Abstract
Background
Artificial intelligence (AI) has emerged as a powerful tool in many sectors including healthcare education. ChatGPT is a widely used generative AI model among learners and teachers globally. In Zambia, there is no information regarding the use of ChatGPT among healthcare students. Therefore, this study assessed the attitudes and usage of ChatGPT and influencing factors among pharmacy students at the University of Zambia.
Methods
This cross-sectional study was conducted from February 2024 to May 2024 among pharmacy students at the University of Zambia using a structured questionnaire. The questionnaire was based on the validated Technology Acceptance Model Edited to Assess ChatGPT Adoption (TAME-ChatGPT) survey instrument on the determinants of attitude and usage of ChatGPT among health students. Attitude toward ChatGPT was assessed using four items grouped into a single variable comprising the primary study measure and dichotomized into “positive” vs. “negative” attitudes.
Results
A total of 385 responses were obtained, with 358 participants (93.0%) who heard of ChatGPT before the study, and 303 used ChatGPT (78.7%). In univariate analyses, the following factors were significantly associated with a positive attitudes towards ChatGPT: low perceived risk (P = 0.009), low anxiety (P = 0.010), and a high score on technology/social influence (P < 0.001), with the latter factor being the only influencing factor regression analysis (aOR: 2.908, 95% CI: 1.752–4.825). Regarding the influencing factors for ChatGPT use, the perceived usefulness was the only significant factor (P = 0.013).
Conclusions
The study results showed the widespread use of ChatGPT among pharmacy students in Zambia highlighting its increasing role as part of the educational process. This study also found that advancement in technology and social influence predisposed most pharmacy students to use Chat GPT. To better implement this advanced generative AI tool in healthcare education, academics and universities must take into account the role of social influence and readiness to accept technology as well as emphasizing the role of usefulness to foster the educational process.
Keywords: Artificial intelligence, Attitudes, ChatGPT, Pharmacy, Students, Technology, Zambia
Introduction
ChatGPT is a leading generative artificial intelligence (AI) model that can perform multiple tasks [1–4]. The opportunities provided by generative AI tools can enhance interaction, innovation, and information dissemination across various sectors, including healthcare education [5–7]. Therefore, these AI models can have revolutionary applications in healthcare through their ability to simulate human-like text-based interactions [8, 9].
Specifically, ChatGPT can foster personalized learning and improve the whole educational process by generating clinical vignettes, providing simplified explanations, creating diverse examples, and devising multiple-choice questions (MCQs) [8, 10, 11]. Such capabilities can provide an effective approach to create a personalized and responsive learning environment [12, 13].
In healthcare education, which involves the need to comprehend complex concepts with the application of knowledge in clinical settings, ChatGPT provides novel opportunities [3, 12]. This is related to ChatGPT’s ability to tailor educational content to individual learning styles and needs enhancing the educational process [8]. Additionally, the global reach of AI-driven platforms such as ChatGPT could provide high-quality learning materials accessible to a broader range of students across diverse geographical and socio-economic landscapes; thus, generative AI including ChatGPT can help to improve educational equity worldwide [14–17].
ChatGPT offers a range of applications in pharmacy and healthcare, including rapid access to drug information, interpretation of medical literature, and generation of patient-friendly summaries [18, 19]. It can support clinical decision-making by answering questions and suggesting treatment options [18]. Academically, students may use it for study aids, examination practice, and writing support, while faculty can leverage it for creating exams, developing patient cases, and conducting research [18, 20]. AI can help pharmacy professionals to optimize medication use and ensure patient safety [21]. Alongside this, AI can be used in pharmaceutical industries in drug discovery because AI approaches speed up and prevent failures in the drug discovery pipeline [22–24].
On the other hand, the integration of generative AI into educational systems is not devoid of challenges [3, 8]. Privacy concerns arise with the handling of sensitive data, while copyright issues touch on the creation and distribution of proprietary educational content [3, 25]. Importantly, there is an ongoing debate about the potential for generative AI to undermine critical thinking skills among students, as the ease of access to information might discourage deeper engagement with learning materials [26]. Further, the ability of generative AI to produce high-quality, original content effortlessly could compromise academic integrity, promoting a culture of dependency that might detract from the learning experience [19, 27]. Furthermore, there are many concerns regarding the accuracy of answers and information provided by AI models such as ChatGPT [28–30]. The use of AI technologies in education has also brought concerns of ethical issues including algorithm biases, personal data privacy, and learner autonomy [31–33]. Therefore, there is a need to promote the responsible and ethical use of AI in education [34].
Previous studies indicated that the adoption and utilization of ChatGPT have become increasingly widespread among university students within healthcare disciplines [18, 35–38]. This trend suggests a growing integration of ChatGPT both in student learning and in educational methodologies across academic settings. Despite this broad usage, there remains a notable gap in the literature regarding its adoption in various geographical contexts. Specifically, there is a paucity of information regarding the attitudes and usage of ChatGPT among students in Zambia. In response to this significant oversight, the present study assessed the attitudes and usage of ChatGPT and influencing factors among pharmacy students in Zambia.
Methods
Study design, site, and population
This cross-sectional study was conducted in February 2024 among undergraduate students at the Ridgeway Campus of the University of Zambia in Lusaka, Zambia. The University of Zambia offers health and non-health programs to undergraduate and postgraduate students with the Ridgeway Campus offering only health programs including Pharmacy training [39, 40]. This institution was chosen because it is the largest public university in Zambia that offers pharmacy training in Zambia. The study was conducted building on previous findings which reported on issues to do with access to the internet [41] and lack of formal integration of AI into the curriculum [42, 43]. Global trends suggest future applications of AI in pharmacy practice, including dispensing support and patient care. To be eligible, a student was supposed to be registered with the University of Zambia and studying pharmacy. This study was conducted among pharmacy students from second to fifth year of study. The pharmacy students were selected because they are the future pharmacists who will be required to use technology during their practice. We excluded pharmacy students who were not available during the data collection period. We also excluded the first year students because they were still doing their premedical studies and being trained at the Main Campus of the University of Zambia.
Sample size Estimation and sampling criteria
The sample size was estimated using Taro Yamane’s formula [44]. A total of 743 undergraduate pharmacy students were registered at the Ridgeway Campus of the University of Zambia, of which 192 were second-year, 221 were third-year, 183 were fourth-year, and 147 were in the fifth-year of study. Since there was no study conducted in Zambia on ChatGPT, we used a finite population of 743 pharmacy students, a margin of error of 5% and a confidence level if 95% to estimate the sample size. The population of registered pharmacy students was obtained the University of Zambia School of Health Sciences management. We obtained a minimum required sample size of 261. Additionally, a 10% non-response rate was factored in, and this resulted in a minimum sample size of 287 participants to be enrolled in the study. We considered 10% non-response rate as a conservative estimate to account for participants who may not respond or complete the survey. This allowance ensured that the final sample size remained statistically valid and representative. Incorporating a 10% non-response rate into sample size calculations enhances the reliability and robustness of study findings. All participants were selected using a simple random sampling method to ensure every student had a chance of being enrolled in the study. Eligible students were randomly selected using computer-generated random numbers after stratification by year of study. Hence, stratified random sampling proportional to year of study was used to select participants in this study. To increase the chances of meeting the desired sample size, we circulated a total of 400 questionnaires.
Data collection
Data were collected using a previously validated questionnaire based on the Technology Acceptance Model, specifically adapted as the Technology Acceptance Model Edited to Assess ChatGPT Adoption (TAME-ChatGPT) [36, 37, 45]. To achieve the study objectives, we employed a validated survey instrument designed by the Technology Acceptance Model (TAM), ensuring a robust framework for assessing the acceptance and application of this technology in a novel educational environment [37]. The questionnaire was reviewed by public health experts at the University of Zambia. The data collection tool had two sections including Section A which had questions on the sociodemographic characteristics of the students. Section B had 35 questions on the attitudes of students towards ChatGPT. Our questionnaire had a Cronbach α value of 0.885, thereby indicating acceptable internal consistency. Data collection was done by two data collectors and lasted for about 20 to 30 min per participant to complete filling the questionnaire.
Statistical analysis
The collected data were entered into Microsoft Excel 2013 and exported to Statistical Package for Social Sciences (SPSS) version 26.0 (IBM Corp., Armonk, NY, USA) for statistical analysis. The primary study measure was the attitudes towards ChatGPT based on the following four items: (1) By how much will ChatGPT revolutionize your world in 2025? “Up to 50%” scored as 1 while “More than 50%” scored as 2. (2) How is ChatGPT likely to influence your educational progression? “Not positively” scored as 1, while “Positively” scored as 2. (3) Are you planning to make substantial changes in your education and career plans because of ChatGPT and other similar artificial intelligence Chatbots? “Yes” scored as 1, “No” scored as 2. (4) Stephen Hawking has predicted that uncontrolled development of AI will ultimately lead to the death of civilization and the end of the human race. Do you believe this will be true during your lifetime? “Yes” scored as 1, while “No” scored as 2. The sum was divided into two categories: “4–6” classified as “negative” while “7–8” classified as “positive”. Univariate analysis was conducted to identify factors that were associated with attitudes of pharmacy students towards ChatGPT based on the chi-square test (χ2). Variables with a p < 0.200 were considered in the adjusted regression analysis conducted using the binary logistic regression. The variables with a p < 0.05 in adjusted logistic regression were considered as determinants of attitudes toward ChatGPT among pharmacy students who heard of ChatGPT. Confounding was determined by identifying variables where OR changed by > 10–20% after adjustment. The significance level was set at a 95% confidence level and p < 0.050.
Ethical approval
We obtained ethical approval from the University of Zambia Research Ethics Committee (UNZAHSREC) with ethical Protocol ID: 20231270128. We also obtained clearance from the Zambia National Health Research Authority (NHRA) with an approval number NHRA034/25/7/2024. The participants were informed about the purpose of the study, and they were enrolled after providing informed and written consent. We adhered to the ethical principles of confidentiality and anonymity by not collecting any personal identifiers. Finally, participation in the study was on voluntary basis.
Results
Description of the study sample
A total of 385 responses were obtained with a majority of respondents being females (n=225, 58.4%), younger than 26 years old (n=313, 81.3%), singles (n=357, 92.7%), and in their fourth or fifth year of study (Table 1).
Table 1.
General features of the study sample (N = 385)
| Variable | Category | N 2 (%) |
|---|---|---|
| Sex | Male | 160 (41.6) |
| Female | 225 (58.4) | |
| Age group | < 26 years | 313 (81.3) |
| ≥ 26 years | 72 (18.7) | |
| Marital status | Single | 357 (92.7) |
| Married | 28 (7.3) | |
| Year of study | Second | 77 (20.0) |
| Third | 75 (19.5) | |
| Fourth | 108 (28.1) | |
| Fifth | 125 (32.5) | |
| Have you heard of ChatGPT before this study? | Yes | 358 (93.0) |
| No | 27 (7.0) | |
| Have you used ChatGPT before this study? | Yes | 303 (78.7) |
| No | 82 (21.3) | |
| How did you know about ChatGPT? 1 | I learnt about ChatGPT in class | 20 (5.6) |
| Specifically searching online for it | 23 (6.4) | |
| Through friends or relatives | 237 (66.2) | |
| Through social media | 78 (21.8) | |
| Have you searched online for ChatGPT? | Yes | 290 (75.3) |
| No | 95 (24.7) | |
| Have you accessed or signed up for ChatGPT? | Yes | 262 (68.1) |
| No | 123 (31.9) | |
| Have you asked a query to ChatGPT? | Yes | 266 (69.1) |
| No | 119 (30.9) | |
| By how much will ChatGPT revolutionize your world in 2025? | Up to 50% | 155 (40.3) |
| More than 50% | 230 (59.7) | |
| How is ChatGPT likely to influence your educational progression? | Not Positively | 80 (20.8) |
| Positively | 305 (79.2) | |
| Are you planning to make substantial changes in your education and career plans because of ChatGPT and other similar artificial intelligence Chatbots? | Yes | 171 (44.4) |
| No | 214 (55.6) | |
| Stephen Hawking has predicted that uncontrolled development of artificial intelligence will ultimately lead to death of civilization and end of human race. Do you believe this will be true during your lifetime? | Yes | 155 (40.3) |
| No | 230 (59.7) |
1 Among those who heard of ChatGPT before the study; 2 N: Number
The role of demographic variables in attitudes towards ChatGPT
Younger age, being single, and advanced academic years were significantly associated with higher likelihood of hearing about ChatGPT before the study (Table 2). Regarding ChatGPT use, higher likelihood was associated with advancing academic years.
Table 2.
The role of demographics in the general attitude towards ChatGPT among the study participants
| Item | Response | Sex | Age group | Marital status | Year of study | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | < 26 | ≥ 26 | Single | Married | Second | Third | Fourth | Fifth | ||||||
| N (%) | N (%) | P, χ2 | N (%) | N (%) | P, χ2 | N (%) | N (%) | P, χ2 | N (%) | N (%) | N (%) | N (%) | P, χ2 | ||
| Have you heard of ChatGPT before this study? | Yes | 150 (41.9) | 208 (58.1) | 0.621, 0.244 | 295 (82.4) | 63 (17.6) | 0.043, 4.089 | 335 (93.6) | 23 (6.4) | 0.020, 5.445 | 63 (17.6) | 73 (20.4) | 100 (27.9) | 122 (34.1) | < 0.001, 21.007 |
| No | 10 (37.0) | 17 (63.0) | 18 (66.7) | 9 (33.3) | 22 (81.5) | 5 (18.5) | 14 (51.9) | 2 (7.4) | 8 (29.6) | 3 (11.1) | |||||
| Have you used ChatGPT before this study? | Yes | 130 (42.9) | 173 (57.1) | 0.303, 1.061 | 249 (82.2) | 54 (17.8) | 0.395, 0.724 | 283 (93.4) | 20 (6.6) | 0.329, 0.953 | 44 (14.5) | 68 (22.4) | 82 (27.1) | 109 (36.0) | < 0.001, 33.638 |
| No | 30 (36.6) | 52 (63.4) | 64 (78.0) | 18 (22.0) | 74 (90.2) | 8 (9.8) | 33 (40.2) | 7 (8.5) | 26 (31.7) | 16 (19.5) | |||||
| How did you know about ChatGPT? | I learnt about ChatGPT in class | 6 (30.0) | 14 (70.0) | 0.147, 5.367 | 16 (80.0) | 4 (20.0) | 0.344, 3.324 | 19 (95.0) | 1 (5.0) | 0.931, 0.445 | 2 (10.0) | 10 (50.0) | 4 (20.0) | 4 (20.0) | 0.010, 21.626 |
| Specifically searching online for it | 9 (39.1) | 14 (60.9) | 22 (95.7) | 1 (4.3) | 22 (95.7) | 1 (4.3) | 8 (34.8) | 5 (21.7) | 8 (34.8) | 2 (8.7) | |||||
| Through friends or relatives | 94 (39.7) | 143 (60.3) | 195 (82.3) | 42 (17.7) | 222 (93.7) | 15 (6.3) | 38 (16.0) | 45 (19.0) | 65 (27.4) | 89 (37.6) | |||||
| Through social media | 41 (52.6) | 37 (47.4) | 62 (79.5) | 16 (20.5) | 72 (92.3) | 6 (7.7) | 15 (19.2) | 13 (16.7) | 23 (29.5) | 27 (34.6) | |||||
| Have you searched online for ChatGPT? | Yes | 126 (43.4) | 164 (56.6) | 0.189, 1.728 | 238 (82.1) | 52 (17.9) | 0.498, 0.459 | 272 (93.8) | 18 (6.2) | 0.159, 1.980 | 43 (14.8) | 66 (22.8) | 78 (26.9) | 103 (35.5) | < 0.001, 26.130 |
| No | 34 (35.8) | 61 (64.2) | 75 (78.9) | 20 (21.1) | 85 (89.5) | 10 (10.5) | 34 (35.8) | 9 (9.5) | 30 (31.6) | 22 (23.2) | |||||
| Have you accessed or signed up for ChatGPT? | Yes | 117 (44.7) | 145 (55.3) | 0.072, 3.241 | 213 (81.3) | 49 (18.7) | 0.999, < 0.001 | 244 (93.1) | 18 (6.9) | 0.657, 0.197 | 26 (9.9) | 65 (24.8) | 77 (29.4) | 94 (35.9) | < 0.001, 57.046 |
| No | 43 (35.0) | 80 (65.0) | 100 (81.3) | 23 (18.7) | 113 (91.9) | 10 (8.1) | 51 (41.5) | 10 (8.1) | 31 (25.2) | 31 (25.2) | |||||
| Have you asked a query to ChatGPT? | Yes | 117 (44.0) | 149 (56.0) | 0.149, 2.086 | 222 (83.5) | 44 (16.5) | 0.104, 2.641 | 251 (94.4) | 15 (5.6) | 0.065, 3.406 | 34 (12.8) | 63 (23.7) | 70 (26.3) | 99 (37.2) | < 0.001, 37.131 |
| No | 43 (36.1) | 76 (63.9) | 91 (76.5) | 28 (23.5) | 106 (89.1) | 13 (10.9) | 43 (36.1) | 12 (10.1) | 38 (31.9) | 26 (21.8) | |||||
| By how much will ChatGPT revolutionize your world in 2025? | Up to 50% | 55 (35.5) | 100 (64.5) | 0.047, 3.942 | 127 (81.9) | 28 (18.1) | 0.793, 0.069 | 147 (94.8) | 8 (5.2) | 0.190, 1.715 | 23 (14.8) | 26 (16.8) | 45 (29.0) | 61 (39.4) | 0.040, 8.311 |
| More than 50% | 105 (45.7) | 125 (54.3) | 186 (80.9) | 44 (19.1) | 210 (91.3) | 20 (8.7) | 54 (23.5) | 49 (21.3) | 63 (27.4) | 64 (27.8) | |||||
| How is ChatGPT likely to influence your educational progression? | Not Positively | 27 (33.8) | 53 (66.3) | 0.111, 2.535 | 62 (77.5) | 18 (22.5) | 0.328, 0.958 | 74 (92.5) | 6 (7.5) | 0.930, 0.008 | 13 (16.3) | 16 (20.0) | 21 (26.3) | 30 (37.5) | 0.653, 1.629 |
| Positively | 133 (43.6) | 172 (56.4) | 251 (82.3) | 54 (17.7) | 283 (92.8) | 22 (7.2) | 64 (21.0) | 59 (19.3) | 87 (28.5) | 95 (31.1) | |||||
| Are you planning to make substantial changes in your education and career plans because of ChatGPT and other similar artificial intelligence Chatbots? | Yes | 79 (46.2) | 92 (53.8) | 0.099, 2.728 | 134 (78.4) | 37 (21.6) | 0.187, 1.744 | 153 (89.5) | 18 (10.5) | 0.028, 4.829 | 40 (23.4) | 27 (15.8) | 61 (35.7) | 43 (25.1) | 0.002, 15.369 |
| No | 81 (37.9) | 133 (62.1) | 179 (83.6) | 35 (16.4) | 204 (95.3) | 10 (4.7) | 37 (17.3) | 48 (22.4) | 47 (22.0) | 82 (38.3) | |||||
| Stephen Hawking has predicted that uncontrolled development of artificial intelligence will ultimately lead to death of civilization and end of human race. Do you believe this will be true during your lifetime? | Yes | 57 (36.8) | 98 (63.2) | 0.118, 2.445 | 130 (83.9) | 25 (16.1) | 0.288, 1.129 | 148 (95.5) | 7 (4.5) | 0.087, 2.924 | 28 (18.1) | 32 (20.6) | 45 (29.0) | 50 (32.3) | 0.859, 0.759 |
| No | 103 (44.8) | 127 (55.2) | 183 (79.6) | 47 (20.4) | 209 (90.9) | 21 (9.1) | 49 (21.3) | 43 (18.7) | 63 (27.4) | 75 (32.6) | |||||
Attitudes towards ChatGPT among the respondents who heard of ChatGPT
Based on the categories of TAME-ChatGPT constructs, the overall attitude of the participants was mainly high perceived risk (n=276, 77.1%), high anxiety (n=296, 82.7%), and high influence of technology/social influence (n=262, 73.2%, Table 3).
Table 3.
The association of TAME-ChatGPT attitude constructs with various factors
| Item | Response | Perceived risk construct category | Anxiety construct category | Technology/social influence construct category | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Low | High | Low | High | High | Low | |||||
| N (%) | N (%) | P, χ2 | N (%) | N (%) | P, χ2 | N (%) | N (%) | P, χ2 | ||
| Have you used ChatGPT before this study? | Yes | 71 (23.4) | 232 (76.6) | 0.577, 0.311 | 52 (17.2) | 251 (82.8) | 0.854, 0.034 | 228 (75.2) | 75 (24.8) | 0.039, 4.278 |
| No | 11 (20.0) | 44 (80.0) | 10 (18.2) | 45 (81.8) | 34 (61.8) | 21 (38.2) | ||||
| Have you searched online for ChatGPT? | Yes | 64 (22.1) | 226 (77.9) | 0.437, 0.604 | 47 (16.2) | 243 (83.8) | 0.251, 1.317 | 218 (75.2) | 72 (24.8) | 0.080, 3.075 |
| No | 18 (26.5) | 50 (73.5) | 15 (22.1) | 53 (77.9) | 44 (64.7) | 24 (35.3) | ||||
| Have you accessed or signed up for ChatGPT? | Yes | 65 (24.8) | 197 (75.2) | 0.157, 2.006 | 49 (18.7) | 213 (81.3) | 0.253, 1.307 | 200 (76.3) | 62 (23.7) | 0.026, 4.945 |
| No | 17 (17.7) | 79 (82.3) | 13 (13.5) | 83 (86.5) | 62 (64.6) | 34 (35.4) | ||||
| Have you asked a query to ChatGPT? | Yes | 63 (23.7) | 203 (76.3) | 0.551, 0.356 | 44 (16.5) | 222 (83.5) | 0.509, 0.437 | 201 (75.6) | 65 (24.4) | 0.084, 2.986 |
| No | 19 (20.7) | 73 (79.3) | 18 (19.6) | 74 (80.4) | 61 (66.3) | 31 (33.7) | ||||
| By how much will ChatGPT revolutionize your world in 2025? | Up to 50% | 30 (21.6) | 109 (78.4) | 0.635, 0.225 | 28 (20.1) | 111 (79.9) | 0.260, 1.267 | 85 (61.2) | 54 (38.8) | < 0.001, 16.765 |
| More than 50% | 52 (23.7) | 167 (76.3) | 34 (15.5) | 185 (84.5) | 177 (80.8) | 42 (19.2) | ||||
| How is ChatGPT likely to influence your educational progression? | Not Positively | 6 (8.2) | 67 (91.8) | 0.001, 11.200 | 3 (4.1) | 70 (95.9) | 0.001, 11.173 | 24 (32.9) | 49 (67.1) | < 0.001, 75.915 |
| Positively | 76 (26.7) | 209 (73.3) | 59 (20.7) | 226 (79.3) | 238 (83.5) | 47 (16.5) | ||||
| Are you planning to make substantial changes in your education and career plans because of ChatGPT and other similar artificial intelligence Chatbots? | Yes | 39 (24.7) | 119 (75.3) | 0.477, 0.507 | 27 (17.1) | 131 (82.9) | 0.919, 0.010 | 135 (85.4) | 23 (14.6) | < 0.001, 21.657 |
| No | 43 (21.5) | 157 (78.5) | 35 (17.5) | 165 (82.5) | 127 (63.5) | 73 (36.5) | ||||
| Stephen Hawking has predicted that uncontrolled development of artificial intelligence will ultimately lead to death of civilization and end of human race. Do you believe this will be true during your lifetime? | Yes | 21 (14.4) | 125 (85.6) | 0.001, 10.138 | 10 (6.8) | 136 (93.2) | < 0.001, 18.871 | 89 (61.0) | 57 (39.0) | < 0.001, 18.777 |
| No | 61 (28.8) | 151 (71.2) | 52 (24.5) | 160 (75.5) | 173 (81.6) | 39 (18.4) | ||||
Higher perceived risks was associated with younger age and being single, while higher influence of technology/social influence was associated with being male or being married (Table 4).
Table 4.
TAME-ChatGPT attitude constructs association with participants’ demographics
| Item | Category | Perceived risk construct category | Anxiety construct category | Technology/social influence construct category | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Low | High | Low | High | High | Low | |||||
| N (%) | N (%) | P, χ2 | N (%) | N (%) | P, χ2 | N (%) | N (%) | P, χ2 | ||
| Sex | Male | 42 (28.0) | 108 (72.0) | 0.051, 3.795 | 29 (19.3) | 121 (80.7) | 0.392, 0.732 | 120 (80.0) | 30 (20.0) | 0.013, 6.111 |
| Female | 40 (19.2) | 168 (80.8) | 33 (15.9) | 175 (84.1) | 142 (68.3) | 66 (31.7) | ||||
| Age group | < 26 years | 60 (20.3) | 235 (79.7) | 0.012, 6.251 | 48 (16.3) | 247 (83.7) | 0.257, 1.284 | 210 (71.2) | 85 (28.8) | 0.065, 3.410 |
| ≥ 26 years | 22 (34.9) | 41 (65.1) | 14 (22.2) | 49 (77.8) | 52 (82.5) | 11 (17.5) | ||||
| Marital status | Single | 70 (20.9) | 265 (79.1) | 0.001, 11.924 | 55 (16.4) | 280 (83.6) | 0.086, 2.953 | 240 (71.6) | 95 (28.4) | 0.012, 6.322 |
| Married | 12 (52.2) | 11 (47.8) | 7 (30.4) | 16 (69.6) | 22 (95.7) | 1 (4.3) | ||||
| Year of study | Second | 12 (19.0) | 51 (81.0) | 0.800, 1.005 | 8 (12.7) | 55 (87.3) | 0.160, 5.172 | 49 (77.8) | 14 (22.2) | 0.209, 4.534 |
| Third | 16 (21.9) | 57 (78.1) | 8 (11.0) | 65 (89.0) | 49 (67.1) | 24 (32.9) | ||||
| Fourth | 23 (23.0) | 77 (77.0) | 19 (19.0) | 81 (81.0) | 79 (79.0) | 21 (21.0) | ||||
| Fifth | 31 (25.4) | 91 (74.6) | 27 (22.1) | 95 (77.9) | 85 (69.7) | 37 (30.3) | ||||
The determinants of attitudes towards ChatGPT among the participants
In univariate analysis and among those who heard of ChatGPT, only the three constructs of TAME-ChatGPT were associated with students’ attitudes towards ChatGPT (Table 5). In binary logistic regression, only higher scores on the technology/social influence construct was associated with higher odds of positive attitudes towards ChatGPT (aOR: 2.908, 95% CI: 1.752–4.825, P<0.001, Table 6).
Table 5.
Univariate analysis results for the variables associated with attitudes towards ChatGPT including the constructs of TAME-ChatGPT attitude scale
| Variable | Category | Attitudes towards ChatGPT | P, χ2 | |
|---|---|---|---|---|
| Negative | Positive | |||
| N (%) | N (%) | |||
| Sex | Male | 61 (40.7) | 89 (59.3) | 0.117, 2.463 |
| Female | 102 (49.0) | 106 (51.0) | ||
| Age group | < 26 years | 134 (45.4) | 161 (54.6) | 0.930, 0.008 |
| ≥ 26 years | 29 (46.0) | 34 (54.0) | ||
| Marital status | Single | 154 (46.0) | 181 (54.0) | 0.524, 0.406 |
| Married | 9 (39.1) | 14 (60.9) | ||
| Year of study | Second | 26 (41.3) | 37 (58.7) | 0.338, 3.369 |
| Third | 30 (41.1) | 43 (58.9) | ||
| Fourth | 53 (53.0) | 47 (47.0) | ||
| Fifth | 54 (44.3) | 68 (55.7) | ||
| Perceived risk construct category | Low | 27 (32.9) | 55 (67.1) | 0.009, 6.813 |
| High | 136 (49.3) | 140 (50.7) | ||
| Anxiety construct category | Low | 19 (30.6) | 43 (69.4) | 0.010, 6.700 |
| High | 144 (48.6) | 152 (51.4) | ||
| Technology/social influence construct category | High | 99 (37.8) | 163 (62.2) | < 0.001, 23.629 |
| Low | 64 (66.7) | 32 (33.3) | ||
Table 6.
Binary logistic regression analysis for the determinants of attitudes toward ChatGPT among those who heard of ChatGPT (Nagelkerke R2 = 0.104)
| Variable | Positive attitude toward ChatGPT | aOR (95% CI) | P value |
|---|---|---|---|
| Sex | Male | 1.221 (0.783–1.903) | 0.378 |
| Female | Ref. | ||
| Perceived risk construct | Low | 1.254 (0.680–2.311) | 0.468 |
| High | Ref. | ||
| Anxiety construct | Low | 1.572 (0.794–3.111) | 0.194 |
| High | Ref. | ||
| Technology/social influence construct | High | 2.908 (1.752–4.825) | < 0.001 |
| Low | Ref. |
Note: Nagelkerke R2 = 0.104 indicates that 10.4% of the variation in attitudes toward ChatGPT is explained by the model
For ChatGPT usage, the only factor that was significantly associated with positive attitudes towards ChatGPT was the higher perceived usefulness (Table 7).
Table 7.
Univariate analysis results for the variables associated with the attitudes towards ChatGPT including the constructs of TAME-ChatGPT usage scale
| Variable | Category | Attitude towards ChatGPT | P, χ2 | |
|---|---|---|---|---|
| Negative | Positive | |||
| N (%) | N (%) | |||
| Sex | Male | 49 (37.7) | 81 (62.3) | 0.197, 1.667 |
| Female | 78 (45.1) | 95 (54.9) | ||
| Age group | < 26 years | 104 (41.8) | 145 (58.2) | 0.911, 0.012 |
| ≥ 26 years | 23 (42.6) | 31 (57.4) | ||
| Marital status | Single | 119 (42.0) | 164 (58.0) | 0.858, 0.032 |
| Married | 8 (40.0) | 12 (60.0) | ||
| Year of Study | Second | 15 (34.1) | 29 (65.9) | 0.509, 2.320 |
| Third | 27 (39.7) | 41 (60.3) | ||
| Fourth | 39 (47.6) | 43 (52.4) | ||
| Fifth | 46 (42.2) | 63 (57.8) | ||
| Perceived usefulness constructs the category | High | 59 (35.5) | 107 (64.5) | 0.013, 6.123 |
| Low | 68 (49.6) | 69 (50.4) | ||
| Behavior/cognitive factors construct category | High | 62 (38.3) | 100 (61.7) | 0.168, 1.897 |
| Low | 65 (46.1) | 76 (53.9) | ||
| Perceived risk of use construct category | Low | 21 (37.5) | 35 (62.5) | 0.458, 0.550 |
| High | 106 (42.9) | 141 (57.1) | ||
| Perceived ease of use construct category | High | 99 (42.9) | 132 (57.1) | 0.551, 0.355 |
| Low | 28 (38.9) | 44 (61.1) | ||
Discussion
To the best of our knowledge, this was the first study that was conducted in Zambia to investigate the usage and attitudes of pharmacy students regarding ChatGPT. This study found that most pharmacy students had heard of and used ChatGPT before the present study. Additionally, most students had searched for Chat GPT online and the majority were already signed up for ChatGPT. ChatGPT is becoming increasingly integrated into the education system worldwide as highlighted by the literature of the tool’s potential to improve learning by the creation of specified educational materials which can include multiple choice questions, study aids, your personal tutor, idea generation, professional communication, and others, especially in healthcare education [1, 2, 8, 20]
The Zambian context through this study indicates that 93% of the pharmacy students had heard of ChatGPT, and about 79% of the students had used this AI technology. This reveals that Zambian students are in line with the current global trend of adopting AI tools to enhance their education. Our findings are in line with several studies conducted in different settings. For instance, a study conducted in the United Arab Emirates (UAE) found that 91% of university students had heard of Chat GPT and 85.4% had used it before the survey [46]. Another study conducted in the United States of America found that 98.2% of students were aware of AI while 71.5% were aware of ChatGPT [47]. In Africa, students reported high awareness of ChatGPT in Zambia and Nigeria [42, 48]. However, the data is significantly higher than in Jordan, where only 23.8% of the healthcare students had heard of ChatGPT in the year 2023 [37]. Recent studies have shown that most students are aware of ChatGPT due to the high use of improved technology currently [49, 50]. The use of ChatGPT among students has been reported in other studies indicating the need to educate students on the usefulness and risks of using AI for academic purposes [46, 51–53]
The findings of the present study also revealed that 79% of the participants had positive attitudes toward ChatGPT’s impact on their educational progression. This aligns with the study that highlights AI’s potential to foster innovative and interactive learning [9]. Among the factors that contribute to the positive attitudes toward ChatGPT include low perceived risk and high social/technology influence [37]. The multivariate analysis confirmed that social and technological influences were the strongest predictors of positive attitudes toward ChatGPT (adjusted odds ratio of 2.908). This underscores the role of peer influence and the increasing importance of technological literacy in education. Only Technology/social influence was a statistically significant determinant of a positive attitude toward ChatGPT, suggesting that peer influence and technological exposure play a key role in shaping students’ acceptance of AI tools
>In this study, most students perceived ChatGPT to be very useful to their academic work. Our findings are in line with those reported in the United States of America where most students perceived ChatGPT to be very useful [54]. Additionally, the perceived usefulness of ChatGPT shapes students’ attitudes towards ChatGPT and accept its usefulness and benefits [54]. In China, the perceived usefulness of ChatGPT was found to increase the adoption and use of ChatGPT among students [55]
Despite the high usage and positive attitudes, a considerable number of students expressed anxiety and concerns about ChatGPT. About 82.7% of students reported high anxiety related to its use, and 77.1% expressed concerns about potential risks. This aligns with a study done by Sallam et al., where concerns about privacy, data security, and the risk of diminishing critical thinking skills are often cited. However, the findings of the current study suggests that education institutions need to address both the positive and negative attitudes towards ChatGPT by emphasizing the safe and effective use of AI tools while addressing concerns related to data privacy and academic integrity, similar to previous studies [4, 37]. In addition to that, the role of educators extends beyond merely introducing AI tools; it includes teaching students how to use these tools critically. Educators can use AI at each stage of teaching and learning to make informed decisions while leveraging the strengths of AI and integrating it into teaching and learning [48, 49, 56–58]. Institutions should ensure that students are equipped with the skills to discern when and how to use AI responsibly to foster independent thinking
We are aware of the limitations of this study. This study was conducted in one university which could affect the generalization of the findings to the rest of the universities offering pharmacy training in Zambia. However, our findings are very significant as they may provide a set of recommendations for educational institutions, policymakers, developers, and the student populace. To fully harness the potential of ChatGPT and similar AI tools in pharmacy education, Zambia must adopt a multi-stakeholder approach. Educators, curriculum developers, and policymakers must collaboratively promote AI literacy, address student concerns, and integrate responsible AI use into teaching and assessment. These efforts will not only align Zambia with global educational trends but also enhance the preparedness of future pharmacists to work effectively in an increasingly digital healthcare environment
Conclusions
The study results showed the widespread use of ChatGPT among pharmacy students in Zambia highlighting its increasing role as part of the educational process. To better implement this advanced generative AI tool in healthcare education, academics and universities must take into account the role of social influence and readiness to accept technology as well as emphasizing the role of usefulness to foster the educational process. Therefore, there is a need for universities offering pharmacy training in Zambia to integrate AI in their curricula in line with global dynamics in technology
Acknowledgements
n/a.
Abbreviations
- AI
Artificial Intelligence
- CHATGPT
Chat Generative Pre-Trained Transformer
- TAM
Technology Acceptance Model
Authors’ contributions
S.M, Conceptualization, data analysis, writing original draft, reviewing and Editing, and proof reading, W. M, R.S.M, & B.K: writing original draft, reviewing and Editing, and proof reading, AFL: writing original draft, proof reading and editing, final validation.
Data availability
Data material used in this study will be made available by the corresponding authors on request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Ratten V, Jones P. Generative artificial intelligence (ChatGPT): implications for management educators. Int J Manag Educ. 2023;21:100857. 10.1016/j.ijme.2023.100857. [Google Scholar]
- 2.Dowling M, Lucey B. ChatGPT for (Finance) research: the Bananarama conjecture. Financ Res Lett. 2023;53: 103662. 10.1016/j.frl.2023.103662. [Google Scholar]
- 3.Sallam M. ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. Healthcare. 2023;11: 887. 10.3390/healthcare11060887. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Al Kuwaiti A, Nazer K, Al-Reedy A, Al-Shehri S, Al-Muhanna A, Subbarayalu AV, et al. A review of the role of artificial intelligence in healthcare. J Pers Med. 2023;13: 951. 10.3390/jpm13060951. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Sallam M, Al-Farajat A, Egger J. Envisioning the future of ChatGPT in healthcare: insights and recommendations from a systematic identification of influential research and a call for papers. Jordan Med J. 2024;58(1):95–108. 10.35516/jmj.v58i1.2285. [Google Scholar]
- 6.Preiksaitis C, Rose C. Opportunities, challenges, and future directions of generative artificial intelligence in medical education: scoping review. JMIR Med Educ. 2023;9: e48785. 10.2196/48785. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Opesemowo OAG, Adekomaya V. Harnessing artificial intelligence for advancing sustainable development goals in South Africa’s higher education system: a qualitative study. Int J Learn Teach Educ Res. 2024;23(3):67–86. 10.26803/ijlter.23.3.4. [Google Scholar]
- 8.Sallam M, Salim NA, Barakat M, Al-Tammemi AB. ChatGPT applications in medical, dental, pharmacy, and public health education: a descriptive study highlighting the advantages and limitations. Narra J. 2023;3: e103. 10.52225/narra.v3i1.103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, et al. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ. 2023; 689. 10.1186/s12909-023-04698-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Coşkun Ö, Kıyak YS, Budakoğlu İİ. ChatGPT to generate clinical vignettes for teaching and multiple-choice questions for assessment: a randomized controlled experiment. Med Teach. 2024. 10.1080/0142159X.2024.2327477. [DOI] [PubMed] [Google Scholar]
- 11.Cheung BHH, Lau GKK, Wong GTC, Lee EYP, Kulkarni D, Seow CS, et al. ChatGPT versus human in generating medical graduate exam multiple choice questions-a multinational prospective study (Hong Kong S.A.R., Singapore, Ireland, and the United Kingdom). PLoS One. 2023;18: e0290691. 10.1371/JOURNAL.PONE.0290691. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Wu Y, Zheng Y, Feng B, Yang Y, Kang K, Zhao A. Embracing ChatGPT for medical education: exploring its impact on doctors and medical students. JMIR Med Educ. 2024;10: e52483. 10.2196/52483. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Al Shloul T, Mazhar T, Abbas Q, Iqbal M, Ghadi YY, Shahzad T, et al. Role of activity-based learning and ChatGPT on students’ performance in education. Comput Educ Artif Intell. 2024;6:100219. 10.1016/j.caeai.2024.100219. [Google Scholar]
- 14.Jaworski A, Jasiński D, Jaworski W, Hop A, Janek A, Sławińska B, et al. Comparison of the performance of artificial intelligence versus medical professionals in the Polish final medical examination. Cureus. 2024;16:e66011. 10.7759/cureus.66011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kamalov F, Santandreu Calonge D, Gurrib I. New era of artificial intelligence in education: towards a sustainable multifaceted revolution. Sustainability. 2023;15: 12451. 10.3390/su151612451. [Google Scholar]
- 16.Montenegro-Rueda M, Fernández-Cerero J, Fernández-Batanero JM, López-Meneses E. Impact of the implementation of ChatGPT in education: a systematic review. Computers. 2023;12: 153. 10.3390/computers12080153. [Google Scholar]
- 17.Opesemowo OAG. Artificial intelligence in mathematics education. Encyclopedia of information science and technology, sixth edition. IGI Global; 2024. pp. 1–18. 10.4018/978-1-6684-7366-5.ch084.
- 18.Anderson HD, Kwon S, Linnebur LA, Valdez CA, Linnebur SA. Pharmacy student use of chatgpt: a survey of students at a U.S. school of pharmacy. Curr Pharm Teach Learn. 2024;16: 102156. 10.1016/j.cptl.2024.102156. [DOI] [PubMed] [Google Scholar]
- 19.Mortlock R, Lucas C. Generative artificial intelligence (Gen-AI) in pharmacy education: utilization and implications for academic integrity: a scoping review. Explor Res Clin Soc Pharm. 2024;15: 100481. 10.1016/j.rcsop.2024.100481. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Batson C, Mara D. The pharmacy students’ guide to artificial Intelligence–AI. J Pediatr Pharmacol Ther. 2024;29:85–9. 10.5863/1551-6776-29.1.85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Chalasani SH, Syed J, Ramesh M, Patil V, Pramod Kumar TM. Artificial intelligence in the field of pharmacy practice: A literature review. Explor Res Clin Soc Pharm. 2023;12:100346. 10.1016/J.RCSOP.2023.100346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Qureshi R, Irfan M, Gondal TM, Khan S, Wu J, Hadi MU, et al. AI in drug discovery and its clinical relevance. Heliyon. 2023; e17575. 10.1016/j.heliyon.2023.e17575. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Sahu A, Mishra J, Kushwaha N. Artificial intelligence (AI) in drugs and pharmaceuticals. Comb Chem High Throughput Screen. 2021;25:1818–37. 10.2174/1386207325666211207153943. [DOI] [PubMed] [Google Scholar]
- 24.Shiammala PN, Duraimutharasan NKB, Vaseeharan B, Alothaim AS, Al-Malki ES, Snekaa B, et al. Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors. Methods. 2023;219:82–94. 10.1016/j.ymeth.2023.09.010. [DOI] [PubMed] [Google Scholar]
- 25.Stahl BC, Eke D. The ethics of ChatGPT – exploring the ethical issues of an emerging technology. Int J Inf Manage. 2024;74: 102700. 10.1016/j.ijinfomgt.2023.102700. [Google Scholar]
- 26.Abbas M, Jam FA, Khan TI. Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. Int J Educ Technol High Educ. 2024;21: 10. 10.1186/s41239-024-00444-7. [Google Scholar]
- 27.Yusuf A, Pervin N, Román-González M. Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. Int J Educ Technol High Educ. 2024;21: 21. 10.1186/s41239-024-00453-6. [Google Scholar]
- 28.Al-Zahrani AM. Unveiling the shadows: beyond the hype of AI in education. Heliyon. 2024;10: e30696. 10.1016/j.heliyon.2024.e30696. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Khlaif ZN, Mousa A, Hattab MK, Itmazi J, Hassan AA, Sanmugam M, et al. The potential and concerns of using AI in scientific research: ChatGPT performance evaluation. JMIR Med Educ. 2023;9: e47049. 10.2196/47049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Kurtz G, Amzalag M, Shaked N, Zaguri Y, Kohen-Vacs D, Gal E, et al. Strategies for integrating generative AI into higher education: navigating challenges and leveraging opportunities. Educ Sci. 2024;14: 503. 10.3390/educsci14050503. [Google Scholar]
- 31.Wang S, Wang F, Zhu Z, Wang J, Tran T, Du Z. Artificial intelligence in education: a systematic literature review. Expert Syst Appl. 2024;252: 124167. 10.1016/j.eswa.2024.124167. [Google Scholar]
- 32.Nguyen KV. The use of generative AI tools in higher education: ethical and pedagogical principles. J Acad Ethics. 2025;1–21. 10.1007/s10805-025-09607-1.
- 33.Aziz MHA, Rowe C, Southwood R, Nogid A, Berman S, Gustafson K. A scoping review of artificial intelligence within pharmacy education. Am J Pharm Educ. 2024;88: 100615. 10.1016/j.ajpe.2023.100615. [DOI] [PubMed] [Google Scholar]
- 34.Amigud A, Pell DJ. Responsible and ethical use of AI in education: are we forcing a square peg into a round hole?? World. 2025;6: 81. 10.3390/WORLD6020081. [Google Scholar]
- 35.Ibrahim H, Liu F, Asim R, Battu B, Benabderrahmane S, Alhafni B, et al. Perception, performance, and detectability of conversational artificial intelligence across 32 university courses. Sci Rep. 2023;13: 12187. 10.1038/s41598-023-38964-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Abdaljaleel M, Barakat M, Alsanafi M, Salim NA, Abazid H, Malaeb D, et al. A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Sci Rep. 2024;14: 1983. 10.1038/s41598-024-52549-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Sallam M, Salim NA, Barakat M, Al-Mahzoum K, Al-Tammemi AB, Malaeb D, et al. Assessing health students’ attitudes and usage of ChatGPT in jordan: validation study. JMIR Med Educ. 2023;9: e48254. 10.2196/48254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Mosleh R, Jarrar Q, Jarrar Y, Tazkarji M, Hawash M. Medicine and pharmacy students’ knowledge, attitudes, and practice regarding artificial intelligence programs: Jordan and West bank of Palestine. Adv Med Educ Pract. 2023;14:1391–400. 10.2147/AMEP.S433255. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Mudenda S, Chisha P, Chabalenge B, Daka V, Mfune RL, Kasanga M, et al. Antimicrobial stewardship: knowledge, attitudes and practices regarding antimicrobial use and resistance among non-healthcare students at the university of Zambia. JAC-Antimicrobial Resist. 2023;5:dlad116. 10.1093/JACAMR/DLAD116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Kalungia AC, Tyson Muungo L, Marshall S, Apampa B, May C, Munkombwe D. Training of pharmacists in Zambia: Developments, curriculum structure and future perspectives. Pharm Educ. 2019;19: 69–78. Available: https://pharmacyeducation.fip.org/pharmacyeducation/article/view/638/711
- 41.Mudenda S. Barriers to effective online learning among pharmacy students in Zambia: opportunities for pedagogical approach of blended learning. Creative Education. 2025;16:401–16. 10.4236/CE.2025.163025. [Google Scholar]
- 42.Mudenda S, Lubinda R, Kasanga M, Musakuzi Z, Mohamed S, Mufwambi W. Artificial intelligence: a knowledge, attitude, and practices survey among pharmacy students at the university of Zambia. Creat Educ. 2024;15:2582–96. 10.4236/CE.2024.1512157. [Google Scholar]
- 43.Mudenda S, Syansowa L, Mwaba M, Kasanga M, Mohamed S, Mufwambi W. Exploring medical students’ knowledge, attitudes, and practices on artificial intelligence: A study at the university of Zambia. Creat Educ. 2025;16:356–67. 10.4236/CE.2025.163022. [Google Scholar]
- 44.Joskow J, Yamane T. Statistics, an introductory analysis. J Am Stat Assoc. 1965;60:678. 10.2307/2282703. [Google Scholar]
- 45.Parikh PM, Talwar V, Goyal M. ChatGPT: an online cross-sectional descriptive survey comparing perceptions of healthcare workers to those of other professionals. Cancer Research, Statistics, and Treatment. 2023;6:32–6. 10.4103/crst.crst_40_23. [Google Scholar]
- 46.Sallam M, Elsayed W, Al-Shorbagy M, Barakat M, Khatib S, El, Ghach W, et al. ChatGPT usage and attitudes are driven by perceptions of usefulness, ease of use, risks, and Psycho-Social impact: A study among university students in the UAE. Front Educ. 2024;9:1414758. 10.3389/FEDUC.2024.1414758. [Google Scholar]
- 47.Delello J, Mokhtari K, De Giuseppe T, Delello JA, Sung W. Exploring college students’ awareness of AI and chatgpt: unveiling perceived benefits and risks. J Incl Methodol Technol Learn Teach. 2023. 10.32043/JIMTLT.V3I4.132. [Google Scholar]
- 48.Orok E, Okaramee C, Egboro B, Egbochukwu E, Bello K, Etukudo S, et al. Pharmacy students’ perception and knowledge of chat-based artificial intelligence tools at a Nigerian university. BMC Med Educ. 2024;24: 1237. 10.1186/s12909-024-06255-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Ali O, Murray PA, Momin M, Dwivedi YK, Malik T. The effects of artificial intelligence applications in educational settings: challenges and strategies. Technol Forecast Soc Change. 2024;199: 123076. 10.1016/j.techfore.2023.123076. [Google Scholar]
- 50.Hasan HE, Jaber D, Tabbah S, Al, Lawand N, Habib HA, Farahat NM. Knowledge, attitude and practice among pharmacy students and faculty members towards artificial intelligence in pharmacy practice: A multinational cross-sectional study. PLoS ONE. 2024;19:e0296884. 10.1371/journal.pone.0296884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.George Pallivathukal R, Kyaw Soe HH, Donald PM, Samson RS, Hj Ismail AR. ChatGPT for academic purposes: survey among undergraduate healthcare students in Malaysia. Cureus. 2024;16:e53032. 10.7759/cureus.53032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Strzelecki A. Students’ acceptance of ChatGPT in higher education: an extended unified theory of acceptance and use of technology. Innov High Educ. 2024;49:223–45. 10.1007/s10755-023-09686-1. [Google Scholar]
- 53.de Winter J, Dodou D, Eisma YB. Personality and acceptance as predictors of ChatGPT use. Discov Psychol. 2024;4: 57. 10.1007/s44202-024-00161-2. [Google Scholar]
- 54.Albayati H. Investigating undergraduate students’ perceptions and awareness of using ChatGPT as a regular assistance tool: a user acceptance perspective study. Comput Educ Artif Intell. 2024;6: 100203. 10.1016/j.caeai.2024.100203. [Google Scholar]
- 55.Shahzad MF, Xu S, Javed I. ChatGPT awareness, acceptance, and adoption in higher education: the role of trust as a cornerstone. Int J Educ Technol High Educ. 2024;21: 46. 10.1186/S41239-024-00478-X. [Google Scholar]
- 56.Mai DTT, Da C, Van, Hanh N, Van. The use of ChatGPT in teaching and learning: a systematic review through SWOT analysis approach. Front Educ. 2024;9:1328769. 10.3389/feduc.2024.1328769. [Google Scholar]
- 57.Zhang X, Tsang CCS, Ford DD, Wang J. Student pharmacists’ perceptions of artificial intelligence and machine learning in pharmacy practice and pharmacy education. Am J Pharm Educ. 2024;88: 101309. 10.1016/j.ajpe.2024.101309. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Busch F, Hoffmann L, Truhn D, Palaian S, Alomar M, Shpati K, et al. International pharmacy students’ perceptions towards artificial intelligence in medicine—a multinational, multicentre cross-sectional study. Br J Clin Pharmacol. 2024;90:649–61. 10.1111/bcp.15911. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data material used in this study will be made available by the corresponding authors on request.