Adapted conjecture map framework for learning scientists and computer scientists¶
Research Method · All research methods
Evidence · 3 claims (3 for) · 1 study (1 qualitative),q1· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
An adaptation of Sandoval's conjecture mapping tool, created by Chang and Roschelle, that supports interdisciplinary design-based research teams in connecting learning theory to technical design. It distinguishes back-end technical decisions (e.g., training data for an AI model) from embodied front-end decisions users directly interact with, and it explicitly includes both beneficial and harmful consequences of technology as embodiments or mediating processes. In this report the framework structured a one-hour collaborative session in which the PECAS Mediator team filled out the map together on a Jamboard template.
Accounts¶
- Adapted conjecture map framework for learning scientists and computer scientists: An adaptation of Sandoval's conjecture mapping tool, created by Chang and Roschelle, that supports interdisciplinary design-based research teams in connecting learning theory to technical design. It distinguishes back-end technical decisions (e.g., training data for an AI model) from embodied front-end decisions users directly interact with, and it explicitly includes both beneficial and harmful consequences of technology as embodiments or mediating processes. In this report the framework structured a one-hour collaborative session in which the PECAS Mediator team filled out the map together on a Jamboard template. (Chang et al. (2022))
Claims¶
- First-time computer scientist users' contributions fit naturally into the adapted conjecture map format [+W]
- Collaborative conjecture map construction surfaced a tension between nuanced learning theory and limited technical capability [+W]
- The adapted conjecture map's framing around unintended consequences proved generative for interdisciplinary discussion [+W]
Related Research Methods¶
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Key Sources¶
- Chang, M.A., Magana, A., Benes, B., Kao, D., & Fusco, J. (2022). Driving interdisciplinary collaboration through adapted conjecture mapping: A case study with the PECAS Mediator [Project Report]. Digital Promise. https://doi.org/10.51388/20.500.12265/156
Page metadata
| Field | Value |
|---|---|
type |
research-method |
id |
adapted-conjecture-map-framework-for-learning-scientists-and-computer-scientists |
title |
Adapted conjecture map framework for learning scientists and computer scientists |
description |
An adaptation of Sandoval's conjecture mapping tool, created by Chang and Roschelle, that supports interdisciplinary design-based research teams in connecting learning theory to technical design. |
status |
review |
moved_from |
theory/adapted-conjecture-map-framework-ls-cs |
generated |
by process:sweep-kinds on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — chang-2022 |
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