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Students' Performance in Remote Flipped Signals Classes

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Electrical and Computer Division Technical Session 1

Tagged Division

Electrical and Computer

Page Count

10

Permanent URL

https://peer.asee.org/37769

Download Count

75

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Paper Authors

biography

Ahmed Dallal University of Pittsburgh Orcid 16x16 orcid.org/0000-0003-0573-2326

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Dr. Dallal is an assistant professor at the department of electrical and computer engineering, Unversity of Pittsburgh, since August 2017. Dr. Dallal primary focus is on education development and innovation. His research interests include biomedical signal processing, biomedical image analysis, and computer vision, as well as machine learning, networked control systems, and human-machine learning.

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Abstract

With advances in technologies and ideologies, online learning has gained popularity and acceptance among students. This has encouraged instructors to adopt flipped instruction in their classes. Besides, after the universities transitioned to remote learning due to COVID-19, the flipped instruction style gained more popularity among instructors. It is ushering in a new cohort of active learners. The asynchronous flipped instruction relies on completing instructional video lectures before class and focusing on class discussions and activities. This allows students to move through course content at their own pace and then share their opinions during class discussions. These discussions encourage higher engagement and expose gaps in understanding. Also, previous research suggests that student learning is improved in the flipped compared to the traditional classroom. The flipped classroom may seem risky, especially in a remote setup, as it put the responsibility on the student to finish video lectures before class time. However, some techniques, e.g., reliability quizzes, can be adopted to ensure that students complete the video lectures before the class. Due to their nature, signal processing courses are well suited for flipping. Students can watch lecture videos that cover the theory before the class. Then, during class time, they work with the instructor and their peers on demos, discussions, and problem-solving. This research studies students’ performance in two remote flipped ECE signals courses – signals and systems, and digital signal processing. The former was partially flipped while the later was completely flipped. The study uses the data collected from the two courses over spring 2020 to summer 2020 with a total enrollment of 100 students in both classes. After switching to remote learning in March 2020, the instructor's (the first author) primary motivation to flip these classes was the desire to tailor class time to students’ needs, questions, and offer an amble of demos that help foster students’ learning. Both courses are composed of equally challenging modules that were followed by homework or a mini-project. The instructor created custom videos for each of the flipped lectures. These lectures were then uploaded on Panopto and shared on the course website. In this paper, we analyze scores from homework assignments, quizzes, and exams to assess the students' performance under the flipped asynchronous instructions. Project report quality is an essential factor that can indicate how well the students learned the modules' topics and their ability to interpret and analyze the results of the experiments. We will also compare students’ scores from course sections that included some flipped instruction to other sections of the same courses without any flipped instruction. Student surveys were conducted to measure flipped learning perceptions, and these will be content-analyzed to determine students’ perception and reception of this technique.

Dallal, A. (2021, July), Students' Performance in Remote Flipped Signals Classes Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37769

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