Students with higher baseline relatedness satisfaction perceive less additional relatedness support from AI chatbot use¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · 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? Baseline relatedness satisfaction negatively predicts perceived relatedness satisfaction after AI chatbot use (β = −.259). → Kevin Zhongyang Shao 2026
Evidence¶
Kevin Zhongyang Shao 2026¶
Kevin Zhongyang Shao, Denise Wilson, Yale Quan, Sep Makhsous. (2026). Designing Needs- and Attention-Aware AI Learning Tools for Engineering Education: Insights from Psychological Outcomes. arXiv. https://arxiv.org/abs/2607.26338 doi:10.48550/arxiv.2607.26338
q2 · i? · associational · r2
SEM result from the 206-student survey. "Higher baseline relatedness was negatively associated with perceived relatedness satisfaction after AI chatbot use (β=−. 259,p=. 014)"; the authors describe a relatedness-specific diminishing-returns pattern.
"Higher baseline relatedness was negatively associated with perceived relatedness satisfaction after AI chatbot use ( 𝛽=−. 259,𝑝=. 014), suggesting that students who initially reported stronger relatedness needs satisfaction perceived less additional relatedness support from AI chatbot use."
Discussion¶
Learner Variables¶
- Belonging — predictor: learners who differ on it differ in outcomes
Related Claims¶
- Engineering students perceive AI chatbot benefits as strongest for relief from competence frustration, moderate for autonomy, and weakest for relatedness — related
- Higher baseline autonomy and higher baseline competence frustration predict greater perceived relief from competence frustration after AI chatbot use, while higher baseline personal agency predicts less — related
- Inattention moderates how baseline competence frustration and baseline autonomy translate into perceived AI benefits, weakening both positive associations — related
- Baseline motivational states shape perceived AI benefits more than demographics, with female-coded gender the only significant demographic effect (lower perceived competence relief) — related
- School-side support (teacher, instructional, and institutional provision) is associated with learners' motivation, engagement, and need satisfaction — related
- Chatbot support systems in online learning are associated with higher learner satisfaction and engagement when perceived as useful — related
- In agentic AI-supported online learning, perceived autonomy, competence, and relatedness are each positively associated with learning motivation — related
- Competence is the strongest independent psychological predictor of AI literacy performance, followed by autonomy; relatedness has no significant independent effect — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
baseline-relatedness-diminishes-perceived-ai-relatedness |
title |
Students with higher baseline relatedness satisfaction perceive less additional relatedness support from AI chatbot use |
description |
Students with higher baseline relatedness satisfaction perceive less additional relatedness support from AI chatbot use |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — kevin-zhongyang-shao-2026 |
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