Domain-Specific Modeling Languages in Computer-Based Learning Environments: a Systematic Approach to Support Science Learning through Computational Modeling

Driven by our technologically advanced workplaces and the surge in demand for proficiency in the computing disciplines, it is becoming imperative to provide computational thinking (CT) opportunities to all students. One approach for making computing accessible and relevant to learning and problem-so...

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Bibliographic Details
Published in:International journal of artificial intelligence in education 2020-11, Vol.30 (4), p.537-580
Main Authors: Hutchins, Nicole M., Biswas, Gautam, Zhang, Ningyu, Snyder, Caitlin, Lédeczi, Ákos, Maróti, Miklós
Format: Article
Language:English
Subjects:
Artificial Intelligence
Behavioral Objectives
Case studies
Classrooms
Computation
Computer Assisted Instruction
Computer models
Computer Science
Computers and Education
Curricula
Design
Earth Science
Earth sciences
Educational Environment
Educational Objectives
Educational Technology
Engineering education
Instructional Design
Language
Learning
Marine Biology
Physics
Problem Solving
Programming Languages
Science education
Semantics
Simulation
Software engineering
STEM Education
Students
Technical education
Thinking Skills
User Interfaces and Human Computer Interaction
Workplaces
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Summary:Driven by our technologically advanced workplaces and the surge in demand for proficiency in the computing disciplines, it is becoming imperative to provide computational thinking (CT) opportunities to all students. One approach for making computing accessible and relevant to learning and problem-solving in K-12 environments is to integrate it with existing Science, Technology, Engineering, and Math (STEM) curricula. However, novice student learners may face several difficulties in trying to learn STEM and computing concepts simultaneously. To address some of these difficulties, we present a systematic approach to learning STEM and CT by designing and developing domain-specific modeling languages (DSMLs) to aid students in their model building and problem-solving processes. The paper discusses a theoretical framework and the design principles for developing DSMLs, which is implemented as a four-step process. We apply the four-step process in three domains: Physics, Marine Biology, and Earth Science to demonstrate its generality, and then perform case studies to show how the DSMLs impact student learning and model building. We conclude with a discussion of our findings and then present directions for future work.
ISSN:1560-4292
1560-4306
DOI:10.1007/s40593-020-00209-z