AC 2012-3049: FACULTY BELIEFS OF ENTREPRENEURSHIP AND DE-SIGN EDUCATION: AN EXPLORATORY STUDY COMPARING ENTREPRENEUR-SHIP AND DESIGN FACULTYDr. Sarah E. Zappe, Pennsylvania State University, University Park Sarah Zappe is the Director of Assessment and Instructional Support in the College of Engineering at Penn State University. In this role, she provides support to faculty in trying innovative ideas in the classroom. Her background is in educational psychology with an emphasis in applied testing and measurement. Her current research interests include integrating creativity into the engineering curriculum, development in- struments to measure the engineering professional skills, and using qualitative data to enhance
be taught; 3) knowledge of how to teach others in that area (content pedagogy), in particular how to use hands-on learning techniques (e.g.- lab work in science and manipulatives in mathematics) and how to develop higher-order thinking skills. 4) an understanding of learners and their learning and development– including how to assess and scaffold learning, how to support students who have learning differences or difficulties, and how to support the learning of language and content for those who are not already proficient in the language of instruction. Page 15.108.2 5) adaptive expertise that allow teachers to
terms, down-selection to a design too early in the product development cycle,with insufficient or inappropriate analysis, test, and evaluation commits one to a sub-optimalconcept, which can cause significant penalties downstream and may even result in an infeasibleor intractable design. For example, improper assessment of the debris threat to fragile thermalprotection system (TPS) on the Space Shuttle and the need for tedious TPS waterproofingoperations after each flight resulted in significant post-flight TPS inspections, repair andreplacements (R&R), and tremendous operational expenses that were not foreseen during theinitial evaluation of competing concepts during down-select and the initial concept developmentstage of the Shuttle
ofthe quarter to see how far the students feel that they have learned the concepts from the course.These questionnaires are designed to assess the students’ learning of the materials and theirawareness of the subject materials before and after taking the course(s). There are questions thatare common to both the questionnaires. The transfer of knowledge is one of the major ways ofassessing the students’ understanding of the concepts. To achieve this objective, the conceptsseen in the classroom need to be reinforced in such a way that the students can relate to situationsoutside the classroom. In this paper we will discuss some of the tools that we have been using in the courses andhow the students reacted in such an environment. The paper
skill level on the band saw as low to moderate. Page 24.523.5Table 2a: Survey-based assessment of Rolling Planter exercise. Answers based on 5-pointLikert scale.Rate your skill % Answers % Answerslevel in the Average Average Below 4 Below 4 Response Ratefollowing areas Before After Before After (%)before and after Project Project Project
students in England 3. Yet fewother studies have systematically compared engineering and business students on theirentrepreneurial interests and characteristics.Gender also may differentiate entrepreneurial interests and characteristics of students. Previousresearch indicates that women are less interested in entrepreneurship and have less involvementin entrepreneurial activities than do men 4. Simultaneously, women tend to have lower self-assessments of their entrepreneurial ability, which may contribute to gender differences inentrepreneurship 5. Understanding how measures of entrepreneurial interests and characteristicsvary by gender among both engineering and business majors would bring new perspectives to thedesign of entrepreneurial programs
Member of the Institute of Electrical and Electronic Engineers, a Fellow of the Chartered Management Institute, and a Licentiate and Fellow of the College of Preceptors. His major studies are co-authored book ”Analysing Jobs” about what engineers do at work; three editions of ”Assessment in Higher Education” ; ”Learning, Adaptability and Change; the Challenge for Education and Industry” and the American educational research award winning ”Engineering Education: Research and Development in Curriculum and Instruction” published by IEEE/Wiley. He is a recipient of a Sci- ence, Education and Technology Division Premium of the London IEE for his contribution to engineering education
do. A long term, thinking-centered processseems central to building students' understanding.2. Provide for rich ongoing assessment. While there are many reasonable approaches to ongoingassessment, the constant factor is the frequent focus on criteria, feedback, and reflectionthroughout the learning process.3. Support learning with powerful representations. The teacher teaching for understanding needsto add more imagistic, intuitive, and evocative representations to support students' understandingperformances.4. Pay heed to developmental factors. Teachers teaching for understanding do well to bear in Page 24.661.3mind factors like complexity
this experience is being administered How the “Advanced Technical German” course they take at the partner university helps students integrate into their institute and make the most out of their technical and linguistic development Why this crucial research experience is an excellent preparation for placing students into competitive internships in companies and also for further graduate studies How applying both technical and linguistic skills in an applied real-world context prepares students for 21st century skills How graduates of the program and current IEP students who completed a year abroad assess learning outcomes and skill/proficiency gains
activities of our instructionalmodel.17 We adopted the knowledge dimension, as shown in Table II, to assess if studentsincrease their mastery of conceptual and procedural knowledge to meet the course objectives.We adapted a coding scheme in the cognitive domain to analyze student utterances andcharacterize student-to-student talks. Table III displays the coding scheme that includesstructural components of verbal discourse and underlying cognitive processes in small groupproblem solving.(2) Event history approach18 Page 24.805.4The adaptation of an event history approach in this study is to take a close look at how the focusof the group discussions
students do: stress, pressure, and timeconstraints. In addition, the “publish or perish” mentality at some institutions can push harriedfaculty over the edge: “The temptation of having to spend just a few hours rather than years ofwork to fulfill a publication quota,” suggests Ned Kock, “can be very strong for some.”13Plagiarism is a conscious decision, according to Richard McCuen, a process consisting of fivesteps: “stimulus event,” the pressure point, such as tenure; “identification of alternatives,”spawned by the stimulus; “information gathering,” usually incomplete and/or myopic;“evaluation and decision,” the actual decision point accompanied by rationalizations; and“postimplementation assessment,” a consideration of the ramifications
requirements ofa bachelor’s program in engineering. Page 23.249.5Biggs4 perceives the benefits of “constructive alignment” in terms of an enhanced focus on thequality of student learning, by making explicit not only the course content the student is expectedto learn, but also the level and nature of mastery. The concept of constructive alignment is verysimilar to the assessment cycle required by accrediting agencies such as ABET5 and MiddleStates6. Through intentional course design, all students are encouraged to use higher-orderthinking, not just the academically gifted ones. Biggs states: “The learner is in a sense 'trapped',and finds it difficult to
isnecessarily broad, this is considered healthy. The keywords reflect both current concerns(e.g. assessment and ABET) and continuing concerns (e.g. teaching and design). Thus,according to Wankat, “the journal appears to be publishing papers of concern toengineering educators5.” Clearly, in the past 10 years, as the lack of research on theissues of K-12 education reveals, K-12 issues are not even on the engineering educator’s“research radar zone.”Recently, the American Society for Engineering Education (ASEE) has embarked on anambitious effort to promote and improve K-12 engineering and engineering technologyeducation. In the last three years the ASEE has created a new K-12 division dedicated toK-12 engineering education, created a guidebook for high
= 0.01 and 0.04 for linear and quadraticcurve fits). In contrast, scores on other items, such as “the instructor gave organized lectures,”were highly correlated (coefficients between 0.80 and 0.92) with overall instructor performancescores. A number of strong inter-item correlations suggested and factor analysis confirmed thatthe evaluation form used at Tulane fundamentally assessed two distinct factors, apparently“instructor performance” and “amount of work,” which accounted for 70% of the variance acrossitems. Although correlation does not imply causation, this study re-confirms that engineeringfaculty seeking improved teaching evaluations should focus on improving instructional practicesassociated with content organization and delivery, or
Survey of First-Year Programs Kenneth P. Brannan, Phillip C. Wankat The Citadel/Purdue UniversityAbstractTo assess the current status of first year programs, two surveys of first year programs inengineering were circulated through the ASEE Freshman Programs Division (FPD) listserv. Thefirst survey was sponsored by the FPD, and the second survey was sponsored by the NAE Centerfor the Advancement of Scholarship on Engineering Education (CASEE). Participation in thesurveys involved 91 institutions in the FPD survey and 49 institutions in the CASEE survey.The FPD survey focused on program structure, staffing, and how advising and tutoring isaccomplished
but even a quick review of the recent literature indicates that thediscussion concerning what is the best teaching method or assessment tool is far fromover.7-12 We have been operating under the assumption that combining the best from allapproaches, and tailoring these to fit the needs and situation of our own students, is themost effective way we can improve learning as well as student attitudes. We draw frommany different techniques and ideas including those already cited and others,13-18 and tryto provide as many opportunities for students to learn as possible. The goal of this paperis to describe our experiences and lessons learned to help other faculty interested inmodifying their courses do so in a cost-effective manner, as well as to
Education emerged. 12 The number of papers from the American Society forEngineering Education (ASEE) annual conference that included the terms “global” or“international” in their titles has been increasing, as shown in Figure 1. The diversity of thisliterature cannot be fully described here. However, the papers fall into a few general categories: - International experiences via exchanges, study abroad, and service projects - International collaboration via distance models - Developing student skills to work internationally Page 22.751.2 - Assessing global competencyFigure 1. Number of papers in the ASEE Annual
asindividuals.Cooperative Learning is a formalized active learning structure where students work together insmall groups to accomplish shared learning goals and to maximize their own and each otherslearning. The most common model of cooperative learning in engineering is that of Johnson,Johnson and Smith. (24, 25) This model has five specific elements: mutual interdependence,individual accountability, face to face interaction, interpersonal and small group skills, andindividual assessment of group functioning.(24) Although different cooperative models exist,(26)the core element in all of these models is the emphasis on cooperative incentives rather thancompetition in the promotion of learning.Problem-based learning (PBL) is an instructional method where relevant
from McGill University, and an M.S. and a Ph.D. in Industrial and Systems Engineering with a Ph.D. minor in Women’s Studies from the University of Wisconsin-Madison. She is Co-PI and Research Director of Purdue University’s ADVANCE program, and PI on the Assessing Sustainability Knowledge project. She runs the Research in Feminist Engineering (RIFE) group, whose projects are described at the group’s website, http://feministengineering.org/. She is interested in creating new models for thinking about gender and race in the context of engineering education. She was recently awarded a CAREER grant for the project, ”Learning from Small Numbers: Using personal narratives by underrepresented undergraduate students to
AC 2011-1720: THE 2011 STATE OF MANUFACTURING EDUCATIONHugh Jack, Grand Valley State University Professor of Product Design and Manufacturing Engineering. His interests include Automation, Robotics, Project Management, and Design. Most recently he was part of the team that developed the Curriculum 2015 report. Page 22.1426.1 c American Society for Engineering Education, 2011 The 2011 State of Manufacturing EducationAbstractThe paper complements the work of other groups and professionals, all trying to assess the statusof manufacturing education. To this end the paper
jump from theory to application while providing an insightful view into the variedscience or engineering related career paths33. The ALVA ethics capstone project is a proxy for acumulative final exam that reflects both general and specific learning objectives. At the end ofthe summer, teacher reflection, review of student assessments and program evaluationdemonstrate that the students have an increased awareness of commonly used ethical concepts;the integrated ethos of the ethics in science - mainly genetics research; and in practice applyingtheir newly acquired skill sets.The ALVA program also gives students the opportunity to work as a scientist or engineeringintern in a biotech company or a campus laboratory. As they work, they begin to
introduction, curriculum flow, and grading for a year long, project based, softwareengineering technology capstone course offered in the junior year. Students are formed intoteams of three or four; then they are set free to discover information about the “tasks.” These“tasks,” if completed correctly, will gain them the ultimate position of “Lead SoftwareEngineering Architect”. Students are involved in a yearlong odyssey targeted at large scalesoftware project management and self discovery of techniques required to build a successfulsystem. The paper discusses incoming student demographics, course structure, use of knowledgegold and experience points as incentives, project approach, and outcome of this curriculummanagement model. A method for assessing
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
asindividuals.Cooperative Learning is a formalized active learning structure where students work together insmall groups to accomplish shared learning goals and to maximize their own and each otherslearning. The most common model of cooperative learning in engineering is that of Johnson,Johnson and Smith. (24, 25) This model has five specific elements: mutual interdependence,individual accountability, face to face interaction, interpersonal and small group skills, andindividual assessment of group functioning.(24) Although different cooperative models exist,(26)the core element in all of these models is the emphasis on cooperative incentives rather than Page
., 2008). While there is sufficient evidencethat youth may learn science through non-school science programs (Cantrell, Pekcan, Itani, &Velasquez-Bryant, 2006; NRC, 2009; Sadler, Coyle, & Schwartz, 2000), there is a lack ofresearch on determining what academics youth might learn in engineering design-based after-school settings. When the after-school curriculum encompasses engineering design, thechallenge is great due to the difficulty in assessing intangibles such as design and deepconceptual knowledge. Additionally, ideal learning outcome measures differ between formalschool settings and informal, after-school ones, as traditional academic measures do not capturethe range of ways youth demonstrate learning in informal settings (NRC
department is responsi- ble for ensuring the quality training of program evaluators, partnering with faculty and industry to conduct robust and innovative technical education research, and providing educational opportunities on sustainable assessment processes for program continuous improvement worldwide. She is Principal Investigator of a NSF-funded validity study of her direct method for teaching and measur- ing the ABET engineering professional skills and is adjunct associate professor in the School of Electrical Engineering and Computer Science at Washington State University where she co-teaches the senior design capstone sequence.Dr. Khairiyah Mohd-Yusof, Universiti Teknologi Malaysia Khairiyah Mohd-Yusof is
Transport Concept Inventory (TTCI),20, 21 covers concepts in heattransfer, fluid mechanics, and thermodynamics. Research used to develop the TTCI alsoinformed the construction of the Heat and Energy Concept Inventory,22 which was used to showthe effectiveness of inquiry-based activities on repairing misconceptions in heat transfer andthermodynamics.23 The Materials Concept Inventory has been used to assess conceptual gains inintroductory materials engineering courses.24 Other concept inventories in chemical engineeringthat have been used to assess student learning include, the Engineering ThermodynamicsConcept Inventory,25 and the Material and Energy Balances Concept Inventory.26Design for DiffusionAlthough significant effort has been made in
strongprofessionalism skills: 6 Self Social - Emotional self-awareness - Empathy Awareness - Accurate self-assessment - Service orientation - Self-confidence - Organizational awareness - Developing others - Self-control - Influence - Trustworthiness - Communication - Conscientiousness - Conflict management Management - Adaptability - Leadership - Achievement drive
targeted literature review of institutionally embedded engineering culture from an educationand practice perspective provides initial insight into exploring the question of how to frameengineering culture in the context of change. Ultimately the goal is to develop a usefulframework to assess engineering education culture and examine culture change motivation thatcan help us explore culture in both the profession and in engineering education as a starting pointfor enabling systemic change in support of sustainable engineering and systems.Our approach was as follows: 1. Review and summarize the engineering education literature for attempts to define and characterize engineering culture, with particular focus on cultural dimensions and
and BryanKarazsia developed and validated a climate change anxiety scale, which consists of items on fourdifferent subscales. The first subscale represents items that measure cognitive-emotionalimpairment. These items examine the effect of climate change on emotions, and a person’sability to concentrate (for example, “I have nightmares about climate change.”) The secondsubscale represents items that measure functional impairment (for example, “My concerns aboutclimate change undermine my ability to work to my potential”). The third measures experienceof climate change (for example, “I have been directly affected by climate change”), and thefourth measures behavioral engagement (for example, “I recycle”) [4].In an assessment of the instrument