Predicting individual performance in student project teams

Matthew Hale, Noah Jorgenson, Rose Gamble

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Due to the critical role of communication in project teams, capturing and analyzing developer design notes and conversations for use as performance predictors is becoming increasing important as software development processes become more asynchronous. Current prediction methods require human Subject Matter Experts (SME) to laboriously examine and rank user content along various categories such as participation and the information they express. SEREBRO is an integrated courseware tool that captures social and development artifacts automatically and provides real time rewards, in the form of badges and titles, indicating a user's progress towards predefined goals using a variety of automated assessment measures. The tool allows for instructor visualization, involvement, and feedback in the ongoing projects and provides avenues for the instructor to adapt or adjust project scope or individual role assignments based on past or current individual performance levels. This paper evaluates and compares the use of two automated SEREBRO measures with SME content-based analysis and work product grades as predictors of individual performance. Data is collected from undergraduate software engineering teams using SEREBRO, whose automated measures of content and contribution perform as well as SME ratings and grades to suggest individual performance can be predicted in real-time.

Original languageEnglish (US)
Title of host publication2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011 - Proceedings
Pages11-20
Number of pages10
DOIs
StatePublished - 2011
Event2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011, Co-located with the 33rd International Conference on Software Engineering, ICSE - Waikiki, Honolulu, HI, United States
Duration: May 22 2011May 24 2011

Publication series

Name2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011 - Proceedings

Conference

Conference2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011, Co-located with the 33rd International Conference on Software Engineering, ICSE
CountryUnited States
CityWaikiki, Honolulu, HI
Period5/22/115/24/11

ASJC Scopus subject areas

  • Software
  • Education

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    Hale, M., Jorgenson, N., & Gamble, R. (2011). Predicting individual performance in student project teams. In 2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011 - Proceedings (pp. 11-20). [5876078] (2011 24th IEEE-CS Conference on Software Engineering Education and Training, CSEE and T 2011 - Proceedings). https://doi.org/10.1109/CSEET.2011.5876078