Learning analytics dashboards (LADs) are becoming more prevalent in higher education to help students, faculty, and staff make data-informed decisions. Despite extensive research on the design and implementation of LADs, few studies have investigated their relation to justice, equity, diversity, and inclusion (JEDI). Excluding these issues in LAD research limits the potential benefits of LADs generally and risks reinforcing long-standing inequities in education. We conducted a critical literature review, identifying 45 relevant papers to answer three research questions: how is LAD research improving JEDI, ii. how might it maintain or exacerbate inequitable outcomes, and iii. what opportunities exist in this space to improve JEDI in higher education. Using thematic analysis, we identified four common themes: (1) participant identities and researcher positionality, (2) surveillance concerns, (3) implicit pedagogies, and (4) software development resources. While we found very few studies directly addressing or mentioning JEDI concepts, we used these themes to explore ways researchers could consider JEDI in their studies. Our investigation highlights several opportunities to intentionally incorporate JEDI into LAD research by sharing software resources and conducting cross-border collaborations, better incorporating user needs, and centering considerations of justice in LAD efforts to improve historical inequities.

Online discussion boards serve an important role in college courses by facilitating social learning and student support. However, the student experience and learning outcomes are likely to depend on the structure of student engagement with one another and the teaching staff. Using social network analysis, we investigated the network structure of 616 course discussion boards at a selective research university. We first examine variation in discussion boards using a wide range of composite metrics from the social network analysis literature. We then develop a typology of discussion board networks using principal component analysis and k-Means clustering to arrive at three clusters: dense discussion; distinct discussion groups; and discussion brokers and hubs.

Learning analytic dashboards (LADs) have become more prevalent in higher education to help students, faculty, and staff make data-informed decisions. Despite extensive research on the design and usability of LADs, few studies have examined them in relation to issues of diversity, equity, and inclusion. We conducted a critical literature review to address three research questions: How does LAD research contribute to improving diversity, equity, and inclusion? How might LADs contribute to maintaining or exacerbating inequitable outcomes? And what future opportunities exist in this research space? Our review showed little use of LADs to address or improve issues of diversity, equity, and inclusion in the literature thus far. We argue that excluding these issues from LAD research is not an isolated oversight and it risks reinforcing existing inequities within the higher education system. We argue that LADs can be designed, researched, and deployed intentionally to advance equitable outcomes and help dismantle inequities in education. We highlight opportunities for future LAD research to address issues of diversity, equity, and inclusion.