through a course that fully utilized CPBL in a whole semester. Themain purpose is to identify students’ perception towards CPBL in two aspects: (1) perception andacceptance/rejection; and (2) the benefits and improvements gained along the learning process.The paper illustrates the extent of acceptance and effectiveness of CPBL for an engineeringcourse taught by a lecturer who had undergone a series of training on cooperative learning andproblem based learning, but is new to implementing CPBL. Through classroom observations,students’ self-reflection notes and interviews with students for one whole semester, the resultsare reported in three stages: (1) beginning of the semester; (2) in the middle the semester; and (3)at the end of the semester
obtained a Ph.D. in engineering in Aug. 2010 from the Katholieke Universiteit, Leuven. She is a member of LESEC (Leuven Engineering and Science Education Centre).Prof. Jos Vander Sloten, Katholieke Universiteit, Leuven Page 25.588.1 c American Society for Engineering Education, 2012 Evaluation of a Technical Writing Program Implemented in a First Year Engineering Design Course C. Heylen1 and J. Vander Sloten2 1 Christel Heylen, Faculty of Engineering, Tutorial Services, K.U.Leuven, Belgium
these areas at graduation.However, the variability of these projects presents significant challenges for common rubricdevelopment and by implication, our ability to retrieve reliable data on student performance inthese categories/attributes. This variability also brings unique challenges to the development of asingle rubric that is 1) flexible enough to apply to a variety of engineering thesis projects, 2)reflective of the learning objectives of the thesis course, and also 3) appropriate for use ingathering reliable data about students’ graduate attributes.This paper describes the development of the rubric, and the inherent challenges in designing avalid and reliable tool that provides flexibility to a diverse group of projects and supervisors
us to explore new ideas in a way that traditional learning may not afford. Sincecyberlearning has such great potential, the study explores ways in which it might be used to promoteexcellence in undergraduate STEM education, and to provide the Division of Undergraduate Education(DUE) Program Officers at the National Science Foundation (NSF) with recommendations on possibledirections they could take. Though originally targeted to Program Officers, STEM educators andresearchers searching for new ways to use cyberlearning to improve STEM education will also benefitfrom these findings. A convergent parallel mixed methods research design7 (p. 77) was used to collect different, butcomplementary data to answer five research questions. 1
,engineering educators seek ways to emphasize and develop broad thinking. The work presentedin this paper provides insight into how engineering education might broaden its coverage tobetter address such modern challenges as globalization, climate change, and issues of socialjustice. In this paper, we present new findings from a recent analysis of semi-structuredinterviews that were conducted during the spring of 2006 as part of the Center for theAdvancement of Engineering Education’s (CAEE) Academic Pathways Study (APS). Theseinterviews of third-year engineering students at a large, public research university in the westernU.S. took place immediately following a short design-scoping task (the analysis of which isreported elsewhere [1, 2]) that asked
study, which includedstudents at the beginning and the end of their sophomore year. Students in the experimentalgroup completed an introductory mechanical design course, while students in the control grouphad no formal design component in their curriculum. We analyze and compare the percentoccurrences of design issues and syntactic design processes from the protocol analysis of bothcohorts. These results provide an opportunity to investigate and understand how sophomorestudents’ design ability is affected by a design course.1. IntroductionDesign has long been considered a central component of engineering education, and a number ofrecent publications have called for an increase focus on design education not only in capstone orcornerstone
gap, this study aims to gain adeeper understanding of the faculty‟s experience with LTS. Herein, we present the thoroughdevelopment of the LTS Faculty Survey, designed with content and construct validationprocesses in mind and included quantitative and qualitative items, as well as key findings fromsurveyed LTS faculty experts (N=25). The survey enabled us to measure characteristics of LTScurricular and extracurricular efforts, perceived barriers faced by faculty, motivations forimplementing LTS efforts, attitudes about LTS, etc. all from a faculty perspective. Key findingssuggest that major barriers for LTS implementation are (1) faculty time/workload, (2) problemscoordinating with the community, and (3) the lack of policy on the role of LTS
-based mentoring program at the University of Colorado atBoulder provides an opportunity to conduct engineering education research to understand andquantify the effect of mentoring on student interests and retention in engineering. Targeted at the Page 25.678.2diverse population of underrepresented minorities and women engineers at the university, thisprogram aims to improve retention rates since the college’s graduation trends lag well behind thenational average for these nontraditional groups [1] [2]. This study examines the efficacy of theYour Own Undergraduate Research Experience at CU-Boulder (YOU’RE@CU) mentoringprogram during its pilot
Foundation’s Research Experiences for Undergraduates (REU)initiative aims to recruit students to careers in research and has funded over 1,700 sites totalingover $435 million (of which over 600 sites receiving $171 million in funding are presentlyactive)1. Research by the STEM education community concurs that these research experienceshave a positive influence on undergraduates in a variety of ways. Yet, many of the specificaspects of the nature benefits to participants and how they accrue to participants are not knownor well understood.Prior work by the first author used Lent’s Social Cognitive Career Theory to study the impact ofREU programs on undergraduate students’ self efficacy for graduate school and researchcareers2. In this prior work, we
graduate students and young faculty members. Analysis of the awardees’dossiers revealed the challenges associated with evaluating the impact of innovations on teachingand learning as well as issues surrounding the dissemination of innovations in engineeringeducation.1. IntroductionIn this paper we report on preliminary results of a study undertaken to determine the impact ofthe Premier Award for Excellence in Engineering Education Courseware on the culture ofengineering education. NEEDS, the precursor to the Engineering Pathway(http://www.engineeringpathway.com/ep/about/index.jhtml) developed the Premier Award “torecognize high-quality, non-commercialcourseware designed to enhance Figure 1: Courseware Defined
perceived the usefulness of their course towards anengineering degree. Even though there were differences between the two sites that extendedbeyond the pedagogies used in first-year courses that could influence student motivation, thedifferences in instructional methods appears to have played a key part in how studentsexperienced their first-year coursework and developed ideas about engineering work.Introduction and Purpose of the ResearchProblem-based learning (PBL) is a pedagogical practice that has been shown to be effective inscience and engineering courses for promoting student learning 1-11. This approach is alsogaining traction as a possible way to promote student motivation and retention in engineeringprograms 12-14, although research
teamwork or design skillsor fundamentals rather than understanding these skills in relation to one another. This paperexamines the E2020 suite of knowledge and skills to 1) determine whether there are engineeringseniors who score highly on all outcomes, and 2) develop and compare profiles of studentswithin an outcomes-based typology for two engineering disciplines.E2020 Learning OutcomesThe E2020 outcomes include a variety of learning goals for graduates, including areas such asbasic engineering and design, professional skills, contextual competence, and interdisciplinaryskills1. Assessment of many of these outcomes poses a challenge, as there are no standardizedtests available for evaluating student knowledge in many areas, and for some skills
programs.Ten companies that hire materials engineering graduates of the universities included in this studywere also selected as content sources. Companies were selected to represent a variety of sizes,industry sectors, and types (e.g. service-oriented, production-oriented, or both). Page 25.786.5 Table 1. Universities included in content analysis. U.S. News U.S. News Undergraduate Undergraduate University
, and skills on a scalethat will meet the need. Although some traditional engineering faculty workshops havehad positive results as reported by Felder and his colleagues, 2, 7, 8 several investigatorshave identified some important issues with the short-term, face-to-face model. 6, 9, 13Specifically, such workshops do not allow time for faculty members to go through thetransitions from awareness to action, 9 can cause an adversarial relationship between thepresenter and the participants, 6 and do not encourage participants’ motivation andcommitment.13 The inadequacy of existing faculty development models is reflected in: 1)the slow adoption of engaging, active-learning methods that have been systematicallytested and shown to improve student
example of which is providedhere.The authors present data from the first implementation of this module in an engineeringdepartment with an identified deficiency in outcome 3j and demonstrate how the deficiency wasresolved through this practice. The department in question had established (prior to this effort)two criteria for assessing outcome 3j and these are indicated in Table 1. The first (J1) can bebroadly described as an awareness of goings-on in engineering both in the public-arena (e.g.high-profile successes or failures) and in the sense of being aware of some of the current researchefforts in engineering sub-disciplines. The second (J2) is concerned with assessing whether thestudent is aware of the impacts and consequences (realized or
separated intention Page 25.855.3and strategy into two major scales, comprising four intention sub-scales and three strategy 2sub-scales respectively. After statistical analysis in several stages 1 they arrived at a finalversion consisting of nineteen items ranked on a positive scale (1-5), where 1 representshardly ever true, and 5 nearly always true. All items are positively scored.The factor analysis conducted on aggregated data from a number of studies was unable todemonstrate the viability of the originally proposed scales. The final version consists oftwo major scales Conceptual Change/Student Focused
concentrated onmethods of teaching and learning such as student research experiences.1 However, it isimportant to realize that STEM educational objectives and outcomes which, over the course ofthe undergraduate degree, represent all levels of Bloom’s taxonomy2 are overlaid with thestudent life experience represented by Maslow’s hierarchy of needs.3 Thus, if a student has notexperienced a sense of belonging, the third level of Maslow’s hierarchy, it may become thebottleneck in the goal to improve learning outcomes and achieve educational objectives.Maslow’s hierarchy of needs presents a theory of human motivation.3 The hierarchy includesfive levels of needs. The lowest level is physiological needs (food and water), and the next levelof needs is
researchoutcomes that reflect knowledge integration12 13 Accordingly, numerous studies in thebibliometric community have focused on research publications to measure intellectual diversityencoded in publication records, by analyzing the association of the journals that they cite tocorresponding Subject Categories (SCs) provided by Thomson Scientific’s Institute for ScientificInformation (ISI) 14 15 16. The present study was designed to investigate how interdisciplinary a body ofengineering education research is in the wider sense of knowledge integration. The projectemployed two complementary bibliometric approaches in terms of the issue of interdisciplinarity,including (1) a top-down approach using pre-defined categories (typically ISI Subject
EngER in that, it allows for a systematic, organizedoverview of K-12 EngER and allows for analysis of this relatively new field. This study could also guideK-12 EngER researchers to choose their research topics, to look for research collaborators, and toexplore niche research areas. The major findings resulted as follows: (1) K-12 EngER has just began totake shape and grow in the last 10 years, (2) the most popular keywords such as STEM, stud*, teac*and curricul* reveal the topics that have been most researched in the past, (3) Engineering Education(EngE) epistemologies have been the most researched area, (4) high school is the most researched for aK-12 EngE curriculum, (5) elementary education compared to other grade levels is underrepresented
assessmentin their classrooms. The results will illustrate a method for quickly classifying students’ errorsassociated with evaluating engineering systems and recommendations for how to designformative feedback for classroom and individual learning system.BackgroundBlack & Wiliam conducted an extensive research review of more than 250 journal articles andbook chapters on the effectiveness of formative assessment [1]. They proposed that efforts tostrengthen formative assessment produce significant learning gains, and eventually raiseacademic standards in classrooms. Specifically, they pointed out that effective formativeassessment involves collecting evidence about how students make progress during learning andmaking necessary instructional
to provide a growing economy, strong health and human services, anda secure and safe nation depends upon a vibrant, creative, and diverse engineering and scienceworkforce”. 1 To contribute to technological advancements, engage in global collaboration,solve complex problems, encourage a more socially just profession, and respond to the predictedshortage of American engineers, it is necessary for this nation’s engineering workforce anduniversity student bodies to be more diverse in its racial, gender, and socioeconomic (SES)representation. The lack of representation in SES is the focus of this research.The purpose of this qualitative study was to give low-SES students an opportunity to share theirstories about the influences that prompted them
, and parsimonious measure of the contextualcompetence of undergraduate engineering students.Introduction The practice of engineering requires more than solving for x. Engineers must be able tosolve real-world engineering problems while also understanding the range of their relevantcontexts. Projects such as the One Laptop per Child program, China’s Three Gorges Dam, andnew ultra skyscrapers illustrate the social, economic, environmental, political, and culturalchallenges of today’s engineering problems. The ABET program accreditation Criteria 3.c, 3.f,3.h, and 3.j promote contextualization of engineering practice [1]. The ABET criteria mandateoutcomes to ensure that engineering graduates cultivate the non-technical skills
, respectively. The test administered was the Modified Purdue SpatialVisualization Test of Rotations with fifteen weeks passing between the pre- and post-tests. Bothtests had the same form to avoid issues pertaining to reliability. In addition, both tests had abalanced design between the experimental and control groups to equally distribute the impact Page 25.922.6effects of testing validity. Students were given 40 minutes to complete the 30 question test.Non-circular and demographic questions were inclusive to the post-test questions. 65 studentswere from the face-to-face sample while 57 students were from the distance education sample.Table 1
,students were forced to confront and repair certain misconceptions acquired at earlier stages oftheir education, to utilize laboratory experiments to gather additional data, and to recognize andthen resolve ethical issues.Here we introduce several issues when implementing MEAs in upper division level classes byproviding two case studies. These issues are circulated around the theme of engineering learningsystems, and in particular to the professional or “soft” skills. Specifically, the following insightsare provided across two MEAs from two different disciplines and engineering schools: 1. The instructional culture challenges involving MEAs implementation in the classroom; 2. How faculty’s personal epistemology for teaching
work within each of them. Table 1 summarizes this agreement.Table 1: Comparison of epistemic commitments and practices in mathematics, science andengineering Science Engineering Design MathematicsGoal Explain natural Solve a problem Identify patterns and phenomenon by through design, structures on which to building general changing the world base conjectures principles, regarding future understanding the patterns and world structures.Common • Ask and refine
thinking in a virtual internshipIntroductionEducational institutions at all levels have historically struggled with motivating and retainingwomen in science and engineering. Blickenstaff [1] and others have referred to this as theproblem of a “leaky pipeline,” in the sense that women opt out of the path from elementaryschool through university and on to STEM careers at various points along the way. Onesignificant “leak” occurs when declaring an undergraduate major in the first year [2, 3]. Researchsuggests that women with an interest in engineering enter undergraduate programs with highlevels of self-confidence, but these levels decline significantly during the first year [4]. Thesingle biggest drop in
, as U.S. employersin high tech industries struggle to find qualified employees amidst a shortage of STEM degreesin the workforce. In August of 2011, President Obama’s Jobs and Competitiveness Councilcalled for an additional 10,000 engineering graduates each year to meet these shortages [1]. Ifthese goals are to be met, educators in engineering disciplines must strive to improve theirgraduation rates, as only 40% of students that begin their education in STEM fields go on tocomplete their degree in that field [2]. Such low graduation rates may be discouraging, but foreducational researchers they highlight the opportunity for significant gains to be made. However,realizing these gains may require a systematic reevaluation of all parts of the
Data, and ii) a flexible typology of fundamental processes ofvalidation (theoretical, procedural, communicative, pragmatic) and the notion of processreliability. Both of these aspects of the framework are illustrated with examples from theaforementioned study. Future work is planned to further develop the conceptual framework as alanguage for the engineering education community to engage in a discourse around shared,contextual and flexible understandings of research quality.Introduction: Questions of quality in qualitative engineering education researchEngineering education research is an inherently interdisciplinary endeavor [1-3] that is currentlybeing undertaken by a community of engineers, social and educational researchers with diverseand
data. The study reportedin this paper uses the same analysis framework, but at a finer grain size using “think-aloud”protocol analysis.The following research questions frame the study: 1. How do the Model Maps created using the coarser grain analysis based on work products compare to the finer grain analysis based on protocol data? 2. Do the coarser grain data give a reasonable representation of a team’s modeling process?Assessing Learning in Virtual LaboratoriesVirtual laboratories, simulations, and educational games have recently been receivingconsiderable attention as an alternative mode to university instructional laboratories to achievelearning.7,8 In engineering and science, the virtual laboratory is most commonly used as
assignment (Figure 1 shows one of the problems from this assignment), aretypical of the prompts we used: 1 Why did you select the system that you used for your free-body diagram? 2 Could you have selected some other system and still solved the problem? 3 How did you model each of the reaction forces? For example, did you consider the reaction to be a pivot, roller, contact with friction, etc.? 4 When computing moments for the moment equilibrium equation, why did you choose the particular point that you used to compute moments about? For example, if you computed moments about point A, why did you pick A and not some other point? 5 Could you have simplified the analysis by picking some other point to take moments about? 6