Exploring the Efficacy of Simulation-Based Learning (SBL) for Enhancing Program Outcomes in Mechanical Engineering: A Case Study on Engineering Graphics.

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Title: Exploring the Efficacy of Simulation-Based Learning (SBL) for Enhancing Program Outcomes in Mechanical Engineering: A Case Study on Engineering Graphics.
Authors: Beldar, Pankaj1 prbeldar@kkwagh.edu.in, Patil, Atulkumar1 a.s.patil@kkwagh.edu.in, Shelar, Mahesh1 mnshelar@kkwagh.edu.in, Galande, Vishal2 vggalande@kkwagh.edu.in
Source: Journal of Engineering Education Transformations. Jan2026, Vol. 39 Issue 3, p146-162. 17p.
Subject Terms: *Mechanical engineering education, *Simulation methods in education, *Machine learning, Technical drawing, Computational fluid dynamics, Computer-aided design software
Reviews & Products: MatLab (Computer software)
Abstract: This research investigates the effectiveness of Simulation-Based Learning (SBL) in enhancing student comprehension of complex mechanical engineering concepts, such as fluid dynamics, thermodynamics, FEA, and mechanics. The integration of tools like MATLAB, SolidWorks, ANSYS Fluent, AutoCAD, FluidSim, BricsCAD, and GeoGebra allows students to simulate theoretical mechanics and engineering graphics, bridging the gap between theory and practice. Additionally, Machine Learning playgrounds offer hands-on AI experience. A key novelty is the development of an Automatic Engineering Drawing Sheet Evaluation Algorithm, utilizing Python-based image processing to automate the assessment of technical drawings, increasing efficiency and accuracy. GeoGebra further serves as a tool for assessing geometric transformations in engineering graphics. Integrating simulation tools into the first-year Engineering Graphics course has significantly enhanced Course Outcomes (CO) and Program Outcomes (PO), particularly PO5 (Modern Tool Usage), with a 94.29% improvement. Tools like AutoCAD and GeoGebra have enhanced student understanding of Orthographic Projections and Isometric Views, reflected in improved test scores and positive feedback. Case studies showcase how these tools align with various POs, highlighting the critical role of SBL in modern mechanical engineering education. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Engineering Education Transformations is the property of Rajarambapu Institute of Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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DbLabel: Education Research Complete
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Engineering+Education+Transformations%22">Journal of Engineering Education Transformations</searchLink>. Jan2026, Vol. 39 Issue 3, p146-162. 17p.
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  Data: This research investigates the effectiveness of Simulation-Based Learning (SBL) in enhancing student comprehension of complex mechanical engineering concepts, such as fluid dynamics, thermodynamics, FEA, and mechanics. The integration of tools like MATLAB, SolidWorks, ANSYS Fluent, AutoCAD, FluidSim, BricsCAD, and GeoGebra allows students to simulate theoretical mechanics and engineering graphics, bridging the gap between theory and practice. Additionally, Machine Learning playgrounds offer hands-on AI experience. A key novelty is the development of an Automatic Engineering Drawing Sheet Evaluation Algorithm, utilizing Python-based image processing to automate the assessment of technical drawings, increasing efficiency and accuracy. GeoGebra further serves as a tool for assessing geometric transformations in engineering graphics. Integrating simulation tools into the first-year Engineering Graphics course has significantly enhanced Course Outcomes (CO) and Program Outcomes (PO), particularly PO5 (Modern Tool Usage), with a 94.29% improvement. Tools like AutoCAD and GeoGebra have enhanced student understanding of Orthographic Projections and Isometric Views, reflected in improved test scores and positive feedback. Case studies showcase how these tools align with various POs, highlighting the critical role of SBL in modern mechanical engineering education. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Engineering Education Transformations is the property of Rajarambapu Institute of Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.16920/jeet/2026/v39i3/26089
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 17
        StartPage: 146
    Subjects:
      – SubjectFull: Mechanical engineering education
        Type: general
      – SubjectFull: Simulation methods in education
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Technical drawing
        Type: general
      – SubjectFull: Computational fluid dynamics
        Type: general
      – SubjectFull: Computer-aided design software
        Type: general
      – SubjectFull: MatLab (Computer software)
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    Titles:
      – TitleFull: Exploring the Efficacy of Simulation-Based Learning (SBL) for Enhancing Program Outcomes in Mechanical Engineering: A Case Study on Engineering Graphics.
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            NameFull: Beldar, Pankaj
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            NameFull: Patil, Atulkumar
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            NameFull: Shelar, Mahesh
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            NameFull: Galande, Vishal
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            – D: 01
              M: 01
              Text: Jan2026
              Type: published
              Y: 2026
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