Deep Learning towards Expertise Development in a Visualization-based Learning Environment

With limited problem-solving capability and practical experience, novices have difficulties developing expert-like performance. It is important to make the complex problem-solving process visible to learners and provide them with necessary help throughout the process. This study explores the design...

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Bibliographic Details
Published in:Educational Technology ＆ Society 2017-10, Vol.20 (4), p.233-246
Main Authors: Yuan, Bei, Wang, Minhong, Kushniruk, Andre W., Peng, Jun
Format: Article
Language:English
Subjects:
Achievement Gains
Analysis
Clinical Diagnosis
Clinical experience
Cognitive models
Computer-assisted instruction
Deep learning
Diagnostic systems
Educational Environment
Electronic Learning
Expertise
Learning
Learning Motivation
Medical education
Medical Students
Methods
Online education
Online learning
Outcomes of Education
Perceptual learning
Pretests Posttests
Problem Solving
Professional development
Questionnaires
Scaffolding (Teaching Technique)
School environment
Semi Structured Interviews
Skill Development
Special Issue Articles
Students
Teaching Methods
Visual learning
Visualization
Visualization (Computers)
Web Based Instruction
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Summary:With limited problem-solving capability and practical experience, novices have difficulties developing expert-like performance. It is important to make the complex problem-solving process visible to learners and provide them with necessary help throughout the process. This study explores the design and effects of a model-based learning approach implemented in a web-based learning environment that not only allows learners to capture and reflect on their problem-solving process in visual formats but also helps them to identify the gap between their performance and that of the expert for effective reflection and improvement. The proposed approach attempts to utilize expert knowledge to transform open-ended problem-solving experience into a systematic and deliberate effort towards expertise development. Twenty-five medical students participated in the study by using the proposed learning environment to complete a number of diagnostic problem-solving tasks. The results show that the approach positively affects students' achievements in subject knowledge, problem-solving performance, and perceptions and motivation for learning in the proposed learning environment.
ISSN:1176-3647
1436-4522
1436-4522