Table 1
General features of educators who participated in the study (N = 236).
| VARIABLE | CATEGORY | COUNT | PERCENTAGE |
|---|---|---|---|
| Age | ≤43 years | 119 | 50.4% |
| >43 years | 117 | 49.6% | |
| Sex | Male | 137 | 58.1% |
| Female | 99 | 41.9% | |
| Nationality | Jordanian | 232 | 98.3% |
| Non-Jordanian | 4 | 1.7% | |
| School | Health | 127 | 53.8% |
| Scientific | 51 | 21.6% | |
| Humanities | 58 | 24.6% | |
| University | Public | 150 | 63.6% |
| Private | 86 | 36.4% | |
| Highest educational degree | PhD | 181 | 76.7% |
| MSc | 55 | 23.3% | |
| Country of highest attained degree | U.S. | 37 | 15.7% |
| U.K. | 54 | 22.9% | |
| Europe | 29 | 12.3% | |
| Jordan | 79 | 33.5% | |
| Arab country other than Jordan | 16 | 6.8% | |
| Others | 12 | 5.1% | |
| Australia | 4 | 1.7% | |
| Canada | 5 | 2.1% | |
| Country of highest attained degree | Non-Arab | 141 | 59.7% |
| Arab | 95 | 40.3% | |
| Rank | Professor | 55 | 23.3% |
| Associate Professor | 52 | 22.0% | |
| Assistant Professor | 74 | 31.4% | |
| Lecturer | 36 | 15.3% | |
| Teaching assistant | 19 | 8.1% | |
| Academic rank | With tenure | 107 | 45.3% |
| Without tenure | 129 | 54.7% | |
| Have you heard of ChatGPT before the study? | Yes | 169 | 71.6% |
| No | 67 | 28.4% | |
| Have you used ChatGPT before the study?1 | Yes | 76 | 45.0% |
| No | 93 | 55.0% |
[i] 1 Among those who heard of ChatGPT.
Figure 1
Scree plot representing the eigenvalues of the factors identified through principal component analysis. The red line indicated the eigenvalue cutoff specified at 1.50.
Figure 2
The final Ed-TAME-ChatGPT items and constructs.
Table 2
Demographic, academic, and Ed-TAME-ChatGPT constructs’ association with the overall Ed-TAME-ChatGPT scores.
| CATEGORY | VARIABLE | TAME CATEGORIES | p VALUE, χ2 | |
|---|---|---|---|---|
| NEUTRAL | POSITIVE | |||
| COUNT (%) | COUNT (%) | |||
| Age | ≤43 years | 31 (63.3) | 18 (36.7) | 0.767, 0.088 |
| >43 years | 18 (66.7) | 9 (33.3) | ||
| Sex | Male | 27 (64.3) | 15 (35.7) | 0.970, 0.001 |
| Female | 22 (64.7) | 12 (35.3) | ||
| Nationality | Jordanian | 49 (66.2) | 25 (33.8) | 0.054, 3.728 |
| Non-Jordanian | 0 (0) | 2 (100) | ||
| School | Health | 30 (65.2) | 16 (34.8) | 0.551, 1.192 |
| Scientific | 14 (70.0) | 6 (30.0) | ||
| Humanities | 5 (50.0) | 5 (50.0) | ||
| University | Public | 32 (69.6) | 14 (30.4) | 0.251, 1.319 |
| Private | 17 (56.7) | 13 (43.3) | ||
| Education | PhD | 38 (67.9) | 18 (32.1) | 0.302, 1.064 |
| MSc | 11 (55.0) | 9 (45.0) | ||
| Country of highest attained degree | Non-Arab | 31 (67.4) | 15 (32.6) | 0.510, 0.433 |
| Arab | 18 (60.0) | 12 (40.0) | ||
| Academic rank | With tenure | 26 (61.9) | 16 (38.1) | 0.603, 0.270 |
| Without tenure | 23 (67.6) | 11 (32.4) | ||
| Perceived usefulness categories | Negative | 4 (100) | 0 (0) | <0.001, 21.776 |
| Neutral | 22 (100) | 0 (0) | ||
| Positive | 23 (46.0) | 27 (54.0) | ||
| Effectiveness categories | Negative | 4 (100) | 0 (0) | <0.001, 21.091 |
| Neutral | 24 (96.0) | 1 (4.0) | ||
| Positive | 21 (44.7) | 26 (55.3) | ||
| Social influence categories | Negative | 6 (100) | 0 (0) | <0.001, 22.659 |
| Neutral | 29 (87.9) | 4 (12.1) | ||
| Positive | 14 (37.8) | 23 (62.2) | ||
| Perceived risk categories | Positive | 6 (33.3) | 12 (66.7) | <0.001, 15.786 |
| Neutral | 24 (63.2) | 14 (36.8) | ||
| Negative | 19 (95.0) | 1 (5.0) | ||
| Technology readiness categories | Negative | 1 (100) | 0 (0) | 0.048, 6.060 |
| Neutral | 12 (92.3) | 1 (7.7) | ||
| Positive | 36 (58.1) | 26 (41.9) | ||
| Anxiety categories | Positive | 8 (44.4) | 10 (55.6) | 0.007, 9.894 |
| Neutral | 25 (61.0) | 16 (39.0) | ||
| Negative | 16 (94.1) | 1 (5.9) | ||
Table 3
Regression analysis of the predictors influencing ChatGPT usage.
| MODEL | COEFFICIENTS1 | p VALUE | VIF3 | |||
|---|---|---|---|---|---|---|
| ADJUSTED R2 = 0.555, SE = 0.322 | UNSTANDARDIZED COEFFICIENTS | SE2 | STANDARDIZED COEFFICIENTS | T STATISTIC | ||
| ANOVA F STATISTIC = 14.343, p VALUE < 0.001 | B | BETA | ||||
| Constant | 0.787 | 0.392 | 2.009 | 0.049 | ||
| Nationality | 0.413 | 0.236 | 0.138 | 1.753 | 0.084 | 1.047 |
| Perceived usefulness categories | 0.162 | 0.073 | 0.198 | 2.218 | 0.030 | 1.343 |
| Effectiveness categories | 0.194 | 0.074 | 0.240 | 2.621 | 0.011 | 1.414 |
| Social influence categories | 0.197 | 0.067 | 0.260 | 2.947 | 0.004 | 1.307 |
| Perceived risk categories | –0.216 | 0.057 | –0.320 | –3.817 | <.001 | 1.180 |
| Technology readiness categories | 0.120 | 0.100 | 0.108 | 1.195 | 0.236 | 1.367 |
| Anxiety categories | –0.073 | 0.062 | –0.104 | –1.172 | 0.245 | 1.322 |
[i] 1Dependent Variable: Overall Ed-TAME-ChatGPT usage score; 2SE: Standard error; 3VIF: Variance inflation factor. Statistically significant P values are highlighted in bold style.