Personalized and transparent automated guidance improved science learning mainly for low-prior-knowledge students, and two specific guidance types yielded similar gains¶
Claim · All claims
Evidence · 1 study (2 entries) · causalr?·q2
Currency · newest study 2017 · 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? In the first of two studies, students demonstrated better learning when automated guidance was personalized and transparent, with the effect significant only at a school with more low-prior-knowledge students. → Passonneau 2017
q2 i? In the second study, two kinds of specific guidance — revisiting ideas versus prompting revision planning — produced similar learning gains. → Passonneau 2017 (2)
Evidence¶
Passonneau 2017¶
Passonneau, R. J., McNamara, D., Muresan, S., & Perin, D. (2017). Preface: Special Issue on Multidisciplinary Approaches to AI and Education for Reading and Writing. Int J Artif Intell Educ. https://doi.org/10.1007/s40593-017-0158-8
q2 · i? · causal · r?
The editors report, citing Tansomboon et al., a study of adaptive guidance for short answers in a web-based science inquiry curriculum; "The effect was significant, but only for a school that comprised more students with low prior knowledge". No effect size is printed.
"The first of two studies found that students demonstrated better learning if automated guidance was personalized (e.g., with use of students' names) and transparent (i.e., students were provided age-appropriate explanations of how the computer selected feedback statements)."
Passonneau 2017 (2)¶
Passonneau, R. J., McNamara, D., Muresan, S., & Perin, D. (2017). Preface: Special Issue on Multidisciplinary Approaches to AI and Education for Reading and Writing. Int J Artif Intell Educ. https://doi.org/10.1007/s40593-017-0158-8
q2 · i? · causal · r?
The editors report the second Tansomboon et al. study comparing revisit-ideas guidance with revision-planning prompts; "found similar learning gains". No effect size is printed.
"The second study compared two kinds of specific guidance, asking students to revisit the ideas and prompting them on ways to plan a revision, and found similar learning gains."
Discussion¶
Related Claims¶
- The ten special-issue papers collectively indicate near-term feasibility of automated guidance and feedback on reading and writing skills — a broader claim this one bears on
- Instructional guidance that helps novices can become redundant or counterproductive as expertise grows. — a broader claim this one bears on
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
personalized-transparent-automated-guidance-science-learning |
title |
Personalized and transparent automated guidance improved science learning mainly for low-prior-knowledge students, and two specific guidance types yielded similar gains |
description |
Personalized and transparent automated guidance improved science learning mainly for low-prior-knowledge students, and two specific guidance types yielded similar gains |
status |
review |
evidence_strength |
weak |
newest_evidence |
2017 |
generated |
by process:wiki-ingest on 2026-10-27 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — passonneau-2017, passonneau-2017-2 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.