Learning in virtual student teams: an examination of shared leadership

Darban, Mehdi

doi:10.1080/15391523.2021.1916800

Cited by 5 publications

(12 citation statements)

References 72 publications

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“…This autonomous interaction encourages active learning and engagement, stimulates critical thinking, and incites students to explore further, thereby enhancing knowledge transfer and interactive learning within virtual student teams. The impact of such an autonomous capability becomes particularly significant given the complexities of communication within virtual teams (Darban, 2022a). Thus, we hypothesize that: H2: Perceived AI autonomy will have a positive association with knowledge update.…”

Section: Ai Autonomy and Learningmentioning

confidence: 98%

“…Furthermore, AI tools, due to their inherent autonomy, can adapt to varying contexts, concepts, and meanings, providing learners with timely and pertinent information. This flexibility enables a dynamic learning experience, a crucial attribute in virtual team settings (Darban, 2022a). For instance, conversational AI tools can accommodate diverse learning preferences within student teams by being available around-the-clock and adapting to students' unique learning needs (Sukhwal et al, 2023).…”

Section: Ai Autonomy and Learningmentioning

confidence: 99%

“…Our work makes four significant contributions. Utilizing research on human-agent teams (e.g., Lyons et al, 2023) and virtual project-based team learning (e.g., Darban, 2022a) to, firstly, develop a framework rooted in anthropomorphism -the attribution of human emotions, qualities, and behaviors to non-human objects (Epley et al, 2007). Unlike other interfaces, AI-enabled systems can produce an immanent degree of anthropomorphism due to their ability to emulate human-like properties (Seeger et al, 2018), which in turn can promote the AI's role within teams (Cohen et al, 2021).…”

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confidence: 99%

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Navigating virtual teams in generative AI-led learning: The moderation of team perceived virtuality

Darban

2024

Educ Inf Technol

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This study advances the understanding of Artificial Intelligence (AI)’s role, particularly that of conversational agents like ChatGPT, in augmenting team-based knowledge acquisition in virtual learning settings. Drawing on human-AI teams and anthropomorphism theories and addressing the gap in the literature on human-AI collaboration within virtual teams, this study examines a multi-level, longitudinal model using a sample of 344 graduate students from 48 student project teams in online project-based learning environments. Our model investigates the direct and interactional effects of AI characteristics —autonomy and explainability— and team perceived virtuality (TPV) on the learners’ knowledge-updating process. Findings indicate that embedding AI in learning teams supports knowledge acquisition and learning intentions. The results reveal that while AI explainability significantly enhances knowledge update perceptions, AI autonomy alone does not directly influence knowledge acquisition. Instead, the positive effect of AI autonomy on knowledge updating is contingent upon a high TPV within the team. These findings offer new theoretical insights into AI’s empowering role in educational contexts and provide practical guidance for integrating AI into virtual team learning. This research underlines the importance of designing AI tools with a focus on explainability and leveraging the synergy between AI autonomy and TPV to maximize learning outcomes.

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Section: Ai Autonomy and Learningmentioning

confidence: 98%

Section: Ai Autonomy and Learningmentioning

confidence: 99%

mentioning

confidence: 99%

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Navigating virtual teams in generative AI-led learning: The moderation of team perceived virtuality

Darban

2024

Educ Inf Technol

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“…Compared with traditional offline learning, online learning has fewer spatial restrictions and richer learning resources, which makes it necessary for learners to have more independent learning to complete their online learning tasks. However, the online learning environment has the characteristics of strong freedom, virtuality, and less effective monitoring, which puts forward higher requirements for learners' online learning engagement (Darban, 2022). Student engagement is a continuous and positive emotional learning state shown by learners in learning (Finn & Zimmer, 2012; Zepke & Leach, 2010).…”

Section: Introductionmentioning

confidence: 99%

The impact of future self‐continuity on college students' online learning engagement: A moderated mediation model

Shen,

Zhang,

Zheng

2024

Psychology in the Schools

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Online learning is becoming more and more common, so how to maintain learners' online learning engagement is very important. This study aims to explore the impact of future self‐continuity on college students' online learning engagement and its underlying mechanism of action. We utilized the Future Self‐Continuity Questionnaire, the Learning Self‐regulation Questionnaire, the Implicit Theories of Intelligence Scale, and the Online Learning Engagement Scale to measure the corresponding variables of a sample with 476 college students. The results revealed that future self‐continuity, autonomous motivation, and implicit theories of intelligence were significant positive predictors of student's online learning engagement. The positive association between future self‐continuity and student's online learning engagement was mediated by the autonomous motivation. Moreover, the mediating effect of autonomous motivation was moderated by the implicit theories of intelligence. Relation to the individual endorsing entity theorists, the mediating effect of autonomous motivation was stronger for individual holding increment theorists. Future self‐continuity has an impact on college students' online learning engagement levels directly or indirectly through autonomous motivation. Attention should be paid to the cultivation training of learners' future scenario imagination and autonomous motivation to facilitate their maintenance of focused online learning engagement.

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“…With that, a new mindset to master these challenges is required (Schilirò, 2021) and a new set of (transversal) competencies to collaborate in virtual teams (VT) must be developed. However, virtually working together in teams is a demanding task for both employees and young professionals (Darban, 2022). This puts pressure on Vocational Education and Training (VET):…”

Section: Introductionmentioning

confidence: 99%

Fostering Innovative Learning and Satisfaction in Virtual Teamwork: Shedding Light on Apprentices

Hiller,

Zarnow

2024

IJRVET

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Purpose: The digital transformation and the increased use of technologies have changed the world of work severely. With it, collaboration and cooperation methods among employees. Therefore, new ways of working together must be applied to work in an international and digital working environment. For Vocational Education and Training (VET), developing new (transversal) competencies to engage in virtual teamwork is necessary to adequately prepare young professionals for the present and future labor market. However, there is little research on the current situation in VET regarding virtual teamwork. Approach: We deployed a cross-sectional design and collected data from N = 181 commercial apprentices in Germany regarding virtual teamwork. We analyze our data using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the interrelationships between input, process, and outcome variables to foster satisfaction and innovative learning in virtual teams as desired targets of VET. To assess these results regarding virtuality, the complexity of tasks, gender of the apprentices, and the size of the training firms, we derived a multigroup analysis (MGA) of our model. Findings: The results indicate that organizational factors have the most significant influence concerning the relationship between input and process factors. Surprisingly, the technical affinity of individuals has only a minor effect. Regarding the relationship between process and outcome factors, motivation and responsibility have the highest impact on innovative learning, whilst communication culture severely affects the perceived satisfaction in virtual teamwork. Conclusion: The findings lead to valuable insights on factors influencing virtual teamwork in VET and can help to design learning programs to prepare young professionals to smoothly transition to and successfully master their future working environments by using new ways of collaboration and cooperation. This is particularly relevant for VET, as prior research has focused primarily on primary and secondary education. Lastly, we identify potential scales and items that help capture some of the inherent constructs of virtual teamwork.

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Learning in virtual student teams: an examination of shared leadership

Cited by 5 publications

References 72 publications

Navigating virtual teams in generative AI-led learning: The moderation of team perceived virtuality

Navigating virtual teams in generative AI-led learning: The moderation of team perceived virtuality

The impact of future self‐continuity on college students' online learning engagement: A moderated mediation model

Fostering Innovative Learning and Satisfaction in Virtual Teamwork: Shedding Light on Apprentices

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