Workshop Paper

Towards a Socio-technical System of Culturally Responsive Teaching: The Interplay between Individuals, Communities, and Resources

Culturally Responsive Teaching (CRT) is a set of instructional practices that acknowledges and incorporates students’ identities and backgrounds into the classroom in a way that makes learning more effective and relevant for culturally, rhetorically, and ethnically diverse students. As classrooms becoming more diverse, recognizing and celebrating students’ cultural traits and characteristics are becoming increasingly effective to cultivating positive educational outcomes.

Toward Understanding Civic Data Bias in 311 Systems: An Information Deserts Perspective

While civic technologies for public issues and services such as 311 systems are widely adopted in many U.S. cities, the impact of the emerging civic technologies and their datalevel dynamics are unclear. Because the provision patterns of civic issues to technological systems are different across neighborhoods and populations, it is difficult for city officials to understand whether the provided data itself reflects civic issues. Also, the disparities in the information provided to civic technologies in different neighborhoods may exacerbate the existing inequality.

Heuristics for Assessing Computational Archival Science (CAS) Research: The Case of the Human Face of Big Data Project

Computational Archival Science (CAS) has been proposed as a trans-disciplinary field that combines computational and archival thinking. To provide grounded evidence, a foundational paper explored eight initial themes that constitute potential building blocks. In order for a CAS community to emerge, further studies are needed to test this framework. While the foundational paper for CAS provides a conceptual and theoretical basis of this new field, there is still a need to articulate useful guidelines and checkpoints that validate a CAS research agenda.

This Is Not Just a Café: Toward Capturing the Dynamics of Urban Places

Social media has provided a huge amount of user-generated data in capturing urban dynamics. Among them, place-level human behavior has been largely detected through people’s check-in records at certain places. Conventionally, places are characterized by a set of pre-defined features, often specified by the owner of the places. In this paper, we argue that capturing socially-meaningful features and dynamics of an urban place may also be done by analyzing human activity traces.