What Are the Characteristics that Software Development Project Team Members Associate with a Good Project Manager?

Medina, Alicia; Francis, Alison J.

doi:10.1002/pmj.21530

Cited by 17 publications

(14 citation statements)

References 51 publications

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“…Therefore, in this work, we adopt the leadership questionnaire presented by Northouse [16] to collect groundtruth leadership assessment due to its well-establishment and having been extensively used in higher education to gauge students' leadership skills in various fields of studies [28]- [31]. Furthermore, Northouse's leadership questionnaire is selected because of its capacity to assess the three areas of leadership abilities that are critical in IT teamwork: administrative (e.g., familiarizing with evaluation criteria, structuring group work, and securing necessary resources), conceptual (e.g., understanding the requirements and scopes, taking active responsibility, and flexibility to changes), and interpersonal (e.g., handling team members and clients, resolving conflicts, understanding team's technical composition) skills [32], [33]. A team leader, for example, may be required to complete documentation for software requirement specifications (requiring administrative skills), manage and oversee software development (requiring conceptual skills), and interact with both clients and teammates (requiring interpersonal skills).…”

Section: A Leadership Assessment In College Studentsmentioning

confidence: 99%

Automatic Assessment and Identification of Leadership in College Students

2022

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As one of the 21st Century skills, fostering leadership competencies in college students has been a focus of research in the behavioral education field. While leaders are expected to have general leadership traits such as communication and resource management, leading teams in particular expertise areas requires additional skills specifically tailored to the tasks involved. For example, in information technology (IT), the roles of leaders are different from those in other non-IT fields due to the characteristics of IT projects. IT leaders, in particular, are required to have not just managerial and interpersonal skills but also necessary technical and practical capabilities. Understanding the key elements that contribute to the emergence and development of student leaders necessitates the ability to assess and recognize leadership in college students. However, current approaches for measuring leadership qualities entail administering questionnaires, which have coverage constraints and may mislabel future leaders if the survey is administered too early in a student's educational phase, when their leadership talents may not have emerged yet. Addressing this problem, this paper introduces LAIGA, a machine learning-based framework for automatically and passively assessing and identifying leaders in college students from their academic profiles and behavior in the learning management system (LMS). The proposed technique can capture students' actions that indicate general leadership qualities and technical competence as evidenced by their academic performances. Specifically, we address two problems: leadership assessment and leader identification tasks. A case study of senior-year college students in the IT major is used to validate the proposed method, yielding 5.87% MAPE in the leadership assessment task and 83.2% F1 in the leadership identification task. Furthermore, the results also show that the proposed method can forecast leadership assessment and identification after graduation, knowing as little as students' information during their first year of study. The findings of this study not only shed light on the ability to use machine learning technologies to automatically assess and identify leadership in college students but also allow educational organizations to understand factors that help develop leadership skills and design mechanisms that promote the growth of student leaders. The proposed method is highly generalizable to other fields of study, as long as students' grades and LMS activities are available. INDEX TERMS Student Leadership, Assessment and Identification, Machine Learning I. INTRODUCTIONA S team efforts are often necessary to tackle increasingly complex challenges, leadership is inherently among essential professional and interpersonal skills to thrive in globally competitive environments. Especially in the IT field, where a software project is typically composed of practi-tioners that have diverse roles, such as project leaders (i.e., assignees or task managers), developers, testers, and peerre...

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Section: A Leadership Assessment In College Studentsmentioning

confidence: 99%

Automatic Assessment and Identification of Leadership in College Students

2022

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“…Although emotions are related to neuroticism (a personality factor), this paper does not discuss them from this perspective. Medina and Francis [26] highlight that a good project manager should involve people in the decisions, and Rose et al [27] state the importance of having the entire team engaged in the decision-making.…”

Section: Decision-makingmentioning

confidence: 99%

Insights on the relationship between decision-making style and personality in software engineering

Mendes

Salleh

et al. 2021

Information and Software Technology

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Software development involves many activities, and decision making is an essential one. Various factors can impact a decision-making process, and by understanding such factors, one can improve the process. Since people are the ones making decisions, some human-related aspects are amongst those influencing factors. One such aspect is the decision maker's personality.Objective: This research investigates the relationship between decision-making style and personality within the context of software project development. Method: We conducted a survey in a population of Brazilian software engineers to gather data on their personality and decision-making style. Results: Data from 63 participants was gathered and resulted in the identification of seven statistically significant correlations between decision-making style and personality (personality factor and personality facets). Furthermore, we built a regression model in which decision-making style (DMS) was the response variable and personality factors the independent variables. The backward elimination procedure selected only agreeableness to explain 4.2% of DMS variation. The model accuracy was evaluated and deemed good enough. Regarding the moderation effect of demographic variables (age, educational level, experience, and role) on the relationship between DMS and Agreeableness, the analysis showed that only software engineers' role has such effect. Conclusion:This paper contributes toward understanding the relationship between DMS and personality. Results show that the personality variable agreeableness can explain the variation in decision-making style. Furthermore, someone's role in a software development project can impact the strength of the relationship between DMS and agreeableness.

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“…On the other hand, there are personality traits and positive attitudes that can support the project leader in learning from failure. Positive reactions result from certain personality traits in project leaders [28]; the power of acceptance (for both failure and post-failure changes), resilience, self-efficacy, self-esteem, transformational leadership, communication and convincing power, are some of the most discussed traits and behaviors that can allow a project leader to learn [29]. The project leader may already have these traits and positive attitudes or may need to develop them.…”

Section: Introductionmentioning

confidence: 99%

Shadow of Your Former Self: Exploring Project Leaders’ Post-Failure Behaviors (Resilience, Self-Esteem and Self-Efficacy) in High-Tech Startup Projects

et al. 2021

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Globally, demands for sustainable strategies in the ICT industry have attracted greater momentum as high-tech projects continue to fail in large numbers. Recent studies have underpinned project resilience as a major factor for overcoming these increasing project failures, delays, or termination. However, the complex behaviors of resilient project leaders, especially in post-failure conditions, have been largely overlooked. To address this critical research gap, the present study identifies the direct relationships between three potential behavioral traits of project leaders (i.e., resilience, self-esteem, and self-efficacy) and examines how they move forward beyond project failures. The present study also explored whether self-esteem mediates project leaders’ resilience and self-efficacy. Drawing on data from 232 project leaders in Pakistan’s high-tech start-ups, the new findings suggest that there are significant positive effects of project leaders’ resilience and self-esteem on their self-efficacy, and that project leaders’ resilience and self-efficacy is significantly mediated by their self-esteem. As the project resilience theory gains traction, the present study findings have pinpointed major steps for meeting project challenges ahead of time, allowing leaders and teams to learn from failures, and also for improving organisations’ ability to implement successful and sustainable high-tech projects especially in emerging economies.

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What Are the Characteristics that Software Development Project Team Members Associate with a Good Project Manager?

Cited by 17 publications

References 51 publications

Automatic Assessment and Identification of Leadership in College Students

Automatic Assessment and Identification of Leadership in College Students

Insights on the relationship between decision-making style and personality in software engineering

Shadow of Your Former Self: Exploring Project Leaders’ Post-Failure Behaviors (Resilience, Self-Esteem and Self-Efficacy) in High-Tech Startup Projects

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