good at generating a bunch of different paths because that's how my brain works. Picking one, oh my God. It's horrible. It's terrifying. (Selyne)While Selyne had many ideas for her future, but was stifled by her fear of choosing one career topursue, Hannah expressed not wanting to plan for the future to avoid being disappointed: I'm going to be working, but I don't want to plan too specifically, I guess, and have plans change or something. …I just ... I don't want to be disappointed, I don't want to have ... I don't want to go in with a preconception that's going to affect how I make my decisions and things. I don't want to say oh, I thought I was going to be here, so I'm going to say no to this
helped me plan out my schedule for everything. So, he’s actually one of—he’sthe reason why I ended up going to Rome, because I told him that I wanted to study abroad in Italyand he’s like, “Oh.” And, he pulled out this folder was like, “Yeah, we have this program.” And Iwas like, “Yeah!” But last fall he was great and answered questions. I actually took an elective notin an engineering class. I think I had the best professor I’ve ever had. This guy, you could tell heloved teaching. He loves teaching, and he was very open to feedback. He asked at the beginningof the term like, “How do you guys learn? What should I do?” and stuff like that. I rememberthinking, and I even said to him, “I wish my engineering professors were more like you.”Jordan: I
: Problem-solving processes,domain knowledge, and translations between symbol systems.Since Polya’s seminal work in mathematics,3 the utility of learning and using a sequence of stepsduring problem-solving has been widely accepted. Although several specific models exist, ageneric 4-step model captures most: (1) Represent the Problem, (2) Goal Setting and Planning,(3) Execute the Plan, and (4) Evaluate the Solution. In the first step, problem representation, thestudent must read the problem statement and discern the objective. There are instructionalinterventions for engineering education that are grounded in this theoretical model of problem-solving. For example, Gray et al.4 developed a systematic approach to solving Statics andDynamics problems
Page 23.874.12 Desire to maintain involvement with a community 2317 18 that is not related to my universityLike Table 5, Table 6 conveys findings for survey items that are not directly linked to the ULOs,but items in Table 6 are directly linked to professional advancement, which is perhaps anunarticulated desired outcome of all undergraduate programs. Responses indicated that while justover 20% of respondents believed their project work provided them with professionallybeneficial connections, it provided approximately twice as many (38%) with knowledge orexperience that helped them change their minds about future plans—something of particularvalue when considering the importance of career satisfaction. Even more
investigate the role of ethnicity infemale engineering students’ educational experiences and vocational plans.13 The authors of thecurrent study propose that the SCCT model might be extended to explain the propensity for newengineers to be satisfied or dissatisfied with their jobs. New engineers’ early work experiencesare critical in that, during this time, they form enduring perceptions about their work, theircompany, and their profession which strongly influence their decisions to stay or quit.14 Theauthors propose then that these experiences moderate new engineers’ job satisfaction, which is aprecursor to many other occupational outcomes including commitment to a career inengineering. Preliminary evidence of this has been provided by the Society
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
for Faculty Affairs and Research. Somerville joined the faculty at newly-founded Olin College in 2001. At Olin, he served on the committee that designed the inaugural curriculum for the institution, and has played leadership roles in strategic planning, as Chair of the Engineering program, and as Associate Dean for Academic Programs and Curricular Innovation. Somerville’s interest in engineering education focuses largely on facilitating change processes and on the application of collaborative design techniques to curriculum revision; in this capacity he has worked closely with a variety of institutions, both nationally and internationally. His educational background includes a Ph.D. and master’s in electrical
; 2) the ability to analyzeissues and identify the “key players” as well as their beliefs and values; 3) the ability to usescientific problem-solving skills to investigate these issues to identify the facts surrounding themand their social, economic, political, legal and ecological ramifications; 4) the ability to evaluatethe issues and determine the most effective means of resolving them; 5) the ability to use adecision-making model to develop an action plan that can be implemented to resolve or helpresolve the issues; and 6) the ability to execute the plan if it is consistent with the student’spersonal value system. Tenants 1 through 4 are tied into the new Professional SocialResponsibly Development Model to describe the development of
me staying up a little later; I’m exhausted to go to work in the morning.” “I stay up until like two in the morning every night, and I get up at seven, because that’s Page 25.136.11 when my 21-month old gets up.” Financial planning and resource utilizationThe adult students in our interview pool are economically diverse, with reported annual incomesranging from $10,000 to $100,000. Four participants specifically mention strategies for fundingtheir education through scholarships, the G.I. Bill, and personal savings before entering college. “And now I have the G. I. Bill that’s providing tuition costs for me, so
and engineeringconcepts and skills. We identified four areas of analysis for each of the three curricula.From the student materials, we analyzed the planning materials, activities andassessments. From the teacher training materials, we looked at what teachers werepresented with at the official summer training institutes (Table 1). Our content analysisfocused on examining the content of the materials. We recorded the number of NCTMmathematics standards specifically connected to the engineering curriculum for each unit(Prevost et al., 2009). Page 22.1318.4 3Table 1: Materials for Analysis
positedearlier in this paper, i.e., that there is too much variability in the methodologies and metrics ofcurrent ranking systems.Another nagging question, beyond that of the focus of the unit of comparison, remains however.This question asks: For what purpose is the comparison being made? The literature reviewyielded a whole range of purposes including: • Comparison of institutions • Evaluation of institutions/colleges/programs • Assessing progress towards strategic plan goals • Accreditation • Performance assessment, e.g., for promotion and tenure decision, of faculty • Guiding individual decision makingThe complexity of the problem of assessment and comparison is depicted by the illustrationdepicted in Figure 1. It shows that the
not promising for continued instruction online in the upcomingsemesters under the COVID-19 epidemic.References[1] Blaich, C. & Wise, K. (2020, September 14). Comparison of how faculty and staff have experienced their institutions’ responses to COVID-19. Higher Education Data Sharing Consortium (HEDS). Available: https://www.hedsconsortium.org/wp-content/uploads/2020.09.14-COVID-19-Survey-Faculty-v-Staff- Memo.pdf[2] The Chronicle of Higher Education (2020, October). ‘On the Verge of Burnout’: Covid-19’s impact on faculty wellbeing and career plans. Available: https://connect.chronicle.com/rs/931-EKA- 218/images/Covid%26FacultyCareerPaths_Fidelity_ResearchBrief_v3%20%281%29.pdf[3] Fox, K
seriously thinking about leaving this academic institution at the end of the semester for reasons other than graduation. (*) 2. I am planning to look for a new academic institution to attend for reasons other than graduation. (*) 3. I intend to ask people about new academic majors because I want to transfer out of my current major. (*) 4. I don't plan on being at this academic institution much longer for reasons other than graduation. (*)
demonstration of performanceexpectations with regards to the learning objectives (e.g., rubrics, exemplars), and students’feedback with respect to the learning objectives. The true potential of these systems to improvestudent learning can only be realized through the engagement of each student with theseelements, where engagement entails active awareness of course learning objectives (thestandards) and expected performance, planning to learn, accessing of feedback, and subsequentactions. Prior work has shown that instructors find the initial workload to create an SBG systemconsiderable [5], and students, unfamiliar with such systems, do not take as much advantage ofthe learning opportunities afforded by an SBG system as instructors would hope [6
professors’ clarifications about theMuddiest Points directly improved their learning, showed their professors cared, andenhanced their overall relationship with their professors. The exercise was also popularamongst professors; several planned to include the exercise in their future courses. InIntroductory Materials courses, Krause and colleagues8,9 found the use of Muddiest Pointactivities informed instructors’ use of formative process feedback and improved studentattitudes, achievement and retention of course content.Most Surprised activities are rarely used in engineering, but have been used by instructorsin other fields in a way similar to Muddiest Point. In the most common form reported inthe literature, Most Surprised is posed as one question
like this were very uncommon, however. This could point to a missing link withrespect to developing a professional sense of social responsibility in engineers that could drawfrom the existing HSS influences that students reported. One student actually discussed howtheir humanities class influenced them negatively with respect to their views of engineering,saying: “Mostly the humanities, the engineering classes I took made me realize how irrelevant my major (mechanical engineering) is to making a difference in the world. I don't plan on using my major for anything in the future- planning on shifting my career path to the humanities/social sciences.”This response came from a female, senior engineering student who
. Page 13.1048.4We use a combination of qualitative and quantitative methods to examine transfer in the contextof problem solving. The participants in this study were students enrolled in a second-semesterphysics course taken by future engineers and physicists, calculus instructors and physicsinstructors. A total of 416 students’ exam sheets were collected and reviewed. Statisticalmethods were used to analyze the quantitative data. A total of 28 students and nine instructorswere interviewed. The video and audio recordings were transcribed and analyzed in light of theaforementioned theoretical framework.A three-phase research plan was used in this study. Phase I was designed to assess horizontaltransfer of knowledge using traditional physics
novices: graduate engineersin the first few years of their career.Need for a longitudinal studyA longitudinal study of one or more cohorts of engineering graduates could provide usefulinsight on these issues.An extensive literature search revealed five recent longitudinal studies of engineeringgraduates12-16.Sheppard et al12 are undertaking an interdisciplinary longitudinal study of the engineeringstudent experience using several research approaches. As part of their study they plan to followthe transition to the workforce of some of the 48 participants as they move from “the end of theirjunior year through their first two years post-B.S. With this cohort, we will focus on the criticaltransition from undergraduate education to either the
) Large Public University (LPU), a large public university in the NorthwestU.S.; and D) Suburban Private University (SPU), a medium-sized private university on the WestCoast.Including students from diverse backgrounds was a key element of the research plan. For thiscohort of students, special attention was paid to understanding how underrepresented studentsnavigate their initial years in engineering education. This was accomplished by employing over-sampling strategies for gender (male/female) and underrepresented minorities (AfricanAmericans, Native Americans, Mexican Americans, Puerto Ricans, other Latino groups) in orderto gain information about a broader range of students.This mixed method study, sponsored by the National Science Foundation
confirmed this. The pilot test replicated all aspects of the lecture and lab planned forweek one of the full course. Data were collected by means of two separate online surveys; onepertaining to the online lecture portion of the training and the other to the traditional lab portionof the training. Both surveys addressed the delivery of the blended-learning course, specificallythe format and technologies used. The goal was to assess whether or not the course could beeffectively taught using the established delivery mechanisms. The lecture survey consisted of sixLikert-style responses and five open-ended questions. Participants were asked to supply theiropinions on areas such as: audio and video quality, ability to follow along, performance of
presentercan also plan to explain concepts in more or less detail, and to highlight or gloss overrelationships between concepts. Extrinsic cognitive load arises primarily from the method by which information ispresented. That is, extrinsic load can be influenced by how information is presented on a slide,including the amount and format of the information, rather than the actual conceptual meaning ofthe information on the slide. Depending on the way that a presenter’s visual aids are structured,extrinsic load may be increased or decreased and may therefore impact audience members’comprehension in a negative or positive way. Meanwhile, Dual Code Theory states that information is more easily learned when verbaland image-based formats are
would benefit from the audience examining the evidence in the body ofthe slide before seeing the assertion, as in the presentation of an assertion for which theaudience has a hostile reaction. Another case would be in a teaching situation in whichthe presenter wants more participation from the students. In such a use, the questionheadline would appear first, and then after the students have addressed the question byexamining evidence in the body of the slide, the presenter would animate in the sentenceheadline. In this way, the audience would benefit both from the active learning of thequestion headline and from the precision of the sentence headline. Given those twobenefits, future plans in the geoscience course are to use question headlines
just dig in. But if there’s a greater cost and going to the store, I gotta plan it out.” • Taking things apart: Participants talked about taking things apart during their making processes, such as “When I was a kid I had an old radio, just a clock radio, and I took that apart to see how it worked, back when I was younger when I had time. That really interested me.” Many shared the same kinds of childhood memories, and even discussed being okay “when you put it back together and you’re either missing a part or have too many.” • Making wrong or unexpected turns: Finally, the theme of making wrong or unexpected turns during the design process was quite common. One said “mistakes turn out to be
, Drexel University Gregory Hislop is a Professor and Senior Associate Dean in the College of Computing and Informatics at Drexel University. His scholarly interests span computing education research, information technology for teaching and learning, and software engineering. Prior to coming to Drexel, Dr. Hislop spent 18 years working in government and industry, where his efforts included software development and support, technology planning and evaluation, and development and delivery of technical education. c American Society for Engineering Education, 2019 Student Software Engineering Learning in HFOSS ProjectsABSTRACT Humanitarian Free and Open Source Software (HFOSS) projects
of expertise: Prospects and limits, New York, Cambridge University Press, 1991, pp. 93-125.[2] C. M. Seifert, A. L. Patalano, K. J. Hammond and T. M. Converse, "Experience and expertise: The role of memory in planning for opportunities.," in Expertise in context, Menlo Park, CA, AAAI Press/ MIT Press, 1997, pp. 101-123.[3] J. K. Phillips, G. Klein and W. R. Sieck, "Expertise in judgment and decision making: A case for training intuitive decision skills," in Blackwell handbook of judgment and decision making, Malden, MA, Blackwell Publishing, 2004, pp. 297-325.[4] G. Klein and R. R. Hoffman, "Macrocognition, mental models, and cognitive task analysis methodology," in Naturalistic decision making and macrocognition, Hampshire
connections between their lived experiencesand their current engineering coursework. We targeted two different types of environments, homeand hobbies, which could include activities at home our outside of students’ home. While severalstudents highlighted PLW and/or playing with Legos, as their main exposure to learning andbecoming interested in engineering, one student, Naomi, identified working with her father athome as her source of interest in engineering: … Working with my dad ... I remember I built a dog house ... I took a saw and I started cutting things out and he stopped me. He's like, “No, you need to have a plan. What are you making this house for, which dog? Where are you going to put it?” I had to think of all of
is also regarded as acomplex repository of knowledge and skills for planning, implementing, monitoring, evaluating,and continually improving the learning process. Self-regulated learning has been studied over morethan two decades in general classroom settings and various assessment methods exist in theliterature. It is commonly agreed that self-regulation is a good predictor of student’s academicsuccess. For instance, relationships were examined in [1] among motivational orientation, self-regulated learning, and classroom academic performance, and their regression analyses revealedthat self-regulation, self-efficacy, and test anxiety emerged as the best predictors of performance. In recent years, studies on SRL have been extended to