common learning styles of engineeringstudents and traditional teaching styles of engineering professors”21 all of our students completedFelder’s learning styles inventory, wrote about the impact of their learning preferences, and wenoted which learning styles were more or less likely to make use of Video AI. We found that ourstudents were predominately active/sensing/visual/sequential learners (see Figure 7) which issimilar the “average” engineering student according to Felder. 200 180 Verbal 160 Reflective Intuitive
beneficial for guests in attendance (transient members of the community;see below), as well as for review of video data from IRIFs.Instructions that are given to the presenting students for their ~25-30 minute PowerPoint ™presentations reflect our design of the IRIF as an activity system for a cross-disciplinarycommunity. First, students are to include both (i) a description of the context/motivation for thework and explanation of key terminology or concepts that may be unfamiliar to attendees whowork in other disciplinary areas and (ii) presentation in reasonable detail of a research “nugget,”e.g. a recent accomplishment/milestone, nascent hypothesis, newly proposed protocol, etc. (i.e.subject matter that might also be presented within a meeting of
morality as the determination of right and wrong behavior while ethics is the processby which morals are synthesized into a coherent system. Furthermore, we adopt three primarypropositions: 1. Morality is intimately involved with everyday experiences; 2. Morality and Ethics can, and should be taught; 3. Moral reflection is an important daily occurrence – Socrates The first proposition is in responses to students (and faculty, administrators, staff, etc.)who consider their daily activities to be outside the range of activities to which moral judgmentsshould be applied. This is what allows students to excuse plagiarism – it is a common activity towhich such esoteric philosophical musings as considerations of
emphasizingand supporting engineering education research. These developments parallel a number of other,broader trends, including efforts to promote engineering education research by the EuropeanUnion’s thematic network on Teaching and Research in Engineering in Europe (TREE).The Australasian conference and journal had consistently high ratios of qualifying papers. Due toreasons discussed in more detail below, we expect these trends to continue into 2008. Qualifyingpapers at the ASEE Global Colloquium, on the other hand, ranged from a low of 25% in 2007 toa high of 44% in 2008. These variations likely reflect yearly changes in the location, thematicfocus, and organization of this conference series.Research Activity by CountryCountry-of-origin
AC 2009-1404: "REAL OUTREACH EXPERIENCES IN ENGINEERING":MERGING SERVICE LEARNING AND DESIGN IN A FIRST-YEARENGINEERING COURSEChristopher Williams, Virginia Tech Christopher Bryant Williams is an Assistant Professor at the Virginia Polytechnic Institute & State University with a joint appointment in the Mechanical Engineering and Engineering Education departments. Professor Williams is the Director of the Design, Research, and Education for Additive Manufacturing Systems (DREAMS) Laboratory. His joint appointment reflects his diverse research interests which include design, methodology, layered manufacturing, and design education.Richard Goff, Virginia Tech Richard Goff is an
the team failed.Each individual student also writes a detailed personal reflection on how their actionscontributed to the team’s failure. This technique has been extremely effective in minimizingresentment among students and allowing students to experience failure in a “safe” environment.An alternative scenario for failure is that one or two individuals on the team fail to complete theirportions of the project, putting the successful efforts of the remainder of the team at risk. Thekey to resolving this issue is to identify potential failure points as early as possible. The structureoutlined above allows for evaluation of individual performance since the research andprototyping phases of the project are performed by individuals and graded
in1016, the effects of the annual mass flow across the earth control surface can be consideredinsignificant.Significant energy fluxes do cross the boundaries of the defined earth thermodynamic system.Approximately 177,500 terawatts (terawatts = 1012 Watts) of short wave radiation,predominately solar radiation from a black body of about 6,000 degrees centigrade6, enters theupper atmosphere. About 50,000 terawatts is reflected back into space7 as described by Equation58. E& r ? aE& i (5)where E& r is the rate of reflected energy flux, a is the albedo or reflectivity of the earth, and E& i isthe rate of incident energy impinging on the earth. The average
current information can be garnered. A second trend which also reflects larger social trends, is the demand for a more "consumer oriented"approach to education. This requires shifting the focus of education from teaching to learning; from instructorto student. Curriculum content and methodologies which were once based on the expertise and preferences ofthe instructor, shift towards the needs and preferences of the learner. In its pure form, this trend would havestudents in the role of designer, researcher, and problem-solver, responsible for their own learning, andcreating their own paths through course content. Instructors shift from a 'sage on the stage' to a 'guide on theside' as they help direct student inquiry, facilitate research and
each unit’s content linked to the projects that are a part of theWATER program. We wanted students to be ready to “hit the ground running” armed withbackground knowledge since we would not be holding class sessions in Benin. Each unit ofcontent required completion of a study guide. Other course assignments have includeddevelopment of a teaching plan; participation in teaching water testing and filter manufacturingactivities; and reflective journaling. Students were assigned to interdisciplinary groups todevelop and implement teaching plans. These plans were developed before travelling to Benin,reviewed by course faculty, and revised as needed. Students also could negotiate individualizedprojects with the instructors.The reflective journaling
technology education curriculum. The projectused engineering design challenges in order to lead teachers into experiencing the engineeringprocess, the application of mathematics and science in order to optimize solutions, predict theirbehavior, and analyze solutions, and to reflect on their learning and the implementation process.The Bridges for Engineering Education professional development was highly rated byparticipants as useful and beneficial. It is interesting to note that three of the most important Page 11.762.7things learned by the public school students who participated were:1. Engineering is a very intellectually demanding process.2
master’s, so we expect a lot. You can do many things on your own. We’re not going to teach you everything, you know a lot of it.’”Trisha’s advisor had discussions with her and made recommendations about her ideas, but leftthe decisions up to her. Edward experienced an advisor who did not provide structured orsupported autonomy, “will not teach him everything.” Edward came away from his first meetingknowing that his advisor had high expectations, but would not provide support to meet thoseexpectations irrespective of Edward’s level of competence. Nonetheless, Edward did expresssome level of autonomy in his work and the precedence that Edward’s advisor set at thebeginning of his program is reflected in the structure of Edward’s
graduate students who will work as GTAs, aworkshop specifically about creating a reflective teaching statement, and additional workshops thatmay be more tailored to each participant’s discipline.Additionally, participation in a six-week-long pedagogy seminar is also required and provides a greatopportunity for students to learn more about teaching methods across disciplines. The pedagogyseminar is designed so that students from diverse disciplines may learn about general teachingstrategies and new strategies that are emerging, compare and contrast teaching strategies that areused in their own disciplines, as well as design a full syllabus for a class they would want to teach inthe future. The seminar fosters open discussion about effective
, skills, and ability to solve complexproblems and to produce excellent solution(s) within the structure of the team. This concept wasfurther developed to include defining team and task, team climate, communication, and reflection(for a detailed description, please see Table 1)23-26.Design competence focused on finding and evaluating variants and recognizing and solvingcomplex design problems. These were further defined as having the ability to discover and designmultiple solutions to a given problem and to effectively evaluate those solutions to determine thebest solution, and having the ability to see the overall picture of a complex design problem, thenbreaking it into smaller, more manageable parts to solve while keeping the overall problem
reflect distinct characters that result from different political, intellectual, andprofessional influences on engineering education. In particular, engineering ethicseducation in China has demonstrated a stronger emphasis on theoretical knowledge,whereas ethics teaching in the US focuses more on ethical decision-making inengineering practice. We suggest that the differing emphases result partly from Chinesescholars’ attempt to establish engineering ethics as an academic discipline, and,compared with its counterpart in the US, a weaker professional identity for engineers inChina. We conclude this paper by summarizing lessons engineering ethics educators in bothcountries might learn from each other. We also suggest a few questions for
on talent. The Cronbach’s alpha was also applied to the full data set.The negative questions were adjusted by subtracting each response from 7, thus ensuring equivalent scale. Theresulting fit between matched pairs of positive and negative formulation is interpreted as a measure of confidence intwo aspects of the student responses: (1) the extent to which students are reading and interpreting individualquestions; and therefore (2) the reliability of the entire data set as a reflection of student opinion.Results of Analysis of Survey Responses Multiple analyses were pursued relative to these data. These included basic assessment of the reliability ofthe data, as well as consideration of the data as separated by such groupings as
involvement for some time asan essential aspect of meaningful learning” [6]. On the heels of the critique of traditionalapproaches to teaching and learning came the movement towards student engagement and activelearning in engineering classrooms. Studies focused on approaches such as cooperative learning,problem and project based learning, learning communities and service learning sought to supportthe idea of increasing student engagement [5], [10]. In addition, engineering educatorsrecommended specific changes be made to the engineering curriculum to reflect the importanceof actively engaging students [11]. However, despite various studies on this issue “the engineeringcurriculum has been slow to respond” [12, p. 286]. Some scholars [13] attributed
systems problems.In this paper, the hands-on activities were designed for the students to immerse themselves into asystem, participate in the system, and experience the behavior of an operating system first-hand.These activities are sometimes thought of as games; however, these games were connected to thefirst three of the learning objectives. The students led games and participated in games. The teamthat led the games was responsible for obtaining structured written feedback from theparticipants, developing their own reflective feedback and developing a full written report of thegame.Roadmap for Using Hands-on Discovery Activities (HODA) in a CST CourseIn 2017, Hands-on Discovery Activities (HODA) were incorporated into an existing CST
. Their plans, actions, policymaking,reflections, and frustrations all aim to explore possible reactions to the challenges brought bythese dominant images. 1It is worth noting that the idea of dominant images is not an empirical concept. In other words,the dominant image active learning in American engineering education does not necessarily inferthat most American engineering schools and programs have adopted or developed active learningwell. Rather, dominant images often have normative value. Engineering programs and facultymay have different feelings about active learning, but active learning as a social image is relevantto their educational
failure Learning from failure (LFF) Establishing the cost of production or delivery of a service, including Cost of production (CoP) scaling strategies Building, sustaining and leading effective teams and establishing Effective teams (ET) performance goals Table 2. Assessment Outcomes for the Four Modules Module AO1 AO2 AO3 AO4 Thinking Articulated creative Reflected on the Applied divergent- Applied an ideation
found eachproject and reflected on the integration of prior coursework into their design projects. Finally,student design reports were scored by instructors and students self-reported design mastery,using a common rubric.Results and Discussion: After completing each integrated project, students demonstratedimproved design knowledge and cognizance of integrating prior coursework knowledge intotheir designs. Students also reported significant confidence gains in four major areas: (1) designprocess and approach, (2) working with hardware, (3) working with software and interfacingwith hardware, and (4) communicating results. Focus group responses support the observedquantitative improvements in student design confidence. Further, instructor scoring
6Van Wie (26946), “Using Reflection to Facilitate Writing Knowledge Transfer in Upper-LevelMaterials Science Courses” by Mallette and Ackler (26638), and “Writing across Engineering:A Collaborative Approach to Support STEM Faculty’s Integration of Writing Instruction in theirClasses” by Ware, Turnipseed, Gallagher, Elliott, Popovics, Prior, and Zilles (26720). Thesepapers were presented in three different sessions (2 in LEES and 1 in chemical engineering); onewas funded by the NSF, while another had significant institutional funding.Many of the papers presented at the 2019 conference exemplify the fourth trend observed in the2016 analysis: collecting data (typically from student evaluations or surveys) for a single course(sometimes even for a
decisions today, related to yourdesign project?”). We found that students reliably accounted for the decisions observed.Based on these subconstructs, we developed Likert statements written as simple concepts [48]with a 7-point bipolar scale, with a middle option to reduce measurement error [49]. Researchsuggests that using item-specific scales, as opposed to the commonplace agree/disagree scale,can improve the quality of responses [50]; we thus avoided agree/disagree scales and focused ondeveloping scales that reflected the construct we sought to measure. For instance, we avoidedscales that focused on frequency (e.g., always to never), as in our discourse analysis, weobserved that even infrequent decisions were sometimes very impactful. This
grades of zero (i.e., incomplete assignments, D), misseddays of classroom instruction (E), and missed days of Discovery (F) by student between schools.N=77 and 53 for Schools A and B, respectively. P-values reflect nonparametric U-tests between schools.Aggregate assessment of classroom performance from both schools presented consistent meanfinal course grades (excluding the 10-15% Discovery portion) of 67% (Figure 2A); given thissimilarity it was determined that further comparative analysis between school cohorts wasjustified. However, performance on Discovery variables was significantly different (p < 0.0001)between school cohorts; School A students averaged 67% (remarkably consistent to their
. Survey responses were first descriptively coded, guided bythe research question. Throughout the coding process, themes were the unit of analysis.Subsections of text within an individual response were deemed to contain essential thought, andthen coded accordingly. This process is in line with utterance coding within verbal qualitativeanalysis [30]. All coding was performed by two researchers, and the researchers reached 100%consensus after discussion in inter-rater reliability (IRR). Focused codes were developed [31], [32] to further interpret Incubator participantunderstandings of teaching and learning. In developing our codes, we asked a more specificquestion: How are BME students’ articulations of teaching and learning reflecting
participants were male, reflecting the demographics of the schoolat the time of the formal meetings.Samples of this size are commonly accepted in qualitative studies investigating social andexperiential phenomena. This size also seems appropriate because we were able to engage almosteveryone who shared the experiences in question. Even in cases where the target population islarger, scholars of qualitative and phenomenological research recommend limiting the sample size.This is done to allow the researcher to delve deeply into the phenomenon and the data. For instance,Dukes (1984) recommended a sample size of 3-10 for phenomenology (cited in Creswell, 2007).A literature review by Guest, Bunce, and Johnson (2006) identified recommendations
. Student artifacts of engagement with this module included a research topic tree, a key word tree, and a written reflection. (See Appendix E.)Assessment Instruments Two assessment instruments were developed by the researches based upon the uniqueneeds of the study. The Final Course Activities Evaluation Rubric was developed to evaluate andprovide a total score relating to whether, or how well, a student could critically evaluate andselect credible and meaningful resources in their research and writing. A second rubric, the 10Supplemental Course Activities Engagement Rubric,was developed in order to better understandhow engaged
strategies for completing the assignment. The third and fourth segments (Peer Review and Self- Review) accelerate learning throughapplication of a rubric and reflection on self-performance. In these segments, studentsdemonstrate an understanding of task requirements by critiquing the work of others. Then,students consolidate their learning gains by reviewing their own submission and reflecting onways to improve. The fifth and last segment collects performance data /peer commentary anddisplays results both to instructors and students. This last segment reinforces learning by givinga composite
ability tomonitor progress towards self-generated goals, and the ability to reflect on performance andmake adjustments and manage time effectively, to comprise the overarching construct of self-regulation in learning [4].Students who are better at self-regulation often outperform those who have not developed theseskills [5]. Although the literature on this topic heavily focuses on students’ use of strategies orperformance, there is a growing body of research focused on students’ backgrounds andunderlying beliefs regarding learning. These individual difference variables may globallyinfluence a student’s disposition, use of strategy, and thus, performance [4, 6]. Although thereare several potential lines of inquiry available, the present study was
been combined together.In addition to the survey, at four times during each semester, a full class period was used toproduce open-ended responses to a reflection prompt (n=16 for Fall 2015 and n=16 for Fall2016, a total of 126 reflections). Reflections prompts were not focused on the canvas (e.g.“Explain a struggle you have had during the design process to this point and describe the variousways you overcame that struggle. What might you abstract that you can use in other designexperiences?”). Lastly, a faculty assessment focus group met on May 21, 2015 and consideredtwo prompts: 1) “I like…” and 2) “I wish…” regarding the course as a whole.As mentioned previously and important to our assessment, Crismond and Adams (2012) proposethat students
process, (d) teamwork and cooperative and collaborativelearning, (e) reflection on how and when these practices could be institutionalized in thecapstone course. Faculty participated in monthly group workshops followed by individualcoaching sessions with two members of the professional development leadership team. Thetwo-member coaching team was comprised of two “experts” – one in the EM and the other inpedagogical practices. The coaching sessions included open-ended questions for facultyreflection on implementation of EM and instructional teaching strategies.Coaching sessions were documented through a Google form, which captured coachingdiscussion details on the following: (i) pedagogy-related topics discussed during the coachingsession, (ii) EM