Educational Data Crossroads: Data Literacy for Data-Driven Decision Making in Postsecondary Education

Abstract

Purpose

This paper discusses how educational policies have shaped the development of large-scale educational data and reviews current practices on the educational data use in selected states. Our purposes are to: (1) analyze the common practice and use of educational data in postsecondary education institutions and identify challenges as the educational crossroads; (2) propose the concept of Data Literacy (DL) for teaching (Mandinach & Gummer, 2013a) and its relevance to researchers and stakeholders in postsecondary education; and (3) provide future implications for practices and research to increase educational DL among administrators, practitioners, and faculty in postsecondary education.

Design/methodology/approach

We used two guiding conceptual frameworks to analyze the common practice and use of educational data in postsecondary education institutions and identify challenges as the educational crossroads. First, we used the 4Vs of Big Data by Rajan (2012) to examine the misalignment between the policy mandate and the practices. The elements of the 4Vs of Big Data – volume, velocity, variety, and veracity – help us to depict how Big Data enables educators to organize, store, manage, and manipulate vast amounts of educational data at the right moment and at the right time. Second, we used the conceptual framework for DL proposed by Gummer and Mandinach (in press). They interpret DL “as the collection, examination, analysis, and interpretation of data to inform some sort of decision in an educational setting” (p. 1, in press).

Findings

Using the guiding frameworks, we identified four educational data crossroads as follows:

Crossroad 1: Unintended Increase in Workload Volume;

Crossroad 2: Unrealistic Expectations of Data Velocity;

Crossroad 3: Data Variety in Silos; and

Crossroad 4: Data Veracity and Policy Agenda Mismatch.

In this paper, we explain each of these crossroads in more detail with some examples.

Originality/value of the paper

Much of the existing body of literature, exemplary practices, as well as federal and state funding has been focused on K-12 education contexts. In this paper, we identify current practices and challenges of educational data in the institutions of higher education. Additionally, this paper presents the application of the exemplary practices of data literacy development in postsecondary education and implications for future practices of data literacy development in postsecondary education.

Citation

Starobin, S.S. and Upah, S. (2014), "Educational Data Crossroads: Data Literacy for Data-Driven Decision Making in Postsecondary Education", The Obama Administration and Educational Reform (Advances in Education in Diverse Communities, Vol. 10), Emerald Group Publishing Limited, Leeds, pp. 141-170. https://doi.org/10.1108/S1479-358X20130000010007