Burks, G. R., & Amos, J. R., & Castleberry, C. W. (2019, June), Embedded Tagging and Radar Map Shape Analysis for Assessing Student Outcomes  Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32702

\bibitem{asee_peer_32702}
  Burks, G. R., \& Amos, J. R., \& Castleberry, C. W. (2019, June), \emph{Embedded Tagging and Radar Map Shape Analysis for Assessing Student Outcomes}
  Paper presented at 2019 ASEE Annual Conference \& Exposition , Tampa, Florida.
  10.18260/1-2--32702

Gabriel R. Burks, Jennifer R. Amos, and Colin Widmer Castleberry.  "Embedded Tagging and Radar Map Shape Analysis for Assessing Student Outcomes".  2019 ASEE Annual Conference & Exposition , Tampa, Florida, 2019, June.  ASEE Conferences, 2019.  https://peer.asee.org/32702 Internet.  21 Feb, 2025

\bibitem{asee_peer_32702}
  Gabriel R. Burks, Jennifer R. Amos, and Colin Widmer Castleberry.
  "Embedded Tagging and Radar Map Shape Analysis for Assessing Student Outcomes".
  \emph{2019 ASEE Annual Conference \& Exposition , Tampa, Florida, 2019, June}.
  ASEE Conferences, 2019.
  https://peer.asee.org/32702 Internet.  21 Feb, 2025

@INPROCEEDINGS{asee_peer_32702
author = "Gabriel R. Burks, Jennifer R. Amos, and Colin Widmer Castleberry"
title = "Embedded Tagging and Radar Map Shape Analysis for Assessing Student Outcomes"
booktitle = "2019 ASEE Annual Conference \& Exposition "
year = "2019"
month = "June"
address = "Tampa, Florida"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/32702}
number = {10.18260/1-2--32702}
}

TY  - CPAPER
AB  - Computer-based assessment has been shown to offer many benefits on the outcomes of student performance [1]. The computational strengths of computer-based platforms allow for more in-depth collection and analysis of data from students of today than the many years previous. This access to data and performance outcomes allow us to learn more about the individual student instantly and to use this feedback to tailor adapted teaching and learning experiences on the fly. Here the University of Illinois Urbana-Champaign-developed PrairieLearn (PLN) platform is used to administer, assess, and collect minimally invasive tagged data from quizzes, homework, and exams of undergraduate students in sophomore-level engineering course. The information gathered from this platform is represented using an accessible radar plot format then analyzed using a novel method, based on the shape of the radar plot, to develop a greater understanding of the individual strengths and deficiencies of students. Finally, to establish appropriate context for this data it is correlated to a common student success metric and analyzed for potential trends.
AU  - Gabriel R. Burks
AU  - Jennifer R. Amos
AU  - Colin Widmer Castleberry
CY  - Tampa, Florida
DA  - 2019/06/15
PB  - ASEE Conferences
TI  - Embedded Tagging and Radar Map Shape Analysis for Assessing Student Outcomes
UR  - https://peer.asee.org/32702
DO  - 10.18260/1-2--32702
ER  -