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

Abstract

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 combined 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 systems such as AdobeConnect, auto tracking camera and high quality audio in both local and remote classrooms. As an innovative active learning environment, an 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 (Highly integrated model assessment technology and tools) [11] to evaluate how students think through and model complex, illdefined and ill-structured realistic problems.

Computer technologies for model‐based collaborative learning: A research‐based approach with initial findings

“…Another goal was to reduce the workload for instructors preparing and delivering such a hybrid learning course so that the interinstitutional collaboration can continue and be replicated by other colleges when funding ends. The feedback from the students and a summative learning assessment indicated that this goal was met . However, our research has shown that telepresence students are less likely to ask questions or participate in office hours with the distant professor, preferring instead to rely on local personnel.…”

“…The six courses share one common theme, which is to encourage deep learning to cultivate students' problem-solving competence. The evidence of student achievement for the first phase of the project has been reported in reference [6]. One noteworthy achievement is that the project from 2014-2016 resulted in five publications with undergraduate co-authors [6].…”

“…The evidence of student achievement for the first phase of the project has been reported in reference [6]. One noteworthy achievement is that the project from 2014-2016 resulted in five publications with undergraduate co-authors [6]. The interinstitutional collaboration offered over a hundred students the opportunity to take the hybrid CSE courses from 2014-2016.…”

“…When these students are now exposed to encyclopedic knowledge presented in lectures, they tend to lose interest and focus. Liu et al observed that most college educators encounter these challenges: (1) a rapidly changing job market that requires STEM (science, technology, engineering, and mathematics) faculties to update curricula more frequently; (2) an increasing proportion of students lack the motivation to participate in traditional lecture‐based instruction; and (3) learning gaps are increasing as more and more students are ill‐prepared in reading and mathematics.…”

“…When teaching the Differential Equation course, they integrated small mathematical modeling modules that used a system engineering process and the dynamic system modeling tool Stella to help students represent and solve challenging problems. Early modest success with that course became the precursor of the model‐based learning courses reported below , which represent an inter‐institutional effort with a focus on collaborative teaching and course development for courses in Computational Science and Engineering (CSE). In addition to modeling tools used for representation, problem‐solving and assessment, the course made use of video‐based synchronous instruction with local teachers and tutors to ensure active participation and provide required elaboration and personalization.…”