Teaching testing seriously in academia

1969-09-01 · Source: cs.SE updates on arXiv.org · Field: Education & Learning — Academic Research & Higher Education, Skill Development & Professional Training · Depth: Advanced, extended

Summary

A position paper argues that academic testing education is misaligned with professional practice and the empirical nature of testing, particularly as systems grow more complex and incorporate AI. It proposes P4TEST, a pedagogical framework, and an instructional design based on the Four-Component Instructional Design (4C/ID) model to teach testing as an empirical, inquiry-driven professional skill. P4TEST makes explicit core competencies, epistemic moves, and habits of mind, guiding curriculum design, scaffolding, and assessment. The framework outlines four task classes (TC1-TC4) of increasing complexity and decreasing scaffolding, from analyzing worked examples to authentic testing, and suggests puzzle-based learning and video-based assessment for cultivating critical thinking and evaluating whole-task performance.

Key takeaway

For academic educators designing software testing curricula, you should move beyond traditional rationalist approaches. Implement the P4TEST framework and 4C/ID model to teach testing as an empirical, inquiry-driven skill. Focus on whole-task learning, gradually increasing task complexity and reducing scaffolding. Incorporate puzzle-based activities and video-based assessment to cultivate critical thinking and evaluate authentic testing performance, preparing students for real-world AI-powered systems.

Key insights

Testing education should shift from a rationalist to an empirical, inquiry-driven paradigm to foster critical reasoning.

Principles

• Testing is an empirical, inquiry-driven professional skill.
• Effective teaching of complex skills requires scaffolding.
• Cultivate specific "habits of mind" for critical testing.

Method

P4TEST, based on 4C/ID, guides curriculum design through four task classes (TC1-TC4) of increasing complexity and decreasing scaffolding, integrating whole-task learning and supportive information.

In practice

• Use puzzle-based learning to foster critical thinking.
• Implement video-based assessment for whole-task performance.
• Design curricula with increasing task complexity.

Topics

• Software Testing Education
• P4TEST Framework
• 4C/ID Model
• Empirical Testing
• AI Systems Testing
• Pedagogical Scaffolding
• Video-based Assessment

Best for: AI Scientist, Research Scientist, Domain Expert

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.SE updates on arXiv.org.