Daniel Meulbroek, D. Ferguson, M. Ohland, F. Berry
{"title":"Forming More Effective Teams Using CATME TeamMaker and the Gale-Shapley Algorithm","authors":"Daniel Meulbroek, D. Ferguson, M. Ohland, F. Berry","doi":"10.1109/FIE43999.2019.9028552","DOIUrl":null,"url":null,"abstract":"Research on student preference in team formation has led to the work in progress of algorithmic integration into an existing team formation algorithm. Forming student teams that are more likely to be successful is a goal of every teacher or instructor using teams as a part of their pedagogy. CATME is a team formation and team management website tool. It contains team formation, peer evaluation and teamwork training tools to help an instructor make and manage student teams. CATME’s team building algorithms include validated teamwork research with practical constraints provided by instructors.CATME’s Team-Maker algorithm uses a heuristic score based on instructor-determined criteria to form teams that optimize the student team composition. The tool includes 20 built-in questions for the instructor to choose from with the option to create individual questions. One question type not accounted for in the current CATME algorithm is a preference ranking question.Augmenting the Team-Maker algorithm to include student project preference as a part of the heuristic score will ease the time struggle of instructors while still forming well-balanced groups. Given that the problem at hand is very similar to the stable marriage problem, the Gale-Shapely algorithm was determined as the best possible options. The Gale-Shapley algorithm, better known for its implementation in the Medical Residency Matching Program, matches entities based on ranked preference lists. Once the algorithm terminates, no two unmatched resident/residency entities prefer each other over their current assignment.This paper documents the testing of the Gale-Shapley algorithm, illustrating methods to use student/instructor/ sponsor ranked preference lists for project selections. These techniques will be used to form teams in the 2018/2019 academic year and results included in final paper versions.","PeriodicalId":6700,"journal":{"name":"2019 IEEE Frontiers in Education Conference (FIE)","volume":"128 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Frontiers in Education Conference (FIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FIE43999.2019.9028552","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Research on student preference in team formation has led to the work in progress of algorithmic integration into an existing team formation algorithm. Forming student teams that are more likely to be successful is a goal of every teacher or instructor using teams as a part of their pedagogy. CATME is a team formation and team management website tool. It contains team formation, peer evaluation and teamwork training tools to help an instructor make and manage student teams. CATME’s team building algorithms include validated teamwork research with practical constraints provided by instructors.CATME’s Team-Maker algorithm uses a heuristic score based on instructor-determined criteria to form teams that optimize the student team composition. The tool includes 20 built-in questions for the instructor to choose from with the option to create individual questions. One question type not accounted for in the current CATME algorithm is a preference ranking question.Augmenting the Team-Maker algorithm to include student project preference as a part of the heuristic score will ease the time struggle of instructors while still forming well-balanced groups. Given that the problem at hand is very similar to the stable marriage problem, the Gale-Shapely algorithm was determined as the best possible options. The Gale-Shapley algorithm, better known for its implementation in the Medical Residency Matching Program, matches entities based on ranked preference lists. Once the algorithm terminates, no two unmatched resident/residency entities prefer each other over their current assignment.This paper documents the testing of the Gale-Shapley algorithm, illustrating methods to use student/instructor/ sponsor ranked preference lists for project selections. These techniques will be used to form teams in the 2018/2019 academic year and results included in final paper versions.