Higher education continues to be confronted with significant learning and teaching challenges. Still reeling from the effects of the pandemic, the sector has grappled for the past year with the advent and impact of generative artificial intelligence (AI). Since the introduction of ChatGPT by OpenAI in November 2022, a growing number of studies have discussed AI models and their impacts and influence on higher education. However, the novelty of what we aim to do in a future paper, outlined in the current one, lies in the systematicity of our approach. There is yet to be a study in which a systematic search strategy is developed to critically review extant research longitudinally across all available generative AI chatbot models within higher education. This protocol paper identifies a prospective systematic approach to reviewing the emergent literature. In addition, this protocol paper documents the structural approach to facilitate a systematic literature review. We seek to offer a systematic approach to create an open-access resource to support future learning and teaching scholars to gain timely access to pre-examined literature on different forms of generative AI and their impact on higher education. This protocol paper, as such, offers an approach that can be used to initiate closer scrutiny of the metadata of articles published on AI models in higher education since its initiation in November 2022. We also suggest that the protocol presented in this paper be considered a relevant and rigorous approach for conducting systematic literature reviews in other domains.
CITATION STYLE
Ismail, F., Tan, E., Rudolph, J., Crawford, J., & Tan, S. (2023). Artificial intelligence in higher education. A protocol paper for a systematic literature review. Journal of Applied Learning and Teaching, 6(2), 56–63. https://doi.org/10.37074/jalt.2023.6.2.34
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