now calling, The System. The Systemconsisted of four main elements, both listed and shown in figures:1. MSP430 Launchpad Evaluation Kit (see Figure 1),2. Sidekick Basic Kit for TI LaunchPad (see Figure 2),3. Grove Base Booster Pack (see Figure 3), and the4. Grove Starter Kit for Launchpad (see Figure 4). Figure 1. MSP430 Launchpad Evaluation Kit Figure 2. Sidekick Basic Kit Figure 3. Grove Base Booster Pack Figure 4. Grove Starter Kit for LaunchpadStudents spent the first class lesson exploring the different items, their functions, andbrainstorming how things worked. Each student was asked to rate themselves on howcomfortable they felt with coding, using The
facultymembers respond that it is not technical mastery, but “mathematical maturity” that matters. Weconducted a qualitative thematic analysis of 27 interviews with engineering faculty membersfrom 11 disciplines who taught engineering courses that list part of the core engineeringmathematics sequence as a direct prerequisite. We examine which mathematical skills, habits,and attitudes constitute “mathematical maturity” for engineering students according to theseengineering faculty members. We constructed an initial coding scheme from literature onmathematical epistemology, mathematical competencies, and symbol sense, with additionalcodes allowed to emerge during coding by two researchers.Some of the findings of this study are presented here. 1) Faculty
Engineering at the University of Akron (UA) ran aNational Science Foundation funded Research Experience for Teachers (RET) site from 2012-2016 and started a new cycle in 2016-2019. This paper is a summary of the 2012 – 2016 site.The main objective of this RET site was to bring ten high school science teachers to TheUniversity of Akron (UA) campus for eight weeks each summer to increase their knowledge ofengineering research and enable them to effectively disseminate this knowledge in their highschool classrooms. This was accomplished through a combination of (1) an independent researchproject for each teacher in the laboratory of a UA faculty member and (2) hands-on professionaldevelopment activities to reinforce the fundamentals of engineering
among educators about the definition of creativity. Someconsider creativity as the ability to invent, whereas others classify creativity asdivergent thinking or even imagination 1. In short, creativity is the ability to create andto innovate and is a characteristic and an ability of creative people 2, 3. Whenevaluating creativity within education, projects completed by students are usuallyused as the evaluation criterion, and the process, environment, and characteristics ofcreativity themselves are rarely explored or analyzed. Although some studies on thesubject have been performed, the majority have only defined or probed thedevelopment of creative thinking from a single dimension.All current learning management platforms collect digital
and implementing an innovative solution. We analyzed process mapsusing an a priori coding scheme which was modified from a coding scheme that was originallydeveloped to analyze expert-created process maps1. The coding scheme focused on the content ofthe map along two categories: (1) stage of innovation and (2) focus area. Analysis revealed thatstudents identified a majority of components at the opportunity identification (earliest) stage ofinnovation and included a decreasing number of components in each later stage of innovation.Students also emphasized the technological elements of the process, with lesser, but moderate,emphasis on strategic and societal elements.Investigating the Variety of Ways Engineering Students Experience
step of the design process and thus targets particular POED.This course structure is anchored in the experiential learning cycle of David Kolb [1] by thelearning statement, a reflective learning exercise. We provide our course map of the relationshipof the POED to each assignment addressed in this paper in Figure 1. Through course lectures we provide the information and context required for students tocomplete assignments and, through reflection, identify competencies needed as Junior Engineers.Lecture topics range from discussion of the assignments and the POED to design processstrategies and tools. For example, we give a lecture on ‘attention-directing tools,’ which enablestudents to make informed decisions based on qualitative data
Table 1). The surveys probed self-reporteddifferentials in 1) teachers’ confidence in teaching engineering concepts and 2) changes in theirteaching practices as a result of exposure to (and experiences with) K-12 engineering educationresources and outreach opportunities, including the frequency with which they integratedengineering into their classroom teaching. The surveys employed a combination of Likert-style,open-ended, and multiple-choice questions. Table 1: Descriptions of TeachEngineering (TE) impact surveys for three K-12 teacher populations. Survey Population All TeachEngineering.org users from September 27 to TE site pop-up survey
guidingresearch question was: “To what extent can affordances of physical manipulatives be built intovisuo-haptic simulations? We have designed an experiment where students moved objects withdifferent friction on different surfaces. Our study comprised seven students who were promptedwith “what-if” scenarios where they first predicted what they thought might happen, and thentested their predictions by using a physical manipulative setup. We characterized students’interactions using Gaver’s (1991) classification of affordances. Our results suggest a higher levelof student engagement and motivation when using the physical manipulative setup. However,they also show greater confusion about: 1) density vs. weight, 2) mass vs. surface area, and 3)softness vs
encounter during capstone design and willencounter in the real-world. The second goal is to improve assessment of students’ abilities toapply sustainable engineering design concepts across different problems or design challenges.We hypothesize that with guided practice and feedback, engineering undergraduate students willbecome better at drawing upon and integrating diverse knowledge domains when they are facedwith new, complex problems during professional practice. Project work began in September2015 through the NSF Research in Engineering Education program.Cognitive flexibility theory (CFT)1 provides a basis for assessing and improving students’knowledge transfer and the connection-building required to adequately address sustainabilityproblems
the development anduse of problem solving in the context of design, or design thinking skills, has yet to bedetermined.This Works in Progress paper seeks to provide additional insight into the role of knowledgestructure, knowledge retention, and misconceptions in solving open-ended biomedicalengineering design problems. Correlations in problem solving performance to level ofmetacognitive awareness will also be assessed. As part of a larger multidisciplinary study, weseek to develop a model for undergraduates’ STEM problem solving performance that will serveas a tool to guide support of students’ problem solving skill development.Goals and Research QuestionsThe overall goals of this study are to (1) analyze students’ problem solving work in
combined findings from both phases of the study.2. Research Question(s)Mixed-methods research follows from a pragmatic perspective, hence the research questionsguide and determine the entire process such as selection of research design, sample size, and datacollection methods11-13 The research questions for this study are: 1. The overarching research question is: “What is the relationship between engineering students’ programming self-efficacy beliefs and their experience learning computer programming?" 2. The quantitative research question is, “Are there differences in students’ programming self-efficacy beliefs after taking an introductory computer programming course?" 3. The tentative qualitative question is
toprofile the quality of reflection. Table 1 summarizes the dimensions of reflection.Table 1: Summary of Reflection Dimension Attributes. Dimension Attributes Descriptive Problem or concern is identified and described. Comparative Outside perspectives and/or data are gathered to reframe the problem, question assumptions and/or preconceived notions and provide basis for comparison/critique. Evaluative Conclusions are made with a broadened perspective of how teaching impacts the learning environment and how students learn. Decisions to implement a change or to continue with current teaching style
students could bring work from any class in which they might have awriting assignment. The resulting implementation resulted in only 1 or 2 students attending thefirst two sessions, and no attendees at the later sessions. Because of this the workshops weretransitioned to a technical writing module that is completely online within the virtual programspace, allowing participants to complete activities on their own time, consult references asneeded, or contact the PIs with specific questions they may have.A second activity that underwent a trial phase with limited success was a series of studentsuccess workshops. The University’s Center for Academic Achievement offers a series ofstudent success workshops throughout each semester covering topics such
section; the“scientific method” students outperformed “neurotransmission” students on scientific methodquestions, while “neurotransmission” students outperformed “scientific method” students onquestions pertaining to neurotransmission.Research QuestionsBecause creating digital video is not a widely accepted form of communication expected ofundergraduate students, the following research questions were proposed for this study: 1. Does learning differ between students who create media while receiving media- literacy instruction and students who receive media-literacy instruction alone without creating any media? 2. Do “video term-paper” projects and lessons in media literacy improve student
influenced by the existing framework of thepre- and post- tests for the assessment of learning (Dietrich et al, 2015). For both the IntroDBand QueryDB animations, the questions that assess student learning are related to categories ofassessed concepts, which are shown in Table 1 for each animation. Questions range from high-level concepts to specific details in identifying data for answering queries or missing parts of anSQL query. Table 1. Categories of Concepts Assessed in the Two Animations IntroDB Category QueryDB Category Spreadsheet Anomalies Set Operations Database Anomalies (None) Filtering operations Primary Keys
project include investigation of common design patterns, a progression ofstudent experimentation behaviors, and validation studies of a design conceptions instrument.(1) Investigated common patterns of student design behaviors.1 This publication exploredthree protocols to measure students’ engineering design solution quality, taking into account bothobjective and subjective design criteria. We compared high school students’ design solutions andestablished a metric called Trade-Off Value as a way to measure artifact quality. This method ofmeasuring measure artifact quality by focusing on how well a designer has balanced bothcomplementary and competing design criteria provides additional information on an importantdesign behavior and an opportunity
engineering education, and community partnerships in secondary education. c American Society for Engineering Education, 2017 WIP: Examining micro-interventions to improve classroom community in introductory engineering classroomsThe field of engineering education, like many areas in higher education, is steeped in tradition.Engineering departments are known for traditional lecture-style classrooms with highenrollment, particularly at the lower levels, where direct instruction, along with grades basedlargely on a handful of multiple choice exams, are the norm [1]. Introductory courses -- the startof an unforgiving workload -- serve to “weed out” students at an early stage, and typically
example, communication skill development seminars,workshops, and mock interviews were coordinated prior to events like the Engineer Career Fairwhereas visits to local industries were scheduled later in the semester to avoid overlap withmidterm exams and research activities.FindingsThe demographic profile of the participants for each semester is listed in Table 1. During the firstthree years of the program, a total of 29 scholars have been awarded 54 scholarships, with astudent population that is 62% white, 28% African-American, and 10% Hispanic. Within theprogram, there are more males (62%) than females (38%).Table 1: Participants’ Gender and Demographic Profile since the program started. RACE/ ETHNICITY Year 1 Year 2 Year 3
-based instructional practices (i.e.active learning, cooperative learning, think-pair-share, etc.) and opportunities for their inclusion.Following the TLE, sequentially, two additional faculty review the video and are privy to thepre-observation reflection statement, the comments from the TLE, and any other reviews orannotations that preceded their own reviews. The peer reviewers are provided a table ofinstructional attributes, adapted from Berquist and Philips (1975) to guide their review (Table 1).The reviewers are also provided a list of evidence-based instructional practices and theiroperational definitions. Table 1. Table of attributes used to guide peer-review. Instructor’s Organization (The instructor…) presented the material in an
in the next section. Each module has sixcomponents: 1) assigned background material, 2) a list of supplemental resources, 3) a lecturevideo, 4) a faculty conversation video, 5) a multiple choice quiz, and 6) a written discussionassignment. The assigned background material ranges from third party videos describing atechnology in more depth (such as [1]) to scholarly articles discussing related issues (such as[2]), to short stories illustrating relevant issues (such as [3]). A list of supplemental materials isposted along with the assigned background material. This list provides students with a startingpoint to dig further into a desired topic as well as find resources for the course project. Thelecture videos are 20-40 minutes long
to a recent study, students aretethered to digital technology [1]. Therefore, digital technology is now essential for them toconstruct and manage their lives. For this reason, this generation has different expectationsregarding how they learn and how they want to be taught.A hallmark of digital technology might be interactivity. Interactivity can be achieved throughdiverse experiences, including two-way or reciprocal communication [2-4], tailored content (i.e.,customization or personalization) [5-6], and synchronous interaction with a system [2].Interactivity is viewed as residing in the medium or technological feature itself. It suggests andpermits interaction [7-8]. Therefore, the very presence of interactive features can constitutediverse
an advanced degree. In particular, a master’s degree has been shown to have a positiveimpact on engineers’ careers. Evidence shows that those with a master’s degree tend to stayabreast of changes in technology as well as ways to adapt to new technology.1 ABET has longencouraged continuing education.2 In 2007, the National Science Foundation sponsored the5XME workshop, which encouraged participants to discuss how to help US institutions trainstudents to become the best engineers in the world. One of the workshop’s recommendations wasto establish the master’s degree as an essential element of the field of engineering. “The mastersdegree should introduce engineering as a profession, and become the requirement forprofessional practice”3 and as
have learned from those experiences.Data Sources: There were 9 participants in this study—2 alumni, 6 seniors, and 1 junior. Allparticipants have completed the GCSP requirements and have described most of theirexperiences in their final portfolios. The primary data source was the portfolios which describedtheir GCSP experiences. Semi-structured interviews were conducted with 3 of the currentstudents who will be graduating this semester. In the future, we will conduct additionalinterviews using the portfolios for artifact elicitation to gain further insights into the meaningstheir chosen GCSP experiences hold for them as they navigated the process of becoming a GrandChallenge Scholar-Engineer.Data Analysis: Open and axial coding methods were
in STEM fields. 1,2,3 . Under the umbrella of active learning,however, a large variety of different (and sometimes contradictory) methodologies have beenproposed; including project-based learning, problem-based learning, gamification, tinkering,collaborative learning, class competitions, and many others. As educators become more interestedin student-centered pedagogies, the question of which specific techniques are most effective isincreasingly important.Because active learning is still an emerging paradigm, the number of studies examining distinctapproaches is somewhat limited, and the difficulty of isolating those techniques in the classroomenvironment is a recognized concern. 1 In this paper, we wish to contribute to the growing pool
(STEM) [1-2]. To date, 92 students from 64 universities, morethan half of whom were female, have taken part in this program.REU programs are designed around the needs of the undergraduate student participants. Theresearch projects, seminars, laboratory/industry tours, meeting with mentors, networking eventsand other activities are all set up to maximize the positive impact of a research experience on thestudents. After all, numerous studies have shown that active participation in hands-onundergraduate research is one of the most effective ways to attract and retain talentedundergraduate students, to motivate them towards pursuing careers and advanced degrees inengineering and science, to help them feel more connected to their educational
project are the formalized opportunity to continue to engage in the discipline byproviding professional expertise and to contribute to a more diversified next generation ofengineering faculty.The mentoring and advocacy-networking paradigm was developed through an extensive reviewof the literature across disciplines with a targeted focus on diverse mentoring relationships inscience, technology, engineering, and mathematics fields (Johnson, 2015; Kram, 1985; Zellers,Howard, & Barcic, 2008). The model moves beyond advisory mentoring to include professionalnetworking and advocacy by emeriti faculty who are uniquely situated to provide theseresources. The new paradigm encompasses three domains of mentorship: (1) career development(emeriti faculty
, the paper discusses the student and instructor reactions to the course, lessonslearned, and suggestions for future offerings. The material developed for this course will beposted online so that other educators may use it in their teaching.IntroductionAutonomous vehicles and robotics are perennial hot-topics in the field of engineering. Roboticsare frequently used as a teaching tool at the K-12 level to draw students into STEM fields [1, 2]and Robotics Summer Camps and extra-curricular activities have even been created for K-12students [3, 4, 5, 6]. In higher education, although elements of robotics programs are found inmost engineering disciplines, including Aerospace, Mechanical, Industrial, Electrical andComputer Engineering, as well as
-testingenvironmentencouragesstudentstotryvariedexampleproblems.SeeFigure4.Asubsequentreviewofsolutiondetails(providedbyCATE)isalsoavailabletoillustratesolutiondetails,ifdesiredbyastudent.CATE’sactivelearningmodeandquizzingfeaturesareintendedtobothbuildstudentconfidenceastheyverifytheirabilities.Italsoprovidesacheckontheirlevelofmastery,astheyrealizewhattheydon’tknow.ThisfollowsguidancefromArnoldandMcDermott[2]establishedthatrereadingwithoutself-testingcanleadtooverconfidenceregardingperceivedmastery.FurthermoreBrown[3]suggeststhatattemptingtosolveaproblemandfailingisbetterthannoattemptatall.CATEprovidesasafeenvironmentforfailing,withnoconsequencestoacoursegrade.AlsoCATEcangeneratebillionsofcircuittopologies(forACcircuitswithdifficultylevel3).WorkbyRoedigerandKarpicke[1
. NECST employs several activities that provide the additional scaffolding tosupport students as they make this transition. While we believe these activities may be suited forother situations, the program helps address the unique challenges northern New Jersey faces withrelation to graduate studies in computing fields.There have been significant efforts toward addressing the current and future shortfalls andmismatches in the computing, information, and technology workforce [1]. These efforts includeattracting more students into computer science, fostering a realistic and interdisciplinary approach tocomputing, and increasing cooperation and collaboration between institutions. The NECST Program[2], funded through the NSF S-STEM program [3