study.Table 3. Descriptive Statistics of Indicators for Cohort Comparisons Traditional Cohort Inverted Cohort % or % or n Mean (SD) n Mean (SD) Learning Style - Active/Reflective: Reflective 266 53% 285 58% Learning Style - Sensing/Intuitive: Sensing 266 61% 285 63% Learning Style - Visual/Verbal: Visual 266 79% 285 81% Learning Style - Sequential/Global: Sequential 266 60% 285 62% Prior academic
Program will bediscussed, and the results and findings will be compared with results from the 2012 Program.The views expressed in this document are those of the authors and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. Government. Page 24.1279.4IntroductionTo meet the technology needs of our increasingly complex global society, engineers in the 21stcentury are now expected to exhibit key attributes to ensure their success and the success of theengineering profession, according to the National Academy of Sciences in their groundbreaking2004 report entitled The Engineer of 2020
-educated women have increased their share ofthe overall workforce”1. The gender gap in STEM employment is not an anomaly; it reflects thedisparity in the relative numbers of men and women pursuing STEM education, of which the K-12 years, particularly high school, are this paper’s focus.Female high-school students are more likely to aspire to attend college than are their malecounterparts, and young women enroll in college, persist, and graduate from it at higher rates aswell2. So why does this STEM-specific gap exist? This paper employs the tools of “genderanalysis” to address this question.Gender analysis provides a framework for thorough analysis of the differences between women’sand men’s “gender roles, activities, needs, and opportunities in a
example, an original pilot item read, “I would like to learn how tomake safer cosmetics.” The engineering education experts and researchers did not find this itemto be gender neutral and removed it from the construct. They also aimed to make the engineeringattitudes section a more comprehensive measure by including items relevant to engineeringcareers requiring a Bachelor’s degree as well as those not requiring a Bachelor’s degree, liketechnologists. The team developed new questions to include words like “design,” “create,” and“imagine” as well as words like “build” and “fix.” They renamed the engineering section“Engineering and Technology” to reflect the new focus on the work of not only engineers butalso of technologists and other skilled
entireclass, we award every participant of each survey with 0.1% extra credit on the 100%scale for the course. The maximal number of points that a student can earn viaparticipation in surveys was 1.6% in the Fall 2012; for comparison, the reward for earlysubmission of homework was ~3-fold higher. We believe that extra credit forparticipation is justified, because thoughtful feedback requires reflection on learning andteaching, which in turn stimulates meta-communication and comprehension of the coursematerial. The average amount of extra credit for participation in surveys earned bystudents in the Fall 2012 was 0.86%, while the width of each letter grade bin was 4%(straight scale, no “curve”); thus extra credit points only slightly influenced the
architectural styles is that they go beyond simple narratives of designexperiences, and capture design expertise that has been refined through careful reflection in aneffort to codify important lessons. By providing students with a solid foundation inunderstanding the applicability, key characteristics, advantages, and disadvantages ofarchitectural styles, educators can provide learners with valuable starting points for their owndesign activities as well as build expertise in identifying critical design trade-offs.The instruction of architectural styles, however, remains challenging, primarily due to afundamental disconnect between the dynamic nature of the software compositions thatarchitectural styles model and the static artifacts most commonly used
quite pleased to work on an interesting, relevant large-scaledataset of their choice, and see how the methods taught would work in practice; their enthusiasmwas reflected in the results obtained.6.2 Reflection and DiscussionOne of the biggest challenges we faced with the design of the course was from the unexpectedinterest from non-CS majors. While this was a pleasing observation, it did require us toreconsider the depth of some material, and perhaps consider some different techniques in thefuture, as the interest is continuing to expand. We are strongly considering offering two variantsof the course: one course would be the existing data mining course as an elective for thecomputer science major, with a prerequisite of taking a course on data
be fair with one student taking particularissue with the fact that their grade depended in part on peer evaluations. There was alsoexpressed concern regarding the fact that not all group members could be assigned a 10/10 on thepeer evaluations (see Appendix 1). Finally, while not asked as part of the EGR 450questionnaire, the same student group indicated unanimous support for the online screencasts inthe EGR 250 course questionnaire during the previous semester. The primary student request Page 23.1158.13was the addition of extra screencasts with example problems. The student support for the TBLformat is further reflected in the
effect is reflected in the coefficientb1 of the interaction between Ri and Mi. Additionally, we run multiple regression analyses forfirst-time engineering students using almost the same models except that Ei is deleted.Logistic regression models are applied to study dichotomous outcome variables that measurefirst-time student course-taking behaviors. The form of logistic models differs from multipleregression models (1) and (2) only in the outcome variables: Y01FRA = b0 + b1∙Ri∙Mi + b2∙SAT + b3∙Gi + b4∙Ei + ck∙Yk (3) Y01W = b0 + b1∙Ri∙Mi + b2∙SAT + b3∙Gi + b4∙Ei + ck∙Yk (4) Y01S = b0 + b1∙Ri∙Mi + b2∙SAT + b3∙Gi + b4∙Ei + ck∙Yk (5)Y01FRA in (3) is an indicator of full course load
. In the K-12 setting, engineering can help students learn to use informed judgment to make decisions, which can lead to informed citizenry. Students must be empowered to believe they can seek out and troubleshoot solutions to problems and develop new knowledge on their own. Engineering requires students to be independent, reflective, and metacognitive thinkers who understand that prior experience and learning Engineering from failure can ultimately lead to better solutions. Students must also learn to manageThinking (EThink) uncertainty, risk, safety factors, and product reliability. There are additional ways of
whole, Figures 11 and 12 show ALEKS performancefor the course. Figure 11. Initial ALEKS assessment pie chart for overall class performance. Figure 12. Final ALEKS assessment pie chart for overall class performanceTable 5 reflects the initial and post assessment results and percent increase for each topic. Theseresults reflect significant growth for the class as a whole for all topics. Table 5. Class performance—mastery of ALEKS topics: initial and final assessment. Class Initial Class Final ALEKS Objectives/Topics % Increase Assessment Assessment
contexts. Thus, in this term project students were asked to reverseengineering an existing product as if they were going to compete in the market. By addressingengineering challenges that reflect real industry scenarios, students understand the practicalsignificance of their education.1.4.5 Collaboration and Communication Students cultivate crucial soft skills such as effective communication, and teamwork. Theseabilities are highly prized in the professional engineering field, where the success of projectsfrequently relies on cross-disciplinary collaboration [19].1.4.6 Interdisciplinary Projects – Summary © American Society for Engineering Education, 2024 2024 ASEE Midwest Section Conference
institution’s goal of reaching R1 status (Ford, 2023; Weissman, 2023).The Carnegie Classification® is the leading framework for recognizing and describinginstitutional diversity in U.S. higher education. The Carnegie Commission on Higher Educationdeveloped the system in 1973 to support its research and policy analysis program. Derived fromempirical data on colleges and universities, the Carnegie Classification® was updated in 1976,1987, 1994, 2000, 2005, 2010, 2015, 2018, and 2021 to reflect changes among colleges anduniversities. The system includes any institution of higher education that conferred at least onedegree during 2019-20, as reported through the National Center for Education Statistics (NCES)Integrated Postsecondary Education Data System
the GPCG and AC methods asshown in the histograms 11a, 11b, 11c, 11d, exhibit distinct trends. Both Q1-GPCG and Q1-AChave approximately symmetrical feedback distributions with skewness values of 0.11, thoughQ1-AC has a slight bias towards higher ratings, and Q1-GPCG shows a neutral pattern. Incontrast, Q2-AC shows a skewness of -0.96, reflecting a strong preference for higher ratings,while Q2-GPCG, with a skewness of 0.96, tends towards lower ratings. Observation 1 The Additional Context(AC) method, providing course-relevant information, is better for generating feedback on project proposals as it not only offers feedback but also responds to questions regarding proposal rubrics related to the course, which cannot be answered by
low values correspond to ‘veryweak/unimportant/little’ and high values correspond to ‘very strong/important/much.’ Most ofthe participating students had no previous experience with research before the Fellowship, whichoffers an explanation for the increase in response for students’ general perception of themselvesas a researcher. Of the three blocks of interest, the lowest numerical responses (Likert responseoption 1-4) from students in the pre survey consistently came from questions in the “identity”section related to their identity as a researcher. Generally, in the post results the mean value ofresponses increased, but only about half of the respondents reflected a somewhat strong or better(Likert response options 5-7) relationship to the
practice with testing. Studentsparticipating in blocked practice had better practice performance, but those participating ininterleaved practice had better test performance in both trials. Interleaved practice helps studentsdiscriminate between various kinds of problems and learn the appropriate method for each one. Itrequires that students organize tasks and solution methods. Therefore, during interleaved practicestudents are practicing two things: the skill being taught as well as the skill of identifying whichsolution method should be used [5]. Interleaved practice naturally covaries with distributedpractice. Therefore, some of the benefits of interleaved practice may reflect the benefits ofdistributed practice, such as practice pulling from
Mindfulness Uniqueness MindfulnessIndicate how frequently or infrequently you currently have each experience. Pleaseanswer according to what really reflects your experience rather than what you thinkyour experience should be. Please treat each item separately from every
,possibly reflecting the multifaceted nature of educational environments, research designs, andmethods of inducing CF. This study aims to build on the foundation laid by previous research,offering new insights into the nuances of CF's effects in educational settings and its implicationsfor both theory and practice. The variability of results from studies of CF can be partially attributed to differences inresearch paradigms and how CF is induced. In the first paradigm, CF is induced through therepetition of different tasks. The impact of CF is then measured by comparing performance on thefirst task to later tasks. For example, Ackerman and Kanfer [12] examined the effects of CF bycomparing final scores on the SAT for groups who took the exam
, like, that’s exactlywhat we’re focusing on… but the numbers are kind of how we define it in our heads which canlead to assumptions.” (Female, white)“…then they tokenize you. So, it’s like they don’t actually stand in your corner, but they’ll useyour photo to be like we’re so cool and diverse.” (Female, Chinese Asian)The university culture towards failure further exacerbates the often-hidden inequities and stressesthat can lead to feeling left out at a technical university. Despite over 30 years of scholarshipexploring how failure can lead to supporting learning outcomes given chances for reflection,iteration, and post-failure educational support [9], students at Mines largely see themselves asfacing an institution that does not support failure
university undergraduate BME programs and the job market,” IEEE Pulse, vol. 6, no. 2, pp. 42–45, 2015, doi: 10.1109/MPUL.2014.2386575.[4] J. Berglund, “The real world: BME graduates reflect on whether universities are providing adequate preparation for a career in industry,” IEEE Pulse, vol. 6, no. 2, pp. 46–49, 2015, doi: 10.1109/MPUL.2014.2386631.[5] C. P. Rivera, A. Huang-Saad, C. S. E. Jamison, and A. Wang, “Preparing Early-career Biomedical Undergraduates Through Investigations of Stakeholder Needs: A Qualitative Analysis,” presented at the 2020 ASEE Virtual Annual Conference Content Access, Jun. 2020. Accessed: Feb. 08, 2024. [Online]. Available: https://peer.asee.org/preparing-early- career
from the American Society of CivilEngineers (ASCE) requires that curriculum include application of the “principles ofsustainability, risk, resilience, diversity, equity, and inclusion to civil engineering problems,”application of “an engineering code of ethics,” and application of “professional attitudes andresponsibilities of a civil engineer” [1]. The importance of these criteria is reflected directlywithin the preamble to ASCE’s Code of Ethics, which provides four fundamental principles forengineers to govern their professional careers, the first being to “create safe, resilient, andsustainable infrastructure” [2]. The importance of sustainability, both within civil engineeringeducation and the civil engineering profession, is well
Table 5: Stakeholder Requirementsstrategies, the MRC lab will cultivate an educational setting that prepares graduates to makemeaningful contributions as soon as they enter the workforce.This approach to the design, of the MRC Lab reflects a multidisciplinary perspective, integrat-ing aspects of mechatronics, robotics, and control to create a dynamic environment for learningand innovation. Here, students, researchers, and practitioners can engage in practical problem-solving, collaborate across disciplines, and develop new technologies and solutions focused onrobotic dexterity and precision.Furthermore, the Measures of Effectiveness (MOEs) for the MRC Lab, as detailed in Table6, are defined and related to the stakeholder requirements. They are
education institutions, and the potentialimpacts of considering OR theories for engineering education.Introduction Resilience is a complex concept analyzed by the literature and can be defined as the“ability to recover from or adjust easily to misfortune or change”2. Since the COVID-19pandemic shocked the world, various research has been developed to understand and reflect onthis phenomenon. One scope of this research analyzes the educational context, and how highereducation institutions responded in their practices while learning about external shocks. Whilesome universities suffered from this unexpected disastrous scenario, some were sufficientlyprepared to smoothly pivot to the obligated online modality to learn and teach. This
-normed historical social practices that preserves the system of white supremacy”[33, p. 25]. Batty and Leyva, in their article “A Framework for Understanding Whiteness inMathematics Education'' explain that focusing on colorblindness changes the much-needed deepreflexive conversation on the way that “colorblind” systems and institutions hurt POC, to“supposedly non-racial arguments or proxies of student failure, uncaring parents, and devaluingof education, which leaves Whiteness invisible and allows those who assert it to defend theirviews in apparent nonracial ways” [49, p. 56]. Addressing colorblindness is regularly left up to the individual, which redirects theresponsibility away from the much-needed deep reflection of institutions. By
on them [35]. At their private,four-year liberal arts college, Zayn reflected on the experience of having a nonbinary professorto look up to: I was so excited when [the nonbinary faculty member] came here, and I got to take a class with them last semester. And it’s so nice just feeling like I see someone who is also nonbinary.The participant went on the say: It means a lot. Just because it’s like [nonbinary professor] [has] a very similar experience to me in that [they have] gone through the classes, [they] know what this field is like and how it’s very male dominated. But not just male dominated, but also very heteronormative and cisgendered.Due to the underrepresentation of nonbinary individuals in engineering
disciplinespresents complex dynamics that require further exploration. Understanding the nuancedexperiences of grief among women in academia, especially those in STEM, is crucial fordeveloping tailored support systems and a more inclusive and supportive academic environment.Coping StrategiesCoping is defined as the cognitive and behavioral ways that an individual responds tochallenging circumstances [68]. Everyone copes differently with grief due to differences andvaried life experiences, and there are evidently many ways that individuals can respond to grief,as reflected in the BRIEF COPE questionnaire, a 28-item survey that contains 14 sub-scales tocapture various coping strategies[69]. These are: active coping, planning, positive reframing,acceptance