Perceptual-Adaptive Learning Modules (PALMs): From Cognitive Science to Product PoC

Perceptual-Adaptive Learning Modules (PALMs) are web-based learning aid software based on Cognitive Science principles. They address crucial aspects of learning—such as pattern recognition—that traditional instruction methods have overlooked.

Metadata

• Target Audience: Medical students and residents
• Platform: Responsive Web App
• Team: Domain Experts x3, Project Manager x1, Engineer x3, Designer x1 👋
• Timeline: Initial development in 2014 with continuous optimization since and various iterations with different subjects

Objective

This was initially a pilot product to help the company pivot from K-12 math to medical education. The goal was to build our first medical module.

Problems

The core technology and development framework were there when I joined the team. But, many user-facing aspects of the product had issues (e.g., sub-optimal legibility, poor touch-screen usability, ambiguous progress indicators, lack of onboarding, dated visual language, content-related anomalies, discouraging user experience, etc.). Additionally, since the team had been iterating on the concepts for years, the framework had accumulated poor practices and outdated libraries, making solution implementation complicated.

My Role

As the first and only design hire, my role was to partner with our main domain expert—to materialize her vision—while working closely with the engineers to redesign the interfaces and address usability issues.

Example Contribution: Standardization

To streamline the development process for PALMs and improve the user experience for the learners, I introduced new components that include many visual and behind-the-scenes patterns.

Example Contribution: Enhanced Feedback Cues

To ensure the learning feedback cues are universally usable, understandable, and quick to parse.

Example Contribution: Progressive Disclosure

I revised the general flow and inserted new nodes to provide dedicated real estate for timely hand-holding and way-finding indicators. These inserts host static and dynamic messages that aid users build an accurate mental model of the journey.

Example Contribution: Messaging & Positioning

To communicate the technical behind-the-scenes aspects of the product, I co-scripted and created an explainer video, helping novice users understand PALMs.

Outcome

PALMs have helped many medical students, trainees, and professionals develop deep understanding and automaticity with complex subjects. The efficiency and effectiveness of PALMs in training recognition and interpretation of clinical tests and maintaining this training over many months has been demonstrated in published research and presentations at meetings targeting both clinical specialties and medical education.

References

1. Krasne S, Stevens CD, Kellman PJ, Niemann JT. Mastering Electrocardiogram Interpretation Skills Through a Perceptual and Adaptive Learning Module. AEM Educ Train. 2020;5(2):e10454. Published 2020 May 5. doi:10.1002/aet2.10454
2. Romito BT, Krasne S, Kellman PJ, Dhillon A. The impact of a perceptual and adaptive learning module on transoesophageal echocardiography interpretation by anesthesiology residents. Br J Anaesth. 2016;117(4):477-481. doi:10.1093/bja/aew295
3. Rimoin L, Altieri L, Craft N, Krasne S, Kellman PJ. Training pattern recognition of skin lesion morphology, configuration and distribution. Journal of the American Academy of Dermatology.
4. Krasne S, Hillman JD, Kellman PJ, Drake TA. Applying perceptual and adaptive learning techniques for teaching introductory histopathology. J Pathol Inform. 2013;4:34. Published 2013 Dec 31. doi:10.4103/2153-3539.123991