Novel Diagnostic Educational Resource: Use of a web-based adaptive learning module to teach inflammatory reaction patterns in dermatopathology to medical students, residents, and fellows

Knapp, Calvin; Slaught, Christa; Latour, Emile; Glasser, Daniel; Reder, Nicholas P.; Shinohara, Michi M.; Pantanowitz, Liron; Parwani, Anil V.

doi:10.1016/j.jpi.2022.100099

Journal of Pathology Informatics

2022

DOI: 10.1016/j.jpi.2022.100099

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Novel Diagnostic Educational Resource: Use of a web-based adaptive learning module to teach inflammatory reaction patterns in dermatopathology to medical students, residents, and fellows

Calvin Knapp

Christa Slaught

Emile Latour

et al.

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2024

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Diagnostic errors during perceptual learning in dermatology: a prospective cohort study of Finnish undergraduate students

Salava,

Salmela

2024

Clinical and Experimental Dermatology

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Background Perceptual learning modules (PLMs) have been shown to significantly improve learning outcomes in teaching dermatology. Objectives We aimed to investigate the quantity and quality of diagnostic errors during undergraduate PLMs and their potential implications. Methods The study data was acquired during eight successive dermatology courses (2021-2023) from 142 undergraduate medical students. Digital PLMs were held before, during, and at course ends. We investigated the amount and distribution of diagnostic errors, differences between specific skin conditions and classified them based on the type of errors students made. Results Diagnostic errors were not randomly distributed. Some skin conditions were almost always correctly identified, whereas in some diagnoses significant number of errors were made. Errors could be classified in three groups: mostly systematic errors of relevant differential diagnoses (similarity errors), partly systematic errors (mixed errors) and random errors. While significant learning effect during the repeated measures was found in accuracy (p<.001, η²p=.64), confidence (p<.001, η²p=.60) and fluency (p<.001, η²p=.16), the three categories differed in all outcome measures (all p <.001, all η²p>.47). Visual learning was more difficult in the similarity category (all p <.001, all η²p>.12) than in the mixed and random categories. Conclusions Error analysis of PLMs provided relevant information about learning efficacy and progression, systematic errors of tasks, and more difficult to learn conditions. This information can be used in the development of adaptive, individual error-based PLMs to improve learning outcomes, both in dermatology and medical education in general.

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Diagnostic errors during perceptual learning in dermatology: a prospective cohort study of Finnish undergraduate students

Salava,

Salmela

2024

Clinical and Experimental Dermatology

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Implementation of the Digital Health Approach to Support Learning for Health Students Based on Bloom’s Taxonomy: A Systematic Review

Budi,

Putri,

Puspitasari

et al. 2024

Healthc Inform Res

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Objectives: Health students’ ability to utilize technology effectively is vital for improving the quality of future healthcare services. Relevant digital health education must be comprehensively integrated into training programs, continuing professional development activities, and school curricula to keep them current. This study investigated the most effective digital health approaches to enhance health students’ cognitive, affective, and psychomotor skills, thereby preparing them for the workforce.Methods: A literature review was conducted by searching for articles from 2013 to 2023 in PubMed, Science Direct, ERIC, and Scopus. The search used the PICO model, focusing on experimental studies and digital learning.Results: The review identified 26 studies, categorizing digital education methods into platform-based (46.2%), tools-based (30.7%), and training-based approaches (23.1%). Participants included health students (57.7%), healthcare professionals (34.6%), and a combination of both (7.7%). The content materials primarily targeted curriculum objectives (65.4%) and clinical applications (34.6%). The outcomes, classified according to Bloom’s taxonomy, were divided into cognitive (84.6%), affective (76.9%), and psychomotor (46.1%) domains.Conclusions: Digital health education benefits from a variety of approaches. A platformbased approach is recommended for delivering theoretical and methodological materials, a tools-based approach for simulations, and a training-based approach for practical skills to enhance the cognitive domain. Both platform-based and trainingbased approaches are advised to improve the affective and psychomotor dimensions of learning. This study underscores the importance of an integrated digital learning system in health educational institutions to prepare students for evolving health systems and to improve learning outcomes and skill transfer.

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Novel Diagnostic Educational Resource: Use of a web-based adaptive learning module to teach inflammatory reaction patterns in dermatopathology to medical students, residents, and fellows

Cited by 2 publications

References 10 publications

Diagnostic errors during perceptual learning in dermatology: a prospective cohort study of Finnish undergraduate students

Diagnostic errors during perceptual learning in dermatology: a prospective cohort study of Finnish undergraduate students

Implementation of the Digital Health Approach to Support Learning for Health Students Based on Bloom’s Taxonomy: A Systematic Review

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