• Register
  • Login
  • Persian

Research in Teaching

  1. Home
  2. Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Editorial Board

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

Journal Metrics

News

Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students

    Authors

    • Sayran Marofi 1
    • shoeab vaisi 2
    • vahed mamandi 3

    1 Student of Educational Management and Planning, Faculty of Psychology and Educational Sciences, University of Tehran, Iran.

    2 Master's student, Department of Educational Sciences, University of Kurdistan, Sanandaj, Iran.

    3 Master's student in medical education, Iran University of Medical Sciences, Tehran, Iran.

,

Document Type : Research Paper

10.22034/trj.2025.142184.2069
  • Article Information
  • References
  • Download
  • How to cite
  • Statistics
  • Share

Abstract

Abstract
Higher education is fundamentally related to advances in innovative technologies and high computing capacities of intelligent machines (Bayne, 2008). And artificial intelligence is a booming technology field that can change every aspect of our social interactions (Barakina et al., 2021). In education, artificial intelligence has begun to produce new teaching and learning solutions that are now being tested in various fields (Pedro et al.). Artificial intelligence (AI) refers to the ability of a digital machine to perform tasks normally associated with intelligent beings (TKF, 2021). And basically the term artificial intelligence, which was created by John McCarthy in 1955, is defined as a machine with intelligent behavior such as perception, reasoning, learning or communication and the ability to perform human tasks (Chang et al., 2021). Therefore, its explosive growth increasingly changes the ways of interaction, communication, life, learning and work of people (Pedro et al, 2020). Also, artificial intelligence (AI) is defined as a computer system capable of performing certain tasks that were traditionally performed by humans. These systems can include capabilities such as speech recognition, vision, and intelligent behaviors. In the field of education, there are various theories about the use of artificial intelligence that examine its effects on teaching and learning. One of these theories was presented by Zouhaier Slimi in 2023, who examined the impact of artificial intelligence on higher education and its effects on teaching and learning, assessment, ethics, required skills, and career prospects. Also, Helen Crompton and Diane Burke in 2023 presented a systematic review of artificial intelligence in higher education from 2016 to 2022, exploring new trends and different uses of artificial intelligence in the field. Another article entitled "Ethical Artificial Intelligence for Teaching-Learning in Higher Education" by Mohammed Airaj in 2024 examines the ethical aspects of artificial intelligence in higher education and its effects on teaching and learning. These theories suggest that artificial intelligence can significantly reduce the workload of teachers, personalize learning for students, revolutionize assessments, and develop intelligent educational systems. Also, the ethical dimensions of artificial intelligence and the possible effects of the Covid-19 pandemic on the future of research and applications of artificial intelligence in education have also been examined.
For this reason, artificial intelligence has attracted the attention of researchers in the field of education and they believe that one of the main goals that AI will pursue is to assist in personal learning or support students based on their learning status, preferences or personal characteristics (Hwang , 2014). Therefore, the use of artificial intelligence in education (AIED) has created new opportunities for designing constructive learning activities and developing programs or more technologically advanced learning environments (Kay, 2012). In addition, artificial intelligence technology and big data are combined for deep mining and analysis of educational data, it can also promote teaching reform and improve teaching quality (Pannu, 2015). Artificial intelligence promotes the development of adaptive learning, and strives to incorpoate all aspects of testing, teaching, learning, and practice into an adaptive learning system to facilitate student learning (Wang, 2021). Also, in addition to the opportunities that artificial intelligence will create in education, it can also lead to challenges, including the implementation of related activities or systems for most researchers and specialists in the fields of computers and education is still a challenge (Hwang et al., 2020). . In recent years, extensive research has been conducted in the field of artificial intelligence in education, which shows the potential and numerous challenges that this technology brings to universities and educational institutions. According to the nature of the topic and research objectives, the current research method is placed in the group of qualitative research with interpretive paradigm. Since the goal was to analyze the lived experience and people's perceptions of the implementation of a phenomenon (plan), therefore, the phenomenology method was used to examine the lived experiences of professors and students of Tehran University. which conforms to the logic and cognitive foundations of this research method (Mohammadpour, 2012). The phenomenology method is one of the qualitative research methods that examines and deeply analyzes the viewpoints, feelings and experiences of the sample group in relation to a certain phenomenon or phenomena (Hatch, 2002; Creswrll, 2012; Creswell, 2014). Sampling method: The sampling method was carried out in a purposeful and criterion manner and theoretical saturation criterion; That is, people were invited to participate who met the important and predetermined criteria desired by the researcher. Based on the purposeful and criteria-based sampling method, the sampling process should usually continue until the new interviews do not add more information to the previous ones and the researcher witnesses the repetition of data patterns according to the desired criteria. Based on this, the data collection continued until a lot of data was obtained from the sample interviews of professors and students of all three mentioned universities. Also, it was tried to maximize the diversity of the participants in the sample. And among the professors and students of Tehran University, interviews were conducted until the data was saturated, 20 people participated, including 9 professors and 11 students. . Artificial intelligence as a powerful tool in higher education leads to the improvement of the quality of teaching and learning. This technology helps professors and students to access up-to-date content faster, categorize content and improve evaluation methods. And artificial intelligence helps to adapt education to individual needs and support the learner, and leads to access to various resources with little time and without wasting time. For example, AI-based learning management systems are used to schedule courses, conduct online tests, and provide instant feedback to students. In addition, artificial intelligence can analyze educational data and identify students' learning patterns. These analyzes help professors in setting up curricula and providing educational content according to the individual needs of students. Also, artificial intelligence predicts learning problems and provides appropriate solutions to solve these problems. The findings of this research show that artificial intelligence plays an important role in improving the quality of teaching and learning for professors, improving learning for learners, and as a research assistant. However, there are also challenges and problems that need to be addressed. These challenges include increasing inequality among people, reducing learning opportunities and learning experiences for learners, as well as insufficient literacy of people about the proper use of artificial intelligence. For the optimal use of artificial intelligence in higher education, it is necessary to pay attention to these challenges and provide appropriate solutions to deal with them. Increasing inequality among individuals: Unequal access to AI technologies can exacerbate educational inequalities.

Keywords

  • artificial intelligence
  • higher education
  • challenges and opportunities

Main Subjects

  • Education and teaching
  • XML
  • PDF 1.56 M
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • CHICAGO
  • VANCOUVER
References
Airaj, M. (2024). Ethical artificial intelligence for teaching-learning in higher education. Education and Information Technologies.
Akinwalere, S., & Ivanov, V. (2022). Artificial intelligence in higher education: Challenges and opportunities. Border Crossing, 12(1), 1-15.
Aler Tubella, A., Mora-Cantallops, M., & Nieves, J. C. (2024). How to teach responsible AI in higher education: Challenges and opportunities. Ethics and Information Technology, 26(3).
Barakina, E. Y., Popova, A. V., Gorokhova, S. S., & Voskovskaya, A. S. (2021). Digital technologies and artificial intelligence technologies in education. European Journal of Contemporary Education, 10(2), 285-296.
Bayne, S. (2008). Higher education as a visual practice: Seeing through the virtual learning environment. Teaching in Higher Education, 13(4), 395-410.
Bond, M., et al. (2024). New advances in artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education.
Chang, T. C., Seufert, C., Eminaga, O., Shkolyar, E., Hu, J. C., & Liao, J. C. (2021). Current trends in artificial intelligence application for endourology and robotic surgery. Urologic Clinics, 48(1), 151-160.
Creswell, J. W. (2012). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Thousand Oaks, CA: Sage.
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: Sage.
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, 22.
Dever, D., et al. (2020). Providing customized prompt feedback in higher education using AI. Journal of Educational Technology.
Hatch, J. A. (2002). Doing qualitative research in education settings. Albany, NY: State University of New York Press.
Hié, A., & Thouary, C. (2023). How AI is reshaping higher education. AACSB.
Hornberger, M., Björnsdorf, A., & Nerdal, C. (2023). What do university students know about artificial intelligence? Development and validation of an AI literacy test. Computers and Education: Artificial Intelligence, 5, 100165.
Huang, J., Saleh, S., & Liu, Y. (2021). A review on artificial intelligence in education. Academic Journal of Interdisciplinary Studies, 10(206).
Hwang, G. J. (2014). Definition, framework and research issues of smart learning environments-a context-aware ubiquitous learning perspective. Smart Learning Environments, 1(1), 1-4.
Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100001.
Kay, J. (2012). AI and education: Grand challenges. IEEE Intelligent Systems, 27(5), 66-69.
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18), 10424.
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., Baltes, J., Guerra, R., Li, P., & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in Psychology, 11, 580820.
Meade, P., et al. (2023). Students’ perspective on the use of artificial intelligence in education. SpringerLink.
Michel-Villarreal, R., et al. (2023). Challenges and opportunities of generative AI for higher .education as explained by ChatGPT. Education Sciences, 13(9), 856.
Mohammadpour, A. (2012). Qualitative research methods. Tehran: Nashr-e Ney.
Morris, L., & Manion, L. (2000). Research methods in education (5th ed.). London: Routledge.
Nguyen, N. (2023, May 16). The opportunities and challenges of AI in higher education. FeedbackFruits.
Orga Pisica, A., et al. (2023). Implementing artificial intelligence in higher education: Pros and cons from the perspectives of academics. Societies, 13(5), 118.
Pannu, A. (2015). Artificial intelligence and its application in different areas. Artificial Intelligence, 4(10), 79-84.
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2020).Artificial intelligence in education: Challenges and opportunities for sustainable development.
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. Artificial intelligence in education: Challenges and opportunities for sustainable development.
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.
Slimi, Z. (2023). The Impact of Artificial Intelligence on Higher Education: An Empirical Study. Deusto University-Spain, National University of Sciences and Technology Oman.
TKF, C. (2021). A holistic approach to artificial intelligence (AI) curriculum for K-12 schools. TechTrends, 65, 796-807.
Wang, Y. (2021). An improved machine learning and artificial intelligence algorithm for classroom management of English distance education. Journal of Intelligent & Fuzzy Systems, 40(2), 3477-3488.
    • Article View: 1,172
    • PDF Download: 891
Research in Teaching
Volume 12, Issue 4 - Serial Number 40
February 2025
Pages 181-213
Files
  • XML
  • PDF 1.56 M
Share
How to cite
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • CHICAGO
  • VANCOUVER
Statistics
  • Article View: 1,172
  • PDF Download: 891

APA

Marofi, S. , vaisi, S. and mamandi, V. (2025). Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students. Research in Teaching, 12(4), 181-213. doi: 10.22034/trj.2025.142184.2069

MLA

Marofi, S. , , vaisi, S. , and mamandi, V. . "Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students", Research in Teaching, 12, 4, 2025, 181-213. doi: 10.22034/trj.2025.142184.2069

HARVARD

Marofi, S., vaisi, S., mamandi, V. (2025). 'Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students', Research in Teaching, 12(4), pp. 181-213. doi: 10.22034/trj.2025.142184.2069

CHICAGO

S. Marofi , S. vaisi and V. mamandi, "Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students," Research in Teaching, 12 4 (2025): 181-213, doi: 10.22034/trj.2025.142184.2069

VANCOUVER

Marofi, S., vaisi, S., mamandi, V. Explaining the challenges and opportunities of artificial intelligence in higher education from the point of view of professors and students. Research in Teaching, 2025; 12(4): 181-213. doi: 10.22034/trj.2025.142184.2069

  • Home
  • About Journal
  • Editorial Board
  • Submit Manuscript
  • Contact Us
  • Sitemap

News

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Newsletter Subscription

Subscribe to the journal newsletter and receive the latest news and updates

© Journal management system. designed by sinaweb