Innovative Model, Tools, and Learning Environments to Promote Active Learning for Undergraduates in Computational Science & Engineering

Volume 8, Issue 3 (December 2017), pp. 11–18

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@article{jocse-8-3-2,
  author={Hong Liu and Michael Spector and Matthew Ikle and Andrei Ludu and Jerry Klein},
  title={Innovative Model, Tools, and Learning Environments to Promote Active Learning for Undergraduates in Computational Science \& Engineering},
  journal={The Journal of Computational Science Education},
  year=2017,
  month=dec,
  volume=8,
  issue=3,
  pages={11--18},
  doi={https://doi.org/10.22369/issn.2153-4136/8/3/2}
}

This paper presents an innovative hybrid learning model as well as the tools, resources, and learning environment to promote active learning for both face-to-face students and online students. Most small universities in the United States lack adequate resources and cost justifiable enrollments to offer Computational Science and Engineering (CSE) courses. The goal of the project was to find an effective and affordable model for small universities to prepare underserved students with marketable analytical skills in CSE. As the primary outcome, the project created a cluster of collaborating institutions that combines students into common classes and used cyberlearning learning tools to deliver and manage instruction. The instrumental tools for educational technologies included Smart Podium, digital projector, teleconference system such as AdobeConnect, auto tracking camera and high quality audios in both local and remote classrooms. As innovative active learning environment, R&D process was used to provide a coherent framework for designing instruction and assessing learning. Course design centered on model-based learning which proposes that students learn complex content by elaborating on their mental model, developing a conceptual model, refining a mathematical model, and conducting experiments to validate and revise their conceptual and mathematical models. A wave lab and underwater robotics lab were used to facilitate the experimental components of hands-on research projects. Course delivery included interactive live online help sessions, immediate feedback to students, peer support, and teamwork which were crucial for student success. Another key feature of instruction of the project was using emerging technologies such as HIMATT [8] to evaluate how students think through and model complex, ill-defined and ill-structured realistic problems.