Our very own DLIS Faculty will be presenting at the competitive ASIS&T conference next week in Vancouver! Below are titles and panel information about each presentation. For more information and a full program please visit https://www.asist.org/am18/ .
Faculty Member: Angela Murillo, Ph.D.
Palmer, C., Weber, N., Greenberg, J., Lin X., Oh, S., Howison, J., Murillo, A.P. (2018).
Confronting the expanse of data education: From local open data to global cyberinfrastructure.
As the demand for data science and data-intensive capabilities grows in all sectors, educators in schools of information and library and information science are working to deepen and expand their programs to meet workforce expectations. This panel will examine current trends and investments in data education and professionalization, with an emphasis on the unique contributions information professionals bring to the data workforce. Educators will present on current initiatives that represent the breadth and complexity of preparing information professionals for work in data intensive environments. Their unique approaches anticipate and respond to workforce demand, address significant educational challenges, and offer models for making progress within the varying contexts of schools in different regions of the U.S. and Asia. Half of the session will be reserved for audience engagement designed to leverage and share the wealth of experience of the educators and students in attendance. The exchange will generate ideas about new directions and successful approaches that educators can apply to set priorities, position their programs, and collaborate to enrich and provide leadership in data education.
*It’s worth noting that this panel represents five different programs. We will be discussing the various ways we are addressing the demand and need for data science and date-intensive education in information and LIS schools.
Faculty Member: Kyle Jones, Ph.D.
Jones, K. M. L., Crooks, R., McCoy, C., & VanScoy, A. (2018). Contexts, critiques, and consequences: A discussion about educational data mining and learning analytics.
The capture, aggregation, and analysis of student data is becoming ubiquitous at all levels of education—from primary to post-secondary—as institutions increase their adoption of information technologies to serve administrative and educational ends. In part, this has led to a growing interest among education scientists and administrators in strategically mining and analyzing troves of data in order to uncover student behaviors and intervene in student life. As is the case in other contexts where actors are pursuing Big Data’s supposed benefits, educational data mining is fraught with moral, ethical, and political conflict. The panel is composed of four researchers who analyze and critique educational data mining practices and learning analytics initiatives in particular micro- and macro-contexts, including academic libraries and professional advising, urban schools, graduate-level online learning, and higher education generally. Each panelist also represents a unique conceptual background, pulling from work in information ethics and policy, critical data studies, documentation studies, and higher education policy to empirically analyze and critically evaluate tools, systems, practices, policies, and values. Through their individual but thematically intertwined perspectives, the panelists will present their research and lead audience members in discussion.
Faculty Member: Ayoung Yoon, Ph.D.
MLIS Student: Paula McNally
Yoon, A., Copeland, A., & McNally, P. (accepted).
Empowering communities with data: Role of data intermediaries for communities’ data utilization.
Data have significant potential to address current societal problems not only at the federal and state levels, but also in smaller communities, in neighborhoods, and in the lives of individuals. While the proposition for this potential is that data are and will be shared with and reused by and for communities at different levels, not all data are not systematically or routinely shared for reuse with communities due to social, structural and technical infrastructure barriers. Data intermediary organizations can play a significant role in removing existing barriers while unlocking the potential of data for all, particularly for communities with limited human or financial resources, limited access to existing data infrastructures, and underserved populations. Considering the significance of the data intermediary organizations on local communities, this study aims to explore the role of intermediaries that usually facilitate community members/organizations’ data utilization. The findings of this study reveal that data intermediary organizations play four major roles that are crucial in communities’ data utilization: (1) democratizing data, (2) adding value to existing data, (3) enhancing communities’ data literacy, and (4) building communities’ data capacity. This study has several important implications to offer a solution to overcome the challenges of data reuse at the local level.
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