Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings - SEKE 2017 |
| Subtitle of host publication | 29th International Conference on Software Engineering and Knowledge Engineering |
| Pages | 608-614 |
| Number of pages | 7 |
| ISBN (electronic) | 1891706411 |
| Publication status | Published - 2017 |
Abstract
Estimating dynamic components in projects involves understanding human factors which are substantial in software development. Communication and collaboration in teams consist of social-driven characteristics with influences on the continuous delivery of software. Efficiently estimated meetings become increasingly important due to budget calculations and shortened release cycles. Experiences of project managers combined with retrospectives on historical data records support a better understanding of team dynamics. But interpreting complex effects is not always trivial, in particular without further analyzes. In several studies, information relationships are investigated through linear correlation measures. Additional analyses for higher correlations are often neglected due to the advanced functional characterization. This leads to statistical gaps with significances for explored data relationships and their functional interpretation. In this paper, we present a systematic identification and visualization of team communication effects and diversities for field study records of 34 student software projects. We combine methodologies from system dynamics with exploratory data analysis to extract and emphasize significant effects. These insights help to sensitize for advanced investigations about the statistical measures of correlation and to interpret sophisticated structures. Furthermore, it reinforces potentials for a team's communication performances and enables an enhanced understanding about how student teams meet and communicate.
Keywords
- Data visualization, Exploratory data analysis, Student software projects, Team dynamics
ASJC Scopus subject areas
- Computer Science(all)
- Software
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Proceedings - SEKE 2017: 29th International Conference on Software Engineering and Knowledge Engineering. 2017. p. 608-614.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Characterizing Relationships for System Dynamics Models Supported by Exploratory Data Analysis
T2 - A Conceptualizing Approach about the Meeting Diversity in Student Software Projects
AU - Kortum, Fabian
AU - Klünder, Jil
AU - Schneider, Kurt
N1 - Funding Information: This work was funded by the German Research Foundation under grant number 263807701 (TeamFLOW, 2015-2017).
PY - 2017
Y1 - 2017
N2 - Estimating dynamic components in projects involves understanding human factors which are substantial in software development. Communication and collaboration in teams consist of social-driven characteristics with influences on the continuous delivery of software. Efficiently estimated meetings become increasingly important due to budget calculations and shortened release cycles. Experiences of project managers combined with retrospectives on historical data records support a better understanding of team dynamics. But interpreting complex effects is not always trivial, in particular without further analyzes. In several studies, information relationships are investigated through linear correlation measures. Additional analyses for higher correlations are often neglected due to the advanced functional characterization. This leads to statistical gaps with significances for explored data relationships and their functional interpretation. In this paper, we present a systematic identification and visualization of team communication effects and diversities for field study records of 34 student software projects. We combine methodologies from system dynamics with exploratory data analysis to extract and emphasize significant effects. These insights help to sensitize for advanced investigations about the statistical measures of correlation and to interpret sophisticated structures. Furthermore, it reinforces potentials for a team's communication performances and enables an enhanced understanding about how student teams meet and communicate.
AB - Estimating dynamic components in projects involves understanding human factors which are substantial in software development. Communication and collaboration in teams consist of social-driven characteristics with influences on the continuous delivery of software. Efficiently estimated meetings become increasingly important due to budget calculations and shortened release cycles. Experiences of project managers combined with retrospectives on historical data records support a better understanding of team dynamics. But interpreting complex effects is not always trivial, in particular without further analyzes. In several studies, information relationships are investigated through linear correlation measures. Additional analyses for higher correlations are often neglected due to the advanced functional characterization. This leads to statistical gaps with significances for explored data relationships and their functional interpretation. In this paper, we present a systematic identification and visualization of team communication effects and diversities for field study records of 34 student software projects. We combine methodologies from system dynamics with exploratory data analysis to extract and emphasize significant effects. These insights help to sensitize for advanced investigations about the statistical measures of correlation and to interpret sophisticated structures. Furthermore, it reinforces potentials for a team's communication performances and enables an enhanced understanding about how student teams meet and communicate.
KW - Data visualization
KW - Exploratory data analysis
KW - Student software projects
KW - Team dynamics
UR - http://www.scopus.com/inward/record.url?scp=85029528892&partnerID=8YFLogxK
U2 - 10.18293/SEKE2017-143
DO - 10.18293/SEKE2017-143
M3 - Conference contribution
SP - 608
EP - 614
BT - Proceedings - SEKE 2017
ER -