Apprehensions of Integrating Artificial Intelligence into Higher Learning: A Systematic Review
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| Title: | Apprehensions of Integrating Artificial Intelligence into Higher Learning: A Systematic Review |
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| Language: | English |
| Authors: | Norbert Nombo (ORCID |
| Source: | International Journal of Technology in Education and Science. 2026 10(2):379-397. |
| Availability: | International Society for Technology, Education, and Science. e-mail: ijtesoffice@gmail.com; Web site: http://www.ijtes.net |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Information Analyses |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Literature Reviews, Higher Education, Artificial Intelligence, Technology Uses in Education, Technology Integration, College Students, Student Attitudes, College Faculty, Teacher Attitudes, Computer Attitudes, Educational Policy, Educational Benefits, Barriers, Fear |
| ISSN: | 2651-5369 |
| Abstract: | The integration of artificial intelligence in higher learning has been studied and commented upon by several researchers. One thing that is obvious is that there are several authors who are hopeful that artificial intelligence has positive prospects for higher learning. On the other hand, there are also several authors who think that artificial intelligence is negatively affecting higher learning. While some authors report on hopes only and others on fears only, some others report both fears and hopes. This systematic review engages a total of 61 reports, including journal articles and grey literature, to address three issues. The first is about the extent to which researchers admit to the existence of negatives of AI in higher education. The second is about the factors that these researchers associate with the fears they admit. The third is a summarized identification of sources of this fear. Literature for this review was collected from various online sources, and the PRISMA 2020 flowchart was used for screening. Finally, content analysis was conducted using NVIVO computer software. Results show that, to a large extent, authors admit to the existence of various kinds of disadvantages in using AI in higher learning. These disadvantages lead to fears related to ethics and compromise established standards of higher education. Higher education policy makers and managers are, therefore, called upon to take necessary precautions in designing AI-supported systems and put in place reliable and effective guidelines for their use. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1506284 |
| Database: | ERIC |
| Abstract: | The integration of artificial intelligence in higher learning has been studied and commented upon by several researchers. One thing that is obvious is that there are several authors who are hopeful that artificial intelligence has positive prospects for higher learning. On the other hand, there are also several authors who think that artificial intelligence is negatively affecting higher learning. While some authors report on hopes only and others on fears only, some others report both fears and hopes. This systematic review engages a total of 61 reports, including journal articles and grey literature, to address three issues. The first is about the extent to which researchers admit to the existence of negatives of AI in higher education. The second is about the factors that these researchers associate with the fears they admit. The third is a summarized identification of sources of this fear. Literature for this review was collected from various online sources, and the PRISMA 2020 flowchart was used for screening. Finally, content analysis was conducted using NVIVO computer software. Results show that, to a large extent, authors admit to the existence of various kinds of disadvantages in using AI in higher learning. These disadvantages lead to fears related to ethics and compromise established standards of higher education. Higher education policy makers and managers are, therefore, called upon to take necessary precautions in designing AI-supported systems and put in place reliable and effective guidelines for their use. |
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| ISSN: | 2651-5369 |
