Spiro Maroulis

Complex Systems View of Educational Policy Research

Agent-based modeling and network analysis can help integrate knowledge on “micro-level” mechanisms and “macro-level” effects. Education researchers have struggled for decades with questions such as “why are troubled schools so difficult to improve?” or “why is the achievement gap so hard to close?” We argue here that conceptualizing schools and districts as complex adaptive systems, composed of many networked parts that give rise to emergent patterns through their interactions (1), holds promise for understanding such important problems. Although there has been considerable research on the use of complex systems ideas and methods to help students learn science content (2), only recently have researchers begun to apply these tools to issues of educational policy.

What Would It Take to Change an Inference? Using Rubin’s Causal Model to Interpret the Robustness of Causal Inferences:

We contribute to debate about causal inferences in educational research in two ways. First, we quantify how much bias there must be in an estimate to invalidate an inference. Second, we utilize Rubin’s causal model to interpret the bias necessary to invalidate an inference in terms of sample replacement. We apply our analysis to an inference of a positive effect of Open Court Curriculum on reading achievement from a randomized experiment, and an inference of a negative effect of kindergarten retention on reading achievement from an observational study. We consider details of our framework, and then discuss how our approach informs judgment of inference relative to study design. We conclude with implications for scientific discourse.

The Role of Social Network Structure in Street-Level Innovation

In considering how peer relationships can aid street-level bureaucrats in doing their jobs, existing literature has emphasized the importance of peers in providing the social and emotional support required to deal with uncertain and stressful working situations. By applying a social network perspective to examine the innovative behavior of a sample of teachers in a large urban high school, this article highlights the importance of an additional factor: the location of a frontline worker’s position in the larger structure of social connections within the organization. In particular, multilevel statistical models reveal a positive association between the extent to which an experienced teacher is located in a network position that bridges across different organizational subgroups and his or her level of innovation, suggesting that experienced frontline workers may benefit from the information diversity that comes from having multiple and diverse social contacts. More generally, the study highlights the value of complementing individual and organizational insights with network-level perspectives for understanding the discretionary behavior of frontline professionals.

Interpreting School Choice Treatment Effects: Results and Implications from Computational Experiments

Providing parents and students a choice to attend schools other than their assigned neighborhood school has been a leading theme in recent education reform. To evaluate the effects of such choice-based programs, researchers have taken advantage of the randomization that occurs in student assignment lotteries put in place to deal with oversubscription to popular schools and pilot programs. In this study, I used an agent-based model of the transition to school choice as platform for examining the sensitivity of school choice treatment effects from lottery-based studies to differences in student preferences and program participation rates across hypothetical study populations. I found that districts with higher participation rates had lower treatment effects, even when there were no differences in the distributions of school quality and student preferences between districts. This is because capacity constraints increasingly limited the amount of students who are able to attend the highest quality schools, causing the magnitude of the treatment effect to fall. I discuss the implications of this finding for interpreting the results of lottery-based studies involving choice schools.

CSCW and education: viewing education as a site of work practice

Educational institutions, whether they are formal or informal, present a work environment in which technology, and social and cultural interactions mediate unfolding work. The interaction between CSCW and the work of education can hold great potential for both improving the educational institutions as well as providing greater explanatory power to CSCW theories that support the work of groups and the designs that are instantiated in those theories. The goal of this workshop is to build a community interested in the intersection between CSCW and educational work practice.

Rethinking Social Welfare Fraud from a Complex Adaptive Systems Perspective

Despite efforts to control fraud in public assistance programs, the perception and realities of the problem persist. Serious barriers related to data collection and research methods impede the understanding of how and why fraud occurs, thereby limiting options for improving program integrity. This article argues that based on a complex adaptive systems (CAS) perspective, social welfare fraud can be understood as a collective outcome emerging from repeated interactions among stakeholders during the routinized business processes of public assistance programs. While dealing with fraud, great attention must be paid to how it occurs and persists, not just how serious the problem is or who commits these crimes.