ASEE Computers in Education Journal

ASEE's Computers in Education Journal

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Mike Borowczak

Learning Analytics of Outcomes-Based Engineering Programs’ Data

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Learning Analytics of Outcomes-Based Engineering Programs’ Data


1 College of Computer Science and Information Systems, Najran University, Saudi Arabia
2 Faculty of Computer Science and Information Systems, Thamar University, Thamar, Yemen

Abstract

In the recent years, learning analytics is attracting attention in tertiary education sector. This paper presents a case study of applying learning analytics approaches to discover knowledge from Outcome Based (OB) engineering programs’ data. More specifically, Association Rule Mining approach is applied to a dataset extracted from the Self-Study Reports of 152 engineering programs accredited by American Board of Engineering and Technology (ABET). In doing so, the dataset has been processed and transformed into a suitable representation. Apriori algorithm is then applied to generate rules involving PEOs and ABET SOs. The generated rules are filtered, and the filtered rules are used to draw a set of generic rules for mapping each PEO to ABET SOs and to discover the correlations among ABET SOs.

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COVID-19 Technology Student Success Challenges : Influence of Tools and Strategies

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COVID-19 Technology Student Success Challenges : Influence of Tools and Strategies

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1 University of Houston

Abstract

COVID-19 brought rapid and substantial change to course formats as colleges and universities transitioned from on-campus to online instruction to mitigate the spread of the pandemic. While faculty and administrators sought solutions to maintain instructional quality and student success, students endeavored to adapt to the changes. This study investigated a) College of Technology students’ perceptions of their potential for success including initial reactions, adaptation, and perceptions of impacts to grades and learning; b) course features and tools preferred by Technology students; and c) factors that enabled Technology students’ course completion.

Keywords

covid-19, technology, tools

Introduction

The declaration of COVID-19 as a pandemic brought expansive changes to higher education including massive disruptions to students as they were forced to transition from on-campus to online classes (Binkley & Amy, 2020; Brownlee, 2020).

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gruepr, a Software Tool for Optimally Partitioning Students onto Teams

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gruepr, a Software Tool for Optimally Partitioning Students onto Teams


1 Northeastern University, Boston, MA, 02115, USA

Abstract

Abstract—Choosing how to split a group of students into teams for project work can be a time-intensive task for an instructor. An instructor might have a complex set of parameters to optimize, perhaps desiring each team to have a certain number of times throughout the week where they can meet, while also seeking to create teams that are homogeneous in some characteristics and heterogeneous in other characteristics. Demographic composition may also be considered, and perhaps the instructor has certain students that must be placed on the same team or must be placed on different teams. Maybe teams will be formed several times, and no student should have the same teammate twice. A few software tools can be found in the literature to assist an instructor with this task, but few of them seem to be easily and freely accessible.

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Teaching Signal Processing Applications using an Android Echolocation App

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Teaching Signal Processing Applications using an Android Echolocation App

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1 Electrical and Computer Engineering, Clarkson University
2 Education, Clarkson University
3 School of Electrical, Computer, and Energy Engineering, Arizona State University

Abstract

An Android application that realizes an audible version of echolocation has been implemented. Bundled within the app are videos, notes, problems, and discussion questions, thus creating an “eModule”. The eModule contains material that is relevant to several educational levels including K-12 and undergraduate engineering. By using the echolocation features of the app, at the K-12 level, teachers are able to introduce labs, and science and engineering practices into their lesson plans. By using data collection and interpretation, undergraduate students can be exposed to various concepts in signals and systems, digital signal processing, and machine learning.

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Educational Challenges Presented by COVID-19 at Technical Colleges Offering Aviation Maintenance Technology Program

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Educational Challenges Presented by COVID-19 at Technical Colleges Offering Aviation Maintenance Technology Program

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1 Department of Biomedical Engineering, Georgia Institute of Technology
2 School of Computing, Clemson University
3 National Center for Autonomous Technologies, Northland Community and Technical College
4 Department of Aviation Technologies, Southern Illinois University Carbondale
5 Center for Workforce Development, Clemson University
6 Departments of Civil and Industrial Engineering, Clemson University

Abstract

In mid-March, many schools in the United States were forced to stop teaching in-person classes and switch to an online format due to the COVID-19 pandemic; as a result, teachers had to quickly implement new technologies and instructional strategies in the classroom. This rapid pandemic response especially affected teachers and students in Aviation Maintenance Technology (AMT) programs around the country as AMT instruction is inherently hands-on in nature.

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