trend of usage with noon being thebusiest time. In fall 2018, the hours of operation were from 11:00 AM until 10:00 PM. Thesehours were changed to 8:00 AM to 7:00 PM based on how few visitors came to the makerspaceat night. In fall 2019, the hours were changed again to reflect the current hours of operationwhich are 10:00 AM to 5:30 PM. Figure 6 shows both fall 2018 and spring 2018 hours ofoperation and the number of visitors during each open hour. Number of Visitors During Open Hours Fall 2018 Spring 2019 350 300 Number of Visitors 250 200 150
. This exposed our students tocollaborators among different fields, with their own terminology, goals, work methods andpractical approaches. Our paper reports on the initial experiment during the Fall 2019 term,involving two sections of an Artificial Intelligence class and one section of a Deep Learningclass. We are planning to continue this collaboration in the future.Keywords: Collaborative Learning, Interdisciplinary, Inter-Class teamwork 1. IntroductionStudents at California Polytechnic State University, San Luis Obispo (Cal Poly) are exposed topractical, hands-on educational activities throughout their course of studies, reflected by theuniversity’s “Learn by Doing” motto. In the Computer Science, Software Engineering andComputer
electrical circuit with light and multimeter.The Sketchtivity and Mechanix tools continue to be adjusted by the Texas A&M UniversityComputer Science Sketch Recognition Lab (TAMU SRL) with the fine-tuning driven by bothprogrammatic efficiencies and instructor feedback. Students adapt well to the guidance providedin Sketchtivity and are drawn to the game. Mechanix is a greater challenge such that, whendeploying all three tools concurrently, students tend to abandon their work in Mechanix as toodifficult. Pre-teaching the truss analysis process, couched in curriculum, is critical to createfoundational understanding to best interpret the guidance and hints provided by the tool.At the end of the course I have students submit a reflection regarding
question.The second question focuses on different types of data. The varied backgrounds and experiencesof the students mean their disciplinary perspectives are different and will be reflected in the typesof data they will work with in their research practices [4]. Students have a general understandingof what data is but may not be aware of the different types of data sources (i.e., primary,secondary and tertiary). The worksheet provides a short description of the types of data sourcesto facilitate recall of the in-class lectures and discussions on the topic. Students are asked toidentify a minimum of three data sources, and a variety of sources (where applicable).The third question addresses the challenge of identifying appropriate data sources to
students to better understand the damping and its associated properties through the development and implementation of new instructional tools, a course assessment questionnaire was conducted in the Fall 2018 class to reflect the impact of the presented curriculum development activities on student learning. In order to determine the effects of the two developed vibration systems on this course, a course assessment questionnaire designed by the author [10, 11] was used to collect student perceptions and the results were compared with the student feedback collected in the Fall 2017 class [7, 8]. 4.1 Course Goals Table 3 shows how students compared their level of knowledge for related topics before and after this
. A few others plan to start graduate school in Fall 2020. Of the 48 who went on topursue graduate degrees in water science and engineering, 34 (71%) were female and 18 (38%)were URM. No statistical differences in the likelihood to attend graduate school were observedbased on gender or race/ethnicity. Our legacy assessment will further characterize the educationand career trajectories of our program alumni, as well as their retrospective reflections regardingthe impact participating in our program had on their education and career choices.Alumni tracking for the three comparison environmental engineering REU Programs found thatover 60% of participants of the Clarkson REU attended graduate or professional school [9],approximately 60% of the CU
participation for women.MethodsThis work presented here is part of a larger mixed-methods study, employing an exploratorysequential study design: first, qualitative data were collected and analyzed, which then informedthe development of a survey to collect quantitative data [5].Qualitative Interview AnalysisAs part of the qualitative study [4], fifteen interviews were conducted with female students,prompting them to reflect on their team project in their first-year engineering course and discusswhat contributed to their satisfaction, or dissatisfaction, with their team experience. Studentswere asked to describe their team project; discuss which tasks they performed in the project andwhether there were any tasks they wished they did more or less of; and
-Fitzpatrick and G. D. Hoople, “Cultivating an Entrepreneurial Mindset: An Interdisciplinary Approach Using Drones,” Advances in Engineering Education, vol. 7, no. 3, 2019. www.advances.asee.org/wp-content/uploads/vol07/issue03/Papers/AEE-25- Hoople.pdf15 G. D. Hoople, A. Choi-Fitzpatrick, and E. Reddy, “Drones for Good: Interdisciplinary Project Based Learning Between Engineering and Peace Studies,” International Journal of Engineering Education, vol. 35, no. 5, pp. 1378-1391, 2019. https://www.ijee.ie/latestissues/Vol35-5/12_ijee3801.pdf16 E. Reddy, G. D. Hoople, and A. Choi-Fitzpatrick, “Interdisciplinarity in Practice: Reflections on Drones as a Classroom Boundary Object,” Journal of Engineering Studies, vol. 11
lower than expected correction rates,indicating the necessity to enhance undergraduate solid mechanics education. Considering overallperformance by category provides additional evidence with regards to the limited understandingamong students on the multi-scale nature of materials and linkages to observed mechanicalbehavior and properties, Figure 5 (f). The collected student data indicates that although most ofthe students were able to identify the meaning of each keyword and categorize them properly inthe “materials processing” category (77% of students correctly categorized the keywordsbelonging to “materials processing” category), the macro-scale mechanics parameter resultsindicate significant misconceptions as reflected by the observation
, the amount of solder used for each connection,neatness and shape and the visual inspection of potential cold solder joints, among otherconsiderations. Although many students had soldered before, the training was an opportunity torefresh and refine these skills. All students who had prior soldering experience indicated theybenefited from the training.Lessons Learned by StudentsAs part of the project experience, one requirement was to talk about and submit a summary oflessons learned after the demonstration session. This gave each person in the class an opportunityto reflect on their experience to critically evaluate what they would be doing differently the nexttime they designed a board. Much of the feedback received indicated that students
testing week.There is a spike in student motivation. Many students share that they enjoy finally being able tobegin building their project. During the Week 7’s construction week, many report struggles,setbacks and trouble with coding, resulting in a decrease in motivation. Week 8 is the lastconstruction and testing week. Some teams report their design starts functioning properly whileothers still struggle to get it to work. Week 9 is the presentation and demo day. Many reflect theyenjoy growing together as a team, have fun building the project and learn a lot. Some complainabout uncooperative team members and challenges of the project. 7 6 Self-Determination Index (SDI
” may be a more effective strategy forultimately attaining a distribution of gender within engineering that reflects the largercommunity.References1. Roy J, ASEE. Engineering by the Numbers [Internet]. 2018. Available from: https://ira.asee.org/wp-content/uploads/2019/07/2018-Engineering-by-Numbers- Engineering-Statistics-UPDATED-15-July-2019.pdf2. Bystydzienski JM, Brown A. “I Just Want to Help People”: Young Women’s Gendered Engagement with Engineering. Fem Form. 2012;24(3):1–21.3. Diekman AB, Clark EK, Johnston AM, Brown ER, Steinberg M. Malleability in communal goals and beliefs influences attraction to stem careers: evidence for a goal congruity perspective. J Pers Soc Psychol. United States; 2011;101(5
overhangs to prevent the direct sunlight, shade the windows, andsupport diffusing the daylight inside the space. Another supporting action ca be using a designedceiling geometry configuration that can help to diffuse daylight instead of the conventional flatceilings.The mixed overhang/light shelf became as one horizontal surface, as shown in Fig.11. Oneachievable method to tackle this issue is to take advantage of a white reflective coating on thetop layer of the light shelf finish material. By implementing this strategy, 50% of the floor areaachieved adequate daylighting, which means an additional 30% of the spaces have sufficientdaylighting. In addition, high efficiency LED lights, are added for the rest of the spaces to evenlydistribute light
EGEE-420 EGEE-445Figure 2. The achievement gap between URM and non-URM students in all ECS disciplines. The performancedemonstrates a perpetuation of the achievement gap in lower-division math and science courses that continued intheir senior years. The net result of this achievement gap is a delayed graduation rate. Figure 3 shows the 4-,5- and 6-year graduation rates for URM and non-URM ECS students at CSUF. It appears thatthere is an upward trend over the years in the graduation rate of both URM and non-URMstudents. However, the graduation rate of URM students still lags the graduation rates of generalstudent peers.Figure 3. The perpetuation of achievement gap reflected in the overall graduation rate of
example, recently RPi 4 isavailable with 4 GB RAM which has facilitated taking on computationally-intensive machine visionand cybersecurity projects. Table I shows the key concepts targeted in each course. As mentioned earlier CSCI 4390 is anexception where students may choose to do an RPi based project, therefore, there are no establishedkey concepts targeted for CSCI 4390. It should be noted that key concepts shown do not reflect allthe topics covered in the course in which an RPi is used. Once RPi is part of a course, it is used bythe student for most of the projects assigned in the course. Therefore, an RPi is used in a targetedcourse for many more topics than shown in the table. TABLE I Key Concepts in Targeted Courses Course
. By the end ofthe semester, 75% of the students reported being satisfied with their assigned teams while 7%were not satisfied (there was decrease in the number of students with neutral opinions).Overall, these results are very encouraging, since it reveals an overall positive perception and itdoes not reflect a drastic change of opinion as the semester progresses. Indeed, based on anecdotalfeedback, instructors have noticed a decrease in the number of interpersonal conflict within thestudent teams compared with previous versions of this course. Unfortunately, the instructors didnot collect any data prior to the use of junto for a more rigorous comparison.Figure 2: Survey results illustrating student’s perception about the team selection and
initiatives to address malleable traits in studentsthat might hinder their academic success.Acknowledgement This material is based upon work supported by the National Science Foundation under GrantNos. DUE-1626287, DUE-1626185, and DUE-1626148.). 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. We would like to thank all thestudents who participated in this study. Without their time spent in thoughtful response, thiswork would not be possible.References1. Gordeeva, T.O. and Osin, E.N. (2011). Optimistic attributional style as a predictor of well- being and performance in different academic settings. Ch. 14
media presence. 3. Develop technological currency in the student body.The first priority was identified as the most important with the other two priorities to be carriedout with an eye toward the first. A couple challenges affect the primary goal. First, unlike mostU.S. research institutions with a seperate college of engineering, CSE grants degrees in thephysical sciences, math, computer science, and engineering. Students in science and math areless encouraged by their course curriculum to seek out the use of design and prototypingresources so those students need additional programming and attention if the Anderson Labs is tomore closely reflect the diversity of the college as a whole. Second, the primary space is locatedin the Mechanical
objective is to make the hook from stainless steel so it does not rust or stain the tools. AVernier Calipers were made available to students to measure tools and hooks dimensions. Theinstructors explained how to read a Caliper.The students should make 3-4 hooks (figure 5) for a separate tool. Each student has to make hisown design, reflecting his creativity and his own imagination. 3D-printing of these hooks is agood exercise to test them on a real pegboard. A more in-depth analysis is performed, such asheat transfer through the hook, and stress analysis (figure 6) to test the strength of the hooks tohold the objects they were designed to support and search the weaknesses of such an object. Inaddition, as part of this work, each student needs to
person holds the idea that they are incapable of achieving success in a math class, they have a “fixed” mindset about math. These students place themselves at risk of failure because they do not work towards growing in their understanding of mathematics [9]. A person’s dislike for math often occur during the beginning stages of school [9]. Moreover, one’s dislike and uncomfortableness towards math may remain with a person for many years and can lead to a lack in self-confidence by hurting one’s rationale and thoughts [4]. Possessing a fixed mindset can hinder one’s potential for math success as this mindset lacks self-reflection and embracing new ways of learning [3]. A person with a fixed
department itself. This growth has been reflected to this graph. To compare the data for thetwo Fall semesters of 2018 and 2019, the numbers of students in Fall 2019 have been almost twotimes bigger than the ones in all three listed courses. Figure 5. Enrolled students who have taken embedded system integration track courses from Fall 2018 to Spring 2020.The total numbers of the listed courses are not small. However, they are divided by the multiplelaboratory sections. In each laboratory section, there are 16 to 20 students or less. The numbersof sections from Fall 2018 to Spring 2020 are shown in Figure 6. As the enrolled students havebeen increased, the numbers of lab sections also have been increased
pre-and post-test surveys as well as program activity attendance, course enrollment, and mentoringteam constellation will be used.EQ3, “To what extent are student and faculty competencies and interdisciplinary andtransdisciplinary skills changing over the course of the training program? Additionally, to whatextent are these changes reflected in longer-term outcomes?,” is an outcome evaluation questionfocusing on competency, technical, and professional skills change over the programimplementation. Data from or about NRT trainees, students attending open activities, andstudents receiving no program exposure (retrospective cohort) data will be compared usinginstitutional research sources, faculty-administered student competency assessments, and
are repeatable at other universities.Limitations of the StudyIn this study, the prior exposure of the participants to sketching and CAD modeling packages isnot explored. In the student population in SJSU, it is typical that around 10% of the students inthe design graphics class possess some extent of CAD training. However, this is not expected tosignificantly bias the results. This factor will be explored in future studies.AcknowledgementsPartial support for the work is provided by the National Science Foundation grant number DUE-1611763. Any opinions, findings, and conclusions or recommendations expressed in this paperare those of the authors and do not necessarily reflect the views of the National ScienceFoundation. The authors would also
content ofthe quest has been mastered, leading to its approval or that the quest has been returned,demonstrating that they have not yet mastered the content. Whether quests are returned orapproved, students receive personalized feedback on their completed work.Figure 1: Screenshot of a quest within the Rezzly platform[17]. Quests within Rezzly are scaffolded based on content area and level of difficulty. Eachquest belongs to a category that reflects the goals of the first year engineering program. Thecategories are summarized in Table 2.Table 2: Quest Categories in the Homework Platform Summarized Category Topic Examples Number
, consistency of contracts and recognizes valuable contributions • Employ an open loop evaluation system that allows ongoing tracking, [12] analysis, communication and synthesis and communication of findings for continuous improvement of the faculty and the institution • Require more equitable scrutiny and evaluation among various faculty [13] groups to communicate the need for quality irrespective of faculty status •Allow time for active learning for adjunct faculty including reflection, [12] writing and self-improvement audits College Communication • Integrate the use of two way communication platforms and powerful [4] technological tools into processes to help build rapport
also required in 2019 for the first time. These required the students to reflect on what theylearned and did the previous week and set goals for the following week. These were added to encourageself-paced learning, effective use of videos, and goal setting. The percentage of course grade comingfrom homework and a semester-long, group project was decreased to allow for the addition of videoquizzes and journal entries to the grading scheme.Population AnalysisThe dataset includes 156 students who completed the course across three years – 2017 and 2018, whichwere taught with a traditional instructional model, and 2019, which was taught using a flipped coursemodel. Student grade in the course, final exam score, cumulative GPA entering the semester
made strong statements such as “AI projects human needs or intentthrough computational reduction to serve human needs” and that AI is, “an automated method tospeed and improve decisions and outcomes to advance benefits to society.” These positivestatements were surprising since the second day of the workshop was dedicated to AI ethics,security and privacy. One possible explanation could be the optimism shared by workshopparticipants pertaining to AI and its potential to have positive impact in STEM and society.Participants’ AI definitions did reflect that although they didn’t have a common definition of AI,they recognized the role of computers and machines in expanding human knowledge andcapabilities. None of the participants parsed AI into
technical communication strategies developed over thecourse of the projects, as students work to develop an interactive means for the general public toexplore and understand their technical research.Discussion & Student FeedbackThis course exposes students to forms of technical communication beyond typical lab reports toresearch proposals, journal articles, and poster presentations that some engineering students maynever be given the opportunity to practice otherwise in their undergraduate experience. Thisexposure opens doors to new possibilities of what engineering work students thought they werecapable of, particularly within the first year of their college experience.Student experiences also reflect the course’s ability to prepare students
conditions in FEA software. Thedifficulties arise in ensuring the implemented loading and support conditions in the FEAsimulation reflect or match actual loading and support conditions of the real product.(3) The meshing and convergence where users need to define the global finite element size andfine mesh element size refinements in stress concentration areas or important areas. This can bedifficult for students to master. A convergence condition approach will be typically satisfied byusing smaller element sizes around stress concentration areas. The smaller element size meansmuch longer simulation time and much larger required internal memory for the computer.(4) Data analysis where users need to properly interpret and to verify the simulation
more severe. Onecurrent type of violation is contract cheating, first coined by Lancaster and Clarke in 2006, whichinvolves paying a third-party to complete an assignment instead of the student enrolled in theclass [4]. Some researchers have even discovered “ghost students,” in which a fee is paid foranother person or company to enroll in an online course for an entire semester on behalf ofsomeone else [5]. Even though contract cheating and ghost-students are extremely severeviolations because of the awareness of the deviousness of the act, the underlying motivations forthese types of violations often reflect the same causes as other forms of academic integrityviolations [4].Students have cited a variety of motivations for engaging in academic