as “one of the more instructionally powerful and least understoodfeatures” of learning.1 Appropriate feedback can help to address student misconceptions,improve transfer of knowledge, and increase retention and satisfaction in school. However, bothimplementing and studying feedback is complicated; feedback content and effectiveness varieswidely depending on the learning environment and the people involved in the feedback process.Feedback effectiveness can change depending on its timing, complexity, structure and content.Furthermore, students react to feedback differently based on differences in their personalities,backgrounds, academic capacities, and understanding of the material.This paper empirically investigates feedback in a project
Youngstown State University, with a Bachelors of Engineering degree in Electrical Engineering in 1981. He then obtained his MS and Ph.D. in Electrical Engineering from GA Tech in 1982, and 1988 respectively. He joined the Electrical and Computer Engineering department at the University of New Mexico where he is currently professor and was the chair between 2005 and June 30, 2011. Since July 1, 2011, Professor Abdallah is the Provost and Executive Vice President for Academic Affairs at UNM. Professor Abdallah conducts research and teaches courses in the general area of systems theory with focus on control and communica- tions systems. His research has been funded by national funding agencies, national laboratories, and by
engineering overview assignment given to the first year students rightat beginning of their study had managed to lead them into the desired mindset of what theyshould prepare themselves for while learning to be future engineers.IntroductionIn the 21st Century, there is a high demand for engineering graduates who have soundtechnical knowledge as well as positive attitude and good professional skills, such as problemsolving, communication, teamworking, etc.1, 2. Nevertheless, learning engineering content initself can be challenging to most students, resulting in problems on maintaining students'interest and motivation to learn, as well as retaining them3. In addition, the lack ofunderstanding and connection of how the material they have to learn or the
education—and engineering in particular—remains largely unexplored. In order to inform and examinedesigns for idea-centered, knowledge-building discourse communities in undergraduateengineering education, this paper reports on an analysis of the data collected in a sophomoreengineering mechanics course using knowledge-building pedagogy. This includes attempts tomeasure (1) changes in the learners’ conceptualization of the learning process based upon surveydata and (2) changes in the nature of their knowledge-building contributions over time based onan analysis of knowledge-building discourse.Learning EnvironmentParticipantsData was collected over a two-year period in a four-credit, semester-long introductoryengineering mechanics course at Smith
influences that encourage engineering faculty members toemphasize interdisciplinary knowledge, topics, and skills. Our conceptual framing is based onthe assumptions of the academic plan model, which posits that a variety of factors, both internaland external to faculty and their institutions, influence faculty as they plan and design courses 46.The academic plan model (Figure 1) builds on the observation by Toombs and Tierney47 that acurriculum is “an intentional design for learning negotiated by faculty in light of their specializedknowledge and in the context of social expectations and students’ needs” (p. 183). Toombs andTierney identified three essential parts of a curriculum design process: the “content” that is to betaught; the “context” in
retention of new knowledge and acquisition of desirable personal traits.Any such method that engages students in the learning process is labeled as: “active learning”method. In essence, active learning requires doing meaningful learning activities in groups underthe guidance of an informed and experienced teacher. As stated by Christensen et al (1), “To teachis to engage students in learning.” The main point is that engaging students in learning isprincipally the responsibility of the teacher, who becomes less an imparter of knowledge andmore a designer and a facilitator of learning experiences and opportunities. In other words, thereal challenge in college teaching today is not covering the material for the students, but ratheruncovering the
faculty Page 24.1006.2members, who taught in both conditions, also completed reflection papers related to theirexperiences. The following describes guiding research questions for the study.Research questions: 1. Do students in inverted classrooms spend additional time actively working with instructors on meaningful tasks in comparison to those students in control classrooms? 2. Do students in inverted classrooms show higher learning gains as compared to students in traditional classrooms? 3. Do students in inverted classrooms demonstrate an increased ability to apply material in new situations as compared to students in
their effectiveness, the adoption of these practices has beenslow and not necessarily persistent11-16. Our own research with instructors in electrical/chemicalengineering17 and introductory physics instructors18 confirms that more than one-third of facultywho have tried to implement one or more nontraditional teaching methods discontinue their use(e.g., Figure 1).Figure 1. The largest group of faculty (35%) have tried nontraditional teaching methods and Page 24.1120.2 then discontinued their use Research has identified a number of barriers to the use of these nontraditional teachingmethods, such as instructor concerns about
Figure 1. Vygostky’s activity theory model for this study. Page 24.582.4Research Design and MethodsInstructional ContextThe course entitled “Introduction to Rechargeable Batteries” is an elective course for upper levelundergraduate and graduate students interested in developing an understanding on the materialsscience of rechargeable batteries. This course included an introduction to basic electrochemistry,principles of electrochemical devices, and electroactive materials as used in rechargeable batterysystems. The instructional goal for the course was to provide students expertise regarding thefundamental analytical and computational modeling
community of practice. Consequently, theseresearchers may be unable to adopt best practices from and exchange relevant information withthe greater community. Page 24.279.21. IntroductionResearch collaboration often occurs between colleagues working within similar as well asdifferent disciplines. Collaboration is known to boost creativity, increase access to relevant skillsand knowledge, provide intellectual companionship, and grow researcher network size.1-3Through collaborations, social capital is leveraged as a transfer of information and knowledge isfacilitated through formal and informal networks.4 Additionally, future opportunities
engineering problems” 1.While many courses in different engineering curriculums have a focus on problem solving,statics is typically the first course in many students’ undergraduate engineering coursework thatrequires them to use an engineering problem solving process. Many researchers have spentsignificant resources investigating how students learn in statics and how to effectively teachproblem solving in statics courses. For instance, Steif, Lobue, Kara, and Fay developed anintervention where students where engaging in talk about salient features of the statics problem2.Steif and team found that students that were engaged in body centered talk were better atrepresenting unknown forces on free body diagrams than students that did not participate in
revised theoretical understanding is gained through the researchprocess. This framework does need additional exploration within engineering and thephysical sciences. Additional findings will contribute to engineering education’s currentdiscourse on graduate education and identity.!!!![1] Mann, L., P. Howard, F. Nouwens, F. Martin (2008). Professional identity: A framework for research inengineering education. Proceedings from 2008 Australasian Association for Engineering Education,Yeppoon.[2] Case, J. M., G. Light. (2011). Emerging methodologies in engineering education research. Journal ofEngineering Education, 100(1), 186-210.[3] Meyers, K. L., M. W. Ohland, A.L. Pawley, C.D. Christopherson. (2010). The Importance of FormativeExperiences for
experience as an intentional form of thinking where aperson revisits an experience with a specific meaning making lens. While reflection has nothistorically received a great deal of attention in engineering education scholarship, we aremotivated by calls for greater consideration of reflection. For example, in her NationalAcademies piece calling for curricular change in undergraduate engineering, Ambrose notes that“…students learn by doing, but only when they have time to reflect—the two go hand in hand.Why, then, don’t engineering curricula provide constant structured opportunities and time toensure that continual reflection takes place?” (p.1).30 There is opportunity for more research onand efforts to support reflection in engineering education
the value of heutagogyin academic versus workforce development environments in science, technology, andengineering. Page 24.830.2Andragogy, Self-Directed Learning, and HeutagogyAndragogy is a theory that holds a set of assumptions about how adults learn. Accordingto American Council on Education, adult learners are learners over the age 25 and oftenreferred to as non-traditional learners. These individuals usually have additionalresponsibilities such as family, career, military or community and are seeking a degree oreducational offering to enhance their professional or personal lives (American Council onEducation, n.d.)[1]. According to National
. Page 24.834.1 c American Society for Engineering Education, 2014 Judging the Quality of Operationalization of Empirical- Analytical, Interpretive and Critical Science Paradigms in Engineering Education ResearchIntroductionParadigms are basic sets of beliefs that guide disciplinary inquiry. They can be constructed froma proponent’s responses to basic questions of ontology, epistemology, and methodology. Thethree basic questions are1: 1. Ontological: What is the nature of the “knowable”? Or, what is the nature of “reality”? 2. Epistemological: What is the nature of the relationship between the knower (the inquirer) and the known (or
doing (problem formulation and problem solving), and design andengineering learning (focused on change in the student’s conceptual understanding of design).Research Methods and ParticipantsTo best address the research questions, this study uses multiple methodologies to collect andanalyze data around engineering students’ learning. Empirical evidence of what design andengineering thinking looks like and how it changes over time, and how students conceptualizedesign and engineering, comes from two participant groups: (1) a spread of undergraduateengineering students across fields of engineering, and (2) a homogeneous group of MechanicalEngineering graduate students in a project-based learning course in design and innovation forMaster’s students
institution, which is home to studentengineering design teams, such as a Formula design team. We found that these experiencesenhanced students’ self-directed autonomy and allowed them to take control of their learningtrajectory. We discuss implications for future research and educational practices.IntroductionIt has been estimated that over a human lifespan about 90% of a person’s learning occurs in non-formal environments, that is, people learn through informal experiences.1 As part of theircollege-based undergraduate degree experience, a large portion of engineering students areinvolved in different informal learning experiences, such as co-curricular design teams, studentorganizations, undergraduate research, or studio-based environments. However
adopt appropriate teaching methods for different students.Key words: engineering problem-solving, eye gaze data, visual attentionI. IntroductionSolving complex problems is an important symbol of human intelligence and has alwaysfascinated researchers. Though mental problem-solving studies originated in psychology, todaysome of their methods and techniques are applied and developed in other areas such asmathematics [1], computer science [2], engineering [3], and medicine [4]. Although theseresearchers come from different backgrounds, the questions of common interest are how exactlypeople solve problems and how their performance may be improved.According to Budny’s research on freshman performance in engineering courses at Purdue
increase in the use of visual Page 24.1363.2models for abstract concepts in textbooks, DVDs, and online resources.To our knowledge, however, there has been little systematic research on whether and howvisual models help engineering students better understand abstract concepts especially in theareas of industrial engineering, engineering management, and systems engineering. Toaddress this issue from an engineering education research perspective, two essential questionsare (1) to what extent do visual models of such concepts help students develop a completemental model and (2) whether better mental models lead to better understanding of thedomain
, theresults tend to be context specific[1],[2],[3]. One possible cause of this is the exclusion of any linkof human errors to cognitive processes.The starting point for the present research is based on Action theory. This is a goal-directedtheory that assumes the existence of a conscious choice that guides a person's behaviour to someoutcome[4],[5].In this theoretical context, an error implies that through some intended action, thegoal was not attained[1]. Rooted in this theory, two models of human error taxonomy commonlycited in the literature are: the Generic Error Modeling System model[1] and the Skill-Rule-Knowledge (SRK) model[6]. These models further classify errors as being either the failure ofactions to go as intended (slips, lapse) or as
. Forresponse rates of 40% to 90%, in steps of 10%, 40 survey trials at each rate were simulated. Ineach trial at each response rate, the corresponding number of respondents was randomly selectedfrom the 300 member dataset. For example, if the response rate was 60%, 240 students wererandomly selected as respondents for each trial. From the respondents, the percent of studentsheaded to industry vs. graduate or professional school vs. other activity as well as the percent ofthose students headed to industry who were successfully placed were computed. The results forthe % of graduates headed to industry are illustrated in Figure 1 and those for % of graduatesheaded to industry who were successfully placed are illustrated in Figure 2. The collection
?Through the qualitative analysis the research team was able to gain a more in-depthunderstanding of why students selected certain solution paths.1. Introduction and BackgroundThe overall purpose of this research is to determine if the use of model eliciting activities (MEAs)in the classroom helps to improve students’ ability to solve engineering problems. Model ElicitingActivities are open-ended realistic problems constructed around a few main concepts1-8. Originallydeveloped by mathematics educators, and used at the pre-college level, we have been refocusingMEAs for use in upper division engineering courses. MEAs require the team to develop ageneralizable, mathematical model to solve the problem and to present both the solution methodand the
CPACE computational competencies. • Brief discussion of our efforts to develop and validate assessments to measure computational competencies for engineering students.Introduction The learning sciences have influenced repeated calls for improving engineering educationthat focus on providing students with the opportunities to integrate their knowledge acrossdisciplines through authentic problem solving 1- 6. Computation for engineering cannot simply beaddressed with one or two courses in computing or a few examples scattered in the curriculum,but must be integrated as part of an engineer’s training to become a “Holistic Engineer” 7. One of the challenges of preparing engineers for the rapidly changing workplace is to providethe
, is tainted by prevalent acts that are considered unethical,” adding that it is “tainted byillegal acts”2.As a part of the effort to curb unethical behavior, the mandate of construction related accreditingbodies have instituted requirements for literacy of ethics in the curriculum. The AmericanCouncil for Construction Education (ACCE) requires ethics integration in constructioncurriculum (at least 1 semester hour). The ACCE also states: In addition, oral presentation, business writing, and ethics must be integrated throughout the construction-specific curriculum. Example courses in this division include: Human relations, psychology, sociology, social science, literature, history, philosophy, art, language, political
theoretical frameworks from the literature. The nine constructsmeasured by the SASI are intrinsic motivation, academic self-efficacy, expectancy-value, deeplearning approach, surface learning approach, problem solving approach, leadership, teamworkskill, and major indecision, each using a five-point Likert scale (strongly disagree, disagree,neutral, agree, and strongly agree).Table 1 shows characteristics of the SASI, in terms of origins of items, the number of items, andsub-factors of each construct if any. Several studies supported the solid evidence of reliabilityand validity of the SASI9,10. For example, Reid (2009)10 provided validity and reliabilityevidence of each construct measured by the SASI using multiple factor analyses and
about the effectiveness of extra-curricularacademic programs and surveys related to educational research. Unfortunately, response ratesare typically low as is the case with surveys in general 1. Low response rates make it challengingto draw meaningful assessment and/or research-based conclusions. Our research focuses onincreasing the likelihood of students responding to surveys and in particular to surveys groundedin real-time data collection methods. Real-time data collection means gathering informationabout experiences within the context of the current situation. This approach is also calledExperience Sampling Methods (ESM) 2. ESM are different than standard interview and surveymethods in that they aim to capture the essence of an experience
of Mathematics. He earned his B.S. in Earth Science Education from Boise State University in 2011 with a minor in Physical Science and was a NSF Robert Noyce Scholar. Nathan’s research interests include STEM education, grading and assessment practices, self-efficacy, and student conceptions of science. Page 24.1379.1 c American Society for Engineering Education, 2014 Why I Am an Engineering Major: A Cross-Sectional Study of Undergraduate StudentsAbstractAccording to a recent report 1 K-12 students tend to like mathematics and science. Further, in
pros to the practice, noting that it makes students question theircompetency, causes stress and frustration, and focuses student attention on the system rather thanon their own learning. Many participants equated the practice with teachers who do not careabout their students. More research is needed to understand how engineering faculty canencourage healthy competition, challenge students, and ward off grade inflation withoutengaging in practices that discourage otherwise successful students.1. Introduction We'll have like a 30 percent average [on exams]….When you take the exam, it makes you feel horrible. You come out of there like, “I answered a fifth of that right, at most.” It’s sort of like, “Well, gee, what did I
, longitudinal study. As a result, we are not yet in aposition to extrapolate, responsibly draw firm conclusions or identify trends, nor can we identifyspecific curricular or pedagogical implications. What we can do at this stage is highlight some ofour initial findings that will inform the analysis of the rest of the data. In this paper, we focus onTéa,1 one of eleven participants, based on the artifacts collected to date, although reference willbe made to comments and work of other participants. We hope to show through this preliminaryanalysis how one student uses the experiences and opportunities provided both by the curriculumand this research project to develop a sense of professionalism and how to practice it as achemical engineer as she tries on
engineering. Thereare several guiding principles of constructivism 14,20,24,36,41:1. Understanding comes from interactions with the environment. A learner’s knowledge comes from his/her pre-existing knowledge and experience; and new knowledge is formed when connecting previous experience to the new content and environment.2. Conflict in the mind or puzzlement is the stimulus for learning and determines the organization and nature of what is learned.3. Knowledge involves social negotiation and the evaluation of the viability of individual understanding.The literature suggests that a change in the development of curriculum in teaching IFEM coursesis worth exploring. When compared to