Using Learning Styles to Staff and Improve Software Inspection Team Performance

Author(s):  
Anurag Goswami ◽  
Gursimran S. Walia ◽  
Urvashi Rathod
2015 ◽  
Vol 25 (09n10) ◽  
pp. 1721-1726 ◽  
Author(s):  
Anurag Goswami ◽  
Gursimran Walia ◽  
Abhinav Singh

Inspections of software artifacts during early software development aids managers to detect early faults that may be hard to find and fix later. Results showed inspection ability does not depend on educational background and technical knowledge. This paper presents the results from an industrial empirical study, wherein the Learning Styles (i.e. ability to perceive and process information) of individual inspectors were manipulated to measure its impact on the fault detection effectiveness of inspection teams. Using inspection data from professional developers, we developed virtual teams with varying LS’s of individual inspectors and analyzed the team performance. The results from the current study show that teams of inspectors with diverse LS’s are significantly more effective at detecting faults as compared to teams of inspectors with similar LS’s. Therefore, LS’s can aid software managers to create high performance inspection team(s) and manage software quality.


2008 ◽  
Vol 11 (2) ◽  
pp. 76-82 ◽  
Author(s):  
Sarah M. Ginsberg

Abstract This qualitative study examined student perceptions regarding a hybrid classroom format in which part of their learning took place in a traditional classroom and part of their learning occurred in an online platform. Pre-course and post-course anonymous essays suggest that students may be open to learning in this context; however, they have specific concerns as well. Students raised issues regarding faculty communication patterns, learning styles, and the value of clear connections between online and traditional learning experiences. Student concerns and feedback need to be addressed through the course design and by the instructor in order for them to have a positive learning experience in a hybrid format course.


2017 ◽  
Vol 76 (3) ◽  
pp. 91-105 ◽  
Author(s):  
Vera Hagemann

Abstract. The individual attitudes of every single team member are important for team performance. Studies show that each team member’s collective orientation – that is, propensity to work in a collective manner in team settings – enhances the team’s interdependent teamwork. In the German-speaking countries, there was previously no instrument to measure collective orientation. So, I developed and validated a German-language instrument to measure collective orientation. In three studies (N = 1028), I tested the validity of the instrument in terms of its internal structure and relationships with other variables. The results confirm the reliability and validity of the instrument. The instrument also predicts team performance in terms of interdependent teamwork. I discuss differences in established individual variables in team research and the role of collective orientation in teams. In future research, the instrument can be applied to diagnose teamwork deficiencies and evaluate interventions for developing team members’ collective orientation.


2017 ◽  
Vol 7 (2) ◽  
pp. 78-85 ◽  
Author(s):  
Heikki Mansikka ◽  
Don Harris ◽  
Kai Virtanen

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.


2017 ◽  
Vol 102 (10) ◽  
pp. 1462-1470 ◽  
Author(s):  
Stephen H. Courtright ◽  
Brian W. McCormick ◽  
Sal Mistry ◽  
Jiexin Wang

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