,recommendation, or favoring by the United States Government or any agency thereof. The viewsand opinions of authors expressed herein do not necessarily state or reflect those of the UnitedStates Government or any agency thereof.References[1] P. Maxigas, "Hacklabs and hackerspaces:Tracing two genealogies," Journal of Peer Production, no.2, Jul. 2012, Accessed: Jun. 29, 2020. [Online]. Available: https://eprints.lancs.ac.uk/id/eprint/88024/.[2] S. Mersand, "The State of Makerspace Research: a Review of the Literature," TechTrends, vol. 65, no. 2, pp. 174–186, Mar. 2021.[3] R. Dattakumar and R. Jagadeesh, "A review of literature on benchmarking," Benchmarking: An International Journal, vol. 10, no. 3, pp. 176–209, Jan. 2003.[4] R. M. Epper
students along with the resulting output waveform of the amplifieras presented in Figure 2(b2). Students were asked to analyze the given circuit to identify thepossible reason(s) why the output waveform was distorted (the lower half was cut-off).Since the modality, the student population, and the challenge questions were different in the Fall2019 and Spring 2020 semesters due to the ongoing pandemic, a direct comparison of theassessment results cannot be made. However, assessment results for both modes reflect somecommon areas of improvement and provides a qualitative understanding of the student skilllevels in this course. Based on our preliminary assessment results, we plan to develop a rigoroustroubleshooting skill improvement instructional
is seen either via the lens of structural componentpresence/absence or via their thought process (content, discursiveness and reflectivity). Thisleads to the observation that students focus on articulating the claim rather than justification ofthe claim. Seah and Magana (2019) note that student arguments were not supported by sufficientor quality evidence to justify their design choices in Information Technology.IMPLICATIONSThese findings have implications for future research, for the development of instructionalmaterials for engineering classrooms, and for undergraduate engineering degree programs. Asengineering educators and researchers begin to explore this topic, they have many lessons tolearn from the extant research in science and math
Requirements Through 2018. LuminaFoundation, 2010.[4] A. P. Carnevale, N. Smith, and J. Strohl, “Recovery: Job Growth And EducationRequirements Through 2020,” Jul. 2013.[5] G. Markle, “Factors Influencing Persistence Among Nontraditional University Students,”Adult Educ. Q., vol. 65, no. 3, pp. 267–285, Aug. 2015.[6] “National Center for Educational Statistics: Enrollment in Postsecondary Institutions Fall2011 and graduation rates, selected cohorts 2003-2008. Retrieved fromhttps://nces.ed.gov/programs/digest/d11/tables/dt11_200.asp.”[7] C. Hittepole, “Nontraditional Students: Supporting Changing Student Populations.” StudentAffairs Administration in Higher Education, 2015.[8] R. Brindley and A. Parker, “Transitioning to the classroom: reflections of
,” J. STEM Educ., vol. 18, no. 2, pp. 10–17, 2017.[4] T. Kinoshita, G. Young, and D. B. Knight, “Learning after learning: Perceptions of engineering alumni on skill development,” Proc. - Front. Educ. Conf. FIE, vol. 2015- Febru, no. February, 2015.[5] L. C. Strauss and P. T. Terenzini, “The Effects of Students’ In- and Out-of-Class Experiences on their Analytical and Group Skills: A Study of Engineering Education,” Res. High. Educ., vol. 48, no. 8, pp. 967–992, Dec. 2007.[6] G. Young, D. B. Knight, and D. R. Simmons, “Co-curricular experiences link to nontechnical skill development for African-American engineers: Communication, Teamwork, Professionalism, Lifelong Learning, and Reflective Behavior Skills,” in 2014
. Question pertained to the topics currently covered in theDifferential Equations course and their perceived importance by the respondents. There is avariation between these topics and those surveyed in 2017; this reflects the desire of the team tooffer some other topics not covered in 2017.Question 2: What is your perception of what the students learn and/or the level of instruction inMATH 301 (Differential Equations – in terms of topics covered) (Conditional on answering“yes” to Question 1 above).Fourteen people answered this question; the results can be seen in Graph 3. As can be noted, noengineering faculty chose “Exceeded Expectations”, thus confirming the necessity of thisinitiative, but 71% claimed that the course and/or student achievement
the author(s) and do not necessarily reflect the views of the NationalScience Foundation. The authors wish to thank the STRIDE team and survey participants fortheir engagement with this study.References [1] M. Credé and N. R. Kuncel, “Study habits, skills, and attitudes: The third pillar supporting collegiate academic performance,” Perspectives on Psychological Science, vol. 3, no. 6, pp. 425-453, 2008. [2] A. Godwin, “Unpacking Latent Diversity,” in American Society for Engineering Education (ASEE) Annual Conference and Exposition, Columbus, OH, 2017. [3] J. J. Lin, P. K. Imbrie, K. J. Reid, and J. Wang, “Work in progress—Modeling academic success of female and minority engineering students using the student attitudinal
differently from students in RH 330and PH 113. Therefore, post-course comparisons were run after computing difference scores foreach course. This was done by subtracting students’ post-course ratings from their pre-courseratings. An ANOVA to compare courses was then run on the difference scores. This is done sothat any differences found better reflect actual differences between courses rather than inflateddifferences due to the unequal starting point. Page 12.514.6When comparing student survey responses across courses, 1 statistically significant differenceappeared. Students in CSSE 371 reported a significantly lower increase in tablet PC usage frompre
, consulting and reassessing as and when necessary iv. Metacognitive monitoring of oneself, people needing attention and the general process of the case, problem, project or situation.The time dimension provides for instant reflex actions (short term), and deliberative diagnosisand action with review and reflection (long term). The survival dimension involves theconstruction of learned routines that become tacit over time enabling the professional to respondquickly to situations with increasing responsibility and complexity.None of these studies provide detailed information on what the graduates are actually doing intheir work and hence can provide information to evaluate in detail the strengths and weaknessesof their undergraduate
change with time and relate toexperiences they are having on campus.In his third year, Joe talks about balancing skills and knowledge with “willingness to learn andexplore”. During this time he is trying to decide if he should pursue industry or research and hisinterview responses reflect his struggle with this decision. His basis for distinguishing thebetween two career avenues is not clear.By her fourth year, Anna’s beliefs about skills needed for success are more grounded inengineering. Similar to Hillary’s answer in the first year, Anna’s answers are generic. Annatalks about having “many, many skills: writing skills; people skills; management skills; skills tobe aware of, of umm, the project as a whole and where you’re going with it” and
) and do not necessarily reflect the views of the National Science Foundation. Inaddition, the authors thank Dr. George Toye for tending to the database storage needs of theproject, Elizabeth Lee for her assistance in coding the data, Mia Clark for her assistance inediting, and Patrick Ferguson for providing data on the School, as well as Claire Dwan and hertranscription services.References1. S.D. Sheppard, K. Silva, "Descriptions of Engineering Education: Faculty, Student and Engineering PractitionerPerspectives," 2001 Frontiers in Education Conference Proceedings, October 9-11, 2001, Reno, NV.2. L. Saks, “Undergraduate Science Majors
secondary classroom, and the application/presentation component. This willprovide more closure to the lesson and allow teachers the opportunity to synthesize the data thatthey collect and make sense of it. Additionally, while teachers work on their presentations, theywill have opportunities to interact with members of the professional development team anddiscuss conceptual questions in small groups. The post-lesson discussion period will also bemore directed towards means of classroom implementation to provide a more organized forumfor teachers to reflect on implementation.It is important to note that although we were interested in exploring how teachers connectedconcepts from quantum dots to their curricula (research question 1), we were not able
order to apply the findings ofthis research to future school settings, the data collection would have to be limited to a quantityand scope that would not be onerous to busy educators. Thus a strategic decision was made tolimit the set of potential variables to a more manageable size. The BY data from 8th grade wasthe earliest data collected about the students and represented the earliest point in the NELS studyat which academic assessments could be made. Prior research findings in the literature were Page 13.55.5used to select a smaller set of variables to be tested. A set of 66 variables was selected. Thesevariables reflected aspects of
students in an academic scholarship program going intograduate school full-time and over a 30% rate of such transfer students.I. IntroductionFor some time, there has been a growing concern about the future of the United States in terms Page 13.1287.2of new discoveries and inventions. One of the people leading this battle cry is Professor Romer,“a big-name Stanford University economist.”1 He argues that discoveries don’t simply appearwhen inspiration strikes, but reflect the effort put into innovating. The bottom line for thisconcern is that the number of undergraduate engineering degrees being earned in the UnitedStates has been declining since 1996
program. This approach isholistic, comprehensive in nature and includes developers, designers, instructors, students andevaluators with a broad focus on the effectiveness of the program and is consistence with theapplied research. Type I studies can be characterized by their reliance upon contextually specificprojects and contextually specific conclusions.3 This approach includes improvements in theinstructional program and the conditions which are conducive to efficient design, development,and/or evaluation of the instructional program.4,5,6, 7 Additionally, some Type I developmentalstudies reflect traditional evaluations in which the actual development process is not formallyaddressed; rather, only the product or program evaluation is described
structure, knowledge is gained by support, participation and nurturingwith others17,18. These areas of motivation were assessed because of their strong connection toachievement, spending time on complex activities, learning and growth goals, the use of deeperand more reflective strategies for learning, more risk taking and the focus on the learningprocess21.Valuing Science It is a goal of the HARP program for students to learn to value science education,discovery and future careers in science. This goal will be assessed specifically by measuring theincrease in students valuing the problem solving process, the calibration process, the scientificmethod in application to real life problems, documenting for repeatability, data analysis
the research on learning and multimedia presentationdesign, which emphasizes the importance of providing images that promote integration betweenconcepts. Not reflected in Table 3 are the decorative images from the use of PowerPoint defaultbackgrounds, such as those shown in Figure 5. In our survey, we determined that 47% of theslide sets examined of slides used such a background. As asserted by Carney and Levin,19 suchdecorative images slightly reduce the comprehension by audiences.Table 3. Common practice statistics on image level.Classification Definition StatisticsDecorates Not relevant to text 5%Partially Represents
the videos in order tolearn the material necessary to be successful in the quizzes. This helps to assure that studentswill be prepared for the in-class activities. Second, the instructor can use the results of thequizzes as a launching point for discussion and adjust the class plan as necessary to address anystudent misconceptions or lack of understanding, in a form of just-in-time teaching. 8The classroom flip method may be perceived to be particularly beneficial to students who prefercertain types of learning environments. According to the Felder-Solomon Learning Styles Index,students may classify themselves along four dimensions as being a certain type of learner:active/reflective, sensing/intuitive, visual/verbal, and sequential/global
consider new ways to thinkabout our data. As Tufte says, “if displays of data are to be truthful and revealing, then the logicof the display design must reflect the logic of analysis”.5 Multiway plots assist us in extractingthe story the data tell. Page 14.1009.4Method and results: transforming column charts to multiway plotsEighth-semester persistence data. To interpret multiway plots in contexts that speak toengineering education audiences, we use categorical data from MIDFIELD (the Multiple-Institution Database for Investigating Engineering Longitudinal Development) on eighthsemester persistence disaggregated by race and gender. MIDFIELD data
based on the work students self reported they had donewith respect to course and project assignments. Again, the purpose of the assessment and itsevaluation was to have the student’s reflect upon their time management periodically during thecourse. The six assessment surveys are posted on the web7. The class had two medium-sizedprogramming assignments, a midterm, and a final. Each programming assignment was to becompleted within 6 weeks. All grades were percentages.In study 1 we report results from two analyses. First, we test our hypothesis by examining thecorrelation between all 47 student assessment, exam, and program grades. Second, we examinethe fourth and sixth assessment scores to evaluate the validity of the assessment questions. Wehope
: built into the key program features were evaluation criteriathat efforts be “radically, suddenly, or completely new; producing fundamental, structuralchange; or going outside of or beyond existing norms and principles” [6]. With an innovativedepartment head or dean at the helm, change had to be rooted in engineering education research,a social science understanding of organizations, and a theoretical change framework that couldmove research to practice, with team composition reflecting this varied expertise. Facultydevelopment efforts, incorporation of professional practice, and a plan for scalability thatcountered anticipated obstacles had to be baked in to the original vision and project plan.With NSF investing relatively large amounts of
& Lechuga, 2017; Trowler, 2014).Researching such learning communities involves a systematic exploration of many contextualaspects, including “the culture of the institution, the administrative hierarchy, students, faculty,and external constituencies” (Pasque & Lechuga, 2017, p. 2).The recent surge in ethnographic or participant-centered, qualitative research in higher educationaligns with an increased awareness that classrooms, programs, lectures, work sessions and thelike all operate within a system that is multilayered and often hierarchical (Bryk, Sebring,Allensworth, Easton, & Luppescu, 2010). As such, final scores or reflections may hint at thecomponents, activities, and resources most useful to, or constraining the
of Peer Designed Instruction? 2. Does Peer Designed Instruction increase student motivation when compared to other courses students have taken at the University of Texas at El Paso? 3. Does motivation in this context change based on gender? 4. Does motivation in this context change based on the student having been a Student Instructor?To answer these questions, a mixed-methods approach was used to collect student feedback via athree-part survey. In the first part, a series of multiple choice and open-ended questions wereincluded to allow students the opportunity to reflect on their experience. Questions one throughten are a set of introductory open-ended questions related to the
the total activity time and total lecture time on a specific concept. From Figure9(b), we observe that the basics concept had the highest weight in the exam. However, the pointsallocated to exam questions on conditions and functions does not align well with the timeallocated for class time. Conditions, which has the least class time, accounted for 9.17% of theexam grade, whereas functions accounted only for 5.42%, despite devoting the highest amount ofclass time. This analysis empowers instructors to design fair exams based on their in-class timeallocation or adjust the in-class activities to reflect the exam expectations.Preceptor SurveyTo measure the overhead of the FEAL form administration and its impact on the preceptors’ability to
information independently[66]. This mechanism reduces the cognitive load of storing information and allows for greaterinformation processing capacity.When engaging in problem solving, experts have been shown to participate in systematic real-time “reasonability” checks, contrasted with novices who proceed to the end without taking timeto reflect [67]. This behavior of expert problem-solvers perfectly aligns with our definition ofengineering intuition as the ability to assess solutions. In real-world engineering, ill-definedproblems are of particular interest. Studies have shown that ill-defined problems are often notsolved systematically, but rather through reactionary, intuitive processes to navigate thedecisions of problem-solving [68].Motivation
, Effective Learning.”, Palo Alto, CA: Davies-blackPublishing, 1995.11. Dale, E., “Audiovisual Methods in Teaching,” (3rd ed.), New York: Dryden Press, 1996.12. Wankat, P.H., “Reflective Analysis of Student Learning in a Sophomore Engineering Course,” Journal ofEngineering Education, Vol.88, no.2, 1999, pp.195 -203.13. Finelli, C., Klinger, A., & Budny, D.D. (2001), “Strategies for Improving the Classroom Environment,” Journalof Engineering Education, Vol 90, no.4, 2001, pp. 491-497.14. Smith, K.A., Sheppard, A.D., Johnson, D.W. & Johnson, R.T. (2005), “Pedagogies of Engagement: Classroom-Based Practices,” Journal of Engineering Education, Vol. 94, no.1, 2005, pp. 87-101..
the experiences theygain through their funding. Additional attention should focus on the role of postdoctoralpositions both in industry and academia on engineering doctoral career advancement. Educationwas categorized for all positions within academia and K-12 employment. Future work shouldinvolve looking at what types of positions graduates obtain within Education, such as tenure-track faculty positions or lecturer or other part-time positions.AcknowledgementsThis research was funded by the National Science Foundation through grants #1535462 and#1535226. Any opinions, findings, and conclusions in this article are the authors’ and do notnecessarily reflect the views of the National Science Foundation.ReferencesAustin, A.E. (2002). Preparing
grant from the National Science Foundation (Award # EEC-1730576). Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. The authors are grateful to Catherine McGough and Rachel Lanning fortheir assistance in collecting and analyzing survey data.References[1] W. Sarasua, N. Kaye, J. Ogle, N. Benaissa, L. Benson, B. Putman and A. Pfirman, “Engaging Civil Engineering Students Through a ‘Capstone-like’ Experience in their Sophomore Year.” Proceedings of the 2020 Annual American Society of Engineering Education (ASEE) Conference and Exposition, Virtual Conference, June 21 – 24, 2020.[2] Ogle, J.H., Bolding
outcomes, reflecting the skills and attributes that all MechanicalEngineering students are expected to possess at the time of graduation. These student outcomesare based on documentation collected during the annual assessment process and represent acombination of direct and indirect measures, such as the performance of student work, FE examresults, formal survey data, as well as data of specific curriculum courses' completion. Thecourse of Thermodynamics represents a significant portion of the FE exam (~10%). In thisevidence-based practice study, students were tested weekly under the FE exam format (3 minutesper question, 4-5 questions) in a pre-set time interval. The exams were administered throughGoogle Classroom and Google Forms, and students
researchprojects that were funded by the universities. The data presented in this study has been collectedfrom a total of 13 research projects in the fields of architecture and manufacturing. Both currentand past research projects have been included to reflect on if undergraduate research (UR)encouraged them in future research opportunities, whether UR encouraged them to enter intograduate schools, or UR impacted their professional development. All the data presented for eachproject including students current position has been tracked over time and collected by theauthors. Student demographic data has been presented in the study to see if there is any effect ofgender, students’ academic year, GPA, immigration status, on their willingness to be engaged