In-service science educators use AI far less in subject-specific DiKoLAN areas (SIM, DAP, DAQ) than in general areas¶
Claim · All claims
Evidence · 1 study · associationalr2·q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? AI use averaged 15 mentions in the subject-specific areas (SIM, DAP, DAQ) versus 28.8 mentions in the general areas (COM, PRE, ISE, DOC, AFA). → Nikolai Maurer 2026
Evidence¶
Nikolai Maurer 2026¶
Nikolai Maurer, Mathea Brückner, Christoph Thyssen, Sebastian Becker-Genschow, Johannes Huwer. (2026). Science educators' AI literacy and AI usage in teaching: Implications for post-qualification programs. Computers and Education Open 10. https://doi.org/10.1016/j.caeo.2026.100376
q3 · i? · associational · r2
Survey of subject-level AI use across the DiKoLAN areas (nsubject = 115 data sets), distinguishing classroom use from lesson preparation and follow-up. The printed means show "M = 15 mentions" for subject-specific versus "M = 28.8 mentions" for general areas; ISE was most used and DAQ least.
"Overall, AI is used much less frequently on average in the more subject-specific areas (SIM, DAP, DAQ; M = 15 mentions) than in the more general areas (COM, PRE, ISE, DOC, AFA; M = 28.8 mentions)."
Discussion¶
Related Claims¶
- Educators use AI tools mainly for personalized learning and language support and frequently use generative AI for lesson planning — related
- AI use is predominantly independent of the science subject taught, with one exception: chemistry teachers most often cite lack of subject-specific relevance — related
- The most common purpose of AI in instructional design is enhancing or assisting the design process itself (22 of 28 studies, 78.5%) — related
- Perceived institutional AI regulation differs significantly across STEM subjects, with mathematics and natural sciences perceived as prohibitive and computer science as permissive — related
- Language learning was the most common subject domain for AIEd in higher education, at 17% — related
- Ghanaian pre-service science teachers use AI mainly for research and content delivery rather than assessment or student engagement — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
ai-use-skews-to-general-dikolan-areas |
title |
In-service science educators use AI far less in subject-specific DiKoLAN areas (SIM, DAP, DAQ) than in general areas |
description |
In-service science educators use AI far less in subject-specific DiKoLAN areas (SIM, DAP, DAQ) than in general areas |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
recheck_by |
2031 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — nikolai-maurer-2026 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.