Institutions, Anomie, and Violent Crime: Clarifying and Elaborating Institutional-Anomie Theory

A limited but accumulating body of research and theoretical commentary offers support for core claims of the “institutional-anomie theory” of crime (IAT) and points to areas needing further development. In this paper, which focuses on violent crime, we clarify the concept of social institutions, elaborate the cultural component of IAT, derive implications for individual behavior, summarize empirical applications, and propose directions for future research. Drawing on Talcott Parsons, we distinguish the “subjective” and “objective” dimensions of institutional dynamics and discuss their interrelationship. We elaborate on the theory’s cultural component with reference to Durkheim’s distinction between “moral” and “egoistic” individualism and propose that a version of the egoistic type characterizes societies in which the economy dominates the institutional structure, anomie is rampant, and levels of violent crime are high. We also offer a heuristic model of IAT that integrates macro- and individual levels of analysis. Finally, we discuss briefly issues for the further theoretical elaboration of this macro-social perspective on violent crime. Specifically, we call attention to the important tasks of explaining the emergence of economic dominance in the institutional balance of power and of formulating an institutional account for distinctive punishment practices, such as the advent of mass incarceration in the United States.

Violence, Crime, and Violent Crime

I propose a dual conceptualization of violent crime. Since violent crime is both violence and crime, theories of aggression and deviance are required to understand it. I argue that both harm-doing and rule breaking are instrumental behaviors and that a bounded rational choice approach can account for both behaviors. However, while some of the causes of harm-doing and deviance (and violent and nonviolent crime) are the same, some are different. Theories of crime and deviance cannot explain why one only observes individual and group differences in violent crime and theories of aggression and violence cannot explain why one observes differences in all types of crimes. Such theories are “barking up the wrong tree.”

Action Research and Learning Analytics in Higher Education

Teaching is a dynamic activity. It can be very effective, if its impact is constantly monitored and adjusted to the demands of changing social contexts and needs of learners. This implies that teachers need to be aware about teaching and learning processes. Moreover, they should constantly question their didactical methods and the learning resources, which they provide to their students. They should reflect if their actions are suitable, and they should regulate their teaching, e.g., by updating learning materials based on new knowledge about learners, or by motivating learners to engage in further learning activities. In the last years, a rising interest in ‘learning analytics’ is observable. This interest is motivated by the availability of massive amounts of educational data. Also, the continuously increasing processing power, and a strong motivation for discovering new information from these pools of educational data, is pushing further developments within the learning analytics research field. Learning analytics could be a method for reflective teaching practice that enables and guides teachers to investigate and evaluate their work in future learning scenarios. However, this potentially positive impact has not yet been sufficiently verified by learning analytics research. Another method that pursues these goals is ‘action research’. Learning analytics promises to initiate action research processes because it facilitates awareness, reflection and regulation of teaching activities analogous to action research. Therefore, this thesis joins both concepts, in order to improve the design of learning analytics tools. Central research question of this thesis are: What are the dimensions of learning analytics in relation to action research, which need to be considered when designing a learning analytics tool? How does a learning analytics dashboard impact the teachers of technology-enhanced university lectures regarding ‘awareness’, ‘reflection’ and ‘action’? Does it initiate action research? Which are central requirements for a learning analytics tool, which pursues such effects? This project followed design-based research principles, in order to answer these research questions. The main contributions are: a theoretical reference model that connects action research and learning analytics, the conceptualization and implementation of a learning analytics tool, a requirements catalogue for useful and usable learning analytics design based on evaluations, a tested procedure for impact analysis, and guidelines for the introduction of learning analytics into higher education.