural South African University

The emergence of artificial intelligence, exemplified by generative chatbots such as ChatGPT, has elicited optimism among some educators regarding enhanced teaching and learning methods. Simultaneously, it has raised concerns among others, who perceive these chatbots as being disruptive to established pedagogical norms developed over centuries. This study investigated pre-service teachers’ perceptions regarding integrating ChatGPT into physical sciences teaching at a rural South African university. A case study research design utilizing a qualitative approach was adopted to collect, analyze, and interpret data. This methodology was employed to gain comprehensive insight into the viewpoints held by final year Bachelor of Education Honors physical sciences students serving as pre-service teachers. The study explored the benefits and potential challenges of incorporating emerging technologies such as ChatGPT into physical sciences teaching. The theoretical framework guiding the study was the technological, pedagogical content knowledge (TPACK) framework. Eleven purposively sampled physical sciences pre-service teachers participated in semi-structured interviews. The collected data were analyzed using thematic analysis. The research findings indicate that ChatGPT has the potential to contribute to the teaching of physical sciences in the areas of lesson planning, preparation, presentation, and formative assessment. However, the study revealed that ChatGPT is unable to answer certain questions in the physical sciences accurately and this was of great concern. These findings shed light on how artificial intelligence generative chatbots can be incorporated into physical sciences learning. The findings provide insights for policymakers, who can facilitate the use of these tools in lesson preparation; science educators, who should leverage the chatbots to enhance learner engagement; and researchers, to help them deepen their understanding of the role of emerging technologies in science education.

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Publication Details

Journal
International Journal of Learning Teaching and Educational Research
Published
2024-11-30
DOI
https://doi.org/10.26803/ijlter.23.11.24
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.24
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article

Exploring Pre-Service Teachers’ Perceptions of ChatGPT Integration into Physical Sciences Teaching: A Case Study at a Rural South African University

Rebecca Bessong, Ndanganeni Florence Litshani, Mamotena Mpeta, Samuel Jere
2 citations
International Journal of Learning Teaching and Educational Research
Artificial Intelligence in Healthcare and Education
0.24
article

Exploring Pre-Service Teachers’ Perceptions of ChatGPT Integration into Physical Sciences Teaching: A Case Study at a Rural South African University

Rebecca Bessong, Ndanganeni Florence Litshani, Mamotena Mpeta, Samuel Jere
article en
2 citations

Abstract

The emergence of artificial intelligence, exemplified by generative chatbots such as ChatGPT, has elicited optimism among some educators regarding enhanced teaching and learning methods. Simultaneously, it has raised concerns among others, who perceive these chatbots as being disruptive to established pedagogical norms developed over centuries. This study investigated pre-service teachers’ perceptions regarding integrating ChatGPT into physical sciences teaching at a rural South African university. A case study research design utilizing a qualitative approach was adopted to collect, analyze, and interpret data. This methodology was employed to gain comprehensive insight into the viewpoints held by final year Bachelor of Education Honors physical sciences students serving as pre-service teachers. The study explored the benefits and potential challenges of incorporating emerging technologies such as ChatGPT into physical sciences teaching. The theoretical framework guiding the study was the technological, pedagogical content knowledge (TPACK) framework. Eleven purposively sampled physical sciences pre-service teachers participated in semi-structured interviews. The collected data were analyzed using thematic analysis. The research findings indicate that ChatGPT has the potential to contribute to the teaching of physical sciences in the areas of lesson planning, preparation, presentation, and formative assessment. However, the study revealed that ChatGPT is unable to answer certain questions in the physical sciences accurately and this was of great concern. These findings shed light on how artificial intelligence generative chatbots can be incorporated into physical sciences learning. The findings provide insights for policymakers, who can facilitate the use of these tools in lesson preparation; science educators, who should leverage the chatbots to enhance learner engagement; and researchers, to help them deepen their understanding of the role of emerging technologies in science education.

International Journal of Learning Teaching and Educational ResearchVol. 23(11)
University of Venda (ZA)
Openalex Percentile: Top 39%
Artificial Intelligence in Healthcare and Education
0.24
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