Wei, S., & Pramanik, A., & Ohland, M. W., & Ferguson, D. M. (2021, July), Design and Validation of a System to Assign Students to Projects Based on Student Preferences  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36914

\bibitem{asee_peer_36914}
  Wei, S., \& Pramanik, A., \& Ohland, M. W., \& Ferguson, D. M. (2021, July), \emph{Design and Validation of a System to Assign Students to Projects Based on Student Preferences}
  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.
  10.18260/1-2--36914

Siqing Wei, Amarto Pramanik, Matthew W. Ohland, and Daniel M. Ferguson.  "Design and Validation of a System to Assign Students to Projects Based on Student Preferences".  2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July.  ASEE Conferences, 2021.  https://peer.asee.org/36914 Internet.  24 Apr, 2024

\bibitem{asee_peer_36914}
  Siqing Wei, Amarto Pramanik, Matthew W. Ohland, and Daniel M. Ferguson.
  "Design and Validation of a System to Assign Students to Projects Based on Student Preferences".
  \emph{2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July}.
  ASEE Conferences, 2021.
  https://peer.asee.org/36914 Internet.  24 Apr, 2024

@INPROCEEDINGS{asee_peer_36914
author = "Siqing Wei, Amarto Pramanik, Matthew W. Ohland, and Daniel M. Ferguson"
title = "Design and Validation of a System to Assign Students to Projects Based on Student Preferences"
booktitle = "2021 ASEE Virtual Annual Conference Content Access"
year = "2021"
month = "July"
address = "Virtual Conference"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/36914}
number = {10.18260/1-2--36914}
}

TY  - CPAPER
AB  - Automating team assignments for project-based courses has the potential to significantly improve efficiency and effectiveness of the process by freeing up instructor time, improving the average match preference, and reducing the variability of preference matching. This paper discusses the design and testing for a new project preference matching algorithm as part of Team-Maker system of CATME Team Tools. A new ranking question type in the Team-Maker system allows students to rank a list of projects from a scale of most desired to least desired. The ranking algorithm attempts to match students with the project of the highest possible rank. Initial testing finds that the algorithm places more than 95% of students into one of their top 3 projects under ideal conditions—when there is an equal number of teams and projects when all projects are considered equally desirable, and when project preference is the only team formation criterion. When used in combination with the other team formation criteria in the Team-Maker system, the ranking algorithm performs less effectively. This is especially true when those other criteria have similar weights to that of the ranking question. Nevertheless, when other criteria had a low weight relative to project preference, the algorithm still placed more than 80% of students to their top 3 projects. Algorithm testing so far has relied on randomly generated student preferences, however. Empirical research is still needed to validate the effectiveness of this new feature with real students and project choices. It would also be imperative to investigate the effects of different combinations of criteria and associated weights to propose the optimal team-making strategy for instructors.
AU  - Siqing Wei
AU  - Amarto Pramanik
AU  - Matthew W. Ohland
AU  - Daniel M. Ferguson
CY  - Virtual Conference
DA  - 2021/07/26
PB  - ASEE Conferences
TI  - Design and Validation of a System to Assign Students to Projects Based on Student Preferences
UR  - https://peer.asee.org/36914
DO  - 10.18260/1-2--36914
ER  -