Angela E. B. Stewart

Socio-cultural context influences how learners engage with, experience, and make sense of learning. As such, Learning Analytics systems must intentionally account for this context in their design and interpretation. While many researchers in the field are already addressing these issues, sometimes implicitly or under different frameworks, we argue for a more unified focus on socio-cultural context as a guiding construct. Drawing on scholarship from education, sociology, anthropology, and psychology, we define socio-cultural context in terms of power, norms, and identity. Through two case studies of our own work on collaboration and engagement analytics, we illustrate how overlooking socio-cultural context can lead to incomplete systems that do not account for the variety of ways students might show up in learning spaces. We build on existing work and propose socio-cultural context as an organizing lens for future research. Doing so enables interdisciplinary collaboration and design that ultimately ensures analytics better serves learners.

Collaborative problem solving (CPS) is viewed as an essential 21st century skill for the modern workforce. Accordingly, researchers have been investigating how to conceptualize, assess, and develop pedagogical approaches to improve CPS. These efforts require theoretically-grounded and empirically-validated frameworks of CPS which have been emerging over the past decade with various levels of validity data. The present paper focuses on validating the generalized competency model (GCM) of CPS with respect to predicting individual learning outcomes following CPS among triads. The GCM consists of three main facets–constructing shared knowledge, negotiation/coordination, and maintaining team function–mapped to behavioral indicators (i.e., observable evidence). It hypothesizes that scores on all three facets should positively predict CPS outcomes, including group-to-individual learning transfer. We tested this hypothesis in a study where 249 students who comprised 83 triads engaged in collaborative gameplay with the Physics Playground game environment remotely via videoconferencing. We found that the only CPS facet predicting individual physics learning was maintaining team function, after accounting for pretest scores, students’ perceptions of team collaboration, and their perceived physics self-efficacy. This facet was also the only significant predictor of individual learning regardless of how facet scores were computed (i.e., reverse coding of negative indicators, separating the sums of positive and negative indicators, and no reverse coding of negative indicators). Implications for the GCM and other CPS frameworks are discussed.

Social computing education is gaining traction across computer science and information science disciplines, yet lacks a standardized pedagogical framework for topics to teach, as well as strategies for engaging students. This workshop aims to convene experts in CSCW to develop a cohesive framework for undergraduate and graduate social computing courses. Emphasizing ethical and cultural considerations, the workshop will explore core topics spanning sociological, psychological, technical, and design aspects of social computing. Through interactive sessions, attendees will collaboratively shape a curricular framework that is responsive to diverse country contexts and ethical imperatives. At the conclusion of the workshop, we anticipate we will publish a framework for topics and pedagogical approaches to social computing, as well as a repository of existing courses.

Teaching is one of many professions for which personalized feedback and reflection can help improve dialogue and discussion between the professional and those they serve. However, professional development (PD) is often impersonal as human observation is labor-intensive. Data-driven PD tools in teaching are of growing interest, but open questions about how professionals engage with their data in practice remain. In this paper, we present ClassInSight, a tool that visualizes three levels of teachers’ discussion data and structures reflection. Through 22 reflection sessions and interviews with 5 high school science teachers, we found themes related to dissonance, contextualization, and sustainability in how teachers engaged with their data in the tool and in how their professional vision, the use of professional expertise to interpret events, shifted over time. We discuss guidelines for these conversational support tools to support personalized PD in professions beyond teaching where conversation and interaction are important.

This panel aims to generate conversation toward creating a more equitable CHI. In recognizing our community’s hard work thus far, this panel seeks to engage panelists and participants with thought-provoking questions about their interpretation of what allyship means to them. We will consider both formal definitions as well as participants’ personal views. All attendees (including panelists) will be encouraged to discuss the experiences and goals to garner and promote actionable items for the community. We intend to have an open dialogue on allyship, diversity, equity, and inclusion to achieve a CHI for all.