Minneapolis, MN
August 23, 2022
June 26, 2022
June 29, 2022
Computers in Education 4 - Online and Distributed Learning I
10
10.18260/1-2--41249
https://peer.asee.org/41249
291
Robert M. Nickel received a Dipl.-Ing. degree in electrical engineering from the RWTH Aachen, Germany, in 1994, and a Ph.D. in electrical engineering from the University of Michigan, Ann Arbor, Michigan, in 2001. During the 2001/2002 academic year he was an adjunct faculty in the Department of Electrical Engineering and Computer Science at the University of Michigan. From 2002 until 2007 he was a faculty member at the Pennsylvania State University, University Park, Pennsylvania. Since the fall of 2007 he is a faculty member of the Electrical and Computer Engineering Department at Bucknell University, Lewisburg, Pennsylvania. During the 2010/2011 academic year he was a Marie Curie Incoming International Fellow at the Institute of Communication Acoustics, Ruhr-Universität Bochum, Germany. Prof. Nickel is author/co-author of over 40 peer-reviewed scientific articles, mainly in the areas of speech signal processing, natural language processing, and machine learning.
Sarah Appelhans is a postdoctoral research assistant at Bucknell University. She earned her PhD in Cultural Anthropology at the University at Albany (SUNY). Her dissertation research, "Flexible Lives on Engineering's Bleeding Edge: Gender, Migration and Belonging in Semiconductor Manufacturing", investigates the intersections of gender, race/ethnicity, and immigration status among semiconductor engineers. She is currently the resident social scientist in the Electrical Engineering Department at Bucknell, exploring how to teach convergent (deeply interdisciplinary) problems to undergraduate engineers. Past research projects include studies of governance in engineering education and the influence of educational technology on engineering education.
Rebecca Thomas is a Visiting Assistant Professor in the Department of Electrical and Computer Engineering at Bucknell University in Lewisburg, Pennsylvania. She holds a B.S. and M.Eng. in Electrical Engineering from the University of Louisville and a Ph.D. in Electrical Engineering from North Carolina State University.
Stu is an associate professor and chair of the department of Electrical and Computer Engineering at Bucknell University, in Lewisburg, PA. While his teaching responsibilities typically include digital design, computer-related electives, and senior design, his focus
Stewart Thomas is an Assistant Professor in the Department of Electrical and Computer Engineering at Bucknell University in Lewisburg, Pennsylvania. He received the B.S. and M.Eng. in Electrical Engineering from the University of Louisville in Louisville, KY. and the Ph.D. in Electrical and Computer Engineering from Duke University in Durham, North Carolina. He is a member of ASEE and IEEE.
One of the major changes in the higher education ecosystem over the last decade has been a rise in the availability of education-based software products, including education-based web-pages and web-services. Globally the investment in education-based startups in 2017 was $9.5B which surged to $18.7B in 2019 [1]. The COVID-19 pandemic further fueled record investment in this sector, with the US seeing $2.2B invested in 130 startups in 2020, up from $1.7B in 2019 and $1.4B in 2018 [2,6]. Early indicators show that 2021 will again see further increases [3]. While the majority (92%) of these investments are aimed at consumer and corporate sectors, there is potential for the innovations developed to diffuse into both the P-12 and higher education spaces [4]. What is evident from the investment numbers is that an integration of learning technologies specifically into higher education is progressing at a relatively slower pace [4]. It is the goal of this work-in-progress to identify some of the reasons for this slower progress. Our hypothesis is that, while some of these reasons may be obvious, there are also more subtle and/or counterintuitive reasons for the reduced interest in higher education.
To study the subject we are compiling a database with a large number of education-based software products, web-pages, and web-services, with a commensurate analysis of the type, breadth, and respective strengths and limitations of the products. In our study, we are limiting ourselves to employing publicly accessible descriptions of each product (including descriptions provided by the software provider as well as third parties). This excludes products that are still in the development stage. Additionally, we do not endeavor to explicitly test the products ourselves, which would not be feasible given the large number and variety of available products. The intent is not to comprehensively describe each product in detail, but to instead develop an ontology of the types of available products and services including their potential strengths and limitations. We see value in this ontological framework as an aid to navigating and understanding the vast set of available tools. Work on the database has already begun and it currently encompasses close to 100 products across 15 categories, such as: Learning management systems, manual grading and auto-grading tools, feedback tools, discussion tools, reading tools, classroom activity tools, communication tools, interactive resources and information materials, digital textbook companies, dashboard programs, circuit design tools, chatbot systems, and written materials scanning and recognition (including optical character recognition).
To evaluate the ontology, we presented the preliminary findings to engineering faculty and solicited their feedback regarding (i) what type(s) of product they may already be using and why, (ii) what other type(s) of product may be of interest to them, and (iii) what type(s) of product is/are currently not of interest to them and why. Data were collected through one-hour-long faculty interviews in which the use of the educational-technology tools was discussed among other topics. Using this feedback, the resulting database of products continues to be refined, including respective type labels for each product to allow for fast searching and browsing, and wider dissemination. The process of searching for a suitable tool for a particular task is typically quite time-consuming for a faculty member, and oftentimes it is not even clear if the desired tool even exists. In this paper, we present the database with our current classifications and a brief summary of our results from the faculty interviews. We are hoping that the paper and the database provide a useful alternative to aid faculty in finding an existing tool more quickly to support their teaching with technology.
The motivation and need for the proposed study grew out of an ongoing NSF RED project where we endeavor to fuse the concept of convergence, loosely defined as "deep integration," into our undergraduate engineering curriculum. Increasingly software and data systems at colleges and universities, and the affordances they do and do not offer, are integral to university structures. If the respective software systems do not support certain activities and functions then the programs are simply not useful to the faculty [5]. Additionally, any subset of systems needs to seamlessly integrate to form a coherent and usable learning support system that faculty, students, and staff can use without issue and/or barrier. The goal of the proposed activity within our grant is, thus, to build structures to collect, analyze, and display data in support of developing skills in addressing convergent problems.
[1] R. D. Shulman, "EdTech Investments Rise to a Historical $9.5 Billion: What Your Startup Needs To Know," Forbes, Jan-2018.
[2] https://www.edsurge.com/news/2021-01-13-a-record-year-amid-a-pandemic-us-edtech-raises-2-2-billion-in-2020
[3] https://www.holoniq.com/notes/global-edtech-funding-2021-half-year-update/
[4] https://campustechnology.com/Articles/2020/01/30/Higher-Ed-Tech-Investments-Soar.aspx?Page=1
[5] F. McCluskey and M. L. Winter, "The Idea of the Digital University." Washington, DC: Westphalia Press, 2012.
[6] T. Wan, "US EdTech investments peak again with $1.45 billion raised in 2018," EdSurge, 15-Jan-2019.
Nickel, R., & Appelhans, S., & Thomas, R., & Thompson, S., & Thomas, S., & Abouelnagga, A., & Kreusch, N. (2022, August), Work-in-Progress: A Review of the Type, Breadth, and Limitations of Publicly Available Educational Technology Products in 2022 Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41249
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