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An essential part of entrepreneurial activity is the drafting and narrating of an entrepreneurial vision. This study is premised on the observation that entrepreneurial groups form an interaction arena for the practice of imagining the future and asks how the content of entrepreneurial visions is shaped by the conditions of the group. Taking an entrepreneurship-as-practice lens, which we enrich with sociological theory on the future (Beckert) and small groups (Fine), we engage in an in-depth case study of 12 entrepreneurial groups. We show how the content of entrepreneurial visions is configured by four elements (i.e., fictional expectation for the business or the group; future orientation that is continuing or divergent) and name two group conditions (i.e., role confidence and hierarchical congruence) that direct their configuration. We propose that lacking role confidence can impede thinking about the future of a business and that narrative hierarchies that challenge structural hierarchies can open a window for divergent future orientation. This study contributes to a novel theoretical understanding of where entrepreneurial visions come from by emphasizing politics of expectations within groups and calling to consider group conditions as a relevant context for entrepreneurial visions.

In this article, we reflect upon the combination of crowd science and online teaching, which we refer to as Crowd Science infused Learning. We discuss Crowd Science infused Learning's conceptual design and its viability in sociology and related disciplines. For this purpose, our research project ‘Data Traces’ serves as an empirical case. In the project, we developed an online platform that provided a 45-minute teaching unit, training students in using different forms of digital data: websites, newspaper articles, and administrative register data. Afterwards, students were assigned to predefined, small-scale research tasks contributing to a real-world research project on the social relations in entrepreneurial groups. By completing the tasks, the students could apply their knowledge, gain insights, and contribute actively to an ongoing research project. This combination links students' learning experience with the collection of data for research purposes. We also implemented game elements in the platform's design to support students' motivation. After a brief outline of the Data Traces Project's chronology and key conceptual decisions, the article focuses on a critical discussion of the combination of crowd science and online teaching. Despite significant challenges, we believe that Crowd Science infused Learning is a promising approach and identify opportunities and conditions for a successful combination of crowd science and online teaching.