Using Student Samples in Criminological Research

Professors have long relied on the assistance of their students in various aspects of the research process. For example, students often contribute in their role as research assistants and as co‐authors on scholarly papers and presentations. They also participate in another important way—as samples in their professors’ research projects. In criminology and criminal justice, student samples are often used in behavioral studies, tests of criminological theories, pilot tests of methodologies, and in evaluating attitudes toward crime and justice issues. This article provides an overview of the types of studies that have used students as samples in criminological research. Attention is given to the strengths and weaknesses of using such an approach, and implications for continuing to use students in criminological research are discussed.     

Considerations for Faculty Preparing to Develop and Teach Online Criminal Justice Courses at Traditional Institutions of Higher Learning

Criminal justice programs at traditional institutions of higher learning have been moving toward offering courses online and, in some cases, placing entire programs online for the better part of the past decade. In competition with for‐profit institutions, many traditional colleges and universities have expanded their distance education programming to include online courses and programs to attract students. As a result, the number of criminal justice students has increased, as have the profits for home institutions. With this growth in the online education market, the criminal justice faculty member has been thrust, willingly or unwillingly, into the world of online teaching—a method of instruction foreign to many instructors. From the authors’ experience at their current (and in the case of the lead author a second) institution, this paper addresses many issues that must be considered by faculty members before embarking on this type of time‐intensive initiative.     

A Study of the Use of Ontologies for Building Computer-Aided Control Engineering Self-Learning Educational Software

This paper describes research on the use of knowledge models (ontologies) for building computer-aided educational software in the field of control engineering. Ontologies are able to represent in the computer a very rich conceptual model of a given domain. This model can be used later for a number of purposes in different software applications. In this study, domain ontology about the field of lead–lag compensator design has been built and used for automatic exercise generation, graphical user interface population and interaction with the user at any level of detail, including explanations about why things occur. An application called Onto-CELE (ontology-based control engineering learning environment) uses the ontology for implementing a learning environment that can be used for self and lifelong learning purposes. The experience has shown that the use of knowledge models as the basis for educational software applications is capable of showing students the whole complexity of the analysis and design processes at any level of detail. A practical experience with postgraduate students has shown the mentioned benefits and possibilities of the approach.     

Ethical Issues Affecting Human Participants in Community College Research

Reverse transfer students, those students who matriculated at four-year colleges and then transferred to two-year colleges, have been enrolling in community colleges since at least the 1960s. Consisting of both undergraduate reverse transfers and post-baccalaureate reverse transfers (individuals who already have at least a bachelor s degree), these students represent at least 16 % of community college enrollments nation-wide. A concern about the admission of reverse transfers is that they may take enrollment spaces, particularly in selective programs, at the expense of potential students with no previous college experience and with weaker academic backgrounds. Analysis of documents written about reverse transfers indicates that their enrollment has been justified under a variety of rationales, including providing a second chance for these individuals in school and in the job market.     

Invisible and Indispensable: Parttime Teachers in California Community Colleges

Abstract

Although parttime instructors constitute a substantial portion—often a majority—of community college faculties, they are accorded a low status on campus, with less than half the salary and none of the benefits of fulltime faculty members. This study points up a number of misconceptions that administrators have been using to justify discriminatory treatment of parttime teachers.     

Causal Attributions for Success or Failure of Students in College Algebra

Research in the field of attribution theory and academic achievement suggests a relationship between a student's attributional style and achievement. Theorists and researchers contend that attributions influence individual reactions to success and failure. They also report that individuals use attributions to explain and justify their performance. Studies in mathematics education identify attribution theory as the theoretical orientation most suited to explain academic performance in mathematics. This study focused on the relationship among a high risk course, low success rates, and attribution by examining the difference in the attributions passing and failing students gave for their performance in College Algebra. Students from a large urban community college in South Florida (n = 410) self-reported their performance on an in-class test by providing open-ended attribution statements to explain the cause of their performance. They then attributed their performance along the dimensions of locus of causality, stability, personal controllability, and external controllability using the Causal Dimensions Scale (CDSII). The open-ended attribution statements were coded in relation to ability, effort, task difficulty, and luck and compared using a Pearson chi- square procedure. The quantitative data compared the passing and failing groups and their attributions for performance on the test using One-way ANOVA and Pearson chi-square procedures. The results of the quantitative data comparing passing and failing groups and their attributions along the dimensions measured by the CDSII indicated statistical significance in locus of causality, stability, and personal controllability. The results comparing the open-ended attribution statements indicated statistical significance in the categories of effort and task difficulty.     

Exploring the Lived Experiences and Intersectionalities of Mexican Community College Transfer Students: Qualitative Insights Toward Expanding a Transfer Receptive Culture

ABSTRACT

This qualitative study examines the experiences of six Mexican community college transfer students attending a research-intensive institution in the Pacific Northwest. Using semi-structured interviews, the objectives of this study were to 1) understand how Mexican students made meaning of their transfer experiences and 2) how those experiences could inform conceptual and practical thinking toward building a transfer receptive culture at the receiving institution. We use intersectionality as a site of material and discursive possibility to encourage predominantly White receiving institutions to recognize how they position Mexican community college transfer students on campus. Concluding are conceptual and practical recommendations that emphasize institutional and organizational responsibility in creating equitable environments for Mexican community college transfer students.     

Diagnosing Global Case Influence on MAR Versus MNAR Model Comparisons

When missingness is suspected to be not at random (MNAR) in longitudinal studies, researchers sometimes compare the fit of a target model that assumes missingness at random (here termed a MAR model) and a model that accommodates a hypothesized MNAR missingness mechanism (here termed a MNAR model). It is well known that such comparisons are only interpretable conditional on the validity of the chosen MNAR model’s assumptions about the missingness mechanism. For that reason, researchers often perform a sensitivity analysis comparing the MAR model to not one, but several, plausible alternative MNAR models. In the social sciences, it is not widely known that such model comparisons can be particularly sensitive to case influence, such that conclusions drawn could depend on a single case. This article describes two convenient diagnostics suited for detecting case influence on MAR–MNAR model comparisons. Both diagnostics require much less computational burden than global influence diagnostics that have been used in other disciplines for MNAR sensitivity analyses. We illustrate the interpretation and implementation of these diagnostics with simulated and empirical latent growth modeling examples. It is hoped that this article increases awareness of the potential for case influence on MAR–MNAR model comparisons and how it could be detected in longitudinal social science applications.     

Models and Strategies for Factor Mixture Analysis: An Example Concerning the Structure Underlying Psychological Disorders

The factor mixture model (FMM) uses a hybrid of both categorical and continuous latent variables. The FMM is a good model for the underlying structure of psychopathology because the use of both categorical and continuous latent variables allows the structure to be simultaneously categorical and dimensional. This is useful because both diagnostic class membership and the range of severity within and across diagnostic classes can be modeled concurrently. Although the conceptualization of the FMM has been explained in the literature, the use of the FMM is still not prevalent. One reason is that there is little research about how such models should be applied in practice and, once a well-fitting model is obtained, how it should be interpreted. In this article, the FMM is explored by studying a real data example on conduct disorder. By exploring this example, this article aims to explain the different formulations of the FMM, the various steps in building a FMM, and how to decide between an FMM and alternative models.