This chapter discusses the challenges, characteristics, and transitional roles of adult learners. Implications for student services professionals are presented.

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This scholarly paper describes and analyzes the role of career and technical education (CTE) in Iowa community colleges. Iowa's community colleges are doing a good job of responding to the changing workforce needs of the state and providing smooth career pathways. However, changes in the population and economy of the state will call for further changes in CTE programs. The distinctive characteristics of CTE in Iowa community colleges, the impact of community college CTE programs on the state's economy, the role of accountability, and the future implications for CTE in the state are discussed. Recommendations based on the results of the study include improving articulation agreements, increasing retention among at-risk students, and increasing collaboration among Iowa's 15 community colleges.

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Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a 2.0 grade point average (GPA) in their first semester of college. Data analysis from student cohorts starting in the Fall 2007 through Fall 2009 identified two groups of students-one predicted to earn less than a 2.0 and the other predicted to earn a 2.0 or higher. The first semester college GPA and retention rates of both groups of students were tracked to examine the accuracy of the model in predicting student success and subsequent retention rates. Multi-year analyses illustrates that the model can be used to identify students who are at risk of earning less than a 2.0 GPA. Additional analysis demonstrates there is a relationship between predicted and actual first semester GPA and retention rates. Since the data used to develop the model are commonly available at most institutions, this study provides a practical approach for the SEM research professional to identify potentially academically at-risk students, which subsequently can be used to assist students and improve student success and degree completion. Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a 2.0 grade point average (GPA) in their first semester of college. Data analysis from student cohorts starting in the Fall 2007 through Fall 2009 identified two groups of students-one predicted to earn less than a 2.0 and the other predicted to earn a 2.0 or higher. The first semester college GPA and retention rates of both groups of students were tracked to examine the accuracy of the model in predicting student success and subsequent retention rates. Multi-year analyses illustrates that the model can be used to identify students who are at risk of earning less than a 2.0 GPA. DisciplinesAdditional analysis demonstrates there is a relationship between predicted and actual first semester GPA and retention rates. Since the data used to develop the model are commonly available at most institutions, this study provides a practical approach for the SEM research professional to identify potentially academically at-risk students, which subsequently can be used to assist students and improve student success and degree completion. Provide feedback or get helpIncreasing retention and graduation rates continues to be a critical challenge facing institutions of higher education. From a global perspective, the 2011 report from the Organization for Economic Co-operation and Development (OECD) highlighted the UnitedStates' decline...