Table 1.
Scales’ characteristics
| basic scale description | validation samplea | factor structure | |||||
|---|---|---|---|---|---|---|---|
| scale | type | items | target population | N | Age (years) | no. of factors | factor description |
| AI literacy test32 | performance-based | 31 including 30 multiple-choice items with 4 options each and 1 sorting item | university students | 1286 | 23.6 ± 4.5 | 1 | single factor |
| AI-CI33 | performance-based | 20 multiple-choice items | middle school students | 981, 108 | ? | 1 | single factor |
| AILQ35 | self-report | 32 5-point Likert items | secondary school students | 363 | 13.1 ± 1.4 | 6 level one factors, 4 level two factors | (F1) affective learning: (F1a) Intrinsic motivation (F1b) confidence (F2) behavioural learning: (F2a) behavioural commitment (F2b) collaboration (F3) cognitive learning: (F3a) know and understand (F3b) evaluate and create (F4) ethical learning |
| AILS36,46,47 | self-report | 12 7-point Likert items | general population | 325, 402, 536 | 29.7 ± 7.3, ?, ? | 4 | (F1) awareness (F2) use (F3) evaluation (F4) ethics |
| AISES31 | self-report | 22 7-point Likert items | general population | 314 | ? | 4 | (F1) assistance (F2) anthropomorphic interaction (F3) comfort with AI (F4) technological skills |
| Chan & Zhou’s EVT based instrument (knwl. of gen. AI subscale)37 | self-report | 5 5-point Likert items | university students | 405 | 29.9 ± ? | 1 | single factor |
| ChatGPT literacy scale38 | self-report | 25 5-point Likert items | college students | 822 | 22.7 ± 2.6 | 5 | (F1) technical proficiency (F2) critical evaluation (F3) communication proficiency (F4) creative application (F5) ethical competence |
| GSE-6AI30 | self-report | 6 4-point Likert items | medical students | 469 | 19.7 ± 2.5 | 1 | single factor |
| Hwang et al.’s instrument39 | self-report | 19 5-point Likert items | college students | 318 | ? | 4 | (F1) critical understanding (F2) artificial intelligence social impact recognition (F3) artificial intelligence technology utilization (F4) ethical behaviour |
| Intelligent TPACK40 | self-report | 29 7-point Likert items | teachers | 647 | ? | 5 | (F1) technological knowledge (F2) technological pedagogical knowledge (F3) technological content knowledge (F4) technological pedagogical content knowledge (F5) ethics |
| Kim & Lee’s instrument41 | self-report | 30 5-point Likert items | middle school students | 1222 | ? | 6 | (F1) societal impact (F2) understanding of AI (F3) AI execution plans (F4) problem solving with AI (F5) data literacy (F6) AI ethics |
| MAILS42 | self-report | 34 11-point Likert items | adults | 300 | 32.1 ± 11.7 | 8 level one factors, 4 level two factors | (F1) AI literacy: (F1a) use & apply AI (F1b) understand AI (F1c) detect AI (F1d) AI ethics (F2) create AI (F3) AI self-efficacy: (F3a) AI problem solving (F3b) AI learning (F4) AI self-competency: (F4a) AI persuasion literacy (F4b) AI emotion regulation |
| MAIRS-MC43,48 | self-report | 22 5-point Likert items | medical students | 865, 502 | 21.3 ± 2.0, 22.7 ± 2.8 | 4 | (F1) cognition (F2) ability (F3) vision (4) ethics |
| Pinski & Belian’s instrument44 | self-report | 13 7-point Likert items | general population | 50 | 32.8 ± 13.2 | 5 | (F1) AI technology knowledge (F2) human actors in AI knowledge (F3) AI steps knowledge (F4) AI usage experience (F5) AI design experience |
| SAIL4ALL34 | performance-based | 56 true/false or 5-point Likert items | general population | 619 for true/false version, 393 for Likert scale version | 45.8 ± 12.2 for true/false version, 46.3 ± 15.4 for Likert scale version | 4 themes (subscales) – each with 1–2 factors | (T1) what is AI? (T2) what can AI do? (T3) how does AI work? (T4) how should AI be used? |
| SNAIL45,49–51 | self-report | 31 7-point Likert items | adult non-experts, university students, medical students | 415, 25, 653, 377 | 39.5 ± 13.6, 22.9 ± 2.3, 25.6 ± ?, 22.5 ± 3.2 | 3 | (F1) technical understanding (F2) critical appraisal (F3) practical application |
ain case the scale has been revalidated, the numbers refer to the original sample followed by the revalidation samples. N = number of participants used for scale development. ? = not reported.