4-act progressive-disclosure case structure aligned with occupational poisoning workflow¶

Design · All designs
Evidence · 2 claims (2 for) · 1 study (1 causal), q2 · 1 of 1 report an effect size · 2 claims rest on one study

Description¶

A scripted 4-act CBL model that progressively releases key information with teacher-verified distractor cues. Act 1 focuses on problem framing and initial hypothesis generation; Act 2 on occupational history elicitation and laboratory cues; Act 3 on field investigation and exposure attribution; Act 4 on management and prevention decision-making.

Design Implications¶

Context¶

Requirements¶

Each act provides only the minimum information required for the current task, retaining other cues as to be elicited or verified

Constraints¶

The intervention's scope is bounded by exploratory reasoning and should not be regarded as a general clinical-reasoning enhancer

Target Learners¶

undergraduate medical students

Learning Goals¶

clinical reasoning, exposure assessment, and epidemiologic thinking in occupational medicine

Claims¶

Examples¶

-

Key Sources¶

Waseem J, Ritter Nicola L, McMordie J, Su P, Hu M, Chen C, Xu S. (2026). Generative AI–Assisted Progressive-Disclosure Case-Based Learning for Clinical Reasoning in Occupational Medicine: Quasi-Experimental Study. JMIR Medical Education. https://doi.org/10.2196/103584

Page metadata

Field	Value
`type`	`design`
`id`	`four-act-progressive-disclosure-cbl`
`title`	`4-act progressive-disclosure case structure aligned with occupational poisoning workflow`
`description`	`A scripted 4-act CBL model that progressively releases key information with teacher-verified distractor cues.`
`status`	`review`
`generated`	by `process:settle-candidates` on `2026-11-04`
`trust`	unverified — no one has confirmed this page's content
`sources`	1 — `waseem-j-2026`

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