Teachers authoring student-AI dialogue prompts predominantly write highly specific tasks targeting higher-order thinking (92% at DOK 2–3)¶
Claim · All claims
Evidence · 1 study (2 entries) · designr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
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.
q2 i? 80.9% of teacher-authored prompts provided detailed, concrete task descriptions rather than open-ended explorations. → Alex Liu 2026
q2 i? 92% of prompts targeted DOK 2–3, with 48.9% targeting DOK 3 strategic thinking and only 5.3% targeting DOK 1 recall. → Alex Liu 2026 (2)
Evidence¶
Alex Liu 2026¶
Alex Liu, Min Sun, Lief Esbenshade, Victor Tian, Zachary Zhang, and Kevin He. (2026). Teacher-Authored Prompts for Configuring StudentAI Dialogue: K12 Classroom Implementation. https://arxiv.org/abs/2604.16738 doi:10.48550/arxiv.2604.16738
q2 · i? · design · r2
Descriptive analysis of 94 teacher-authored prompts coded with LLM assistance and 100% human validation in the Spring 2025 pilot. The article reports "80.9% of prompts provided detailed, concrete task descriptions" against the three-level task specificity rubric.
"Teachers predominantly authored highly specific tasks. 80.9% of prompts provided detailed, concrete task descriptions, with only 16.0% using moderately specific prompts and a single prompt (1.1%) minimally specified."
Alex Liu 2026 (2)¶
Alex Liu, Min Sun, Lief Esbenshade, Victor Tian, Zachary Zhang, and Kevin He. (2026). Teacher-Authored Prompts for Configuring StudentAI Dialogue: K12 Classroom Implementation. https://arxiv.org/abs/2604.16738
q2 · i? · design · r2
DOK coding of the same 94 prompts under Webb's framework with full human validation. The article reports 48.9% at DOK 3, 42.6% at DOK 2, and 5.3% at DOK 1; a single prompt (1.1%) targeted DOK 4.
"Nearly half of prompts (48.9%) targeted DOK 3 (strategic thinking), requiring students to engage in reasoning, analysis, or problem-solving that goes beyond routine procedures. An additional 42.6% targeted DOK 2 (skills and concepts), while only 5.3% targeted DOK 1 (recall/reproduction)."
Discussion¶
Related Claims¶
- A design-enactment gap in cognitive demand: 37.7% of conversations under-reached the teacher-targeted DOK level, and under-targeting increased with target ambition — related
- In an OLS regression, explicit finish lines in teacher prompts were associated with smaller DOK gaps, while explain-reasoning epistemic framing was associated with larger gaps — related
- Student-AI conversations under teacher-authored prompts largely stay on the intended task (71% fully on-track; fewer than 1% substantially off-track) — related
- In teacher-AI learning task design studies, GenAI tools are predominantly used for lesson planning, prompt generation, and creative ideation, while traditional AI tools are commonly used for designing analytics and feedback — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
teachers-author-specific-higher-order-ai-prompts |
title |
Teachers authoring student-AI dialogue prompts predominantly write highly specific tasks targeting higher-order thinking (92% at DOK 2–3) |
description |
Teachers authoring student-AI dialogue prompts predominantly write highly specific tasks targeting higher-order thinking (92% at DOK 2–3) |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — alex-liu-2026, alex-liu-2026-2 |
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