Teaching Biosocial Criminology I: Understanding Endophenotypes Using Gottfredson and Hirschi’s Self‐Control Construct

Criminology is experiencing a paradigm shift in theory and research that articulates a more interdisciplinary, biosocial mode of inquiry. Unfortunately, however, graduate‐level criminal justice education rarely encompasses biosocial training. The current review is the first in a series of works that seeks to fill this biosocial training void by providing instruction on concepts in the biological sciences and neurosciences that have direct relevance to criminal justice education and criminology. Here we introduce endophenotypes and demonstrate their relevance to the study of crime using the self‐control construct from Gottfredson and Hirschi’s general theory. Because biosocial criminology is in its nascent stage, it is critical that biosocial criminologists provide service and instruction to their social science‐trained colleagues.     

Measurement Bias Detection Through Factor Analysis

Assessing the correctness of a structural equation model is essential to avoid drawing incorrect conclusions from empirical research. In the past, the chi-square test was recommended for assessing the correctness of the model but this test has been criticized because of its sensitivity to sample size. As a reaction, an abundance of fit indexes have been developed. The result of these developments is that structural equation modeling packages are now producing a large list of fit measures. One would think that this progression has led to a clear understanding of evaluating models with respect to model misspecifications. In this article we question the validity of approaches for model evaluation based on overall goodness-of-fit indexes. The argument against such usage is that they do not provide an adequate indication of the “size” of the model's misspecification. That is, they vary dramatically with the values of incidental parameters that are unrelated with the misspecification in the model. This is illustrated using simple but fundamental models. As an alternative method of model evaluation, we suggest using the expected parameter change in combination with the modification index (MI) and the power of the MI test.     

Principles and Practice of Scaled Difference Chi-Square Testing

We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra–Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001 Satorra, A. and Bentler, P. M. 2001. A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66: 507–514. [Crossref], [Web of Science ®] , [Google Scholar]) and new (Satorra & Bentler, 2010 Satorra, A. and Bentler, P. M. 2010. Ensuring positiveness of the scaled chi-square test statistic. Psychometrika, 75: 243–248. [Crossref], [Web of Science ®] , [Google Scholar]) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction factor (c), depending on the particular structural equation modeling software used. Because of how LISREL 8 defines the SB scaled chi-square, LISREL users should compute c for each model by dividing the model's normal theory weighted least-squares (NTWLS) chi-square by its SB chi-square, to recover c accurately with both tests. EQS and Mplus users, in contrast, should divide the model's maximum likelihood (ML) chi-square by its SB chi-square to recover c. Because ML estimation does not minimize the NTWLS chi-square, however, it can produce a negative difference in nested NTWLS chi-square values. Thus, we recommend the standard practice of testing the scaled difference in ML chi-square values for models M ₁ and M ₀ (after properly recovering c for each model), to avoid an inadmissible test numerator. We illustrate the difference in computations across software programs for the original and new scaled tests and provide LISREL, EQS, and Mplus syntax in both single- and multiple-group form for specifying the model M ₁₀ that is involved in the new test.     

Filipino parents’ school choice and loyalty: a factor analysis

This quantitative study aims to ascertain the significant relationship existing between parents’ profile, and their school choice and school loyalty. Data were gathered using the researcher’s two-part made instrument. Respondents were first asked to fill in a robotfoto for purpose of profiling their baseline characteristics and were later asked to rate listed indicators, using a modified 8-point Likert scale. Using statistical tools such as the ANOVA, factor analysis, correlation, mean, and standard deviation, data were treated indepth. It is interesting to note that although parents are loyal to their alma mater, this does not have a much impact on their choice of school for their children. On the whole, parents’ choice of school is based on its indispensable qualities. Among the three interval-scale profiles of the parent respondents such as age, income, tuition fee payment and number of children, none of these relate to school choice, but age, income, and tuition fee payment negatively relate to school loyalty. From their nominal-scale profiles, significant differences were noted in their school choice when grouped according to civil status, place of work, and terms of payment. With respect to school loyalty, significant differences occurred in their responses when classified according to gender, terms of payment and their active participation in the Parent-Teacher Association (PTA).     

Infusing assessment into mathematics content courses for pre-service elementary school teachers

The present study aims to explore the use of assessment in mathematics content courses for future elementary school teachers. Analysis of self assessment data on mathematical understanding and peer assessment data on oral mathematical presentation showed that pre-service teachers had a balanced understanding of procedural knowledge and problem solving. Conceptual understanding was not in the structure of pre-service teachers’ mathematical knowledge. Understandings of conceptual knowledge, procedural knowledge, and problem solving had no meaningful effects on gains in mathematics performance. Aspects of oral mathematical presentation were associated with improved understanding of procedural knowledge and in particular conceptual knowledge. The result of the study calls for a conceptual approach to mathematical knowledge and sufficient mathematical problem solving in college-level mathematics content courses and in particular the infusion of assessment into college-level mathematics education for pre-service teachers.     

Determinants of Research Productivity in Spanish Academia

This article aims to widen the empirical evidence about the determinants of Spanish academics’ publication productivity across fields of study. We use the Spanish Survey on Human Resources in Science and Technology addressed to Spanish resident PhDs employed in Spanish universities as academics. Productivity is measured as the total number of publications in a three‐year period. We show how personal and academic variables explain differences in productivity within universities and fields of studies and across fields of research. Female workers report lower productivity than their male counterparts, but family responsibilities do not explain this gender gap. The type of contract and tenure or rank do not seem to have any influence on productivity. Researchers seeking professional promotion rather than altruism or personal satisfaction are more productive and young scholars publish more than their older counterparts. Additionally, we find a certain research‐teaching trade‐off and some nuances in the predictors of publication productivity across birth cohorts and fields of study. Finally, international cooperation is one of the most relevant determinants of the number of publications, regardless of the birth cohort. The institutional context in the Spanish research system as regards requirements for promotion and the assessment of research outcomes may contribute to the understanding and interpretation of our results.     

Using the S-STEM Survey to Evaluate a Middle School Robotics Learning Environment: Validity Evidence in a Different Context

Journal of Science Education and Technology - Numerous studies have been undertaken to design, develop, and provide validity evidence for using instruments to measure students’ attitudes...     

Effects of organizational pictures and modality as a feedback strategy on learner comprehension and satisfaction

One of the strongest instructional interventions documented in educational literature is the use of feedback to influence learning outcomes. However, there is lack of empirical research specifically pertaining to the use of multimedia in the feedback message. The purpose of this research was to test whether organizational pictures and modality as a feedback strategy had an effect on learner comprehension and satisfaction. The research design was a 2 Multimedia (Picture Present vs. Picture Absent) × 2 Modality (Narration vs. On-screen Text) × Trial (Trial 1 vs. Trial 2) with Multimedia and Modality serving as between-subject conditions and Trial serving as a repeated measure. One-hundred fifteen university students participated in the study. Findings show statistically significant increases in comprehension scores from Trial 1 to Trial 2 assessments for all four treatment conditions. Learners in the Picture present conditions were statistically more satisfied with the learning experience. Additionally, we used eye-tracking to verify the extent to which the pictures were used in the feedback message. A discussion and recommendations for future research and feedback design are provided.