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Generative Ai As A Learning Buddy And A Teaching Assistant: Preservice Teachers' Use And Attitudes

Date
Publisher
arXiv
This cross-sectional study investigates how preservice teachers in the Global South engage with Generative Artificial Intelligence across academic and instructional tasks while navigating infrastructural barriers such as limited internet access and high data costs. The study surveyed 167 preservice teachers from four teacher education institutions in Ghana. Descriptive statistics and inferential analyses, including multiple and ordinal logistic regressions, were used to examine patterns of GenAI use. Findings show that preservice teachers rely on GenAI as a learning companion for locating reading materials, accessing detailed content explanations, and identifying practical examples. They also use GenAI as a teaching assistant for tasks related to lesson preparation, including generating instructional resources, identifying assessment strategies, and developing lesson objectives. Usage patterns indicate that students in their third and fourth years have significantly higher frequencies of GenAI use compared to those in earlier years. Gender was not a significant predictor of GenAI adoption, in contrast to class level and age. Participants reported positive attitudes toward GenAI, noting that it supports autonomous learning and reduces dependence on peers and instructors for routine academic and teaching activities. However, challenges such as high data costs, occasional inaccuracies in GenAI outputs, and concerns about academic dishonesty were identified as factors that limit more frequent use. The study recommends the integration of GenAI literacy in teacher education programs, with a focus on ethical and responsible AI use to support equitable adoption in the Global South.
Study at a glance
  • Question: How and how often do preservice teachers in Ghana use generative AI, and what shapes their attitudes?
  • Setting and data: Four teacher education institutions in Ghana, 167 preservice teachers across years 2 to 4, surveyed over four weeks.
  • Method: Survey with descriptive analysis, multiple linear regression, and ordinal logistic regression
Why it matters

Little is known about how preservice teachers in the Global South engage with generative AI amid infrastructural constraints like limited internet access, high data costs, and ethical concerns around academic assessments.

Key findings
  • Over 87% of surveyed preservice teachers used generative AI at least occasionally for personal learning, while instructional use was less common, with 19.16% never using it.
  • Preservice teachers primarily used generative AI to find reading materials (38.11%) and content explanations (25.41%) for learning, and to find teaching resources (33.33%) for instruction.
  • Higher academic year and age predicted more frequent generative AI use, but age, gender, and class level did not meaningfully predict attitudes toward generative AI.

Summary drafted with AI from the full paper and may contain errors. See the full paper for details.

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