the workshops. 100% of the scouts learned some/alot of Biomedical Engineering, Manufacturing Engineering and Science, 98.3% of the scoutslearned some/a lot of Electrical Engineering, while 96.6% of the scouts learned some/a lot ofComputer Science. Scouts also reflected that they enjoyed the experience very much. 88.0% ofthe scouts really liked Biomedical Engineering workshop, 87.7% of the scouts really likedElectrical Engineering workshop, 93.3% of the scouts really liked Manufacturing Engineeringworkshop, 87.5% of the scouts really liked Computer Science, and 100% of the scouts reallyliked Science. Students also found the workshops increased their interest in STEM courses.RAMP ProgramAn entrance survey and an exit survey were conducted to
preparedness group, compared with the other groups?A Statics course (CEE 241), one of the most fundamental civil engineering courses, was used tocollect data. The sample size of the study includes 129 students. Both qualitative and quantitativeanalysis were conducted to understand students’ prior knowledge. Data were collected in variousways, including a qualitative survey reflecting students’ confidence levels on prerequisitematerials (qualitative preparedness) and quantitative measurements from a quiz (quantitativepreparedness), as well as final grades (course performance).The rest of the paper is organized into three main sections. Section 2 discusses the objective andscope of the study; Section 3 illustrates data collection and processing for the
framing and reflection [8-12]. This paper will focus on 2the elements of information gathering and application of context, along with ability to discernappropriate information.Problem scoping is considered to be crucial at the outset of the engineering design process whereinformation can not only be used to both develop solutions, but also to redefine the initialproblem framing during the progression of the process. Problem scoping in this vein is the abilityto determine the aspects of problem that need more consideration. For example, determining therole of stakeholders, such as utility companies and Native Americans on the management of areservoir system, or understanding the limitations of
finding,demonstrating, or building fluid mechanical systems in everyday life. We employ two differentinstruments to track students’ experiences in this course. First, we compare students'performance in a fluid mechanics concept inventory assessment that they take at the end of eachsemester. In addition, we also adopt a set of items from the Motivated Strategies for LearningQuestionnaire (MSLQ) to measure the impacts of these changes on students' motivations andattitudes. We reflect on the implications of this transition process and provide an outline of thefuture developments of this work.1. Introduction Teaching and learning in online or hybrid settings play an ever increasing role in science,technology, engineering and mathematics
offeredonline at Hampton University. Student participation in the survey was not required by the in-structor but was optional and completely anonymous for the students.Class Delivery Mode: The teaching of Chemical Engineering Calculations (CME 201- 4 credit), ChemicalEngineering Thermodynamics (CME 307 - 4credit), and Unit Operation Laboratory (CME 411 -2 credits) during COVID-19 was done entirely online, with Blackboard being the deliveryvehicle for instructions. We made use of both synchronous and asynchronous learning methodswhile teaching remotely.Technology Employed: The course involved completing both independent (e.g. reading material, viewing onlinecontent, reflecting on information) asynchronously and dependent (e.g. online interactions
additionalsupports be put in place to help students persist in STEM2-5. This paper will describe theprogram's recruitment strategies, the practices that have been most effective, and thedemographics of the successful applicants. In addition, the paper explores the evolution of cohortcommunity building efforts, starting with mostly faculty-led and planned events to events led bya consultant. Improvement in sense of community has been reflected in the evaluation reports,and selected supporting evidence will be shared from the reports.RecruitmentThis S-STEM grant was awarded in fall of 2018 with the goal of supporting at-risk studentsthrough multiple academic pathways, with our definition of at-risk as students who start atCampbell in a math class before pre
open toquestions. Our department chair is deeply integrated in our program’s teaching and led the chargeas we pivoted to emergency remote teaching (ERT) halfway through the Spring 2020 semester.In this paper, we reflect on how our department’s faculty successfully navigated the transition toERT and share lessons learned on how we continue to maintain high quality education whileonline. We have also reported elsewhere on our students' responses to the adjustments madeduring the COVID-19 pandemic using a compassionate flexibility model [1].Establishment of a Virtual Community of PracticeBefore the pandemic, our department of five faculty already had strong relationships and anetwork of support. When classes were cancelled for a week to prepare
% indicated that they do know an engineer in both surveys, 43% indicated that they do notknow an engineer in both surveys, 18% moved from not knowing an engineer to knowing anengineer, and 11% moved from knowing an engineer to not knowing an engineer [6, 7]. Basedon our analysis, we believe these numbers offer preliminary evidence that we are helpingstudents develop concrete ideas of who engineers are and what they do.Moreover, drawings and descriptions of engineers seemingly shifted towards representingcontent from the PEER. Although the drawings did generally reflect the kinds of actions andartifacts found in other studies (e.g. [9]), in our study more students represented cars, buildings,and the ideas of fixing and repair post compared to pre
theFormation of Engineers program under Grant Number EEC-1916673. Any opinions, findings,and conclusions or recommendations expressed in this material are those of the authors and donot necessarily reflect the views of the National Science Foundation. References[1] C. Quigley, A. Trauth-Nare, and N. Beeman-Cadwallader, "The viability of portraiture for science education research: learning from portraits of two science classrooms," International journal of qualitative studies in education, vol. 28, no. 1, pp. 21-49, 2015, doi: 10.1080/09518398.2013.847507.[2] L. C. Moll, C. Amanti, D. Neff, and N. Gonzalez, "Funds of knowledge for teaching: Using a qualitative approach to connect
currently completing a PhD in Engineering Education under Dr. Dringenberg. His research interests include exploring ideological beliefs as a reflection of tech culture. In his free time, he enjoys watching hockey, writing about programming languages, and playing video games.Dr. Emily Dringenberg, Ohio State University Dr. Dringenberg is an Assistant Professor in the Department of Engineering Education at Ohio State Uni- versity. She holds a B.S. in Mechanical Engineering (Kansas State ’08), a M.S. in Industrial Engineering (Purdue ’14) and a Ph.D. in Engineering Education (Purdue ’15). Her team, Beliefs in Engineering Re- search Group (BERG), utilizes qualitative methods to explore beliefs in engineering. Her research
demonstratedto improve collegiate graduates’ entry-level starting salaries, level of initial position, and jobresponsibilities [10] [11] [12]. The authors discuss the importance of experiential experiences inthe formation of professionalism in RS students [13]. To establish a reflective element withineach RS student experience, each fall the students come together for a one-hour seminar to talkand write about their journey and to continue learning about methods of growing their supportweb with university professors and staff [14].The RS students selected for this program implementation were typically residential applicantsof a low-socioeconomic status (SES) and that selected an under-represented minorityrace/ethnicity in their database entry. There was
aspects. The study’s objective was to create a VR platform consistingof four VR learning modules to teach data types, conditionals, loops, and operators. Each moduledeveloped one CT topic with engaging interactive activities, animated models, and games withbuilt-in self-assessment.This paper details the modules’ development, deployment, and outcomes related to the use of theVR modules within a science and math enrichment camp focused on learning engineering designand coding. The study assessed student use of the four CT topics in their final design project—acoded personal reflection. A lack of the fundamental understanding of CT concepts is a criticalfactor in STEM attrition rates as CT skills are highly interconnected to various branches
programmaticchange in higher education is rather rare [1], [2], [6], [7]. This section discusses the factors that,in retrospect, coincided to enable large scale curricular change to occur at this particular point intime. These factors, in no particular order, are: 1) reflection prior to and the post-hoc results ofan ABET accreditation visit, 2) arrival of an external department chair, 3) a preponderance ofyounger faculty in the department, 4) lingering pressures from lower-than-desired enrollment, 5)an environment that welcomed educational innovations, 6) a promotion and tenure system thatvalued teaching, 7) innovations occurring college-wide from a KEEN Foundation grant, and 8)growing institutional stresses caused by external factors not under the
reflects upon an action when the action is repeated and he or she can make an internal mental construction called a process by which the individual can think of as performing the same kind of action without an external support... An object is results from individual’s awareness of the process’ totality and realizes that transformations can act on it... A schema is a linkage of collected actions, processes, objects, and other schemas that help to form a framework by using general principles in individual’s mind...APOS theory can be appropriately applied to the collected research data due to the involvementof certain mathematical concepts such as limits, derivatives, and asymptotes. The participants ofthis
. Sample items include “High stress is expected for engineering students”and “Engineering students commonly stay up all night working”. Responses were measured on a6-point Likert scale in accordance with agreement with each statement (Strongly disagree,disagree, somewhat disagree, somewhat agree, agree, strongly agree). The use of a 6-point scalerequires participants to take a stance towards agreement or disagreement, which in the case ofrelatively neutral opinions, may reflect the participant’s unconscious bias [8]. For the pilotsurvey, an additional “No basis for judgement” option was added to check for questionsparticipants are consistently unable to answer due to not having experience with the item beingasked about or feeling that they did not
barriers to URM and FGC students. A more in-depth discussion of thesefindings can be found in [3] and [11].Finding 2 – The organizational cultures influenced participants’ perceptions of changepossibilities related to diversity and inclusion, and their role in change. Analysis of the post-design session interviews revealed the influence that the disciplinary/organizational cultures ofboth ECE and BME had on (1) the effectiveness of design thinking toward culture change, and(2) where change occurred (e.g., individual versus systemic levels). Reflecting a more limiteddesign culture within the school, the stakeholders in the ECE design sessions recognized andacknowledged limitations in their ability to make large-scale change within ECE. As such
material is consistent with their future career (Wigfield, 1994; Wigfield &Eccles, 2000). The interest component is based on how students perceive course topics andinstructional methods, interesting (Hidi & Ann Renninger, 2006; Renninger, Hidi, Krapp, &Renninger, 2014). Further, the success component is formed on expectancy for success(Wigfield, 1994; Wigfield & Eccles, 2000). This component reflects students’ self-efficacy aboutthe coursework (Bandura, 1986). The caring component is based on students believes thatinstructors care about their success and well-being (Noddings, 1992).Motivation can be perceived as a student’s intention and engagement in learning as student’saction (Christenson, Reschly, & Wylie, 2012). In other
Education at The Ohio State University. She holds degrees in Electrical Engineering (BS, ME) from the Ateneo de Davao University (ADDU) in Davao City, Philippines, and in Engineering Education (PhD) from Virginia Tech. Her research interests include learning experiences in fundamental engineering courses and data-informed reflective practice. Michelle’s professional experience includes roles in industry and academia, having worked as a software engineer, project lead and manager before becoming Assistant Professor and Department Chair for Elec- trical Engineering at the Ateneo de Davao University.Dr. Tamoghna Roy, DeepSig Inc. Tamoghna Roy works as a Principal Engineer at DeepSig where he is responsible for creating
help them with distraction and how to effectively work at home. 7. Emphasize care and empathy in your work with students (Atman, 2020). As novices learning unfamiliar tasks in an environment that currently is stressful, students may feel anxiety. Tell students about your own experiences with working remotely during the pandemic and strategies that worked for you. Consider using reflections with students to help them process their experiences and identify challenges.As we live and work in the COVID-19 and (eventually) post-COVID-19 eras, we will continue tolearn best practices for working remotely, including conducting research with undergraduatestudents. Our hope is that some of the strategies we have
with it) does not elicitthese same benefits.We only analyzed results from students’ first attempt on the Lesson 1 Quiz. After taking thisquiz, students were able to practice the problems and then retake the quiz. Students wererequired to earn 70% to move on to the next lesson. Therefore, scores on all but the first quizwere relatively high, leading to a restricted range in the data. We reasoned that the first quizattempt reflected knowledge gained after the activity and instruction, which were the target ofour intervention. However, students were aware that they would be able to retake the quiz,potentially impacting their motivation on this assessment. In our future research using thesematerials, we may make the first quiz worth more points
tackleadvanced manufacturing problems through data science. The Engineering Learning frameworkuses cognitive principles in the development of online courses (Spiegel, Sanders, & Sherer, 2018a;Spiegel, Sanders, & Sherer 2018b). As the framework states, “Engineering Learning is anintentional design process that positions students to cognitively engage with content and data usingprofessional tools, while interacting and collaborating with peers to develop their contentexpertise, skills, and professional practices. The end goal is to create the richest opportunities forstudents to become innovative STEM leaders.” Principles included in the framework includealignment with student learning outcomes, engagement with active learning, reflecting on
and exploring the sensor response for different relevant testparameters such as sensor (probe) size and characteristics such as frequency and type (absolutevs. differential) as well as test material properties (see the example for ET in Figure 1). In thisexercise, the students are first asked to predict the sensor (probe) response (based on what theyhave learned in the lectures and reading materials) and then calculate the response using thesimulation software (Figure 2). Afterwards, the students are asked to analyze the response inlight of their initial predictions and reflect on any mismatch. In this first exercise, the studentsonly study the probe physics and not the probe interaction with a flaw, which will be explored inthe second
same lab) worked together on the same mini project.After the boot camp, teachers joined their research group in pairs and spent the remaining fourweeks working on a research project with a mentoring team consisting of a computer sciencefaculty member and graduate students. Weekly social events were planned and attended by allparticipants and research group members. Weekly research seminars gave teacher participants achance to reflect on what they learned each week and to report their progress and next steps tothe entire cohort of teachers and research lab members. During the six-week experience, teachersalso worked regularly with a science education faculty member to develop student-centeredcurricular materials using a lesson plan
of course scale-up from 6 sections in Spring 2014 to 10 sections in Spring2015 to 15 sections in Fall of 2018. In the decision to scale-up the course, key indicators ofsuccess were considered: (1) course enrollment numbers, (2) end-of-semester evaluations, and(3) students’ individual course reflections. When taken together, these key indicators were anespecially vital tool in the decision to scale-up the targeted course.Figure 2: A history of course section scale-up from Spring 2014 to Fall 2018.Sustained Enrollment Numbers Enrollment numbers for the targeted course have remained consistently high sinceimplementation. An analysis of enrollment data from Spring 2014 through Spring 2018 showed acourse enrollment average of 99% (see
own learning. A common misconception is that self-directedlearning can only occur in isolation from all other input from either the educator or fellowstudents. Students can work in a highly self-directed way while being a part of a larger team.Notably, a salient trend in the research suggests that students with highly developedself-directed learning skills connect and consult with a range of peers and leverage theirlearning network to make their choices about the direction of their learning [1].Foundational literature that examines the construction of a successful self-directed learningenvironment suggests that learning should reflect three distinct parts: The learner, the educator,and the learning resources [2]. Significant parts of this
concept or how to proceed, students reflected thatEOEs stepped in to help them figure out how to move forward, providing encouragement andsupport throughout. Their comments suggested that the goal of the EOEs was to ensure thatstudents were successful on a project, even if they had failed attempts along the way. Studentsfelt supported by EOEs throughout the design challenges and perceived that EOEs worked tomake the experience as positive as possible for them.Table 5. Sample Student Statements Related to Fostering Student Agency, Understanding, andProject SuccessSub-theme Student StatementsStudent Agency They [EOE] didn't do it for me. They gave me some directions so then I could figure it out... not every
categories,namely: ten learning journal entries to include reflections on the content learned in the lectures,ten lab journal entries to include reflections on the practical activities, three quizzes with multiplechoice/true-false questions, and two assignments to be completed in groups of up to three students.Evaluation was conducted on teaching components according to student participation and theirquantitative and qualitative feedback. The result of the study shows that students were appreciativeof the HyFlex mode delivered [6]. In another study conducted by Sowell et al., implemented HyFlex in a general electivenutritional course consisting of over 500 hundred students. The nutritional course provides abreadth of knowledge inScience &
2 for the fall 2019 (teams self-selected) and fall 2020 (teamsselected via optimization) semesters. For critical design review (CDR), teams give a detaileddesign presentation covering their project’s requirements, baseline design, and engineeringmodels. The presentation is given to a review board of 10 faculty members, with 30 minutes forthe presentation and 20 minutes questions. Faculty member grades are averaged into the finalteam CDR grade, shown above. Peer evaluations are conducted anonymously immediately afterCDR, where each team member evaluates all other team members on a scale of 1 to 5 on bothtechnical and professional contributions. The critical design review is conducted in mid-November and reflects the progress the team has
possible.(Table 1). Students were then 3. If you were to describe your cohort to someone that has no experiencesasked to reflect on their midpoint with your cohort, what would you say? Please be as specific as possible.written responses and provide any 4. Describe how your cohort functions on assignments related your undergraduate research project, such as the concrete mix design and labamendments to these responses report. Be as specific as possible.during an interview with the 5. How do you think others perceive you in the cohort? Be as specific as possible.researcher at the
own words, what was done in the experimentand what the purpose of the experiment was for that lab section. This assignment was gradedsolely on completion, providing a low-stakes assessment for students to reflect on what theyhave learned. At the beginning of the following lecture, misconceptions identified in the post-labassessments were briefly addressed with the students, which was important in giving students theopportunity to identify their own misconceptions and areas for improvement [11], [12]. We alsorequired students to complete online readings using a collaborative e-reader, Perusall(www.perusall.com), which allows students to see and respond to each other’s questions andcomments directly on a shared PDF. For each reading, students