Annual Report, 2008-2009

The Mennonite College of Nursing at Illinois State University creates a dynamic community of learning to develop exceptionally well-prepared nurses who will lead to improve health outcomes locally and globally. We promote excellence in teaching, research, service, and practice with a focus on the vulnerable and underserved. We are committed to being purposeful, open, just, caring, disciplined, and celebrative.https://ir.library.illinoisstate.edu/mcnar/1004/thumbnail.jp

Project dispute prediction by hybrid machine learning techniques

This study compares several well-known machine learning techniques for public-private partnership (PPP) project dispute problems. Single and hybrid classification techniques are applied to construct models for PPP project dispute prediction. The single classification techniques utilized are multilayer perceptron (MLP) neural networks, decision trees (DTs), support vector machines, the naïve Bayes classifier, and k-nearest neighbor. Two types of hybrid learning models are developed. One combines clustering and classification techniques and the other combines multiple classification techniques. Experimental results indicate that hybrid models outperform single models in prediction accuracy, Type I and II errors, and the receiver operating characteristic curve. Additionally, the hybrid model combining multiple classification techniques perform better than that combining clustering and classification techniques. Particularly, the MLP+MLP and DT+DT models perform best and second best, achieving prediction accuracies of 97.08% and 95.77%, respectively. This study demonstrates the efficiency and effectiveness of hybrid machine learning techniques for early prediction of dispute occurrence using conceptual project information as model input. The models provide a proactive warning and decision-support information needed to select the appropriate resolution strategy before a dispute occurs

Substance Misuse Transitions Between Adolescence and Young Adulthood: Impacts on Young Adult Self-Sufficiency

Substance misuse during the transition to adulthood can be problematic, but it is also socially celebrated. There can be negative short-term impacts associated with intoxication, but are there negative long-term impacts of substance misuse on the transition into adulthood? Let us pause for a moment. Many individuals may have just glazed over thinking, “Adulthood? I’m not doing that any time soon.” But when you consider what qualifies individuals as adults, this research may seem more pertinent. Adults make their own choices. Adults take responsibility for those choices. Adults are financially independent. So, while the notion of adulthood may conjure images of the suburbs and stability, adulthood as actually the ability to be self-sufficient. Something we are all working towards. This research looked at the young adult self-sufficiency outcomes between individuals who have patterns of substance misuse as they transition to adulthood and those who had minimal misuse. Specifically, we considered individuals who Matured-Out of substance use and individuals who continued to use. Continuing users were further divided into Continuing-Cannabis or Continuing-Illicit patterns. For the most part, those who Matured-Out by young adulthood had similar developmental outcomes compared to those who did not misuse substances during the transition to adulthood. Those who continued to use cannabis or illicit substances into young adulthood, however, were less self-sufficient as young adults. These findings have important implications for policies that promote cannabis legalization. As cannabis becomes increasingly available, policymakers and community leaders should have an eye on providing the necessary supports to help young adults gain self-sufficiency regardless of legalization status