Virginia Snodgrass Rangel

High Stakes Accountability and Policy Implementation: Teacher Decision Making in Bilingual Classrooms in Texas

This article contributes to an emerging body of literature on the impact of high stakes testing accountability policies on implementation and teaching practice. It uses a theory of implementation, sense-making, to highlight the process by which policy and context shape teacher decision making. We focus on teachers in bilingual classrooms in an urban district in Texas where we found that teachers make decisions in an environment that exerts both formal and informal pressures to limit the curriculum they offer their students and privilege test preparation. Teachers struggle to reconcile their context, constituted by their students’ specific pedagogical and linguistic needs, with the pressures of their high stakes testing environment.

Putting School Reform in Its Place Social Geography, Organizational Social Capital, and School Performance

For decades, policymakers and researchers have struggled to understand the reasons that schools in disadvantaged contexts have relatively more trouble responding successfully to reform demands. This analysis extends theory regarding the challenges of school change in disadvantaged contexts by illustrating how the internal resources that schools rely on to respond to external policy demands can be affected by the social contexts in which they are embedded. The article draws on data from a study of five high poverty high schools’ responses to the pressures of Texas’ high stakes accountability system. The case study data illustrate how a school’s social context can precipitate instability in some schools and relative stability in others, how organizational stability in turn can affect schools’ organizational social capital, and how organizational social capital can influence schools’ ability to respond to external policy demands.

STEMscopes: contextualizing learning analytics in a K-12 science curriculum

In this paper, we discuss a scalable approach for integrating learning analytics into an online K-12 science curriculum. A description of the curriculum and the underlying pedagogical framework is followed by a discussion of the challenges to be tackled as part of this integration. We also include examples of data visualization based on real student and teacher data. With more than one million students and fifty thousand teachers using the curriculum, a massive and rich dataset is continuously updated. This repository depicts teacher and students usage of an inquiry-based science program, and offers exciting opportunities to leverage research to improve both teaching and learning. The growing dataset, with more than a hundred million items of activity in six months, also poses technical challenges such as data storage, complex aggregation and analysis with broader implications for pedagogy, big data, and learning.

Toward a New Approach to the Evaluation of a Digital Curriculum Using Learning Analytics

Abstract Understanding how an educational intervention is implemented is essential to evaluating its effectiveness. With the increased use of digital tools in classrooms, however, traditional methods of measuring implementation fall short. Fortunately, there is a way to learn about the interactions that users have with digital tools that are embedded into the technologies themselves: user data. The purpose of this article is to outline ways in which researchers can harness learning analytics and user data to gain a deeper understanding of the implementation of digital innovations and their impact on teaching and learning. We discuss four considerations for the integration of learning analytics and user data in implementation research, and we provide an example of integration from an evaluation of a digital science curriculum, STEMscopes.

Teachers’ Sensemaking and Data Use Implementation in Science Classrooms

Accountability policies assume that educators will use student data to improve student learning, but data use in practice has turned out to be harder than theorized. The purpose of this article was to examine how science teachers in Grades 5 to 8 used data in their classrooms. Utilizing sensemaking theory, we found that teachers decided how to use data based on district and school policies and expectations around assessment and data use, balancing those messages with their own understandings of science education. In practice, this led to the privileging of certain kinds of assessment and data use at the expense of others.

A learning analytics approach to characterize and analyze inquiry-based pedagogical processes

Here we describe the use of learning analytics (LA) for investigating inquiry-based science instruction. We define several variables that quantify curriculum usage and leverage tools from process mining to examine inquiry-based pedagogical processes. These are initial steps toward measuring and modeling fidelity of implementation of a science curriculum. We use data from one school districts use of an online science curriculum (N=1,021 teachers and nearly 330,000 page views).

A descriptive analysis of instructional coaches’ data use in science

ABSTRACT A key assumption of accountability policies is that educators will use data to improve their instruction. In practice, however, data use is quite hard, and more districts are looking to instructional coaches to support their teachers. The purpose of this descriptive analysis is to examine how instructional coaches in elementary and middle school science across 3 school districts worked with science teachers around data use. Science teachers and instructional coaches were interviewed about their data use practices and preferences. The findings highlight that coaches play diverse roles in supporting teachers, and that teachers’ data use practices closely align with coaches’ practices and preferences. The discussion concludes with implications for our understanding of data use in specific content areas and for future research.