THE ROLE OF COMMUNITY COLLEGES IN THE TRAINING AND EDUCATION OF LAW ENFORCEMENT AND CORRECTIONS PERSONNEL: A CURRICULUM FOR THE 21st CENTURY

Community colleges are in a unique position to meet the education and training needs of law enforcement and corrections personnel for the next century. The nature of the community college allows the proper blend of vocational and formal education in the design of a common curriculum to meet the needs of law enforcement. Location and cost also become factors as agencies attempt to stretch their training budgets. The community colleges have the flexibility and the resources to meet the needs of law enforcement for a practical, affordable, quality, and achievable education for employees in pre‐service, academy, and in‐service status.     

BETTER COLLEGE INFORMATION FOR STUDENTS: THE ROLE OF THE STATE TWO‐YEAR COLLEGE AGENCY

Prospective two‐year college students often lack adequate information on the range of educational alternatives available to them. Increasingly, state level agencies are playing a role in responding to that need. This article reports on a. national study of state two‐year college agencies to determine the extent and comprehensiveness of the postsecondary educational information they provide to students. Results indicate that most states have information they send to prospective students, but it varies widely in quality and often overlooks information students say they want to know. States with model information are identified.     

MENTORING BY THE COMMUNITY COLLEGE PROFESSOR: ONE ROLE AMONG MANY

The process of mentorship in relationship to the community college professor and the potential to improve and enhance the teaching and learning process is explored in this article. This article suggests that not all community college professors are psychological or intellectually disposed to being or becoming a good mentor. It is put forth that mentoring is a subrole of the community college professor. A framework for understanding the “complete mentor” process, as developed by Cohen (1993) Cohen, N. H. 1993. The development and validation of the principles of adult mentoring scale for faculty mentoring in higher education Philadelphia, PA Unpublished doctoral dissertation, Temple University [Google Scholar], is presented. Implications for practice are offered in a manner that connects the community college professor as mentor with enhancing the instructional process through the nurturing teaching perspective.     

THE WESTERN NORTH CAROLINA TECHNOLOGY CONSORTIUM: A COLLABORATIVE APPROACH TO BRIDGING THE DIGITAL DIVIDE

Community college presidents face an uphill struggle in preparing their institutions for the rapidly changing technological learning environment. Visionary presidents in rural community colleges are presented with yet another challenge: that of finding themselves on the wrong side of the digital divide. This article describes how presidents of 12 rural community colleges in the mountains of western North Carolina formed a technology consortium to collaboratively address critical technology issues. Integral steps in the joint venture were a combined assessment and planning process authorized by the presidents, formation of the Western North Carolina Technology Consortium, and an e-commerce project designed to meet the needs of small busi-nesses and entrepreneurs in the region. Lessons learned and implications for practice are presented for community college presidents seeking ways to collaborate.     

Learning Together: A Family-Centered Literacy Program

ABSTRACT

Blue Ridge Community College in Flat Rock, North Carolina serves a rapidly growing Hispanic population through its Family-Centered Literacy Program. The Hispanic population in the region has been increasing at a staggering rate of 50% per year, most of which is in-migration. These newcomers frequently face challenges adjusting to their jobs, schools, and living environment. The Family-Centered Literacy Program is teaching new skills to new residents to minimize the “culture shock”, and to make community immersion a less difficult process. The program offers evening classes 2 nights a week for parents and their children. Parents attend classes in basic and conversational English and General Education Development (GED) preparation; school-age children receive tutoring and help with homework; and preschool children learn from fluency-building games and activities. The college also provides Spanish instruction for school personnel who want to better communicate with Hispanic students and their parents. The program currently operates in 5 elementary schools. Each school has taken on the role of “community center” for Hispanic families.     

VOCATIONAL PREPARATION: HUMAN RESOURCE DEVELOPMENT SPECIALISTS’ ASSESSMENT

This study investigated the perceptions of Human Resource Development (HRD) Specialists regarding the preparation of Illinois community college vocational/ technical program graduates. Two hundred and forty‐five respondents answered a mail questionnaire concerning the technical, human relations, problem solving and basic skills of program graduates. The graduates were employed in Nursing and Allied Health, Industrial Technology, Secretarial and Clerical, Agriculture, Marketing and Management, Accounting and Data Processing, and Social and Public Services. The perceptions of these HRD Specialists toward community college program graduates are positive. Graduates of Nursing and Allied Health programs were consistently rated higher than graduates of other programs. Overall, graduates were ranked highest on human relations skills and lowest on problem solving skills. Finally, implications for practice included suggestions for involving HRD Specialists in community college vocational programs.     

Unconstrained Structural Equation Models of Latent Interactions: Contrasting Residual- and Mean-Centered Approaches

Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for estimating latent interaction effects as an alternative to the mean-centered approach proposed by Marsh, Wen, and Hau (2004, 2006). Little et al. also differed from Marsh et al. in the number of indicators used to infer the latent interaction factor and how they were represented, but this issue is separate from the mean versus residual centering distinction that was their primary focus. However, their implementation of the Marsh et al. mean-centered approach failed to incorporate the mean structure that Marsh et al. argued was necessary to obtain unbiased estimates. One might suppose that their new approach would suffer this same problem, an issue not addressed by Little et al. However, we demonstrate here why the Little et al. approach obviates this requirement that heretofore was thought to be necessary for all constrained, partially constrained, and unconstrained approaches. Both the Marsh et al. and Little et al. unconstrained approaches typically result in similar results and are much easier to implement than traditional constrained approaches. They differ primarily in that the Little et al. approach is a 2-step approach involving a potentially large number of separate analyses prior to estimating the structural equation model that apparently does not require the estimation of a mean structure, whereas the Marsh et al. approach is a 1-step approach that includes a mean structure.     

General Growth Mixture Analysis of Adolescents' Developmental Trajectories of Anxiety: The Impact of Untested Invariance Assumptions on Substantive Interpretations

Substantively, this study investigates potential heterogeneity in the developmental trajectories of anxiety in adolescence. Methodologically, this study demonstrates the usefulness of general growth mixture analysis (GGMA) in addressing these issues and illustrates the impact of untested invariance assumptions on substantive interpretations. This study relied on data from the Montreal Adolescent Depression Development Project (MADDP), a 4-year follow-up of more than 1,000 adolescents who completed the Beck Anxiety Inventory each year. GGMA models relying on different invariance assumptions were empirically compared. Each of these models converged on a 5-class solution, but yielded different substantive results. The model with class-varying variance–covariance matrices was retained as providing a better fit to the data. These results showed that although elevated levels of anxiety might fluctuate over time, they clearly do not represent a transient phenomenon. This model was then validated in relation to multiple predictors (mostly related to school violence) and outcomes (grade-point average, school dropout, depression, loneliness, and drug-related problems).     

Multivariate Meta-Analysis as Structural Equation Models

Multivariate meta-analysis has become increasingly popular in the educational, social, and medical sciences. It is because the outcome measures in a meta-analysis can involve more than one effect size. This article proposes 2 mathematically equivalent models to implement multivariate meta-analysis in structural equation modeling (SEM). Specifically, this article shows how multivariate fixed-, random- and mixed-effects meta-analyses can be formulated as structural equation models. metaSEM (a free R package based on OpenMx) and Mplus are used to implement the proposed procedures. A real data set is used to illustrate the procedures. Formulating multivariate meta-analysis as structural equation models provides many new research opportunities for methodological development in both meta-analysis and SEM. Issues related to and extensions on the SEM-based meta-analysis are discussed.     

An Evaluation of Latent Growth Models for Propensity Score Matched Groups

Because random assignment is not possible in observational studies, estimates of treatment effects might be biased due to selection on observable and unobservable variables. To strengthen causal inference in longitudinal observational studies of multiple treatments, we present 4 latent growth models for propensity score matched groups, and evaluate their performance with a Monte Carlo simulation study. We found that the 4 models performed similarly with respect to model fit, bias of parameter estimates, Type I error, and power to test the treatment effect. To demonstrate a multigroup latent growth model with dummy treatment indicators, we estimated the effect of students changing schools during elementary school years on their reading and mathematics achievement, using data from the Early Childhood Longitudinal Study Kindergarten Cohort.