questions allow students to think through some in-class illustrativeproblem before lecture. Students attempt to interpret the probabilities and identify the goal. Thisway they will come to the class more prepared and better understand why the instructor chooses acertain approach in solving the problems. The review questions are also included to help studentsassess their previous learning in a timely manner. In addition, the instructor is able to review thequestion statistics before the lecture, hence to understand the common mistakes andmisunderstandings, and adjust the lecture coverage and deliverance accordingly. The preview-deliver-review cycle behind the quiz design is illustrated in Figure 4(a) with anexample given in Figures 4 (b-d). The
Strategic Entrepreneurship: The Construct and its Dimensions,” J. Manage., vol. 29, no. 6, pp. 963–989, Dec. 2003.[9] J. Wheadon and N. Duval-Couetil, “Elements of entrepreneurially minded learning: KEEN white paper,” J. Eng. Entrep., vol. 7, no. 3, pp. 17–25, 2016.[10] R. H. Todd, W. E. Red, S. P. Magleby, and S. Coe, “Manufacturing: A Strategic Opportunity for Engineering Education,” J. Eng. Educ., vol. 90, no. 3, pp. 397–405, Jul. 2001.[11] C. Sievert and K. Shirley, “LDAvis: A method for visualizing and interpreting topics,” in Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces, 2014, pp. 63–70.[12] P. Shankar, B. Morkos, and J. D. Summers, “Reasons for change
, the serial monitor would have many instances of the text,even though the button was only pushed once.The LED is observed tobe turned on because ofthe HIGH signal sentfrom the Arduino, andthe serial monitor hasoutputted text confirmingthat the button waspushed. Figure 11: Push-button and LED output and serial monitorIn the keypad project during thesimulation, the keypad was pushedin the order: 9 D B * A. In the serialmonitor shown below, the outputmatches the keys that were pressedin the corresponding order (Figure12). Figure 12: 4x4 Keypad outputDiscussionThis section further discusses the results of the sample projects mentioned above and how the useof a virtual Arduino
teacher self-efficacy scale is a set of questionnaires [5]. It seems tobe a variant of TSES introduced above and has better coverage. It is designed to help people gaina better understanding of the kinds of things that create difficulties for teachers in their schoolactivities. It has 30 questions which are classified into 7 categories: a. Efficacy to Influence Decision Making b. Efficacy to Influence School Resources c. Instructional Self-Efficacy d. Disciplinary Self-Efficacy e. Efficacy to Enlist Parental Involvement f. Efficacy to Enlist Community Involvement g. Efficacy to Create a Positive School Climate These 30 questions provide a comprehensive coverage of teachers’ self-efficacy. 2.3 Collective Teacher
Studies, vol. 2, no. 3, pp. 175–195, 2010. [4] E. A. Cech, “Culture of disengagement in engineering education?” Science, Technology, & Human Values, vol. 39, no. 1, pp. 42–72, 2014. [5] B. A. Danielak, A. Gupta, and A. Elby, “Marginalized identities of sense-makers: Reframing engineering student retention: marginalized identities of sense-makers,” Journal of Engineering Education, vol. 103, no. 1, pp. 8–44, 2014. [6] C. E. Foor, S. E. Walden, and D. A. Trytten, ““I wish that iI belonged more in this whole engineering group:” achieving individual diversity,” Journal of Engineering Education, vol. 96, no. 2, pp. 103–115, 2007. [7] S. Secules, A. Gupta, A. Elby, and E. Tanu, “Supporting the narrative agency of a marginalized
room vs not succeeding (Figure 2). Students who successfully escaped were morelikely to rate their teamwork and communication as excellent or good vs students that did notescape. Figure 2:Student responses to the questions "How would you rate the effectiveness of your group's teamwork?" (A), "How would you rate the effectiveness of your group's communication during the escape room?" (B). It is unclear, whether successful students were more likely to have good teamwork andcommunication or whether the students that were unsuccessful rated themselves poorly becauseof the failed attempt in the escape room. Questions about their anticipated teamwork andcommunication before realizing the result of the escape room could
studentsreceived a larger grade benefit than higher performing students (Figure 2). In some cases, higherperforming students saw a worsening on their overall grade due to these group-graded events.Courses where team-based graded events represented a larger fraction of the total grade (>25%)saw a significant impact on final course grades, in some cases >5%.Figure 1. Histograms of a 5th term environmental engineering course (a, b) and a 7th term environmental engineeringcapstone course (c, d). Separate final grades were calculated for only individual-graded events (a, c) and all-gradedevents (b, d). Width of bins are based on letter grade ranges.Figure 2. Difference between overall final grade (both individual and team-based graded events) and
preparestudents to (a) work with others, (b) find collaborative solutions, (c) discuss open-endedproblems, or (d) have patience with exploring fuzzy concepts [3]. Thus many first-year courseshave been restructured to focus less on the “nuts-and-bolts” of engineering and more ondeveloping skills for academic success, instilling a sense of community, and generatingenthusiasm for engineering [4]. Under the assumption that “contact is more important thancontent,” the highest-level goals are to create a supportive academic environment, to motivatestudents, and to provide them with information on how to be successful in their major. Emphasisis placed on increasing students’ willingness to study in groups, minimizing the stigma of askingothers for help, and
5 shows a histogram of the Objective Performance values and aplot of STEM SC and Objective Performance. The p-value for the Regression Analysis ofstudents’ STEM SC and Objective Performance is p=0.001, so there is sufficient evidence at theα=0.05 level to conclude that STEM SC can predict student performance. The left end of the x-axis indicates students who identified more closely with STEM and the right are those whoidentified more with non-STEM subjects. Students who associated themselves more closely withSTEM subjects had quantitatively better performing designs. Figure 5. (a) the distribution of Objective Performance values and (b) a plot of Design Performance v STEM SC, showing the regression line of the data
. Turner, P. Hancock, B. Gordon, T. Carroll, and K. Stenger, “Scaffolding social justice in the engineering classroom: Constructing a more restorative, inclusive, engineering practice,” presented at the 2022 American Society of Engineering Education Annual Conference & Exposition, Minneapolis, MN, 2022.[2] D. M. A. Karwat, Engineering for the People: Putting Peace, Social Justice, and Environmental Protection at the Heart of All Engineering. National Academies Press (US), 2019. Accessed: Jan. 23, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK538716/[3] J. C. Garibay, “Beyond traditional measures of STEM success: Long-term predictors of social agency and conducting research for social change,” Res
importance, why it matters andhow it can be improved may be more challenging to answer.References[1] A. Kaswan, “Distributive Environmental Justice,” in Eds. B. Coolsaet, Environmental Justice – Key Issues, New York, NY: Routledge, 2021.[2] B. Coolsaet and P.Y. Néon, “Recognition and Environmental Justice,” in Eds. B. Coolsaet, Environmental Justice – Key Issues, New York, NY: Routledge, 2021.[3] A. McHarg, “Energy Justice: Understanding the ‘Ethical Turn’ in Energy Law and Policy,” in Energy Justice and Energy Law, Oxford: Oxford University Press, 2020.[4] R. Day, “Energy Justice,” in Eds. B. Coolsaet, Environmental Justice – Key Issues, Routledge, 2021.[5] J. Dugan, D. Byles, and S. Mohagheghi, “Social Vulnerability to Long
, 0) = 0, and linearize the dynamics around each equilibrium to write the system dynamics inthe linear state-space form of x˙ = Ax + Bu, A ∈ R4×4 , B ∈ R4×2 (3)The stability properties of equilibrium points are analyzed by investigating the eigenvalues of thelinearized state matrix A, gaining a comprehensive understanding of the robot’s behavior andcontrol.Having the linearized system around the upward equilibrium, the students then investigate thecontrollability of the system and design a state-feedback controller for the robot using the eigenvalueassignment method [19] by deriving a control law in the form of u = −Kx, K ∈ R2×4
portions of the EMG controller at the end of the course. Second, instead of stoppingat assigning, grading, and reflecting on homework assignments at the end of each module,students are additionally tasked with developing elementary design solutions for the portions ofthe EMG controller corresponding to the module. The PBL exercises are conducted as ungradedexercises. For simpler problems, for example, selecting the sampling frequency for digitization ofEMG signals, a small group-discussion was held, and the instructor invited several groups toshare their solutions with the class. For more complex problems such as the paper design of theEMG controller, a group worksheet (see Appendix B) was provided for designing subsystems ofthe circuit. After the
. Carroll, C. J. Finelli, and S. L. DesJardins, “Academic success of college students with ADHD: the first year of college,” Network for Engineering & …, 2022.[6] A. Cuellar, B. Webster, S. Solanki, C. Spence, and M. Tsugawa, “Examination of Ableist Educational Systems and Structures that Limit Access to Engineering Education through Narratives,” in 2022 ASEE Annual Conference & Exposition, 2022.[7] M. L. Sánchez-Peña, N. Ramirez, X. (rose) Xu, and D. B. Samuel, “Work in progress: Measuring stigma of mental health conditions and its impact in help-seeking behaviors among engineering students.pdf,” in 2021 ASEE Virtual Conference Content Access, 2021.[8] M. Chrysochoou et al., “Redesigning engineering education for
alternative design ideas as shown in Figure 4a andb. According to the team, they saw “merit in both designs and decided to move forward with CADdesigns for both. However, problems risen when attempting to model Design 1 led them to selectDesign 2, which had significantly fewer problems in creating a functional SolidWorks model. Themain criteria shaping their decision process were: ease of design given the time constraints andneed for parts outside of what was designed. Design 1 would require a spring to be bought, whichthey would have to calculate its specifications while Design 2 only required a handful of pins,which were made by the team for the prototype.” Figure 4a. Alternative Design 1 b. Alternative Design 2Figure 5a and b
8 or 7 1[1] B. Moulding et al., Science and Engineering for grades 6-12 : investigation and design at the center, 2019.[2] National Academy of Engineering. Committee on Standards for K-12 Engineering Education., Standards for K-12 engineering education? NationalAcademies Press, 2010.[3] S. Järvelä and K. A. Renninger, “Designing for learning: Interest, motivation, and engagement,” in The Cambridge Handbook of the Learning Sciences,Second Edition, Cambridge University Press, 2014, pp. 668–685. doi: 10.1017/CBO9781139519526.040.[4] E. A. Patall, H. Cooper, and S. R. Wynn, “The Effectiveness and Relative Importance of Choice in the Classroom,” J Educ Psychol, vol. 102, no. 4, pp
Teaching Module to Improve Student Understanding of Stakeholder Engagement Processes Within Engineering Systems Design. 57–67. https://doi.org/10.1007/978-3-319-32933-8_6Friedman, B., & Hendry, D. G. (2019). Value Sensitive Design: Shaping Technology with Moral Imagination. MIT Press. https://books.google.com/books?hl=en&lr=&id=8ZiWDwAAQBAJ&oi=fnd&pg=PR13&d q=value+sensitive+design+moral+imagination&ots=vchlHBMvLP&sig=FHupw7lAlTzwR _2hSj601EwARU8#v=onepage&q=value sensitive design moral imagination&f=falseFriedman, B., & Hendry, D. G. (2012). The Envisioning Cards: A Toolkit for Catalyzing Humanistic and Technical Imaginations. SIGCHI Conference on Human Factors in Computing
review of background information gathering. Data sources mayinclude previous site investigations, local experience, and/or an exploration of geologic and soilmaps like those provided by the NRCS Web Soil Survey. An example of a NRCS Web SoilSurvey is shown in Figure 2.a. (a) (b)Figure 2. Background research example: a) from NRCS Web Soil Survey and b) on the model.The students perform a background review of their site, by observing the layers of soil visiblethrough the sides of the container. For a senior-level course, each color of PlayDoh may be givenan analogous soil type to create meaningful connections to the real site they are investigating.Students are asked to describe what
academically thriving students for mentoring activities. b. Mentees participate in weekly mentoring sessions and monthly workshops to learn how to navigate the academic system and manage their academic responsibilities and expectations. 2) Will the development and use of integrative and engaging modules that are high-impact practices for introductory STEM courses decrease the persistence rate in the college of engineering? a. Supplementary modules are being developed for Calculus, Physics, and Chemistry. b. Students will use supporting STEM modules to augment course lectures and prepare for quizzes and exams.Recruitment of Mentees and Mentors and ActivitiesFive mentors in
in flipped classroom methods, the team includes a third-personeducational researcher (Andrea Medina) focusing on high-impact classroom practices. There arethree instructors in the study: Instructor A, Instructor B and Instructor C. Instructor A is the leadinstructional designer and learned FC and active learning from the Transforming STEMTeaching Faculty Learning Program (FLP) hosted virtually by the University of California,Berkley. Instructor A has publications in iterations of the flipped classroom model [20], [21].Instructor C received a grant on diversity-centric learning and project-based learning. InstructorA and C taught years of courses in the flipped classroom modality before the study. Instructor Bhas less training than Instructor
, more than 90% considered the cost and financial aid options to be the major factors forpursuing community college before university. Figures 2(a) and (b) display the word cloud gen-erated respectively from the two open-ended questions of the survey where we asked them to (1)provide reasons that helped them in deciding between community college and 4-year university,and (2) the most important information affecting their transfer decision. The first-word cloud indi-cates that the cost is the major factor in choosing community college, and the second word cloudshows that the availability of scholarships, affordability, and the proximity of the institution to theirhome played a crucial role.Some students mentioned that after high school when they
model for “studying diverse transferstudents and organizational contexts.” In addition to the individual elements identified here,several articles also acknowledge the organizational and institutional factor aspects of transferstudent capital [21], [24]–[26]. Primary factors and constructs that comprise transfer student capital were first proposedby Laanan and are consistently identified throughout literature. The original four factorsincluded: (a) student background and motivations for transfer, (b) community collegeexperiences which included social campus activities and course learning, (c) transfer capitalwhich includes perceptions of the transfer process advising, learning, and study skills, and (d)four-year university experiences
member in the Department of Computer Science. Her professional experience also includes Winthrop University, The Aerospace Corporation, and IBM. She is a graduate of Johnson C. Smith University (B.S., ’00) and North Carolina State University (M.S., ’02; Ph.D., ’05), becoming the first Black woman to earn a Ph.D. in computer science at the university and 2019 Computer Science Hall of Fame Inductee.Shaundra Bryant Daily, Duke University Shaundra B. Daily is a professor of practice in Electrical and Computer Engineering & Computer Sci- ence at Duke University and Levitan Faculty Fellow, Special Assistant to the Vice Provosts. Prior to joining Duke, she was an associate professor with tenure at the University of Florida
under grants EEC#1929484 and #1929478. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author and do not necessarily reflect the views of theNational Science Foundation.References[1] A. Danowitz and K. Beddoes, “Effects of COVID-19 on Stress and Mental Health of Community College Pre-Engineering Students,” in Frontiers in Education Annual Conference, Uppsala, Sweden, Oct. 2022.[2] A. Danowitz and K. Beddoes, “How the COVID-19 pandemic reshaped demographic variation in mental health among diverse engineering student populations,” Australasian Journal of Engineering Education, vol. 27, no. 2, pp. 67–76, Jul. 2022, doi: 10.1080/22054952.2023.2184912.[3] J. K. Hyun, B. C. Quinn, T
has not been rolled out to the students yet and is planned to beoffered starting in Fall 2023, resulting in zero activity competition for the badge. Whencomparing the grouping of activity completion rates by the graduation date, we find that theengagement across sophomore, junior, and senior students is approximately the same. Cumulative recruitment rate with time a) 160 b) 140 120 100 80 60 40 20 0 Sep-21 Oct-21 Nov-21
CiteScore were extracted and reformatted. In the reformatted tabular structure as inTable 1 of Appendix B, column headings were thousands of topics as predictors and CiteScore;each row (also called observation) represented a publication record. The value of each topic waseither 1 or 0, indicating whether each publication contains a certain topic or not. Linearregression was employed to predict CiteScore using topics as predictors. The threshold of theoccurrence of each topic was set to 0.1% of the total number of publications, resulting in 538unique topics. The selection of threshold values has trade-offs. If the threshold value is too small,overfitting in linear regression would occur because there would be a large number of topics aspredictors
students in the advanced level course (structural steel design) mentioned materialuse and design associating sustainability to the topics discussed in their course. Students alsodemonstrated this knowledge through their assignments which supports the findings of Bielefeldt(2011) indicating that emphasizing sustainability concepts early can impact their understandingof its importance in civil engineering. (a) (b) Figure 2: Word cloud of responses from (a) Introduction to Civil Engineering (CVET 180) students, (b) Word cloud of responses from Structural Steel Design (CVET 431) studentsUnderstanding of sustainability-related concepts: Students were asked to indicate how
effectiveness which was about the sense of presence(Fig. 4a). This was expected as a majority of the participants experienced the lessons in a non-immersive (computer display) environment due to Covid-19 protocols. The lowest average in theimpact dimension was for Q3 for the students experiencing the math lessons. This could beattributed to the fact that it pertained to interest in the subject and since the majority of the mathstudents were in pre-calculus algebra and pre-calculus trigonometry, such a response is typical. (a) (b) Figure 4a, 4b. Responses of all studentsThe overall percentage averages of all majors for all dimensions (usability, engagement,effectiveness, and impact) were about 60
Academy, Department of the Army,DoD, or U.S. Government. Reference to any commercial product, process, or service by tradename, trademark, manufacturer, or otherwise neither constitutes nor implies endorsement,recommendation, or favor.References[1] B. Esmaeili, P. J. Parker, S. D. Hart and B. K. Mayer, "Inclusion of an Introduction to Infrastructure Course in a Civil and Environmental Engineering Curriculum," Journal of Professional Issues in Engineering Education and Practice, vol. 143, no. 2, 2017.[2] D. P. Billington, "Engineering in the Modern World: A Freshman Course in Engineering," in Frontiers in Engineering Conference, 1993.[3] S. D. Hart, J. L. Klosky, J. P. Hanus, K. F. Meyer and J. A. Toth, "An Introduction to
self-efficacy is understood to be driving self-perceptions and eventually performance in those tasks. For instance, self-concept in calculus (i.e., a domain) can be expressed as “I am able to understand and follow along the calculus classes”, and self-efficacy in calculus (i.e., task performance) can be expressed by “I am confident I can score at least a B in the upcoming test”.The above definitions for both constructs are adapted from previous research and validating orverifying them is not within the scope of this project. This study agrees with previous findings[7], [44], [45], [46], that state self-concept is a prime predictor for favorable academic outcomesand well-being as a student. Self-efficacy, although crucial for an individual’s