Knowledge and actual use of AI-based tools in female and male
| Male (%) | Female (%) | χ2(2) | P-value | ||
|---|---|---|---|---|---|
| Familiar with AI and GenAI-based tools | Minimally | 95 ((40 | 241 (54) | 25.11 | <0.0001 |
| Moderately | 78 ((33 | 148 ((33 | |||
| Highly | 64 (27) | 58 ((13 | |||
| Total | 237 (100) | 447 (100) | |||
| Actual use of AI and GenAI for teaching/research purposes | Used | 105 (46) | 191 (44) | 5.41 | 0.0669 |
| Have not used but intend to use | 81 (35) | 186 (43) | |||
| Have not used and do not intend to use | 45 (20) | 60 (14) | |||
| Total | 231 (100) | 437 (100) | |||
Knowledge and actual use of AI and GenAI-based tools in lecturers and students
| Lecturers (%) | Students (%) | χ2(2) | P-value | ||
|---|---|---|---|---|---|
| AI and GenAI studies should be integrated into academic staff | Minimally agree | 6 (3) | 33 (7) | 25.11 | <0.0001 |
| Moderately agree | 39 (20) | 153 (33) | |||
| Highly agree | 152 (77) | 279 (60) | |||
| Total | 197 (100) | 465 (100) | |||
| Actual use of AI and GenAI for teaching/research purposes | Used | 109 (56) | 178 (39) | 18.29 | <0.0001 |
| Have not used but intend to use | 66 (34) | 191 (42) | |||
| Have not used and do not intend to use | 20 (10) | 85 (19) | |||
| Total | 195 (100) | 454 (100) | |||
Sociodemographic characteristics of the participants
| Variable | Sub-variable | Frequency (%) |
|---|---|---|
| Gender | Male | 238 (35) |
| Female | 448 (65) | |
| Total | 686 (100) | |
| Academic status | Student | 471 (69) |
| Lecturer | 197 (29) | |
| Other | 16 (2) | |
| Total | 684 (100) | |
| Faculty | Humanities | 89 (19) |
| Social sciences | 167 (36) | |
| Social welfare and health sciences | 94 (21) | |
| Engineering and exact sciences | 25 (5) | |
| Natural and environmental sciences | 29 (6) | |
| Law | 21 (5) | |
| Other or multidisciplinary | 34 (7) | |
| Total | 459 (100) |
Differences in the perception of the risks of AI in academies between lecturers and students
| Lecturers | Students | χ2(1) | P-value | ||
|---|---|---|---|---|---|
| Bias in algorithms or data | Frequency (%) | 119 (62) | 244 (53) | 4.50 | 0.0339 |
| Compromising work efficiency | Frequency (%) | 12 (6) | 55 (12) | 4.75 | 0.0293 |
| Transparency issues in AI and GenAI processes | Frequency (%) | 123 (64) | 207 (45) | 19.02 | <0.0001 |
| A threat to existing academic | Frequency (%) | 19 (10) | 92 (20) | 8.68 | 0.0032 |
| positions | Total | 192* (100) | 461* (100) | ||
Differences in the perception of the benefits of AI and GenAI in teaching and research in academia between men and women and between lecturers and students
| Teaching | Male | Female | χ2(1) | P-value | |
| Decision support tool | Frequency (%) | 79 (35) | 98 (2) | 9.99 | 0.0016 |
| Total | 226 (100) | 424 (100) | |||
| Research | |||||
| Analysing written language using natural language models | Frequency (%) | 70 (31) | 103 (24) | 4.09 | 0.43 |
| Total | 227 (100) | 430 (100) | |||
| Lecturers | Students | χ2(1) | P-value | ||
| Teaching | |||||
| Improving student engagement and persistence | Frequency (%) | 58 (32) | 108 (24) | 3.92 | 0.0478 |
| Systematic tracking of learning process outcomes | Frequency (%) | 38 (21) | 216 (48) | 39.37 | <0.0001 |
| Using AI and GenAI as a consultant for lecturers | Frequency (%) | 86 (48) | 103 (23) | 38.5 | <0.0001 |
| Enhancing accessibility and inclusion | Frequency (%) | 36 (20) | 144 (32) | 9.48 | 0.0021 |
| Total | 180 (100) | 449 (100) | |||
| Research | |||||
| Assistance in literature writing | Frequency (%) | 108 (58) | 204 (45) | 7.66 | 0.0056 |
| Support in data analysis and interpretation | Frequency (%) | 84 (45) | 258 (57) | 8.35 | 0.0039 |
| Prediction models based on existing data to guide future research | Frequency (%) | 48 (26) | 245 (54) | 40.22 | <0.0001 |
| Connecting researchers from similar fields and promoting collaborations | Frequency (%) | 33 (18) | 149 (33) | 14.48 | 0.0001 |
| Total | 186 (100) | 453 (100) | |||