Claims

Students working with multi-view program visualizations spend nearly half their attention on the code view, with attention distribution varying by task topic

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · no dated study recorded · checked against its sources 2026-10-18 (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? Across topics, code drew a median 47% of gaze dwell time, memory 34%, and metaphor 9%, with memory engagement peaking in linked-list tasks (47% median) and metaphor in loop tasks (19% median). → gaze-dwell

Evidence

gaze-dwell

Naaz Sibia, Jessica Wen, Amber Richardson, Yashika Jain, Khushi Malik, Bogdan Simion, Carolina Nobre, Angela Zavaleta Bernuy, Andrew Petersen, and Michael Liut. 2026. Code as Anchor, Memory and Metaphor as Support: Learner Experiences with Multi-View Visualizations. ICER 2026 Vol. 1. https://doi.org/10.1145/3765964.3811662

q2 · i? · associational · r1

Descriptive webcam gaze analysis (WebGazer.js) of 19 undergraduates' dwell time across the three AOIs of the multi-representational tool during scope, while-loop, and linked-list tasks. The article reports "Memory engagement peaked in linked-list tasks (47% median)" and metaphor peaked in loop tasks. No effect size is printed for the overall distribution.

"Overall, Code drew a median 47% of attention, Memory 34%, and Metaphor 9%. This pattern was task-dependent: Memory engagement peaked in linked-list tasks (47% median), while Metaphor gained traction in loop tasks (19% median)."

Discussion

Learner Variables

Page metadata
Field Value
type claim
id gaze-anchored-in-code-despite-multi-view-scaffolds
title Students working with multi-view program visualizations spend nearly half their attention on the code view, with attention distribution varying by task topic
description Students working with multi-view program visualizations spend nearly half their attention on the code view, with attention distribution varying by task topic
status review
evidence_strength moderate
source_checked 2026-10-18
generated by process:wiki-ingest on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 1 — gaze-dwell

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