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While much research has shown that asynchronous learning networks (ALNs) can produce learning equivalent to face‐to‐face (FTF) classrooms, there has been little research that explicitly explores similarities and differences between the learning processes that occur in ALN and FTF activities. This study used a content analytic framework (derived primarily from previous work of Anderson, Archer, Garrison, and Rourke) to analyze transcripts from eight case study discussions, four FTF and four ALN. While previous authors developed a model that studies cognitive, social, and teaching processes in ALN discussions, the current scheme also considers characteristics of the discourse process. The findings provide evidence that ALNs generate high levels of cognitive activity, at least equal to, and in some cases superior to, the cognitive processes in the FTF classroom. The findings also suggest that students assume some aspects of the teacher's role in ALNs, and that student‐to‐student interactions contain a greater proportion of high‐level cognitive indicators than do student‐to‐teacher interactions.

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This article establishes and addresses opportunities for ethics integration into Machine-learning (ML) courses. Following a survey of the history of computing ethics and the current need for ethical consideration within ML, we consider the current state of ML ethics education via an exploratory analysis of course syllabi in computing programs. The results reveal that though ethics is part of the overall educational landscape in these programs, it is not frequently a part of core technical ML courses. To help address this gap, we offer a preliminary framework, developed via a systematic literature review, of relevant ethics questions that should be addressed within an ML project. A pilot study with 85 students confirms that this framework helped them identify and articulate key ethical considerations within their ML projects. Building from this work, we also provide three example ML course modules that bring ethical thinking directly into learning core ML content. Collectively, this research demonstrates: (1) the need for ethics to be taught as integrated within ML coursework, (2) a structured set of questions useful for identifying and addressing potential issues within an ML project, and (3) novel course models that provide examples for how to practically teach ML ethics without sacrificing core course content. An additional by-product of this research is the collection and integration of recent publications in the emerging field of ML ethics education.

In this paper we investigate group maintenance behavior in community-based Free/Libre Open Source Software (FLOSS) development teams. Adopting a sociolinguistic perspective, we conceptualize group maintenance behavior as interpersonal communication tactics-specifically, social presence and politeness tactics-that help maintain relationships among group members.Developer email messages were collected from two FLOSS projects with different development status and content-analyzed to identify frequently-used group maintenance tactics. We then compared the two projects on the group maintenance tactics used, finding differences that reflect changes in the project work practices. Our work contributes theoretically to FLOSS research and has practical implications for FLOSS practitioners.

With the increasing availability of synchronous video-based breakout rooms within online courses, a growing need exists to understand how to best leverage this technology for enhanced online education. To help address this challenge, this paper reports on a case study that explored student activity within online video-based breakout rooms via a Structured Paired Activity (SPA) methodology. SPA, which is adapted from the concept of Paired Programming, defines a general way to structure roles and activities for the participants within the breakout room. Initial qualitative results suggest that the use of SPA in online breakout rooms increases student engagement and process effectiveness. These results are potentially applicable to a broad range of web-based synchronous online courses.