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A table of nine pedagogical activities for teaching interpretability, each paired with an assessment method

Design · All designs
Evidence · no claims cited

Description

Table 1 of the article lays out pedagogically-sound activities mapping learning-science best practices to RDS interpretability practice, including replicating an existing study, reverse engineering a platform, diagnostic learning logs, problem recognition tasks, process analysis, peer review, before-after iteration, design and deploy, and creating a nutritional label for a machine learning platform. "Table 1 showcases several pedagogically-sound activities that map to best practices in the learning sciences and to RDS interpretability practices." Each activity is paired with an assessment method such as metrics evaluation, open coding, cognitive walkthroughs, or A/B testing.

Design Implications

Context

Requirements

  • Activities should be offered through multiple presentation modes and levels of interactivity to maximize engagement and promote heuristics development.

Constraints

  • The authors state that future iterations of the course will tie in further pedagogical principles.

Target Learners

  • diverse groups of students with varying technical and theoretical prior knowledge, from varied disciplinary backgrounds, and with different learning goals

Learning Goals

  • interpretability of data and models
  • transitioning from novice to expert level knowledge

Claims

  • Nutritional Label Ads Course Project [+M]

Examples

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Key Sources

  • Lewis Armanda; Stoyanovich Julia. (2021). Teaching Responsible Data Science: Charting New Pedagogical Territory. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-021-00241-7
Page metadata
Field Value
type design
id interpretability-pedagogical-activities-table1
title A table of nine pedagogical activities for teaching interpretability, each paired with an assessment method
description Table 1 of the article lays out pedagogically-sound activities mapping learning-science best practices to RDS interpretability practice, including replicating an existing study, reverse engineering a platform, diagnos...
status review
generated by process:settle-candidates on 2026-10-27
trust unverified — no one has confirmed this page's content
sources 1 — lewis-armanda-stoyanovich-julia-2021

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