-frequency terms. It was only the keywords and alphabetical strings thatwere used with a naïve-Bayes classifier from the Bayesian Knowledge Discovery project.3 The C4.5algorithm was also used4 and 20,816 cases were analyzed.A similar approach using updated tools could be effective when looking at the interaction betweenemployees in a support environment. There are two sources of text to be analyzed. First, there are chatsessions between employees. Second, when a second-level employee takes a call from a first-level, orsimply provides an assist, there are sets of notes that can be analyzed. The first-level employee shouldbe taking complete notes about the nature of the case and what troubleshooting did not resolve theproblem. Then the second-level
and learning process. The goal of this project is to explore the educational philosophiesenacted in the most impactful undergraduate classrooms, according to graduate students’perceptions, in order to give the new educator a foundation for their own course design process.Previous ResearchWhy Examine Students’ Perceptions of Learning Environments?At the start of the new semester, students enter a classroom not as “blank slates,” but withparticular conceptions about teaching and learning based on their prior experiences5. As a result,the effects of learning activities and perceptions of classroom interactions among the instructorand the students may differ by student5,8. Further, research has also shown that students’conceptions about teaching
. In the mid-1970s, David Kolb published works thatcategorized human learning styles and how they respond to various types of experientiallearning.2 At least three out of Kolb’s four learning styles benefitted most through “concreteexperience” and “active experimentation.”2 Furthermore, Schumann, et. al., reported that manystudents who leave engineering do so because of a lack of interest in the topics.3 In 2010, in aneffort to increase retention rates among engineering programs, the National Science Foundationsponsored a project called “Engage.”4 One of the three objectives of this project is to increaseretention by “Integrating into coursework everyday examples in engineering (E3s).”4 Also, asampling of recent papers that studied the
these things relate to the course goals?With the answers to these questions in mind, the TA and instructor can think about the purposeof other class assignments (pre-class and post-class homework/projects) that will preparestudents with these skills. Questions to consider while creating these assignments, as discussedin the “Active Learning in STEM Courses” mini-course, are as follows: 1. What kind of questions are being asked in these different categories (pre-, in-, and post- class)? Page 26.755.8 2. How do these questions compare across categories and to the exam questions? How do the formats compare? How does feedback on these
expressly devoted to the first-year Engineering Program at Northeastern University. Recently, she has joined the expanding Department of Mechanical and Industrial Engineering at NU to continue teaching Simulation, Facilities Planning, and Human-Machine Systems. She also serves as a Technical Advisor for Senior Capstone Design and graduate-level Challenge Projects in Northeastern’s Gordon Engineering Leadership Program. Dr. Jaeger has been the recipient of numerous awards in engineering education for both teaching and mentoring and has been involved in several engineering educational research initiatives through ASEE and beyond.Dr. Courtney Pfluger, Northeastern University Dr. Courtney Pfluger received her Doctoral degree
education research, interdisciplinarity, peer review, engineers’ epistemologies, and global engineering education.Mr. Corey T Schimpf, Purdue University, West LafayetteDr. Alice L. Pawley, Purdue University, West Lafayette Alice Pawley is an Associate Professor in the School of Engineering Education and an affiliate faculty member in the Gender, Women’s and Sexuality Studies Program and the Division of Environmental and Ecological Engineering at Purdue University. She was co-PI of Purdue’s ADVANCE program from 2008-2014, focusing on the underrepresentation of women in STEM faculty positions. She runs the Feminist Research in Engineering Education (FREE, formerly RIFE, group), whose diverse projects and group members are
interviews of officials within Denmark’s ministries, this can only beconsidered a preliminary look at the institutional responses in Denmark. We also note that ouraccess at DTU was also limited by a recent, controversial decision on the part of one of thePROCEED co-investigators to relocate from DTU to Aalborg University. We believe ourfindings to be of significant interest to engineering educators in the United States. While the fullfindings of our study will be released in an edited volume produced by the PROCEED project, asummary of our findings is presented here for the ASEE audience. In the following section, wefirst present a brief introduction of the Bologna Process and the diverse reactions to it acrossnations and institutions.Varied
. As part ofthis group, I regularly train men, both on- and off-campus, to better serve as gender equity allies.I am a member of the Commission on the Status of Women Faculty, a committee that works todevelop and enhance gender-equitable policies at North Dakota State University. I am primaryauthor of a series of broadly distributed advocacy tips, have participated in a national webinar onengaging male faculty as gender equity allies, and have given several conference presentationson the same topics. Additionally, I currently serve on the planning committee for the NSF-funded project Transforming Undergraduate Education in Engineering (TUEE), which has thegoal of enhancing women participation and success in engineering programs.Dr. Holmes: I
universities design their pedagogicaltraining to support their growth as instructors? To what extent do new engineering graduatestudent instructors reflect on their pedagogical training and apply the new skills from training totheir classroom experiences?To address these questions, this project was designed to explore first semester engineering GSIs’perceptions of their pedagogical professional development through the lens of Wlodkowski'smotivational factors for adult learners.8 As summarized by Felder, Brent & Prince (2011), thereare five key characteristics for motivating adult learners to engage in professional development(e.g., expertise of the facilitator, relevance of the topic, choice on how to apply best practices,praxis (action and
problem statement and building amodel from fundamental principles using explicit assumptions and application of problem spe-cific information. Thus, the answer produced by the student is supported by an explicit chain oflogic that can be examined by everyone.University of New Haven (UNH)In 2004 Tagliatela College of Engineering at UNH introduced a set of common engineering fun-damentals courses for all engineering programs. The set of courses, collectively referred to as theMultidisciplinary Engineering Foundation Spiral Curriculum (MEFSC)19,20, spanned the fresh-man and sophomore levels. First-year courses include project-based courses to introduce the en-gineering design process, project planning, and the use of spreadsheets with Visual Basic
Mechatronics and Entrepreneurship, a GK-12 Fellows project, and a DR K-12 research project, all funded by NSF. He has held visiting positions with the Air Force Research Laboratories in Dayton, OH. His research interests include K-12 STEM education, mechatronics, robotics, and control system tech- nology. Under Research Experience for Teachers Site and GK-12 Fellows programs, funded by NSF, and the Central Brooklyn STEM Initiative (CBSI), funded by six philanthropic foundations, he has con- ducted significant K-12 education, training, mentoring, and outreach activities to integrate engineering concepts in science classrooms and labs of dozens of New York City public schools. He received NYU- SoE’s 2002, 2008, 2011, and 2014
States, Ecuador, Chile and Argentina and 26 workshops in Mexico, Chile and Argentina. He has participated obtaining projects funded by the European Consortium of Innovative Uni- versities, HP Development Company, Agencia Espa˜nola de Cooperaci´on Internacional para el Desarrollo and the University of Arizona. He is a member of the Mexican Council of Educational Research, Vi- cepresident of the Latin American Physics Education Network (LAPEN), coordinator of the Evaluation of Learning and Instruction Topical Group within the International Research Group on Physics Teach- ing (GIREP for French); member of the American Association of Physics Teachers (AAPT) in which he was member and president of the International
—students wearconcert t-shirts showcasing their favorite music artists, instructors play music during class topromote a particular learning environment, groups of students listen to music as they worktogether on a project or as they attempt to solve a homework question. Previous research haslinked musical preference to personality and values, both of which correlate to social identity,and to a lesser extent, academic study habits. Pierre Bourdieu's landmark text La Distinction alsoasserts that social class influences judgments of taste and choices in cultural activities.Researchers have also used markers such as genre taste as a cultural indicator, focusing on"high" arts, such as classical music, ballet, and art museums as measures of culture.1
theirbachelor’s degrees in engineering. We focus on these individuals due to the scarcity of researchon their experiences and the relevance of their perspectives to engineering education.29-31Implications of this work will focus on recommendations for educational research and practice.Framework and LiteratureThe overall EPS project is broadly situated in social cognitive career theory (SCCT) which positsthat a variety of factors influence career choice including self-efficacy beliefs, outcomeexpectations, and learning experiences.32 SCCT has been used extensively in the study ofengineering students’ career choices.33-37 A main goal of our study has been to identify theschool and workplace factors related to the career choices made by engineering
the distinction between collaborative learning on the one hand and cooperativelearning on the other (see, e.g., Olivares 2 ). Cooperative learning is group learning whose main goal is for everymember of the group to learn 3,4 . Our focus is on this type of learning. By contrast, the goal of collaborative learningis for the group to work together to solve a problem, complete a project, etc.; ensuring that each individual memberof the group learns some particular item of knowledge is secondary. We should also add that not all authors use thesedefinitions of cooperative and collaborative learning with some authors conflating the two and others interchangingthe two terms 5,2 . In any case, there seems to be consensus that there are two types of
construction education and training oppor- tunities, emphasizing construction-based workforce development. He has contributed to, and developed curriculum for, construction management training programs in Mexico, Egypt, and Tunisia. He is pas- sionate about connecting underrepresented and unemployed populations with sustainable employment opportunities in the construction industry. Jon has over five years of experience in construction and his commercial project management experience focused on core and shell office building projects and historic building restoration/rehabilitation in Washington DC Page 26.732.1
Hrastinski, KTH Royal Institute of Technology Stefan Hrastinski is Associate Professor at the The School of Education and Communication in Engineer- ing Science, KTH Royal Institute of Technology, and Visiting Professor with specialization in e-Learning, Mid Sweden University. His research focuses on online learning and collaboration in educational and or- ganizational settings. Stefan has conducted research and development projects across various contexts, including higher education, school settings, companies, municipalities and the public sector. He teaches courses in e-learning, and supervise theses on bachelor, master and Ph.D. level.Prof. Inga-Britt - Skogh
spring 2014 panels as a service project as achapter officer served as a member of the panel voluntarily, not for credit in CE 3311. Thestudent chapter participated by drafting the survey given to students (survey was reviewed by theinstructor and adjusted slightly) that is presented later in this paper, administering the survey, andproviding the results after grades had been submitted to the instructor.3.0 AssessmentsSchilling et al.5 describes a taxonomy based approach (i.e. to assign a given written commentinto one or more categories) to qualitatively assess written comments on student evaluations. Asimilar approach was used in a few instances for the assessments that follow.3.1 Student EvaluationsFigure 3 provides a summary of
Paper ID #12638Honing Interpersonal Communication Skills for Difficult Situations: Evi-dence for the Effectiveness of an Online Instructional ResourceMs. Amy Elizabeth Dawson, Arizona State University Amy Dawson, M.A., is a doctoral student in the Counseling Psychology program at Arizona State Uni- versity. Amy is also a research assistant for the NSF funded CareerWISE project housed at ASU.Prof. Bianca L. Bernstein, Arizona State University Bianca L. Bernstein, Ph.D. is Professor of Counseling and Counseling Psychology in the College of Let- ters and Sciences at Arizona State University. Dr. Bernstein is Principal Investigator
various active learning methods. Forexample, only 9 percent said they never had students discuss problems in pairs or groups, and Page 26.890.3only 18 percent never had students work on problems sets or projects in pairs or small groups.There are some important limitations of this work. First, it is unclear the extent to whichinstructor self-reporting is accurate (as noted by the author) or the extent to which therespondents were representative of all instructors. Responses might be more likely from facultyactively engaged in trying to teach statics most effectively. The quality of implementation of thevarious methods varies widely. As shown in a
course, students learnthe basic skills necessary for visual technical communications and spatial visualization. Topicsinclude engineering sketching and drafting, orthographic projection of multi, sectional, andauxiliary views, dimensioning, tolerances (the first half of the semester), and solid modelingusing the Computer Aided Design (CAD) tools (the rest of the semester). In a typical class, theinstructor delivers a short lecture followed by a class activity based on the lecture. For example,in a class that teaches multi-view of objects, the class activity is to derive the multi-view for agiven set of objects on an assignment sheet. The instructor helps the students during this activity.Once they complete the class activity, they are allowed to
Paper ID #13484”It’s Too Hard,” to ”I Get It!” – Engaging Developmental Science as a Tool toTransform First Year Engineering EducationProf. Carmela Cristina Amato-Wierda, University of New Hampshire Carmela Amato-Wierda is Associate Professor of Materials Science at the University of New Hampshire. She shifted her research focus several years ago to the area of cognitive development of STEM concepts and practices in grades K-16. She has held NSF funded curriculum projects in General Chemistry and Materials Science, and has recently developed two science courses for non-scientists, titled: The Science of Stuff and
were achieving their goals.”4 This challenge led to some programs being dropped fromconsideration due to a lack of documentation and evaluation data.4 In addition, minorityretention issues in STEM are complex phenomena, compounding the research and evaluationchallenge.6 While the need for more qualitative studies to understand these complex nuances isevident, there is also a need for more rigorous quantitative work. For example, in a review of 28Louis Stokes Alliances for Minority Participation (LSAMP) projects, although studies wereprimarily quantitative or mixed methods designs, the focus was on participation numbers andgraduation rates of URMs in STEM with no experimental designs.6Tinto7 argues for improved assessment and evaluation efforts
exam was administered. Improved security measures haveprevented additional problems. Development of new problem resources puts considerabledemands on instructor time. During the initial implementation period for the surveying coursesand BREG 321, the author’s time was allocated for LON-CAPA resource development. Oncethe project was underway, all conventional homework problems in those courses were convertedto online delivery through LON-CAPA. Page 26.37.7Table 1. Information about courses in the study. # of Course Title and Notes
implemented with the intention ofmaking assessment more formative, though the differences in perceptions between in classexams and out of class homework may make a difference for students. Though the data onstudent learning is limited in these studies, they did indicate that students reported giving moreattention to instructor feedback [9] and that the mastery system was more “fair” [10], showingpromise for the methods and echoing similar results found in this study.Because the focus of this project was on homework assignments conducted outside of theclassroom, the design of the automated assessment systems were used as a starting point, thoughthe evaluation itself would not be automated. The authors instead focused on emulating theprocess of
stories to the overall project and to the community to “hear” the testimonies and to facilitate adhering to of engineering education the participants’ reality during analysis. -We co-construct meaning-making within the research team so as not to mis-construe or stray from participants’ testimony The concepts underlying the research design The knowledge produced needs to be meaningful
Paper ID #13824Developing an Intensive Math Preparation Program to Enhance the Successof Underrepresented Students in Engineering ˜Prof. Denise Hum, Canada College Denise Hum is an Associate Professor of Mathematics at Ca˜nada College in the San Francisco Bay Area. She received her M.S. in statistics at California State University, East Bay. Her academic interests in- clude accelerated math pathways, Reading Apprenticeship, and increasing the number of women and underrepresented groups in STEM.Ms. Anna Marbella Camacho, Canada College As Project Director for a $5.9 million Hispanic-Serving Institution
of the course, students have atleast 33 hours of hands-on activities. The knowledge gained via theoretical and practicalexercises is reinforced by the computer projects utilizing MATLAB simulation software.In 2009, the first attempt at converting the existing traditional model of the EM course into theblended version has been made. Utilizing the hybrid methodology, several lectures wereconverted into the online format and gradually introduced to the class of 40 students. Feedbackcollected from the students showed an interest in the hybrid/blended version of the course. Astandard assessment model previously conducted for traditionally taught EM coursesdemonstrated an increase in comprehension of the subject. The last contribution was due to
Paper ID #11436Epistemic Network Analysis as a Tool for Engineering Design AssessmentMs. Golnaz Arastoopour, University of Wisconsin, Madison Before becoming interested in education, Golnaz studied Mechanical Engineering at the University of Illi- nois at Urbana-Champaign with a minor in Spanish. While earning her Bachelor’s degree in engineering, she worked as a computer science instructor at Campus Middle School for Girls in Urbana, IL. Along with a team of undergraduates, she headlined a project to develop a unique computer science curriculum for middle school students. She then earned her M.A. in mathematics
from a broad viewpoint to a specific focus (converge). Divergence is associated with activitieslike brainstorming, ideation, building, and prototyping. Convergence is associated with activities such asanalysis, selection, evaluation, and testing.Altogether, five stages comprise this framework. The shape in figure 1 was created to represent and showthis framework as an iterative process versus a linear one. Stage 1 focuses on conversations or actionspertaining to defining requirements, project scoping, and gathering information about a particular project Page 26.1038.5or the needs of stakeholders. Stage 2 focuses on conceptual