Exploiting Digital Learning Management System (LMS) Capabilities for Effective Program Assessment of Competency-based Education

Laramie Vance Potts; Huiran Jin; Mohammad Rabie

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: Engineering Management Division (EMD) Tech Session 1: Program-level innovations in design, delivery, and assessment
Tagged Division: Engineering Management Division (EMD)
Page Count: 19
DOI: 10.18260/1-2--43596
Permanent URL: https://peer.asee.org/43596
Download Count: 228

Paper Authors

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Laramie Vance Potts New Jersey Institute of Technology

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Dr. Laramie Potts is an associate professor in the School of Applied Engineering & Technology at the New Jersey Institute of Technology (NJIT). He serves as the program coordinator of the Surveying Engineering Technology (SET) program at NJIT. He has been working as an educator, consultant, and researcher in geodetic science

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Huiran Jin New Jersey Institute of Technology

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Dr. Huiran Jin is an Assistant Professor in the School of Applied Engineering and Technology at the New Jersey Institute of Technology with joint appointments with the Department of Chemistry and Environmental Science of NJIT's College of Science and Liberal Arts and the Department of Data Science of NJIT's Yi Wu College of Computing. Her research focuses on spatiotemporal analysis and modeling of environmental changes at local to regional and global scales, taking advantage of airborne and satellite data, state-of-the-art data fusion and machine learning and deep learning techniques, and big data analytics.

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Mohammad Rabie

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Abstract

Effective programmatic assessment (PA) is essential for accreditation of professional degree programs leading to licensure. Accreditation organizations for Higher Education Institution (HEI) programs such as the ABET may stipulate student outcomes. Programs seeking accreditation from ABET must present clear proof of a rigorous process that uses student work products to assess student outcomes attained. The value of PA results offers entry points for institutions and/or departments to initiate discussions on the status of student learning and to make informed decisions on program improvements. The concept of PA is well described in the literature; however, studies on implementing and operationalizing a consistent assessment approach using a Learning Management System (LMS) across courses of an academic program are lacking. Best practices on program assessment recommend that numerical scores of student performance should be linked to learning objectives. Few engineering faculties received formal grading training. They tend to rely on historical grading practices, personal experiences as students, or grade student work with a rubric that is disconnected from the learning objectives. Such traditional grading practices tend to mask the various aspects of student learning and therefore lacks the capacity to capture the full breadth of competency-based education. Globally, a high percentage of colleges and universities use a LMS to better manage teaching and learning activities. Despite the significant financial investment in LMS, faculty have not fully exploited its data capture, analytics and visualization capabilities and therefore its utility in support of effective program assessment is mostly underutilized.

This paper seeks to add to the ongoing discussion on effective strategies that improve assessment of student learning in competency-based education. We present a case study to show the data collecting, data analytics and visualization capabilities of the Canvas TM LMS for student outcomes on communications for engineering management and engineering technology programs. In doing so, we address two questions that guided this investigation namely: a) what are the best practices to formulate student assignments given student outcomes for ETAC programs, and b) how to devise and setup up standard rubrics in a LMS for unbiased scoring of student work products.

Citation
Format

Potts, L. V., & Jin, H., & Rabie, M. (2023, June), Exploiting Digital Learning Management System (LMS) Capabilities for Effective Program Assessment of Competency-based Education Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43596

TY - CPAPER
AB - Effective programmatic assessment (PA) is essential for accreditation of professional degree programs leading to licensure. Accreditation organizations for Higher Education Institution (HEI) programs such as the ABET may stipulate student outcomes. Programs seeking accreditation from ABET must present clear proof of a rigorous process that uses student work products to assess student outcomes attained. The value of PA results offers entry points for institutions and/or departments to initiate discussions on the status of student learning and to make informed decisions on program improvements. The concept of PA is well described in the literature; however, studies on implementing and operationalizing a consistent assessment approach using a Learning Management System (LMS) across courses of an academic program are lacking. Best practices on program assessment recommend that numerical scores of student performance should be linked to learning objectives. Few engineering faculties received formal grading training. They tend to rely on historical grading practices, personal experiences as students, or grade student work with a rubric that is disconnected from the learning objectives. Such traditional grading practices tend to mask the various aspects of student learning and therefore lacks the capacity to capture the full breadth of competency-based education. Globally, a high percentage of colleges and universities use a LMS to better manage teaching and learning activities. Despite the significant financial investment in LMS, faculty have not fully exploited its data capture, analytics and visualization capabilities and therefore its utility in support of effective program assessment is mostly underutilized.

This paper seeks to add to the ongoing discussion on effective strategies that improve assessment of student learning in competency-based education. We present a case study to show the data collecting, data analytics and visualization capabilities of the Canvas TM LMS for student outcomes on communications for engineering management and engineering technology programs. In doing so, we address two questions that guided this investigation namely: a) what are the best practices to formulate student assignments given student outcomes for ETAC programs, and b) how to devise and setup up standard rubrics in a LMS for unbiased scoring of student work products.

AU - Laramie Vance Potts
AU - Huiran Jin
AU - Mohammad Rabie
CY - Baltimore , Maryland
DA - 2023/06/25
PB - ASEE Conferences
TI - Exploiting Digital Learning Management System (LMS) Capabilities for Effective Program Assessment of Competency-based Education
UR - https://peer.asee.org/43596
DO - 10.18260/1-2--43596
ER -