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Evaluation of Blended Learning Technologies in a Large Enrollment Case-based Systems Engineering Course

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Conference

2014 ASEE Annual Conference & Exposition

Location

Indianapolis, Indiana

Publication Date

June 15, 2014

Start Date

June 15, 2014

End Date

June 18, 2014

ISSN

2153-5965

Conference Session

Systems Engineering Division Technical Session 3

Tagged Division

Systems Engineering

Page Count

20

Page Numbers

24.547.1 - 24.547.20

Permanent URL

https://peer.asee.org/20438

Download Count

25

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Paper Authors

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Yue Bi University of Virginia

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Yue Bi is an undergraduate student double majoring in Systems Engineering and Economics at the University of Virginia. She has been conducting research on blended learning using statistical analysis for over half a year. With an interest in data analysis and its application to the real world, she has interned at the National Institutes of Health, providing policy recommendations. She has also interned at Ernst & Young, LLP., contributing to the Fraud Technology and Discovery Services team by utilizing relational database and data visualization skills. Currently, she is working with the Virginia Department of Transportation to support its project acquisition process with data analysis, systems integration, and risk management.

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Reid Bailey University of Virginia

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Reid Bailey is an Associate Professor at the University of Virginia in the Department of Systems and Information Engineering.

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Michael C. Smith University of Virginia

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Mike Smith earned his B.S. and M.S. at the University of Tennessee-Knoxville and Ph.D. from the University of Missouri-Columbia. He has worked across a variety of application domains including manufacturing, transportation, defense, and health care. His 20+ years in the private sector and ten years in academia give him the combined perspective of academic rigor and pragmatic problem solving that helps bring solid solutions to challenging problems. Mike and his wife. Amanda, have four children and two grandchildren and enjoy biking, hiking, camping, reading, and hanging out with the grandkids.

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Abstract

Evaluation of Blended Learning Technologies in a Large Enrollment Case-based Systems Engineering CourseBackground: Pedagogical strategies that rely heavily on interaction and feedback amongstudents and faculty, such as project-based, case-based, and design courses can be particularlychallenged as enrollment increases. Blended learning, which combines traditionalface-to-face instruction with online experiences, provides opportunities to handle largernumbers of students while maintaining or improving the interaction and feedback. To this end,several blended learning tools were integrated into an introductory case-basedsystems-engineering course taught at the University of XXX which is facing growingenrollment. These tools, aimed at providing a more active and collaborative learningenvironment, providing better feedback to students more quickly, and increasing theauthenticity of deliverables, included an online discussion board, video-capturing technologythat allowed students to submit recorded presentations, and an online peer reviewmanagement system.Purpose: This study focuses on analyzing feedback and assessments collected from studentsin the course to evaluate the effectiveness of blended learning tools.Design/method: Surveys on self-efficacy and grading were conducted three times throughoutthe course to assess potential impact of the blended learning tools. Students were randomlyassigned to use the video-capturing technology for case submission for different cases,thereby providing a comparison group for analysis. The peer-review management system wasused by all students on only one of the four main cases in the class, with one of the otherthree cases incorporating peer review but without the online tool. The online discussion boardwas open for use by all students. In addition, end-of-course evaluations provided insights intostudent perceptions of the blended learning tools. Statistical tests were conducted forquantitative analysis of the ratings on the surveys and qualitative analysis was done onstudents’ feedback about the technologies used and the general class experience.Results: According to the statistical analyses, students’ self-efficacy ratings do not changesignificantly when their usage of the online discussion technology or method of casesubmission varies. Students’ perceptions about the accuracy and fairness of grading on casepresentations also do not seem to change significantly when their activities with the blendedtechnologies vary. However, students perceived that the overall course experience wasimproved and students had strongly differing perceptions about the different technologiesused. Students preferred the online discussion board to the other two blended learning tools.While students valued the increased feedback that they received from peer review itself, thepeer review tool was less preferred because it was hard to use. The video capturingtechnology was not only the hardest tool to use but the work it facilitated was not shown to beeducationally valuable. The reasons for these preferences are rooted in the online discussiontools’ low barrier to use, overall ease of use, and the increase in accessibility to timelyfeedback from the instructors from the discussion board.Conclusion: Students preferred blended learning tools with low effort to use and high benefitin return. In this case, the benefit of most value was increased feedback and interaction withfaculty and peers facilitated by tools. It is recommended that faculty consider increasedinteraction as a significant benefit of blended learning tools while also weighing the ease ofuse and difficulty of learning as they are also important factors affecting student acceptanceand overall perceptions of such tools.

Bi, Y., & Bailey, R., & Smith, M. C. (2014, June), Evaluation of Blended Learning Technologies in a Large Enrollment Case-based Systems Engineering Course Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. https://peer.asee.org/20438

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