TEAMSCOPE: measuring software engineering processes with teamwork telemetry

Ju, An; Fox, Armando

doi:10.1145/3197091.3197107

Cited by 19 publications

(8 citation statements)

References 19 publications

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“…Results from a case study in a software engineering course at a US university [15] have provided supporting evidence to our approach by showing that…”

Section: Discussionmentioning

confidence: 64%

Scalable Team-Based Software Engineering Education via Automated Systems

Zeitsoff

et al. 2018

2018 Learning With MOOCS (LWMOOCS)

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“…Results from a case study in a software engineering course at a US university [15] have provided supporting evidence to our approach by showing that…”

Section: Discussionmentioning

confidence: 64%

Scalable Team-Based Software Engineering Education via Automated Systems

Zeitsoff

et al. 2018

2018 Learning With MOOCS (LWMOOCS)

Self Cite

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“…Academic software engineering projects are increasingly gaining attention as a reliable method to assess competency levels among ICT students (Raibulet and Fontana, 2018;Ju and Fox, 2018). In (Kennedy and Vossen, 2017), the authors considered a student peer assessment scale in addition to the lecturer's overall scale to enhance the reliability of the evaluation.…”

Section: Background and Related Workmentioning

confidence: 99%

“…In (Kennedy and Vossen, 2017), the authors considered a student peer assessment scale in addition to the lecturer's overall scale to enhance the reliability of the evaluation. Quite recent studies shed the light on the importance of incorporating maintained practices across the project development process in addition to the final product (Ju and Fox, 2018;Frezza, Daniels and Wilkin, 2019). The principal purpose is to quantify to which extent do students pay attention to the good practices of software engineering.…”

Section: Background and Related Workmentioning

confidence: 99%

Female Student Participation in Software Engineering Projects: Opportunities to Model Project Evaluation and to Improve Early Prediction of Teamwork Failure

2020

JEP

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Software engineering project is the preferred mean to measure competency and practical skills among learners in IT-fields. This study investigates the opportunities to model software engineering project final evaluation and improve early prediction of academic software engineering project failure by considering female student participation as a teamwork member, regardless of being a teamwork leader or a teamwork regular member. Four distinct arrangements of software engineering development teamwork are advised and studied. Those arrangements range from female-less participation teamwork to female-dominated participation teamwork. Machine learning techniques are leveraged to build prediction models. Teams are evaluated from two distinct perspectives. First, software products submitted at the end of each project life cycle milestone, namely product perspective. Second, the degree of obeying the good practices of software engineering project development, namely process perspective. Results reveal significant differences due to female student participation. Arrangement of female-less participation attains the worst modeling and prediction performance compared to the other arrangements of female student participation.

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“…Measuring learner's competency in projects remains a challenge due to many factors. Those factors include estimation of tacit knowledge transfer, quantifying on lab practices, dealing with distant learning issues, obeying to good practices, and evaluating teamwork dynamics [13][14][15][16][17][18]. Academic software engineering teamwork requires special care.…”

Section: Introductionmentioning

confidence: 99%

“…Academic software engineering teamwork requires special care. Lack of experience, variance in knowledge levels, and acceptance of other personalities are extra challenges against academic teamwork [14,19]. Undergraduate students or even graduate students may make slight modifications to the project idea or substantial changes, ask to change their teamwork, drop the project, or fail to deliver the final product [20].…”

Section: Introductionmentioning

confidence: 99%

Teamwork Distribution: Local vs. Global Software Engineering Project Development Teamwork

AL-Taharwa

2020

Int. J. Emerg. Technol. Learn.

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Deliverable and course project become the preferred mean to measure learner competency and attainment of intended learning outcomes in IT-fields. Proper setup and evaluation for teamwork projects remains a key challenge for e-learning systems. This study investigates the possibility to improve the early prediction of academic software engineering project failure by treating teamwork differently according to the distribution of teamwork participants. Two configurations of teamwork distribution are considered. In the first configuration, a teamwork may include international participants, but all team participants are affiliated to the same institution, namely local teamwork. In the second configuration, a teamwork may include participants from different institutions, namely global teamwork. Software engineering projects are approached from two distinct perspectives. First, obeying the best practices during the system development life cycle (SDLC), namely, process perspective. Second, characteristics of the final deliverable deployed at each milestone of the SDLC, namely product perspective. A publicly released dataset collected by a designated e-learning environment is leveraged to validate the proposed approach. Results indicate a noticeable variance among local and global distributions. These results puts evidence that the reasons behind software engineering teamwork project failures may vary depending on the distribution of the teamwork, local vs. global. Consequently, it advise to customize e-learning systems differently according to the teamwork distribution.

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TEAMSCOPE: measuring software engineering processes with teamwork telemetry

Cited by 19 publications

References 19 publications

Scalable Team-Based Software Engineering Education via Automated Systems

Scalable Team-Based Software Engineering Education via Automated Systems

Female Student Participation in Software Engineering Projects: Opportunities to Model Project Evaluation and to Improve Early Prediction of Teamwork Failure

Teamwork Distribution: Local vs. Global Software Engineering Project Development Teamwork

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