Living-learning communities improve first-year engineering student academic performance and retention at a small private university

Living-Learning Communities (LLCs), in which students share a residence, one or more classes, and extracurricular activities, have been shown to improve first-year student engagement, academic performance, and retention in non-engineering fields. Research on Engineering LLCs has focused primarily on student engagement. Two studies to examine performance and retention found that LLCs had little effect on first-semester grades but increased first-year retention in engineering by 2 to 12%. Unfortunately, one of these studies did not control for differences in incoming student characteristics, and another used a comparison group that differed little from the LLC group, possibly causing them to understate the LLC’s true effects. To improve our understanding, this paper examines performance and retention in the inaugural Engineering LLCs at a small, private non-profit, regional university in the northeastern United States. Results indicate that 82% of the Engineering LLC participants were retained within the engineering program, compared to 66% of first-year engineering students who chose not to participate. More strikingly, the average first-semester GPA of the LLC participants was 0.31 points (nearly a third of a letter grade) higher than that of the non-participants. To address the possibility that these improvements were caused by differences in incoming student characteristics, linear and logistic regression analyses were performed to control for gender, race/ethnicity, SAT scores, and other factors. These analyses suggest that LLC participation increased GPA by 0.35 points compared to first-year engineering students from prior years, while non-participation lowered GPA by 0.07 points. LLC participation increased the odds of retention in the major by 2.3 times compared to first-year students from prior years, while nonparticipation lowered the odds of retention by 1.35 times

Improving outcomes in outsourced product development: a joint consultant-client perspective

Although firms increasingly outsource front end product development activities to production suppliers or design consultants, this practice has received little scholarly attention. The few existing academic studies report high failure rates but generally present only the client firms’ view of the causes. Our first results from in-depth interviews of both clients and consultants give a richer picture of enablers of success and causes of failure. We confirm some previous findings(internal divisions within the client, “poor communication” between parties),identify new ones (inadequate client capabilities, failure to transfer design intent), and combine them into a comprehensive model of outsourced product development that includes negotiating project scope, continuously managing expectations, and carefully re-integrating the design output into the client’s operations. Finally, we classify several types of client dependency (need for new ideas, extra capacity, or specific technical expertise) and highlight the particular hazards associated with each

Can a five minute, three question survey foretell first-year engineering student performance and retention?

This research paper examines first-year student performance and retention within engineering. A considerable body of literature has reported factors influencing performance and retention, including high school GPA and SAT scores,1,2,3 gender,4 self-efficacy,1,5 social status,2,6,7 hobbies,4 and social integration.6,7 Although these factors can help explain and even partially predict student outcomes, they can be difficult to measure; typical survey instruments are lengthy and can be invasive of student privacy. To address this limitation, the present paper examines whether a much simpler survey can be used to understand student motivations and anticipate student outcomes. The survey was administered to 347 students in an introductory Engineering Graphics and Design course. At the beginning of the first day of class, students were given a three-question, open-ended questionnaire that asked: “In your own words, what do engineers do?”, “Why did you choose engineering?”, and “Was there any particular person or experience that influenced your decision?” Two investigators independently coded the responses, identifying dozens of codes for both motivations for pursuing engineering and understanding of what it is. Five hypotheses derived from Dweck’s mindset theory7 and others8,9 were tested to determine if particular codes were predictive of first-semester GPA or first-year retention in engineering. Codes that were positively and significantly associated with first-semester GPA included: explaining why engineers do engineering or how they do it, stating that engineers create ideas, visions, and theories, stating that engineers use math, science, physics or analysis, and expressing enjoyment of math and science, whereas expressing interest in specific technical applications or suggesting that engineers simplify and make life easier were negatively and significantly related to first-semester GPA. Codes positively and significantly associated with first-year retention in engineering included: stating that engineers use math or that engineers design or test things, expressing enjoyment of math, science, or problem solving, and indicating any influential person who is an engineer. Codes negatively and significantly associated with retention included: citing an extrinsic motivation for pursuing engineering, stating that they were motivated by hearing stories about engineering, and stating that parents or family pushed the student to become an engineer. Although many prior studies have suggested that student self-efficacy is related to retention,1,5 this study found that student interests were more strongly associated with retention. This finding is supported by Dweck’s mindset theory: students with a “growth” mindset (e.g., “I enjoy math”) would be expected to perform better and thus be retained at a higher rate than those with a “fixed” mindset (e.g., “I am good at math”).7 We were surprised that few students mentioned activities expressly designed to stimulate interest in engineering, such as robotics competitions and high school engineering classes. Rather, they cited general interests in math, problem solving, and creativity, as well as family influences, all factors that are challenging for the engineering education community to address. These findings demonstrate that relative to its ease of administration, a five minute survey can indeed help to anticipate student performance and retention. Its minimalism enables easy implementation in an introductory engineering course, where it serves not only as a research tool, but also as a pedagogical aid to help students and teacher discover student perceptions about engineering and customize the curriculum appropriately

First-year engineering living-learning communities improve four-year graduation rates at a small private university

This complete research paper assesses the long-term benefits of first-year student participation in an Engineering Living-Learning Community (ELLC) at a relatively small private university. Prior research on ELLCs has examined short-term results such as first-year student engagement, academic performance, and retention, but relatively few studies have reported data on long-term outcomes such as graduation rates and GPA at graduation. This paper reports the outcomes of four cohorts of Engineering students who entered the study university between 2013 and 2016. Students participating in the ELLC had significantly higher 4-year graduation rates in Engineering (55.7% vs. 42%) and in STEM (64.3% vs. 51.2%), and higher 4-year graduation rates from the university (66.1% vs. 56.8%), than non-honors Engineering students who did not participate in the ELLC. Although the average first-semester GPA of ELLC participants was significantly higher than that of non-participants (3.15 vs. 2.82), the difference faded over time. The average GPA at graduation for ELLC Engineering graduates was 3.22, compared to 3.12 for non-honors non-ELLC Engineering graduates. To determine whether the ELLC’s superior outcomes might be explained by differences in incoming student characteristics between the ELLC and non-ELLC groups, or by student participation in other programs such as a first-year seminar or athletics, multinomial logistic and linear regression were used to control for high school GPA, SAT scores, and other factors. The results indicate that ELLC participation doubled the odds of four-year graduation in Engineering or STEM over non-participation, both significant effects, and increased graduation GPA in Engineering by 0.07 points. This study suggests that a relatively modest intervention implemented in the first year alone may have lasting benefits on student retention and performance, even in small universities that might be thought to have less need for the community development an LLC provides. Introductio

Does choice of programming language affect student understanding of programming concepts in a first year engineering course?

Most undergraduate engineering curricula include computer programming to some degree,introducing a structured language such as C, or a computational system such as MATLAB, or both. Many of these curricula include programming in first year engineering courses, integrating the solution of simple engineering problems with an introduction to programming concepts. In line with this practice, Roger Williams University has included an introduction to programming as a part of the first year engineering curriculum for many years. However, recent industry and pedagogical trends have motivated the switch from a structured language (VBA) to a computational system (MATLAB). As a part of the pilot run of this change,the course instructors felt that it would be worthwhile to verify that changing the programming language did not negatively affect students’ ability to understand key programming concepts. In particular it was appropriate to explore students’ ability to translate word problems into computer programs containing inputs, decision statements, computational processes, and outputs. To test the hypothesis that programming language does not affect students’ ability to understand programming concepts, students from consecutive years were given the same homework assignment, with the first cohort using VBA and the second using MATLAB to solve the assignment. A rubric was developed which allowed the investigators to rate assignments independent of programming language. Results from this study indicate that there is not a significant impact of the change in programming language. These results suggest that the choice of programming language likely does not matter for student understanding of programming concepts. Course instructors should feel free to select programming language based on other factors, such as market demand, cost, or the availability of pedagogical resources

Understanding success and failure in outsourced product development

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references.Companies that develop new products increasingly outsource product design, a trend that has prompted much concern but little evidence on its effectiveness. This dissertation uses a combination of interviews, cross-case analysis, and survey data to examine the meaning, measurement, and causes of success in one type of outsourced development: design and innovation consulting. The first study identifies the many dimensions of success and demonstrates that consultants, clients, and scholars prioritize them differently. Clients emphasize the value and quality of the deliverable, while consultants prioritize design elegance, novelty, and commercial success. Client satisfaction, heretofore little used in outsourcing research, correlates highly with most success dimensions. The second study uses the identified success measures to assess 134 consulting projects. Rates of product commercialization and market success compare favorably to results previously reported for in-house development. Client satisfaction is comparable to that of other service industries but varies greatly across projects. Most outcome measures are robust to measurement timing but depend strongly on the seniority of the respondent and the level of anonymity afforded him or her during assessment. The third study identifies over fifty factors believed to influence project outcomes and distills them into two pedagogical frameworks. The final study combines these factors with theories of customer satisfaction and product development to generate explanatory models of client satisfaction and other project outcomes. Nearly 80% of the observed variation in satisfaction can be explained after the fact, and 36% predicted before the project begins. Contrary to prior reports, design consultancies are least effective at radical innovation. Rather, they excel at rapid innovation in familiar product categories, designing products far more quickly than bureaucratic organizations and inexperienced start-ups can. Client satisfaction is unaffected by corporate cultural distance between parties, and actually declined with decreased physical distance and increased manufacturer involvement, challenging conventional wisdom in product development. The dissertation contributes to understanding of outsourced product development by clarifying key concepts such as success, demonstrating the impact of methodological details on its measure, and developing novel survey methods to gather unique outcome data from a broad range of respondents.by William J. Palm, IV.Ph.D

Leiden University Document Attesting the Study of Philosophy and Criticism

A document attesting the study of Albertus C. Van Raalte in the field of philosophy and criticism at Leiden University.https://digitalcommons.hope.edu/vrp_1830s/1013/thumbnail.jp

The Algorithm Theoretical Basis Document for the GLAS Atmospheric Data Products

The purpose of this document is to present a detailed description of the algorithm theoretical basis for each of the GLAS data products. This will be the final version of this document. The algorithms were initially designed and written based on the authors prior experience with high altitude lidar data on systems such as the Cloud and Aerosol Lidar System (CALS) and the Cloud Physics Lidar (CPL), both of which fly on the NASA ER-2 high altitude aircraft. These lidar systems have been employed in many field experiments around the world and algorithms have been developed to analyze these data for a number of atmospheric parameters. CALS data have been analyzed for cloud top height, thin cloud optical depth, cirrus cloud emittance (Spinhirne and Hart, 1990) and boundary layer depth (Palm and Spinhirne, 1987, 1998). The successor to CALS, the CPL, has also been extensively deployed in field missions since 2000 including the validation of GLAS and CALIPSO. The CALS and early CPL data sets also served as the basis for the construction of simulated GLAS data sets which were then used to develop and test the GLAS analysis algorithms

Network information and connected correlations

Entropy and information provide natural measures of correlation among elements in a network. We construct here the information theoretic analog of connected correlation functions: irreducible $N$--point correlation is measured by a decrease in entropy for the joint distribution of $N$ variables relative to the maximum entropy allowed by all the observed $N-1$ variable distributions. We calculate the ``connected information'' terms for several examples, and show that it also enables the decomposition of the information that is carried by a population of elements about an outside source.Comment: 4 pages, 3 figure