Artificial intelligence is defined as highly advanced machine-based systems that can make predictions, offer suggestions, and make decisions in the virtual or real world in line with goals set by humans (Holmes and Tuomi, 2022). UNESCO considers artificial intelligence to be a technology that has the potential to mimic, and sometimes even surpass, human-specific abilities such as perception, language interaction, reasoning, analysis, problem solving, and even creativity. In fact, the concept of artificial intelligence is quite broad and encompasses various subfields. One subfield that has attracted attention in recent years is generative artificial intelligence. Generative artificial intelligence refers to models that can create original content, such as new images or texts, using the information they learn from a data set. Chatbots, especially ChatGPT (Chat Generative Pre-Trained Transformer), are one of the best-known examples of these generative artificial intelligence tools and are used for a wide variety of purposes in education (Hwang and Chang, 2021).

The opportunities and risks presented by artificial intelligence in education are rapidly rising on the agenda of researchers and education policymakers, and studies in this field are also increasing. Comprehensive review studies reveal the functions of artificial intelligence in higher education under the following headings: a) personalization with adaptive systems, b) automatic assessment and feedback, c) profiling and prediction, d) improving learning experiences (Ouyang, Zheng, & Jiao, 2022; Zawacki-Richter, Marín, Bond, & Gouverneur, 2019; Zhai et al., 2021).

Artificial intelligence offers educators innovative solutions with the power to create a fundamental transformation in the world of education, such as enriching lessons, simplifying administrative tasks, personalizing learning experiences, and increasing collaboration among students. Accessing a wide range of educational content of varying quality and in various formats on the internet can be an exhausting process for both teachers and students. This is where AI-powered tools come into play, helping educators automatically find materials tailored to their needs online; examples include tools such as MagicSchool, Perplexity, and Clever Owl. One of the greatest advantages offered by artificial intelligence is personalized learning systems. An AI-based educational assistant can provide tailored support by focusing on each student’s unique needs (Lee and Qiufan, 2021). At the same time, educators can analyze the feedback provided by AI to discover which pedagogical approaches and content are most effective for which students.

Research and discussions on the potential impact of popular artificial intelligence tools such as ChatGPT on learning and teaching processes continue unabated. In a survey conducted in the US, one-third of university students (n=1000) stated that they used ChatGPT in their assignments, while 60% used these tools in more than half of their assignments (Chan, 2023). This situation has led to bans or restrictions at some universities. However, ChatGPT can help students understand theoretical questions, improve their writing skills, and assist teachers in lesson planning (Ouyang et al., 2022; Neumann, Rauschenberger, and Schön, 2023; Atlas, 2023; Michel-Villarreal, Vilalta-Perdomo, Salinas-Navarro, Thierry-Aguilera, and Gerardou, 2023). While this tool offers innovative opportunities in education, it also brings controversy.

Artificial intelligence literacy requires a combination of technical knowledge and the ability to understand the social and ethical implications of artificial intelligence. Accordingly, artificial intelligence literacy is based on four fundamental areas:

1. Understanding artificial intelligence: This area involves grasping what artificial intelligence is and how it works. It encompasses understanding machine learning algorithms, the types of data these algorithms are trained on, and the limitations and potential biases of artificial intelligence systems.
2. Using and applying artificial intelligence: This includes the ability to use artificial intelligence tools and platforms for problem solving or performing specific tasks. Along with coding and programming knowledge, it also encompasses the ability to analyze and process large data sets.
3. Evaluating and developing artificial intelligence: This involves the ability to assess the quality and reliability of artificial intelligence systems, as well as the skill to develop ethical and fair artificial intelligence systems. It requires not only a deep understanding of the technical aspects of artificial intelligence, but also an understanding of its social and ethical implications.
4. Artificial intelligence ethics: It involves the ability to make informed decisions about the use of artificial intelligence in different contexts by evaluating its moral and ethical dimensions. It encompasses principles such as fairness, transparency, and accountability, and considers the potential effects of artificial intelligence on society and individuals (Yi, 2021).

One of the most powerful ways to develop artificial intelligence literacy and equip students with fundamental knowledge and skills in this field is to integrate artificial intelligence into the core of the curriculum. Addressing the theory and applications of artificial intelligence in higher education from an interdisciplinary perspective is crucial not only in the field of technology but also in preparing the talents of the future in every discipline (Ng et al., 2021). Many universities are taking significant steps in this direction. Some pioneering universities have begun offering educational programs and courses that address the impacts and ethical dimensions of artificial intelligence. Globally renowned institutions such as Harvard, Stanford, MIT, and Carnegie Mellon are conducting comprehensive academic studies and analyses to better understand the effects of artificial intelligence on society, the workforce, and individuals. These programs aim to prepare future experts by examining not only the technology itself but also topics such as responsible use, ethical principles, and social benefit.

• Although artificial intelligence has rapidly found its place in many areas of daily life, its potential in education is still in its infancy, standing before us as an area awaiting development. To fully leverage artificial intelligence in education, we must delve into the foundations of existing learning and teaching theories; artificial intelligence applications must be deeply integrated with pedagogical approaches and learning sciences (Ouyang et al., 2022; Hwang et al., 2020; Ouyang and Jiao, 2021).
• The future of artificial intelligence in education should be shaped by tools that encourage creativity and support problem solving and innovative thinking. Artificial intelligence can make education more accessible through collaboration platforms and inclusive applications. All students should have access to equal educational opportunities with tools suitable for every ability and learning style.
• Educators should be provided with training and resources to enhance their competence and confidence in artificial intelligence, and opportunities to experience effective applications should be facilitated. Through regular assessment and development, a new vision can be created for both educators and students (Atlas, 2023; Hwang et al., 2021; Wang et al., 2021).
• Artificial intelligence can support educators by automating routine tasks and providing personalized feedback. However, human roles such as emotional support and social interaction will remain the responsibility of educators. Therefore, educators will serve as guides who integrate AI-supported methods.
• Universities should develop policies and guidelines for artificial intelligence, creating a roadmap that includes awareness, education, research support, and ethical responsibilities. This will enable them to fully leverage artificial intelligence to deliver an inclusive and enriching learning experience.

You can watch the event, moderated by Prof. Dr. Yasemin Demiraslan Çevik, where our faculty members spoke about the potential of artificial intelligence in higher education, by clicking here or on our YouTube channel. The event was part of the workshop “Restructuring Professional Development in Higher Education in Light of New Paradigms” organized by the YÖMEGA Association.

Atlas, S. (2023). ChatGPT for Higher Education and Professional Development: A Guide to Conversational AI. https://digitalcommons.uri.edu/cba_facpubs/548

Chan, C.K.Y. (2023). A comprehensive AI policy education framework for university teaching and learning. Int J Educ Technol High Educ, 20, 38. https://doi.org/10.1186/s41239-023-00408-3

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278.

Dignum, V. (2023). Responsible Artificial Intelligence: Recommendations and Lessons Learned. In Responsible AI in Africa: Challenges and Opportunities; Eke, D.O., Wakunuma, K., Akintoye, S., Eds.; Springer Nature: Cham, Switzerland, pp. 195–214.

Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57, 542–570. https://doi.org/10.1111/ejed.12533

Hwang, G.-J., & Chang, C.-Y. (2021). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 1–14. https://doi.org/10.1080/10494820.2021.1952615

Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers & Education: Artificial Intelligence, 1. https://doi.org/10.1016/j.caeai.2020.100001

Lee, K.-F., & Qiufan, C. (2021). AI 2041: Ten visions for our future. WH Allen.

Miao, F., & Holmes, W. (2021). AI and education: Guidance for policy-makers. UNESCO. https://unesd oc.unesco.org/ark:/48223/ pf000 0376709

Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D.E., Thierry-Aguilera, R., Gerardou, F.S. (2023). Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Educ. Sci. 13, 856. https://doi.org/10.3390/educsci13090856

Neumann, M., Rauschenberger, M., & Schön, E-M. (2023). We Need To Talk About ChatGPT: The Future of AI and Higher Education,2023 IEEE/ACM 5th International Workshop on Software Engineering Education for the Next Generation (SEENG), Melbourne, Australia, pp. 29-32, doi: 10.1109/SEENG59157.2023.00010.

Ng, D.T.K., Leung, J.K.L., Chu, S.K.W., & Qiao, M.S. (2021). Conceptualizing AI literacy: An exploratory review. Computers & Education: Artificial Intelligence, 2, 100041, 10.1016/j.caeai.2021.100041

Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Educ Inf Technol 27, 7893–7925s. https://doi.org/10.1007/s10639-022-10925-9

Ouyang, F. & Jiao, P. (2021). Artificial Intelligence in Education: The Three Paradigms. Computers & Education: Artificial Intelligence, 100020. https://doi.org/10.1016/j.caeai.2021.100020

Pelletier, K., McCormack, M., Muscanell, N., Reeves, J., Robert, J., & Arbino, N. (2024). 2024 EDUCAUSE Horizon Report, Teaching and Learning Edition (Boulder, CO: EDUCAUSE, 2024).

Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 22– 13. https://doi.org/10.1186/s41039-017-0062-8

Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127, https://doi.org/10.1016/j.caeai.2023.100127.

World Commission on the Ethics of Scientific Knowledge and Technology (2019). Preliminary study on the Ethics of Artificial Intelligence. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000367823

Wang, Y., Liu, C., Tu, Y.-F. (2021). Factors Affecting the Adoption of AI-Based Applications in Higher Education: An Analysis of Teachers’ Perspectives Using Structural Equation Modeling. Educational Technology & Society, 24 (3), 116–129

Yi, Y. (2021). Establishing the concept of AI literacy: Focusing on competence and purpose. Jahr – European Journal of Bioethics, Artificial Intelligence Humanities (AIH special section, 12(2), 353–368. https://doi.org/10.21860/j.12.2.8, 24.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J-B., Yuan, J., & Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from2010 to 2020. Complexity. https://doi.org/10.1155/2021/8812542