The Distribution of Family-Friendly Benefits Policies across Higher Education Institutions: A Cluster Analysis

Cluster Analysis of Family-Related Benefits Policies across U.S. Academic Institutions Although the under-representation of women in science and engineering tenure-track faculty positions is often linked to the conflict between childcare responsibilities and the normative academic tenure-track pathway, previous studies have tended to focus on individual life choices,rather than the effects of institutional-level policies and structure. More recent research on work/life policies in higher education have pushed our understanding of how organizational structure and political climates at the department and institution levels influence the ability of faculty members to integrate career and life responsibilities. Many post-secondary institutions offer more generous work/life benefits than required by the 1993 Family Medical Leave Act (FMLA), which provides employees with 12 weeks of unpaid, job-protected leave for family and medical reasons per year if the employee has worked for the employer at least 12 months. The types of family-related benefits offered, however, vary greatly across post-secondary institutions in the United States. Using cluster analysis, this study identifies the patterns of availability of parental leave and childcare benefits across U.S. academic institutions by grouping institutions into clusters of similar institutions. By so doing, the paper highlights the rates at which different types of institutions adopted family-friendly policies since the FMLA. Cluster analysis is a technique for grouping a collection of cases, such as institutions, by a number of attributes or variables. It is used across many fields including education, engineering,life, social, and physical sciences as an exploratory or data mining technique. This study applies a k-means cluster analysis, a well established technique previously used in engineering education research, to identify patterns in types of benefits policies offered by institutional characteristics or profiles. The characteristics examined include student demographics and enrollment size,faculty size, research expenditures, and instructional expenditures. The data come from the National Study of Postsecondary Faculty (NSOPF) Institution survey conducted by the National Center for Education Statistics with response rates exceeding 86%. The nationally representative 1993 and 2004 samples include 974 and 1,080 public and private not-for-profit institutions that confer associates, bachelors, or advanced degrees, respectively.Preliminary results with six clusters indicate that doctoral research institutions with the highest average instructional and research expenditures are more likely to offer a greater number of family-related benefits to both part-time and full-time faculty compared to associates, bachelors or masters institutions. These doctoral institutions also have the largest average student enrollment and a relatively more diverse student population. Ongoing work includes identifying the rates of adoption of benefits policies following the FMLA. By analyzing both 1993 and 2004,changes in the overall profiles of institutions with different policy arrangements may also be revealed. Research findings will provide a national perspective of academic institutions’ efforts to facilitate work-life integration among faculty to help administrators, policy makers, and other stakeholders shape educational policy

The Dynamics of Attracting Switchers: A Cross-Disciplinary Comparison

A Hazards Model Study of Pathway Analysis in Engineering Factors that indicate, explain, or predict if a student will persist or exit an engineering degree have been a subject of a lot of research in engineering education. Findings from these studies identify factors that lead to success or barriers that lead premature exit from an engineering degree; however, they often focus on students who matriculate into engineering or analyze students once they have matriculated into engineering. We propose studying an alternate pathway, students who switch into engineering from other majors. Examining alternate pathways may yield a fuller picture of the ways into and through engineering degrees and may be leveraged through different institutional policies and programs for attracting engineering students from other fields.Survival analysis is a longitudinal statistical method used to model the hazard or risk of an event occurring for some population. Our study implemented discrete survival analysis and a subset of a database comprising more than 1,000,000 unique students. For our current research, we use a sample population of first-time in college (FTIC) students initially matriculating into non-engineering disciplines in two years with population of ~55,000 at nine institutions. The event of interest is switching into engineering, and time is measured by terms. To better understand the dynamics of “attraction” into engineering we also run similar analyses with Science, Technology and Math (as a similar comparator) and Social Science (as a dissimilar comparator). Survival analysis results allow us to graph the term by term hazard or risk of attraction into engineering(and the comparators) as well as the “survival” rate in the pool of individuals who have not experienced the event, providing us insights into the relative attraction rates of engineering contrasted with other disciplines.Our preliminary results show that the attraction (hazard) rates for engineering are lower than both STM and social science attraction rates; furthermore, the pool of students who abstain from switching is greatest for engineering, and significantly less for STM and social science. Thus engineering has the lowest attraction rates and the highest abstention (which would be viewed as retention from their current department) rates. Interestingly, the hazard rate displays a similar pattern for all three groups, peaking at semester four and dropping markedly after semester six.In the full study, we also plan to examine if attraction and abstention rates differ by gender and ethnicity across engineering and the comparators. These findings agree with other studies using the same database, which gives confidence in the model. The unique contribution of this work will be findings regarding the switching population that yield insight into those students and related insights regarding the students who matriculate in engineering

Access and Definition: Exploring how STEM Faculty, Department Heads, and University Policy Administrators Navigate the Implementation of a Parental Leave Policy

Access and Definition: Exploring how STEM Faculty, Department Heads and University Policy Administrators Navigate the Enactment of a Parental Leave Policy A key feature in various reports exploring women’s persisting underrepresentation in STEM faculty positions in the US is the need to disseminate policy information to all stakeholders involved in issues relating to women STEM faculty underrepresentation and retention. Indeed, the National Academies of Science Beyond Barriers and Bias: Fulfilling the Potential of Women Academic Science and Engineering (2007) and the AAUW’s Why so Few?(2010) identify institutional policies, like parental leave, as a way to address an outmoded institutional structure that is increasingly at odds with the experiences of all faculty. We have undertaken a deep, comprehensive and systematic study of one such policy at one Midwestern institution, exploring the recently instituted parental leave policy that allows women and men faculty and staff to take a paid leave after the birth or adoption of a child. The study uses Dorothy Smith’s institutional ethnography as a method to examine how people’s everyday real world experiences are mediated by textual documents (here the parental leave policy). We interviewed eligible STEM faculty, STEM department heads and university policy administrators to understand how the policy was being enacted or not in the everyday circumstances of STEM faculty and how other university members jointly navigate this process.We have presented prior work at ASEE 2011 on this data; our new paper will delve deeper into two select themes: the difficulty STEM faculty experienced in accessing the policy to meet their needs; and the challenges administrators had at understanding the exact definition of what the policy offered faculty. An emerging theme is that issues of access and definition seem to vary across STEM departments. With our focus on this access and understanding, we integrated our analysis with the work of sociologist Manuel Castells (2000) who examines flows of information between and within networks of people (here we focus on within networks, specifically departmental networks and the larger university network). By using this framework we can examine the different network structures and flows of information within departments which are nested within a larger university network. Disseminating information and coordinating action to address these ongoing issues is a complex problem as evinced by the findings in our initial study (2010). Combining institutional ethnography’s ability to reveal how organizational policy affects how people interact about and choose to enact or not enact a policy with Castells work on flows of information within networks stands to advance our collective understanding of access and understanding of these sorts of policies and suggest routes to improve both for STEM faculty. Findings can offer illustrative lessons about how these processes operate potentially informing other instances of similar policy introduction and maintenance. Further study of this policy comes at a time where broad changes in family friendly policy at NSF have emerged on the horizon; thus this study also offers a benchmark against which to contrast once these larger policy changes have come into effect