Listening

Learning to listen: Downstream effects of listening training on employees' relatedness, burnout, and turnover intentions

Abstract

The present work focuses on listening training as an example of a relational human resource practice that can improve human resource outcomes: Relatedness to colleagues, burnout, and turnover intentions. In two quasi-field experiments, employees were assigned to either a group listening training or a control condition. Both immediately after training and 3 weeks later, receiving listening training was shown to be linked to higher feelings of relatedness with colleagues, lower burnout, and lower turnover intentions. These findings suggest that listening training can be harnessed as a powerful human resource management tool to cultivate stronger relationships at work. The implications of Relational Coordination Theory, High-Quality Connections Theory, and Self-Determination Theory are discussed.
Eli Vinokur , Avinoam Yomtovian , Guy Itzchakov , Marva Shalev Marom and Liat Baron
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Listening
Social-based learning and leadership (SBL) is an innovative pedagogical approach that centers on enhancing relationships within the educational system to address 21st-century challenges. At its core, SBL aims to help teachers transform into social architects who nurture positive social processes among pupils. Emphasizing prosocial education, SBL lays the foundation for cultivating pro-environmentalism and sustainable behavior by fostering a sense of care and responsibility toward others. SBL’s prosocial education program encompasses social and emotional skills, knowledge, and dispositions to empower pupils to actively engage in and contribute to a more democratic, reciprocal, just, and sustainable society. This approach underscores the importance of education in shaping students’ mindsets and life orientations. By nurturing a sense of interconnectedness and responsibility for the well-being of others, SBL provides a promising avenue to transform education by building more sustainable educational systems, thus contributing to creating a more sustainable future. A qualitative case study, which consisted of 18 in-depth interviews and nine observations, examined the impact of an SBL-based teacher training program at an elementary school from 2020 to 2023. The results point to changes in teachers’ perceptions of their roles as social architects and, more specifically, as facilitators of social, emotional, and cognitive processes. The teachers gained recognition as meaningful adults from their students and transitioned to hold integral positions as part of a supportive and connected school community, associating with colleagues and parents. This study thus showcases patterns of socio-organizational communication that can unfold in a school influenced by the SBL approach. SBL’s emphasis on positive social relationships and empowering teachers as facilitators of holistic student development thus further reinforces its potential to transform education for a sustainable and thriving future.
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Netta Weinstein, Guy Itzchakov, Michael R. Maniaci
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Attitudes
Conversational artificial intelligence (AI) can be harnessed to provide supportive parasocial interactions that rival or even exceed social support from human interactions. High-quality listening in human conversations fosters social connection that heals interpersonal wounds and lessens loneliness. While AI can furnish advice, listening involves the speakers’ perceptions of positive intention, a quality that AI can only simulate. Can such deep-seated support be provided by AI? This research examined two previously siloed areas of knowledge: the healing capabilities of human interpersonal listening, and the potential for AI to produce parasocial experiences of connection. Three experiments (N = 668) addressed this question through manipulating conversational AI listening to test effects on perceived listening, psychological needs, and state loneliness. We show that when prompted, AI could provide high-quality listening, characterized by careful attention and a positive environment for self-expression. More so, AI’s high-quality listening was perceived as better than participants’ average human interaction (Studies 1–3). Receiving high-quality listening predicted greater relatedness (Study 3) and autonomy (Studies 2 and 3) need satisfaction after participants discussed rejection (Study 2–3), loneliness (Study 3), and isolating attitudes (Study 3). Despite this, we did not observe downstream lessening of loneliness typically observed in human interactions, even for those who were high in trait loneliness (Study 3). These findings clearly contrast with research on human interactions and hint at the potential power, but also the limits, of AI in replicating supportive human interactions.
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