literacy is commonly referenced as an increasingly important 21st century skillneeded in today's knowledge-based economy. ABET’s criterion 3.i declares that students have“a recognition of the need for, and an ability to engage in life-long learning.” Shuman,Besterfield-Sacre, and McGourty1 propose several attributes of lifelong learning, including“follow a learning plan; identify, retrieve, and organize information; understand and remembernew information; demonstrate critical thinking skills; and reflect on one’s own understanding.”These criteria align well with the core concepts of information literacy. Information literacy ismost popularly defined by the American Library Association as set of skills that enables theability to recognize the need
themodules when they are not subject matter experts, providing a cheat-sheet of FAQ studentquestions or connecting them with a content expert to offer external support could be beneficial.AcknowledgementThis work was made possible by a grant from The National Science Foundation (Grant no.1935683). Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author and do not necessarily reflect the views of The National ScienceFoundation.References[1] R. Panigrahi, P. R. Srivastava, and D. Sharma, “Online learning: Adoption, continuance, and learning outcome—A review of literature,” Int. J. Inf. Manag., vol. 43, pp. 1–14, Dec. 2018, doi: 10.1016/j.ijinfomgt.2018.05.005.[2] S. Appana, “A review of
-selection, smaller class size, and specific curriculum elements, but we do not yetknow (see p. 396 in [10]). There is evidence that educational interventions that “encourageexperiential learning, reflection, group work, active learning, and decision-making are generallymore effective in promoting moral judgment than those that use more traditional pedagogies”(see p. 404-405 in[10]). Co-curricular interventions can also be effective in developing moraljudgment [10]. The research reported in this paper aimed to verify the underlying assumption of strong gains atthe home liberal arts institution (Doane University). The gross indicator of institutional typemay need to be more accurate, as these colleges range from highly-selective elite institutions
, orentrepreneurship, which reflects their interest in pursuing either a career in industry/government, attendinggraduate school, or working with a small business/start-up upon graduation. Unlike Flit-Path, Flit-GAPpathway selections are a collaborative effort coordinated among the three institutions. The collaborationworks on multiple fronts (1) sharing internship opportunities between institutions located in metropolitanareas with a strong presence of industry, government entities, where remote opportunities are enhanced,due to COVID, and expected to continue being enhanced after COVID; (2) offering opportunities to researchpathway students to be co-advised by research mentors located in more than one institution; 3) offeringentrepreneurship pathway
) resides in a region rich in diversity.Over all majors, UMD seeks a balance that is representative of the state’s populationbetween female and male students, as well as underrepresented minority andnon-minority students. However, this balance is not reflected in engineering majors,in which only 27% of students identify as women, and 16% of students are fromhistorically underrepresented racial and ethnic groups. UMD is working to overcomethe disparity in our ability to attract underrepresented students from our localcommunities. A 2021 review by the Washington Post ranked UMD 6th among stateflagship institutions in terms of the gap between the percentage of black high schoolgraduates in the state and undergraduate enrollment. This issue is not
and asked to act as a consultant and interview their partner with thefollowing prompt, “How would you redesign the curricular collaboration experience for yourpartner?” Each person then interviewed their partner to gain insight to their needs. A second roundof interviews was conducted to dig deeper into the ideas developed in the first round. After theinterview, the individuals used their notes to define an actionable problem statement based on theneeds and insights collected in the interviews. The attendees then ideated by sketching five radicalways to solve their partner’s needs. The ideas were then shared with their partner to get feedback.The individuals then reflected and generated a sketch of a big idea solution to the need
Caskey, “Learning Outcomes in Intensive Courses”, Journal of Continuing Higher Education, Volume 42, No. 2, 1994. 7. Carrie Johnson, “Faculty Speak on the Impact of Time in Accelerated Courses”, Journal of Continuing Higher Education, Volume 57, No. 3, 2009, p149-158. 8. Ann Marie Fauvel, “Reflections on an Interdisciplinary Community-Based Team-Taught Adventure”, Journal of Continuing Higher Education, Volume 58, No. 1, 2010. 9. Jan Pritchard, and Jane Mackenzie, “The Variation in Academics’ Experiences of Teaching in an Intense Study Center Compared with their Traditional University Setting”, Journal of Higher and Further Education, Volume 35, Issue 3, 2011, pp. 339-353. 10
the number of bit errors divided by the total numberof bits in the transmitted signal. The transmission loss or information loss in underwater wireless communication isaccompanied by various physical and technical factors which we discussed in an introduction.Besides being channel noisy, underwater wireless communication is affected by surface duct,surface reflection, sound propagation characteristics, bottom bounce etc. Information loss is induced by passing signals via a noisy channel. In our work, conditionalentropy is used to quantify the information loss induced by passing pseudorandom sequencesthrough an underwater channel system. Information loss can mostly be expressed as thedifference of mutual information. The information loss
fine-tune the complexity of questions to suit different levels of student understanding. For example,prompts can be adjusted to generate questions ranging from basic knowledge checks to more intricate,analytical challenges. This capability ensures that assessments can be customized to accurately reflect thelearning stages of students, making them more effective across both introductory and advanced courses.Additionally, AI-generated quizzes can be tailored to focus on specific topics by refining the prompts toemphasize particular learning objectives. This allows educators to align assessments directly with thegoals of their courses, whether it’s to reinforce core principles in a subject or to delve deeper intospecialized areas. For instance, a
throughout different stages and majority of students responded Q8,accordingly. They all claimed that they worked their best with their team except one student (Q10).Responses to technical skills improvement are given in Figure 3 (c). These questions (Q11-Q19)reflect students experience and their learning thought the project. Responses to Q11 to Q14 showsthey “Strongly Agree/Agree” with their learnings. It seems the timing diagram had been the mostchallenging part of the design as four students responded with “No Opinion” with level three outof five and one student did not learn about the I2C protocol at all. More than ten students responded“Strongly Agree” to the rest of the questions (Q15-Q19) which are overall questions on the projecttechnical
the studentsCreative Thinking, Critical Thinking, and Oral Communication [4]. Brooks, Benton-Kupper, andSlayton concluded that assessment of capstone performance is on the reflection and contributionby each team member [5]. These ideas for a capstone class are the foundation for the ECE SeniorDesign course sequence at Missouri S&T (Senior Design is a two-semester sequence in whichthe first semester focuses on the design and organization of the project and the second semesterimplements the concept).Typically, each team is allowed to pick their project independently and no two teams could dothe same project. However, in Fall 2023 the instructor introduced a slight wrinkle in that teamswere allowed to select a coil gun project in which they
shared aspects of identity. Our ownprevious work has focused on how the process in our training practice transforms theseknowledgeable students into effective peer educators and mentors through a cycle of training,observation, reflection, and goal setting [19]. As a corollary to this we also want to interrogatethe impact this new emphasis has on enrolled students’ and facilitators’ feelings of belonging andconnectedness within their workshops and to the larger Cornell community.To support development of community and inclusion, seven trainings in each of Spring 2022 andFall 2022 included emphasis on the use of identify affirming ice breakers and sharing theresearch of social belonging on learning [18]. This training included modeling different
your mental health, it is hard to know that you are not alone in how you are feeling. Normalizing the conversation about mental health makes it much easier to share and work through things.”During Fall 2022-2023, ERASe partnered with the Russ College of Engineering Student Senatorto host a wellness week for the college. The students proposed and led the following activities: • Mindfulness and Journaling: a group meditation followed by a journal reflection • Planting healthy roots: Focus on the correlation between taking care of a plant and decreased symptoms of depression and anxiety. With financial support from Ohio University Student Senate, students were provided with materials to plant succulents and
. Here, faculty were able to analyze the data and beginidentifying where change would be most needed, impactful, and practical.Faculty had the chance to meet internally with a trained learning community facilitator toanalyze and reflect on their own program’s data. After faculty were able to analyze their ownstudent performance and curricular complexity data, faculty had the opportunity to meet indiscipline-specific groups. For example, all participating mechanical engineering faculty at eachuniversity met to share their data and how they made sense of the data.The faculty will continue meeting internally and in discipline specific learning communities overthe course of a year. During this process faculty will be able to ask more clarifying
practice" [5, p. 11]. For example, popular K-12 engineering activities like designinga tower to hold weight or building a roller coaster to meet criteria are often repeated acrosselementary, middle, and high school grades without clear learning progressions [5]. Whileengaging, such building projects generally promote a tinkering approach to develop a workingprototype [6], [7], [8] that does not reflect the work of expert engineers [9], [10]. To support thedevelopment of more authentic engineering learning outcomes and goals in K-12 settings,previous studies have engaged engineering experts, such as professional engineers [11] andphilosophers of engineering [12]. This study builds on that work by exploring the perspectives ofengineering university
visitors were invited to vote for the projects. Out of allthe student projects, visitors have selected the most popular mini-world Slice Of Earth (Figure 1left), the most complex design Dante's Inferno (Figure 1 middle), and the most interesting designField of Stars (Figure 1 right). These projects were also kept in our department for one moresemester for additional visits. Figure 1: Slice Of Earth (left), Dante's Inferno (middle), and Field of Stars (right)CHALLENGES AND REFLECTION We gained insights from this semester-long project on the challenges and opportunities facedby CAD education. While the design of our curriculum was successful, we observed differentchallenges faced by our students during implementation. Commitment to a long-term
questions wasasked twice—once with the phrase “engineering person” and once with “science person.” Weinitially wanted to adapt these items for “person in my field,” but after expert review it wasdetermined that the items would not capture what we were hoping they would capture. Performance/competence reflects the extent to which students perceive their ownknowledge and abilities in engineering. This dimension comprises five items that capturestudents’ confidence in their understanding of engineering in class and out of class, that they cando well on exams, that they understand concepts in engineering, and that others ask them forhelp. These items were adapted from engineering to “my field” for greater applicability. Missing data were
. Her research focuses on individuals’ development from students to professional engineers. She is particularly interested in studying co-op/internship programs, experiential learning opportunities, professional skills development, and diverse student experiences in experiential learning settings.Dr. Aaron W. Johnson, University of Michigan Aaron W. Johnson (he/him) is an Assistant Professor in the Aerospace Engineering Department and a Core Faculty member of the Engineering Education Research Program at the University of Michigan. His lab’s design-based research focuses on how to re-contextualize engineering science engineering courses to better reflect and prepare students for the reality of ill-defined
advised 17 UG theses, 29 MS theses, and 10 Ph.D. dissertations. Hammond is the 2020 recipient of the TEES Faculty Fellows Award and the 2011 recipient of the Charles H. Barclay, Jr. ’45 Faculty Fellow Award. Hammond has been featured on the Discovery Channel and other news sources. Hammond is dedicated to diversity and equity, which is reflected in her publications, research, teaching, service, and mentoring. More at http://srl.tamu.edu and http://ieei.tamu.edu. ©American Society for Engineering Education, 2024 FIE 2023: An aggregate and statistical analysis of the results and feedback of the ASEE ERM premier international conference on engineering education
call (28.1%), and send an email (7.0%) (Figure 3).Figure 2: Introduction to Engineering Students Perception of EmailFigure 3: Introduction to Engineering Students Communication PreferenceTo further clarify, respondents were asked if communication styles reflected communicationtype, using a multiple response type question. For PERSONAL communication (survey definedas with friends & family), respondents preferred sending a text message (34.8%), over making aphone call (34.8%), direct or instant messaging (19.6%), sending an email (1.8%), or via socialmedia by posting content (6.3%). When asked if they had access to their PERSONAL emailaccount via an APP on their phones, all of the responses indicated “Yes.”For BUSINESS communication (survey
the mean fell between the 2.5 – 2.99 range, choice3 for both men and women, with the greater number of women choosing higher GPA ranges, thusthe higher mean. Mean scores for CSE, GCM, and FCM were computed from survey choiceswhere the value labels were as follows: Strongly Disagree (1), Disagree (2), Neither Agree norDisagree (3), Agree (4), Strongly Agree (5). Thus, the higher scores in Table 3 for CSE, GCM,and FCM reflect the strength of agreement with the question.Tests of Relationships: F-test, t-test, and Correlations. Levine’s test for inequality ofvariances (F-test) and independent t-tests (95% confidence interval) were performed for GPArange, CSE, GCM, and FCMs. Findings are depicted in Table 3 and summarized in Table 5.Findings from
Number [EEC-1849430 & EEC-2120746]. Any opinions, findings andconclusions, or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect those of the NSF. The authors acknowledge the support of the entire e4usaproject team.References[1] “The Standards | Next Generation Science Standards.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.nextgenscience.org/standards[2] “Employment in STEM occupations : U.S. Bureau of Labor Statistics.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.bls.gov/emp/tables/stem-employment.htm[3] “Motivational factors predicting STEM and engineering career intentions for high school students | IEEE Conference Publication | IEEE Xplore
studies. Then, wewill delve into the discussion section, where we will interpret the results within the context ofexisting literature and theory. This section will also explore the practical implications of ourfindings for educational institutions. Finally, we will conclude by offering a reflective summaryof the significance of the study and its contributions to entrepreneurial education research.MethodologySurveyA Cronbach's Alpha of 0.890 was attained during the survey validation process for theEntrepreneurial Competencies dimension and 0.876 for the Entrepreneurial Intention dimension.Table 1 shows the corresponding Cronbach´s Alpha reliability analysis by dimensions.Descriptive statistics were used in sample characterization for data analysis
as an analysis toolwith thoughts similar to this: “If engineers are confident in their assumed or measured blastforce and blast profile, Newmark’s Method provides engineers with an extremely accurate wayto predict a structure’s response to a blast load.” Thus, a primary goal of the laboratory wasreached: to demonstrate the benefits of numerical time-stepping procedures in dynamic responsecalculation.Comparison of experimental and numerical results was the focus of this lab, but analytical resultscould – and probably should – be included to provide a complete picture. After reflecting on thelab, the instructor offered the students a comparison with the analytical approaches to estimatingresponse to blast loads in the following lecture period
byJensen and Cross.Further Reflection and Future WorkThe programs in this study are still growing and evolving. Consequently, limitations of this workinclude the current small sample size. One of the consequences of our currently low N is that weare not yet able to break down results by ethnicity, gender identity, or other important identity andbackground variables. However, while it’s true that our N is small (both overall and incomparison with Jensen and Cross), our results do show the strong potential impact ofproject-based engineering programs. As our programs grow and our N increases in future studies,we may observe further differentiation in outcomes with the population studied by Jensen andCross.The results of this research stimulates us to
!Because of the additional time allotted for the fabrication and testing phases, students were ableto reflect on their experience and discuss possible reasons why their predicted results weredifferent from the measured values. This discussion was required as a part of their final report.Table 5 lists excerpts from student team reports that give possible causes for the discrepanciesbetween experimental and analytical data.Table 5. Panel Project Report Excerpts Detailing Reasons for Differences in Measured and Analytical Data The team were able to see how variations and discrepancies in the manufacturing, however small, can cause large variations in performance. Some of the reasons behind some discrepancies between the data are human error
further test/collect data on lubricated and non-lubricated applications.Bibliography 1. Standard Test Method for Calibration and Operation of the Falex Block-On-Ring Friction and Wear Testing Machine. ASTM International, 1 May 2019. 2. Standard Test Method for Ranking Resistance of Materials to Sliding Wear Using Block- On-Ring Wear Test. ASTM International, 1 June 2017. 3. The University of Texas Rio Grande Valley http://www.utrgv.edu/en-us/ 4. The University of Texas Rio Grande Valley - Engineering Technology program http://www.utrgv.edu/_files/documents/admissions/undergraduate/dp-engineering- technology-bs.pdf 5. Fornaro, R.J., Heil, M.R, and Alan L. Tharp, A. L., 2006, “Reflections on 10 years of sponsored
to comprise anAdditive Manufacturing Skills sub-scale. The content reflects the specific skills identified in theproject design. Students respond using a 6-point Likert-type scale from 1 (Completely Uncertain)to 6 (Completely Certain).Cronbach's coefficient alpha was calculated to assess the internal consistency of each scale. TheEngineering Skills Self-Efficacy sub-scale values were good and consistent with those reportedin previous research. The value was borderline for the newly developed Additive ManufacturingSkills scale, suggesting that the number or content of the items may need to be reviewed.The means for all the scales were above the mid-point, suggesting that students had confidencein their abilities. As more data is collected in
engagement. As the communication landscapecontinues to change, instructors should consider soliciting feedback from industryrepresentatives relevant to their graduates.AcknowledgementsThis work is supported by the National Science Foundation under grant number 2120775 . Anyresults expressed are those of the authors and do not necessarily reflect the views of the NationalScience Foundation. The authors would also like to acknowledge the industry representatives fortheir time in completing the survey.References[1] D. P. Dannels, "Learning to Be Professional: Technical Classroom Discourse, Practice, and Professional Identity Construction," Journal of Business and Technical Communication, vol. 14, no. 1, pp. 5-37, 2000/01/01 2000, doi
studies to develop; 4) create more case studies; and 5) evaluate transfer oflearning by varying the sequence of operations in the case study.6. AcknowledgementsThis material was supported by the National Science Foundation’s Improving UndergraduateSTEM Education (IUSE) Program (award no. 2044449). Any opinions, findings, andconclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation.References1. Hsieh, S. and Pedersen, S. “Design and evaluation of modules to teach PLC Interfacing Concepts,” Proceedings of the 2023 ASEE Annual Conference, June 25-28, 2023, Baltimore, MD.2. Hsi, S. and Agogino, A.M. “The impact and instructional benefit of using