TY - GEN
T1 - A Canvas Based Multi-Program Assessment System for ABET CAC and EAC Accreditations
AU - Wang, Wen Li
AU - Tang, Mei Huei
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - This is an Innovative Practice Full Paper. This paper introduces a multi-program assessment system for a department offering multiple majors to seek accreditation from ABET CAC and EAC. The Canvas LMS is our mandated tool for faculty to set up course rubrics, assign grades, and communicate with students. However, it falls short on solving several of our data issues, including data retrieval, data separation, data sharing, data integration, and data security. The Canvas LMS provides no data download for individual rubric criteria of an instrument, hindering analysis to a more granular level. There is also no information to identify a student's major, making data separation for different academic programs difficult. Faculty are reluctant to share student data on Canvas for integration, worrying about a violation to FERPA. Moreover, data sharing and data integration can increase the risk of data security. Our assessment system is built atop of Canvas and is a service oriented web application for faculty to assess student performance and generate instrument reports. The reports reveal only computed statistics for data sharing, integration and security purposes. The provided web services can interact with another system to distinguish student majors and consolidate instruments whose rubric criteria cover the same performance indicators (PIs). The system is a safe and sound methodology to conquer our data problems and can facilitate both formative and summative analyses for the program outcomes evaluation.
AB - This is an Innovative Practice Full Paper. This paper introduces a multi-program assessment system for a department offering multiple majors to seek accreditation from ABET CAC and EAC. The Canvas LMS is our mandated tool for faculty to set up course rubrics, assign grades, and communicate with students. However, it falls short on solving several of our data issues, including data retrieval, data separation, data sharing, data integration, and data security. The Canvas LMS provides no data download for individual rubric criteria of an instrument, hindering analysis to a more granular level. There is also no information to identify a student's major, making data separation for different academic programs difficult. Faculty are reluctant to share student data on Canvas for integration, worrying about a violation to FERPA. Moreover, data sharing and data integration can increase the risk of data security. Our assessment system is built atop of Canvas and is a service oriented web application for faculty to assess student performance and generate instrument reports. The reports reveal only computed statistics for data sharing, integration and security purposes. The provided web services can interact with another system to distinguish student majors and consolidate instruments whose rubric criteria cover the same performance indicators (PIs). The system is a safe and sound methodology to conquer our data problems and can facilitate both formative and summative analyses for the program outcomes evaluation.
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U2 - 10.1109/FIE43999.2019.9028609
DO - 10.1109/FIE43999.2019.9028609
M3 - Conference contribution
AN - SCOPUS:85082453769
T3 - Proceedings - Frontiers in Education Conference, FIE
BT - 2019 IEEE Frontiers in Education Conference, FIE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 49th IEEE Frontiers in Education Conference, FIE 2019
Y2 - 16 October 2019 through 19 October 2019
ER -