AI in education: enhancing learning potential and addressing ethical considerations among academic staff—a cross-sectional study at the University of Jordan

To investigate the ethical implications of AI-driven natural language generation systems (NLG), such as ChatGPT, in university education at the University of Jordan from the perspective of academic staff. Specific objectives include assessing awareness levels, identifying ethical concerns, and exploring institutional support and training needs. A cross-sectional survey of 274 academic staff members (111 females and 163 males) from diverse disciplines was conducted. Participants provided demographic data and responded to questions on knowledge, awareness, ethical concerns, and institutional support related to AI in education. Statistical analyses included descriptive statistics, Chi-square tests, Mann–Whitney U tests, and regression analyses. Varied awareness and usage of AI-driven NLG among academic staff were found, with 46.7% using AI for university tasks, primarily in research (46.4%) and teaching (33.9%). While 62% demonstrated moderate to high knowledge of AI in academia, which varied by academic discipline (p < .001, Table 3). Fewer than one-third were familiar with current ethical guidelines for AI in education (Table 2). Ethical concerns about AI use by students were prevalent (70% of academic staff), especially regarding plagiarism and exam cheating (Table 2). Editing and language corrections (70.8%) were deemed ethically acceptable uses of AI for students (Table 2), with ethical concerns over effortless assignments, sole reliance on AI for research, and exam cheating. Regression analyses revealed that factors such as gender, age, academic rank, teaching experience, and discipline influenced attitudes and knowledge of AI (p < .05, Tables 5 and 6). This study reveals that a significant proportion of academic staff at the University of Jordan use AI and have moderate to high knowledge of it. Although there are gaps in their understanding of AI ethics, they expect students to maintain high ethical standards. This underscores the need for comprehensive ethical guidelines, strong institutional support, and initiatives such as training programs and workshops on ethical AI use to support their role in guiding students in Jordanian academia.

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Publication Details

Journal
International Journal for Educational Integrity
Published
2025-05-26
DOI
https://doi.org/10.1007/s40979-025-00189-4
Citations
11
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
7.20
Controls
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article

AI in education: enhancing learning potential and addressing ethical considerations among academic staff—a cross-sectional study at the University of Jordan

Mahmoud K. AL‐Omiri, Sanaa Aljamani, Rasha A. Alamoush, Marwa M. Alnsour et al.
11 citations
International Journal for Educational Integrity
Artificial Intelligence in Healthcare and Education
7.20
article

AI in education: enhancing learning potential and addressing ethical considerations among academic staff—a cross-sectional study at the University of Jordan

Mahmoud K. AL‐Omiri, Sanaa Aljamani, Rasha A. Alamoush, Marwa M. Alnsour, Latifa Qouzah
article en
11 citations

Abstract

To investigate the ethical implications of AI-driven natural language generation systems (NLG), such as ChatGPT, in university education at the University of Jordan from the perspective of academic staff. Specific objectives include assessing awareness levels, identifying ethical concerns, and exploring institutional support and training needs. A cross-sectional survey of 274 academic staff members (111 females and 163 males) from diverse disciplines was conducted. Participants provided demographic data and responded to questions on knowledge, awareness, ethical concerns, and institutional support related to AI in education. Statistical analyses included descriptive statistics, Chi-square tests, Mann–Whitney U tests, and regression analyses. Varied awareness and usage of AI-driven NLG among academic staff were found, with 46.7% using AI for university tasks, primarily in research (46.4%) and teaching (33.9%). While 62% demonstrated moderate to high knowledge of AI in academia, which varied by academic discipline (p < .001, Table 3). Fewer than one-third were familiar with current ethical guidelines for AI in education (Table 2). Ethical concerns about AI use by students were prevalent (70% of academic staff), especially regarding plagiarism and exam cheating (Table 2). Editing and language corrections (70.8%) were deemed ethically acceptable uses of AI for students (Table 2), with ethical concerns over effortless assignments, sole reliance on AI for research, and exam cheating. Regression analyses revealed that factors such as gender, age, academic rank, teaching experience, and discipline influenced attitudes and knowledge of AI (p < .05, Tables 5 and 6). This study reveals that a significant proportion of academic staff at the University of Jordan use AI and have moderate to high knowledge of it. Although there are gaps in their understanding of AI ethics, they expect students to maintain high ethical standards. This underscores the need for comprehensive ethical guidelines, strong institutional support, and initiatives such as training programs and workshops on ethical AI use to support their role in guiding students in Jordanian academia.

International Journal for Educational IntegrityVol. 21(1)
University of Jordan (JO), Jordan University of Science and Technology (JO), Jordan Hospital (JO)
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
7.20
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