Administering a Digital Logic Concept Inventory at Multiple Institutions

Geoffrey L. Herman; Michael C. Loui

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Conference: 2011 ASEE Annual Conference & Exposition
Location: Vancouver, BC
Publication Date: June 26, 2011
Start Date: June 26, 2011
End Date: June 29, 2011
ISSN: 2153-5965
Conference Session: NSF Grantees Poster Session
Tagged Topic: NSF Grantees
Page Count: 12
Page Numbers: 22.142.1 - 22.142.12
DOI: 10.18260/1-2--17423
Permanent URL: https://peer.asee.org/17423
Download Count: 432

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Paper Authors

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Geoffrey L. Herman University of Illinois, Urbana-Champaign orcid.org/0000-0002-9501-2295

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Geoffrey L. Herman is a Ph.D. Candidate in Electrical and Computer Engineering and a Mavis Future Faculty Fellow at the University of Illinois, Urbana-Champaign. His research interests include cognitive science, identifying and assessing common student misconceptions and difficulties in electrical and computer engineering topics, blended learning (integrating online teaching tools into the classroom), intelligent tutoring systems, and music signal processing. He is a winner of the 2011 Educational Research and Methods Division Apprentice Faculty Grant. He has been recognized with the Olesen Award for Excellence in Undergraduate Teaching for the Department of Electrical and Computer Engineering and the Ernest A. Reid Fellowship for engineering education. He has served as a graduate affiliate for the Center for Teaching Excellence, as the seminar chair for the Dean's Graduate Student Advisory Committee, and as the information chair for the American Society for Engineering Education's Student Constituent Committee.

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Michael C. Loui University of Illinois, Urbana-Champaign

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Michael C. Loui is Professor of Electrical and Computer Engineering and University Distinguished Teacher-Scholar at the University of Illinois at Urbana-Champaign. His interests include computational complexity theory, professional ethics, and the scholarship of teaching and learning. He serves as Executive Editor of College Teaching, and as a member of the editorial board of Accountability in Research. He is a Carnegie Scholar and an IEEE Fellow. Professor Loui was Associate Dean of the Graduate College at Illinois from 1996 to 2000. He directed the theory of computing program at the National Science Foundation from 1990 to 1991. He earned the Ph.D. at M.I.T. in 1980.

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Abstract

Administering a Digital Logic Concept Inventory at Multiple Institutions Instructors in electrical and computer engineering and in computer science havedeveloped innovative methods to teach digital logic circuits. These methods attempt to increasestudent learning, satisfaction, and retention. Although there are readily accessible and acceptedmeans for measuring satisfaction and retention, there are no widely accepted means for assessingstudent learning. Rigorous assessment of learning is elusive because differences in topiccoverage, curriculum and course goals, and exam content prevent direct comparison of twoteaching methods when using tools such as final exam scores or course grades. Because of thesedifficulties, computing educators have issued a general call for the adoption of assessment toolsto critically evaluate and compare the various teaching methods. A commonly accepted benchmark for comparing student learning is to compare the levelof students’ conceptual knowledge upon completion of a course. Conceptual knowledge is oftenpreferred because all courses should teach a fundamental set of concepts even if they emphasizedesign or analysis to different degrees. Increasing conceptual learning is also important, becausestudents who can organize facts and ideas within a consistent conceptual framework are able tolearn new information quickly and can apply what they know in new situations. If instructorscan accurately assess their students’ conceptual knowledge, they can target instructionalinterventions to remedy common problems. To properly assess conceptual learning, manyengineering disciplines have developed concept inventories (CIs) for core subjects in engineeringsciences. CIs are multiple-choice assessment tools that evaluate how well a student’s conceptualframework matches the accepted conceptual framework of a discipline or common faultyconceptual frameworks. We present how we created and evaluated the digital logic CI. The digital logic CI wascreated by using a Delphi process for identifying the important and difficult concepts to includeon the CI. Student interviews and a qualitative grounded theory approach of analysis were usedfor discovering common student misconceptions. We have administered the digital logic CI at several institutions and have checked thevalidity, reliability, and bias of the CI with classical testing theory procedures. These proceduresconsisted of follow-up interviews with students, analysis of administration results with statisticalprocedures, and expert feedback. We discuss these results and present the digital logic CI’spotential for providing a meaningful tool for comparing student learning at different institutions.

Citation
Format

Herman, G. L., & Loui, M. C. (2011, June), Administering a Digital Logic Concept Inventory at Multiple Institutions Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. 10.18260/1-2--17423

TY - CPAPER
AB - Administering a Digital Logic Concept Inventory at Multiple Institutions Instructors in electrical and computer engineering and in computer science havedeveloped innovative methods to teach digital logic circuits. These methods attempt to increasestudent learning, satisfaction, and retention. Although there are readily accessible and acceptedmeans for measuring satisfaction and retention, there are no widely accepted means for assessingstudent learning. Rigorous assessment of learning is elusive because differences in topiccoverage, curriculum and course goals, and exam content prevent direct comparison of twoteaching methods when using tools such as final exam scores or course grades. Because of thesedifficulties, computing educators have issued a general call for the adoption of assessment toolsto critically evaluate and compare the various teaching methods. A commonly accepted benchmark for comparing student learning is to compare the levelof students’ conceptual knowledge upon completion of a course. Conceptual knowledge is oftenpreferred because all courses should teach a fundamental set of concepts even if they emphasizedesign or analysis to different degrees. Increasing conceptual learning is also important, becausestudents who can organize facts and ideas within a consistent conceptual framework are able tolearn new information quickly and can apply what they know in new situations. If instructorscan accurately assess their students’ conceptual knowledge, they can target instructionalinterventions to remedy common problems. To properly assess conceptual learning, manyengineering disciplines have developed concept inventories (CIs) for core subjects in engineeringsciences. CIs are multiple-choice assessment tools that evaluate how well a student’s conceptualframework matches the accepted conceptual framework of a discipline or common faultyconceptual frameworks. We present how we created and evaluated the digital logic CI. The digital logic CI wascreated by using a Delphi process for identifying the important and difficult concepts to includeon the CI. Student interviews and a qualitative grounded theory approach of analysis were usedfor discovering common student misconceptions. We have administered the digital logic CI at several institutions and have checked thevalidity, reliability, and bias of the CI with classical testing theory procedures. These proceduresconsisted of follow-up interviews with students, analysis of administration results with statisticalprocedures, and expert feedback. We discuss these results and present the digital logic CI’spotential for providing a meaningful tool for comparing student learning at different institutions.
AU - Geoffrey L. Herman
AU - Michael C. Loui
CY - Vancouver, BC
DA - 2011/06/26
PB - ASEE Conferences
TI - Administering a Digital Logic Concept Inventory at Multiple Institutions
UR - https://peer.asee.org/17423
DO - 10.18260/1-2--17423
ER -