Researching and Enacting Change in Postsecondary Education

Leveraging Instructors' Social Networks

Charles Henderson, Chris Rasmussen, Alexis Knaub, Naneh Apkarian, Alan James Daly, Kathleen Fisher, Kathleen Quardokus Fisher

• Publisher: Routledge
• Year: 2018
• Print ISBN: 9781138336872
• eBook ISBN: 9780429810176
• Edition: 1
• Topic: Education
• Subtopic: Education General

Calls to improve undergraduate STEM education have resulted in initiatives that seek to bolster student learning outcomes by promoting changes in teaching practices. Written by participants in a series of ground-breaking social network analysis (SNA) workshops, Researching and Enacting Change in Postsecondary Education argues that the academic department is a highly productive focus for the spread of new, network-based teaching ideas. By clarifying methodological issues related to SNA data collection and articulating relevant theoretical approaches to the topic, this book leverages current knowledge about social network theory and SNA techniques for understanding instructional improvement in higher education.

1
Introduction

Naneh Apkarian and Charles Henderson

There is no shortage of calls for change and improvement in postsecondary education. The broad purpose of this book is to understand both how to enact that change and how to study it. The authors come from a range of academic traditions, and the combined knowledge from our varied perspectives has led us here. While much of our independent work has focused on science, technology, engineering, and/or mathematics (STEM) education, we believe this text is relevant for change at the postsecondary department level in any discipline. The lessons learned from social network analysis can be applied to any system of people, and many aspects of department structure and pressures which we focus on in these chapters transcend disciplines.

The LERNUS Project

In 2016, the editors of this book organized two workshops for researchers interested in the use of social network analysis (SNA) to promote change in postsecondary education, funded by NSF (#1550990); this book grew out of that collaboration. The idea was to combine the knowledge and perspectives of individuals to advance research in this area, hence the title Linked Education Researchers of Networks in Undergraduate STEM, or LERNUS. All of the authors of chapters in this text participated in at least one of those workshops, and the entire LERNUS group contributed to the major ideas and themes herein. Chapters 2, 3, and 4 cover (more or less) the shared base LERNUS members brought to the first workshop. We were all concerned with the state of postsecondary education, understood change as a social process, had a basic understanding of the construct of a social network, and had seen K-12 and organizational science results which pointed to SNA as a promising approach in this area. Chapters 5, 6, and 7 represent some of the knowledge we developed through the LERNUS collaboration. A more comprehensive understanding of the relationship of SNA as methodology to theoretical underpinnings, the cataloging of varying instrumentation and methodology techniques, and the cross analysis of data from across studies have helped us all refine our thinking about this work. We hope that others who read this book will come away with new ways of thinking about the process of change in postsecondary education.

The Need for Change

In the US, there has been a strong focus on improving undergraduate STEM education. One of the oft-repeated motivations for this is economics. There is great need for STEM graduates in the workforce, especially as the workplace becomes increasingly technical and technological, but there is a dearth of STEM majors graduating from American colleges and universities (PCAST, 2012). Investigations of the gap, and in particular why undergraduate students who originally intend to pursue STEM degrees change their degree aims, have indicated that poor experiences in introductory STEM courses rather than poor performance are the main culprit (PCAST, 2012; Seymour, 2006; Seymour & Hewitt, 1997). Furthermore, these same investigations have revealed that students from historically underrepresented groups leave the sciences disproportionately more than those from groups already well represented in STEM fields. Thus, there is a need to improve students’ educational experiences in order to retain high-performing and interested students, especially from diverse backgrounds, who can then fill existing opportunities in STEM careers.

For decades, researchers in STEM education fields have explored the ways in which students learn particular content areas and pedagogical approaches that support deeper conceptual understanding and affinity for STEM fields (National Research Council, 2012). Across both STEM and non-STEM disciplines, there has also been a push to explore pedagogy that supports students with a wider range of identities than have traditionally persisted in postsecondary education. One general theme has emerged: active learning¹ or student-centered instructional strategies are better than lecture-based instructional strategies for a wide variety of desirable outcomes. Perhaps the most convincing evidence of this is Freeman et al.’s (2014) meta-analysis of 225 studies comparing pedagogy in science classrooms. Across multiple disciplines, student attrition decreased while, at the same time, student learning increased. There have also been studies which indicate that active learning narrows achievement and retention gaps for students from underrepresented groups (e.g., Kogan & Laursen, 2014). Despite the extensive evidence in support of student-centered or active learning approaches to education, these methods have not become widespread (Apkarian & Kirin, 2017; Brainard, 2007; NRC, 2012; Pol-lock & Finkelstein, 2008), and their use by instructors without support does not produce as positive results (Andrews, Leonard, Colgrove, & Kalinowski, 2011; Larsen, Glover, & Melhuish, 2015). Work must be done to better understand how and why pedagogical change is or is not taken up, and how best to support sustainable and productive adoption of improved pedagogy in postsecondary education.

Why Social Networks?

Historically, many change initiatives designed to improve undergraduate education focused on individual instructors; telling these instructors about new instructional strategies and encouraging them to use these strategies (e.g., Pollock & Finkelstein, 2008; Henderson, Dancy, & Niewiadomska-Bugaj, 2012). However, many now consider the academic department to be the core unit for creating change because of the social nature of knowledge construction (e.g., Austin, 2011; Wieman, Perkins, & Gilbert, 2010). There have been calls to use social networks in the planning and study of institutional change in postsecondary education, both implicitly through declarations of the importance of camaraderie and explicitly by those with exposure to its use in other fields. In particular, Kezar (2014) published a review of literature that makes convincing arguments for increased attention to the social structure of groups undergoing planned changes. In this book, we show how the tools and theories of SNA can be productively used in tandem with theories of learning and change to determine the current state of academic departments, uncover hidden social structures, target participants for involvement in change initiatives, and inform post-secondary education reform efforts to support quality teaching.

In Chapter 2, Henderson, Quardokus Fisher, and Beach discuss in more detail the current literature regarding change in postsecondary education settings. Their review indicates that creating sustainable change is a social process, requiring trust, camaraderie, and support. It has been shown that social ties influence the beliefs and behaviors of individuals. The value of good communication among multiple trusted parties is important for groups to function productively. Well-functioning groups consistently lead to desirable results in a wide variety of contexts. Simply put, social groups and their intricacies matter.

We do not expect readers to already be well-versed in social network theory. Therefore, Knaub and Henderson’s Chapter 3 provides a brief overview of some major features of social networks and network analysis. This is certainly not intended as a substitute for the many texts on networks and analysis, but rather as a primer. Many more comprehensive texts exist for those interested in conducting SNA (e.g., Kadushin, 2012; Scott, 2012; Wasserman & Faust, 1994). The goal of this chapter is more modest: to enable the reader to grasp the basics of social networks in sufficient detail to follow the discussions in the remaining chapters.

In Chapter 4, Mamas and Daly review K-12 SNA literature and identify some major themes among those works that can and should inform studies in postsecondary education. They identify the importance of both formal and informal social networks (and the extent to which these overlap), the quality as well as quantity of relationships among actors, collaboration among those in a community under study, and taking a systems perspective that considers individuals as part of a larger community and organization with contextual factors. The authors provide concrete examples of studies and results related to these themes in their chapter, which can serve as inspirational models for postsecondary education network researchers.

How Can We Use SNA in Higher Education?

Having seen what components and features make up a social network, and a review of prior results in the K-12 education context, Knaub, Henderson, Rasmussen, and Lo present four perspectives through which social networks can be viewed in Chapter 5. These theoretical perspectives are what give the constellations of actors and relationships real meaning. As with other types of research, theoretical perspectives inform the entirety of an empirical study, from the initial questions to design to methodology. This is also true of those with more practical matters: understanding the social network of a department and its impact on a change process is also dependent on theoretical assumptions about relationships and the development of practice. The structuralist perspective assumes that individual practices, behaviors, and beliefs are deterministic and based on those of the people they interact with. Social capitalism conceptualizes social ties as avenues through which resources of many different kinds are shared and accessed. The sensemaking perspective posits that information and ideas exist between people and are constructed through interactions. Using an identity perspective puts the focus on how individuals are perceived and why they might be more or less connected to others in their group.

Following the discussion of theories that can be leveraged alongside social networks, Skvoretz, Risien, and Goldberg in Chapter 6 describe methodological options for studying social networks in departments at postsecondary education institutions. This includes considerations for overall study design to ensure that appropriate data is collected for the researcher’s purposes. The authors of this chapter suggest that researchers consider mixed methods and the inclusion of qualitative data. Details of how to identify social ties are also discussed, highlighting the various benefits and constraints of different approaches for different contexts. Given the main thrust of this book, the majority of this discussion focuses on instrumentation for network data collection, which nowadays is often primarily done via electronic surveys.

The final substantive chapter of this book, Chapter 7, presents analyses of instructor discussion network data from real departments. These data come from multiple ongoing studies by authors of this book, but the comparisons presented in this chapter are original. In presenting their findings, Quardokus Fisher and Apkarian build on the previous chapters to discuss disparities between the studies and how the data were made comparable. This is intended to show how the information in this book can combine to produce results, and what those results can mean. The analysis across 22 STEM departments at multiple universities allows for some discussion of trends in both connectedness (or how much interaction is happening) and the distribution of ties (or who is participating in that interaction). Discrepancies in data collection methods and the non-representative nature of the samples mean that we cannot present this as “typical”; however, it is a collection of data which others may compare to their own results.

Goals for the Reader

This book is aimed at those who wish to study and/or enact change in post-secondary education departments, couched in the context of a nationwide push for pedagogical improvement. We hope that the utility and value of SNA in these endeavors will rapidly become clear and compelling to the reader. We also hope that we are able to present the basics of carrying out network-informed research in postsecondary education settings, in order to demystify the process and grow the ranks of those doing this work.

For those primarily interested in researching change in postsecondary education, we situate SNA in the broader change and education literature and present details of methodology. Our intention is to provide you with the basics of SNA and how it can be used in this research context, so that you can determine whether or not it is an appropriate tool for your particular research purpose.

For those primarily interested in enacting change in postsecondary education, we present lessons from a spectrum of contexts. Our intention is to provide you with more ways to think about the context in which change is to occur and what factors may affect the implementation and sustainability of that change. Knowledge of typically hidden social ties can be a valuable tool for change agents.

Note

1. Here we are referring broadly to “active learning” as pedagogical strategies that promote student inquiry into content. These strategies go by a variety of names, such as inquiry-oriented learning, process-oriented guided inquiry learning, inquiry-based learning, student-centered active learning environment with upside-down pedagogies, and others.

References

Andrews, T. M., Leonard, M. J., Colgrove, C. A., & Kalinowski, S. T. (2011). Active learning not associated with student learning in a random sample of college biology courses. Cell Biology Education, 10 (4), 394–405. https://doi.org/10.1187/cbe.11-07-0061

Apkarian, N., & Kirin, D. (2017). Progress through calculus: Census survey technical report. Mathematical Association of America. Retrieved from http://bit.ly/PtC_Reporting

Austin, A. 2011. Promoting evidence-based change in undergraduate science education. A white paper commissioned by the National Academies National Research Council Board on Science Education. https://sites.nationalacademies.org/cs/groups/dbassesite/documen...

Table of contents

• Cover
• Title
• Copyright
• Contents
• Foreword
• Acknowledgements
• 1 Introduction
• 2 Change in Higher Education
• 3 Social Network Terminology
• 4 Social Network Analysis in K-12 Settings: Review, Implications, and New Directions for Higher Education
• 5 Four Perspectives for Interpreting Social Networks
• 6 Network Measurement and Data Collection Methods in Higher Education: Practices and Guidelines
• 7 Instructor Discussion Networks Across 22 STEM Departments
• 8 Coda
• Author Biographies
• Index