Coding scheme for observable Direction, Integration, and Evaluation in student–AI interaction traces

Research Method · All research methods
Evidence · 1 claim (1 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

An exploratory multilabel coding scheme applied to student turns in AI-mediated conversations, with the student turn as coding unit interpreted in relation to its local sequence and the whole conversation. Direction is coded when "the learner exercises task-relevant control over the purpose, constraints, procedure, artifact, or trajectory of the activity"; Integration when a subsequent action connects to uptake, application, transformation, or reuse of a prior AI contribution; Evaluation when the learner participates in judging a contribution through inspection, comparison, testing, discrepancy detection, diagnosis, correction, or criterion-based judgment. Provenance is recorded separately for content, criteria, and judgments, and evidence is classified as explicit or conservatively inferable.

Accounts

• Coding scheme for observable Direction, Integration, and Evaluation in student–AI interaction traces: An exploratory multilabel coding scheme applied to student turns in AI-mediated conversations, with the student turn as coding unit interpreted in relation to its local sequence and the whole conversation. Direction is coded when "the learner exercises task-relevant control over the purpose, constraints, procedure, artifact, or trajectory of the activity"; Integration when a subsequent action connects to uptake, application, transformation, or reuse of a prior AI contribution; Evaluation when the learner participates in judging a contribution through inspection, comparison, testing, discrepancy detection, diagnosis, correction, or criterion-based judgment. Provenance is recorded separately for content, criteria, and judgments, and evidence is classified as explicit or conservatively inferable. (Jorge Fábrega (2026))

Claims

• Direction is observable in nearly all AI-mediated conversations, while Integration and Evaluation become progressively more observable as conversation length increases [+M]

Related Research Methods

-

Key Sources

• Jorge Fábrega. (2026). Same Performance, Different Process: Epistemic Ownership in AI-Mediated Education. Preprint. https://arxiv.org/abs/2610.02731

Page metadata

Field	Value
type	research-method
id	coding-scheme-for-observable-direction-integration-and-evaluation-in-studentai-interaction
title	Coding scheme for observable Direction, Integration, and Evaluation in student–AI interaction traces
description	An exploratory multilabel coding scheme applied to student turns in AI-mediated conversations, with the student turn as coding unit interpreted in relation to its local sequence and the whole conversation.
status	review
generated	by process:settle-candidates on 2026-10-10
trust	unverified — no one has confirmed this page's content

Frontmatter is the page's machine-readable record — see the Schema & Guide.