Workshop Focus Details

Equity-centered R&D: Why we need it and how to do it

Research and Development (R&D) Processes. 

One of the core aspects of the LA community is designing new tools for teachers and students – often as part of research and development (R&D) cycles, where the ultimate goal is to create new tools (i.e. dashboards), interventions, or improvements. The research and development processes featured at LAK, however, tend to only involve a relatively narrow set of voices in this process overall. This can mean that students and teachers are often not deeply woven into the R&D process, or their various identities are not considered. Although there are some exceptions to this – especially in very recent years, this has not historically been the case: for example, Williamson and Kizilcec (2022) found that diversity, equity, and inclusion were rarely considered in the designs of an LA dashboard (i.e. considering demographics of the dashboard was designed for, etc.) – let alone be included as participants in the design. Further, studies do not typically consider, for example, representation of gender identity, racial/ethnic identity, socio-economic background, or other ways that samples are representative of a larger population unless the research question(s) require attention to these dimensions. 

Beyond considering the representation of participants in data sets, the majority of studies in learning analytics do not raise questions of access (opportunity to engage or learn), other systemic/infrastructure factors, or situational power dynamics that can impact students’ experiences and behaviors when considering achievement outcomes. Moreover, while some studies have considered the learning setting as a mediator of student learning processes and outcomes (e.g., via the lens of tools or resources; Gašević, Dawson, Rogers & Gasevic (2016)), few examine the cultural aspects of the learning context as key design considerations. Implications of these omissions as part of field-wide theoretical advancement or for the development of educational products are to continue to systematically exclude historically marginalized students and participants in the contributions of the learning analytics community.

Equity-centered R&D.

Although it is important for the learning analytics community to center equity in the formation of research questions across the field, employing methods that are designed with equity in mind is a field-wide shift that can increase the relevance of the community’s collective work. As part of her work in mathematics education, Rochelle Gutierrez’s (2012) framework defines 4 dimensions of equity that researchers can consider in designing studies; they include access (the tangible resources that students have available to them to participate in [learning]), achievement (how student outcomes are defined and whether/why there are systemic gaps in those outcomes), identity (students’ personal, cultural or linguistic capacities), and power (who has ‘voice’, whose knowledge counts, etc). Haynes and colleagues (2020) offer guidance to researchers to consider identity from a more complex perspective, one of intersectionality, as a means to reflect on unexamined biases in our methods. Among other approaches, they call for researchers to use a critical lens to uncover micro- and macro-level power relations and to explicitly address how those power relationships shape their methods. They ask researchers to critique their own positionality and biases and to explicitly name the strategies used to disrupt the ways that power has shaped the research study methods.

Taking on equity as part of our methods does not require refocusing our research questions or professional trajectories whole cloth, but does require that we attend to the impacts of our methodological choices as part of the larger R&D enterprise.

The workshop organizers invite you to find out more about the equity-centered R&D work happening as part of the AIMS Collaboratory.