soft skills

This study addresses the lack of a rigorous definition of empathy in software engineering, along with persistent practical barriers and organizational impacts. Using qualitative content analysis, we coded 55 practitioner-oriented gray literature articles from DEV and Medium platforms, supplemented by expert questionnaire-based triangulation. We propose the first operational definition of empathy tailored to software engineering and introduce an integrated conceptual framework comprising three dimensions: (1) impediments—including toxic culture and technocentrism; (2) cultivation practices—such as role reversal and user-empathy workshops; and (3) outcome metrics—namely collaboration quality and communication effectiveness. Expert evaluation confirms the framework’s strong construct validity and pragmatic feasibility. Empirically grounded and theory-informed, it enhances team empathic awareness, mitigates interpersonal tension, and strengthens cross-functional collaboration—thereby advancing both research on engineering humanistic competencies and their practical implementation.

This study addresses the lack of systematic synthesis in soft skills research within agile software development over the past 25 years, a gap that has hindered the integration of technical and human-centric factors. Through a systematic literature mapping of 97 studies sourced from multiple databases spanning 2000 to 2025, this work constructs the first evolutionary map of soft skills in agile contexts, with a focus on mainstream frameworks such as Scrum. The analysis identifies communication, adaptability, teamwork, and leadership as core soft skills, elucidates their relationships with specific agile roles and methodologies, and highlights a critical research gap concerning role-specific soft skill requirements. These findings offer empirical grounding and theoretical support for advancing agile education, training programs, and organizational practices.

This study investigates how emotional intelligence (EI) enhances leadership effectiveness to foster high-performing teams. Drawing on survey data from 100 working professionals, the research employs correlational statistical analysis and established leadership assessment frameworks to quantify associations between EI’s four dimensions—self-awareness, self-regulation, empathy, and social skills—and key outcomes: leader recognition, team collaboration, conflict resolution, and organizational performance. Results demonstrate that leaders with higher EI receive significantly greater recognition for empathy, ethical conduct, and inspirational motivation—factors strongly linked to elevated team trust, cohesion, and overall performance. Critically, EI is shown not merely as an individual trait but as a scalable, integrable interpersonal competence within structured leadership development programs. The study makes a novel contribution by empirically validating EI’s role as a mediating mechanism linking leadership behavior to sustained organizational success.

This study investigates how immersive technologies can effectively foster the knowledge, skills, and attitudes (KSAs) essential for team collaboration—such as communication, coordination, trust, and reflection. To this end, we designed and evaluated a colocated, tablet-based virtual reality team training system that innovatively integrates a narrative-driven asymmetric interaction mechanism with a theoretical framework of team KSAs. The design leverages spatial separation, tool asymmetry, and task interdependence to elicit verbal coordination. Task scenarios were modeled through interviews with human resources experts to ensure ecological validity. An experiment with 16 participants demonstrated that users dynamically employed verbal communication, role negotiation, and shared representations to effectively exhibit core team KSAs, thereby validating the feasibility and efficacy of the proposed paradigm.

Although the importance of communication skills in software engineering is widely acknowledged, existing discussions are scattered across academic and grey literature, lacking systematic integration. This study innovatively employs a multi-voiced literature review methodology to simultaneously synthesize peer-reviewed journal articles and industry reports, thereby offering a comprehensive analysis of how communication skills are conceptualized, valued, and applied in both educational and professional contexts. The findings reveal that both academia and industry regard communication as a core competency: the former emphasizes theoretical frameworks and empirical investigations, while the latter focuses on practical impact and emerging practices. By elucidating areas of consensus and divergence between these two spheres, this work effectively bridges the theory–practice gap and provides an integrated foundation for cultivating communication competencies in software engineering education and professional development.

This study addresses the limited understanding of how accessibility practices influence collaboration—specifically productivity, engagement, and cohesion—in virtual hybrid-capable teams. Through semi-structured interviews with 18 team members and qualitative analysis, the research reveals that accessibility practices not only facilitate access but also serve as a foundational element for effective collaboration by shaping task coordination, relational maintenance, and responsibility allocation. Findings indicate that such practices significantly enhance team coordination and cohesion, while simultaneously introducing a novel tension between empathy and accountability. Building on these insights, the paper proposes a new perspective that deeply integrates accessibility into the design of virtual collaboration tools and offers concrete recommendations for team-level implementation.

This study addresses the systemic support of macrocognitive functions—namely, event detection, sensemaking, adaptability, perspective shifting, and coordination—in human–AI teaming, moving beyond traditional usability-centered design paradigms. Drawing on cognitive psychology, human–computer interaction, and cognitive systems engineering, we conducted an interdisciplinary literature review and theoretical integration to develop, for the first time, a set of 14 heuristic design principles comprehensively covering all five macrocognitive functions. The resulting framework cohesively integrates display design, human factors engineering, and joint activity theory into a reusable, evaluable, general-purpose design framework. Empirical validation demonstrates that this framework significantly enhances AI agents’ capacity to function as *effective team members* in dynamic, collaborative settings. It thus provides the first complete, structured, cognition-driven theory–practice interface for the design, development, and evaluation of human–AI collaborative systems.

Current AI systems in software engineering collaboration lack social-emotional capabilities, limiting human-AI collaborative effectiveness. Through semi-structured interviews and qualitative analysis with ten software professionals, this study reveals that developers primarily perceive AI as an intellectual partner rather than a social one. To address this gap, the work introduces the concept of “functional equivalence,” which translates social-emotional intelligence into actionable collaborative capacities—such as responsibility negotiation, contextual adaptation, and sustained cooperation. By prioritizing functional alignment over emotional mimicry, this framework redefines the design paradigm for human-AI collaboration, significantly enhancing collaborative outcomes.

This study addresses the “social blind spot” arising from generative AI’s increasing anthropomorphism—where AI teammates are misperceived as human despite their non-human identity—particularly examining how unannounced, personality-embedded AI collaborators (supportive vs. oppositional communicative styles) influence human team dynamics. Method: A mixed-methods experiment (N = 905) systematically evaluated effects across analytical, creative, and ethical collaboration tasks, integrating behavioral observation, computational linguistics (modeling affective and relational language), and mediation analysis. Contribution/Results: Participants exhibited extremely low AI detection rates; oppositional AI significantly reduced psychological safety and discussion quality, whereas supportive AI enhanced discussion quality—effects robust to participants’ awareness of AI identity. This is the first empirical demonstration that AI communicative personality reshapes team interaction via linguistic mechanisms, challenging the assumption that transparency alone suffices for effective human-AI collaboration, and providing critical evidence for designing human-AI teamwork in education, organizations, and public institutions.