Bridging the Gap Between Information Literacy (IL) and the Use of ChatGPT Among Higher Education Students
A look at the inherent aspects and potentials with AI and Higher Education.
By Juana M. Lang, Ed.D. and Lucinda Hines, DHA
The Advent of AI
The advent of ChatGenerative Pre-Trained Transformer (ChatGPT), an Artificial Intelligence (AI) language model designed to understand, generate, and respond to human language (Dempere et al., 2023), has caused a ruckus in higher education (HE) institutions as concerns grow about the risks of plagiarism and the use of misinformation in academic papers. Experts claim that the information generated by this Chatbot is sometimes inaccurate; thus, consuming and disseminating AI-generated information irresponsibly in HE can be misleading to society and science and may undermine the very purpose of learning. So, what can leaders and curriculum experts do to mitigate the negative implications of misusing ChatGPT in HE?
The frameworks for Information Literacy (IL) for higher education are essential to creating new knowledge and using scholarship ethically (American Library Association, 2016). Heck et al. (2021) argued that AI had not yet been developed when information literacy was adopted and widely used by scholars worldwide. Head et al. (2020) also asserted that we must effectively adapt IL’s tenets to use ChatGPT and other AI forms in HE.
Information Literacy and Evaluation of ChatGPT-Generated Information
ChatGPT can be an essential tool in supporting HE students’ learning. However, this tool requires users to become ChatGPT literate to understand its pitfalls better. The latter is pivotal when evaluating information generated by ChatGPT (Nazir & Wang, 2023). According to Nazir and Wang (2023), potential problems to consider when using ChatGPT are as follows:
- Generation of misinformation
- Limited understanding
- Biases
- Over-reliant on training data
- Information is generated and dependent on phrasing
Based on previous assertions, could HE institutions entwine an information-evaluation method such as the CRAAP method (currency, relevance, authority, accuracy, and purpose) to assist students in evaluating the information they find in ChatGPT? We believe the CRAAP method can help. However, the process would be slightly different, as ChatGPT differs from other sources of information. Table 1 illustrates some differences in applying the CRAAP method to different sources of information.
Table 1
The CRAAP Method: Examples of Application Variation Among Sources of Information
Continuous Improvement
The integration of the principles of IL exemplified by the CRAAP method may be a valuable resource for HE students when evaluating the information gathered from Chatbots such as ChatGPT. As artificial intelligence continues to evolve and augment our access to information through advanced technology, the ability to critically evaluate and discern this information’s credibility, relevance, and accuracy is paramount. Hence, ongoing efforts should be made to fine-tune the CRAAP method as new technological breakthroughs emerge.
References
American Library Association. (2016). Framework for information literacy for higher education. https://www.ala.org/acrl/standards/ilframework
California State University. (2010, September 17). Applying the CRAAP test. Meriam Library. https://library.csuchico.edu/sites/default/files/craap-test.pdf
Chinonso, O. E., Theresa, A. M.-E., & Aduke, T. C. (2023). ChatGPT for Teaching, Learning and Research: Prospects and Challenges. Global Academic Journal of Humanities and Social Sciences, 5(02), 33-40. https://doi.org/10.36348/gajhss.2023.v05i02.001
Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023). The impact of ChatGPT on higher education. In Frontiers in Education, 8, p. 1206936. https://doi.org/10.3389/feduc.2023.1206936
Head, A. J., Fister, B., & MacMillan, M. (2020). Information literacy in the age of algorithms. Harvard Graduate School of Education. https://files.eric.ed.gov/fulltext/ED605109.pdf
Heck, T., Weisel, L., & Kullmann, S. (2021). Learning information literacy across the globe. In B. Alexander, P. Libbrecht, M. Rittberger (Eds.), Information literacy and its interplay with AI (pp. 129-131). Leibniz-Institut für Bildungsforschung und Bildungsinformation. https://doi.org/10.25656/01:17891
Muis, R., Denton, C., & Dubé, A. (2022). Identifying CRAAP on the internet: A source evaluation intervention. Advances in Social Sciences Research Journal, 9(7), 240-241.
Nazir, A., & Wang, Z. (2023). A comprehensive survey of ChatGPT: advancements, applications, prospects, and challenges. Meta-Radiology, 1, 100022. https://doi.org/10.1016/j.metrad.2023.100022
Dr. Juana Lang
Dr. Lucinda Hines
ABOUT THE AUTHORS
Dr. Juana Lang is a "Fellow in Residence" for the Center for Leadership Studies and Organizational Research. Dr. Lang is an educator with over 26 years experience having earnied a Doctorate in Education from the University of Phoenix. She is a researcher and scholar who frequently engages the RSE enterprise in a number of academic activities.
Dr. Lucinda Hines is a "Fellow in Residence" in the Center for Leadership Studies and Organizational Research. Dr. Hines is a healthcare executive who earned her Master of Business Administration degree from Charleston Southern University, and then a Doctorate in Healthcare Administration through the University of Phoenix. She is a researcher and scholar who frequently engages the RSE enterprise in a number of academic activities.
Dr. Sai Raghav