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

Returning Students in Engineering Education: Making a Case for “Experience Capital”

Students returning to college are not generally studied, where most of the research on non-traditional students is focused on individuals returning to earn their undergraduate degree. There are, however, many students returning to receive graduate degrees as they pursue new directions in life by interest or economic necessity. Undergraduate students with experience have clear educational related goals, practical approaches to problem-solving, and high learning motivation.Returning graduate students are expected to model similar behaviors. These individuals bring a lifetime of personal and professional expertise, which we identify as “experience capital.”A review of the literature reveals that capital has been pondered since early western philosophers considered the concept of social capital in terms of „community governance‟. Others credit Dewey with the first use of the term „social capital‟. Since then, development of other capitals include human, cultural, and symbolic. Human capital is viewed as knowledge, skills, and attributes; cultural capital as an indicator of class position acquired by family and education ; and symbolic as the prestige, recognition, and fame. Today, social capital is viewed as the networks,relationships, and connections of influence and support. Experience capital is the partial union of social, human, cultural, and symbolic capital, which individuals develop from their persona land professional experiences as they progress through life.This is an exploratory study capturing the perceptions of “experience capital” of individuals with several years of professional experience in their discipline returning for a doctoral degree in engineering education. The research question this study addresses is: what “experience capital”do returning students bring to an engineering education doctoral program? The participants will be interviewed; open coding will be used to identify common themes. The results of this qualitative study will position the experiences of the participants at the partial union of social,human, cultural, and symbolic capital, in a space called experience capital

AfrOBIS: a marine biogeographic information system for sub-Saharan Africa

AfrOBIS is one of 11 global nodes of the Ocean Biogeographic Information System (OBIS), a freely accessible network of databases collating marine data in support of the Census of Marine Life. Versatile graphic products, provided by OBIS, can be used to display the data. To date, AfrOBIS has loaded about3.2 million records of more than 23 000 species located mainly in the seas around southern Africa. This forms part of the 13.2 million records of more than 80 000 species currently stored in OBIS. Scouting for South African data has been successful, whereas locating records in other African countries has been much less so

AfrOBIS: a marine biogeographic information system for sub-Saharan Africa

AfrOBIS is one of 11 global nodes of the Ocean Biogeographic Information System (OBIS), a freely accessible network of databases collating marine data in support of the Census of Marine Life. Versatile graphic products, provided by OBIS, can be used to display the data. To date, AfrOBIS has loaded about 3.2 million records of more than 23 000 species located mainly in the seas around southern Africa. This forms part of the 13.2 million records of more than 80 000 species currently stored in OBIS. Scouting for South African data has been successful, whereas locating records in other African countries has been much less so

The Impact of Entrepreneurship Education in Higher Education: A Systematic Review and Research Agenda

Using a teaching model framework, we systematically review empirical evidence on the impact of entrepreneurship education (EE) in higher education on a range of entrepreneurial outcomes, analyzing 159 published articles from 2004 to 2016. The teaching model framework allows us for the first time to start rigorously examining relationships between pedagogical methods and specific outcomes. Reconfirming past reviews and meta-analyses, we find that EE impact research still predominantly focuses on short-term and subjective outcome measures and tends to severely underdescribe the actual pedagogies being tested. Moreover, we use our review to provide an up-to-date and empirically rooted call for less obvious, yet greatly promising, new or underemphasized directions for future research on the impact of university-based entrepreneurship education. This includes, for example, the use of novel impact indicators related to emotion and mind-set, focus on the impact indicators related to the intention-to-behavior transition, and exploring the reasons for some contradictory findings in impact studies including person-, context-, and pedagogical model-specific moderator