point), Interactive lecture plustraditional lab (2 points), and Interactive lecture plus project-based lab (3 points). “Traditionallecture” was defined as chalkboard or whiteboard style presentation; “traditional lab” wasdefined as guided activities; “interactive lecture” was defined as active learning or problem-based instructional approach; and “project-based lab” was defined as open-ended type ofactivities or projects. The active learning scores for the five courses were averaged to obtain theaverage active learning score for each institution. Fig. 1 (a) shows the average active learningscores broken down by Basic Carnegie Classification and Fig. 1 (b) shows the average activelearning scores with respect to class size, where small is 0-25
Otto cycle and 13. Air Conditioning Processes Diesel cycles b) Analyze the performance of a simple Brayton cycle and one with regeneration. c) Analyze the performance of a simple Rankine cycle and one with reheating and regeneration. d) Analyze the performance of a simple vapor compression cycle. • Analyze the thermodynamic performance of non-reacting gas mixtures. This involves the ability to
theirprofessional toolset, refactoring is taught only late in the traditional computing curriculum.A valuable outcome of our study was an educational intervention that really pushes the bound-aries of what is possible to teach to novice programmers, those who have never had any priorprogramming experience. The unique aspect of our study was teaching the very fundamentalsof programming simultaneously with the principles and mechanics of refactoring and automatedrefactoring support required to remove code duplication. In particular, the study participants wentthrough a learning experience, guided by an online interactive tutorial that taught them E XTRACTC USTOM B LOCK1 , the refactoring transformation that replaces duplicate code snippets with calls toa
. Figure 5: System diagram for remote vacuum cleanerThe system has three main components: a mobile platform as the remote testbed system, alocal server is the gateway between the testbed and remote clients and the remote client. Themobile platform consists of a drive system, sensors for navigation, an embedded processor(Arduino board) for local control and data management, an XBee for wireless communicationwith the local server, and an IP camera for real time video. The IP camera has its owncommunication route via a WiFi channel. The video is then embedded within the GUI foruser monitoring. Images of completed mobile platform are shown in Figure 6. (b) Close up view of electronics. (a
process as attending class, taking exams, or reading textbooks.However, the formal exercise of assigning grades only started in the late 18th century.Considering the extensive history of higher education, it is remarkable that the formal markers oflearning assessment have only played their role for a comparatively short period of time. Durm(1993) explains that the first college grades were not of the letter (i.e., A, B, C, D, F) variety.Instead, schools typically used descriptive labels such as Yale College’s optimi, second optimi,inferiores, and pejores system from 1785. Durm attributes the first letter grade system, asroutinely employed today, to Mount Holyoke College in 1897 where an A (95-100), B (85-94), C(76-84), D (75), and E (below 75
. Osmotic dehydration is considereda simple yet effective preservation technique for increasing shelf life by removing water whilepreserving the sensory and nutritional characteristics of fruits and vegetables. It is often appliedas a pre-drying step prior to a conventional hot air-drying process to reduce the moisture to alevel needed for long-term storage. In this lab module, your team must develop an osmoticdehydration process to achieve dried pineapple with aw < 0.7 within 12 hours of oven drying at50°C.Final report: Based on your measurements and data analysis, determine and discuss thefollowing in your final report:(a) The amount of fresh pineapple, sucrose, and water needed to produce 1 ton of osmo-hotair-dried pineapple wedges(b
technology use does not detract or distract from the collaborative learning atmosphere[18].Results and DiscussionsThe instructors designed and administered a Google survey which was responded by all of theparticipating students. Prior to this COIL, each of the students had been involved in some formof collaborative learning but this was the first time they participated in COIL. The questionscentered around three core areas: a. Perception of the students on the effectiveness of COIL in the acquisition of employable skills b. Specific employable skills gained from the COIL c. Difficulties faced and how they were addressed during the COIL d. Intercultural competency skills students benefited from through the COILThe first and third
Course Truck (1/16th scale) was used in this build 1. A Raspberry Pi 3B+ 2. A PCA9685 PWM controller. 3. A microSD card, at least 8GB in capacity. 4. SanDisk Extreme 32GB microSDHC card 5. An external battery to power Raspberry Pi. 6. A Pi Camera with ribbon cable. 7. An external battery to power Raspberry Pi. a. Mobile device power banks typically come with a USB A to Micro USB cable, which will fit the micro USB port on the Raspberry Pi. b. An Anker Astro E1 power bank was used in this build. 8. Dupont female to female jumper cables. a. This is to connect the Pi to PWM controller board. 9. A Pi Camera with ribbon cable. a. A fisheye lens is recommended, for a wider
mechanicalengineers. Future research will expand this to other engineering disciplines.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.EEC 1751369. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] J. F. Hair, W. C. Black, B. J. Babin, R. E. Anderson, and R. L. Tatham, Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall, 2006.[2] Z. S. Roth, H. Zhuang, V. Ungvichian, and A. Zilouchian, "Integrating Design into the Entire Electrical Engineering Four Year Experience."[3] B. I. Hyman, "From capstone to cornerstone
alignment with the screencast topics; this isreversed for negative polarity prompts.)Table 4. Survey prompts: APSC 100 survey prompts used to assess screencast impact. Screencasts Prompt Polarity Prompt text assessed Being able to complete an activity easily and without errors is a sign you A + 3,4,5,8,9 are NOT learning from that activity. B + 1 People have the ability to change how intelligent they are. It is better to go to bed on time the night before an exam rather than lose C + 6
, Fundamentals of Electric Circuits, 4th ed. New York: McGraw-Hill, 2008.[5] R. C. Dorf and J. A. Svoboda, Introduction to Electric Circuits, 9th ed. Hoboken, NJ: Wiley, 2013.[6] F. T. Ulaby and M. M. Maharbiz, Circuits: Natl. Technol. Science Press, 2013.[7] D. A. Bell, Fundamentals of Electric Circuits, 7th ed. Oxford: Oxford University Press, 2009.[8] A. R. Hambley, Electrical Engineering Principles and Applications, 6th ed. Upper Saddle River, NJ: Pearson, 2014.[9] A. M. Davis, Linear Circuit Analysis. Boston: PWS Publishing Co., 1998.[10] A. B. Carlson, Circuits. Pacific Grove, CA: Brooks/Cole, 2000.[11] C.-W. Ho, A. E. Ruehli, and P. A. Brennan, “The modified nodal approach to network analysis
university. Thestatements about their relationship to technology were a part of an electronic questionnaireabout the beginning of the engineering studies, presented to the group at the end of the firstsemester in autumn 2017. The second group comprised upper secondary school students whoattended a university course in Basic Electronics in three consecutive years from 2017 to2019 (Group B, N=101). These students were motivated to study this technology-relatedtopic but did not necessarily intend to pursue a career in engineering. The course wasvoluntary, and the participants were awarded both university and upper secondary schoolcredits for the completion of the course. The questions were a part of the feedbackquestionnaire of the course. In the first
to have a 20 second timeout limit. (a) (b)(c) Fig. 1 Example platform interfaces of a 2:1 mux design (a) source debugging (b) simulation (c) hardware verification2.2 Digital I and Digital I LabThis freshman or sophomore courses teach the fundamental concepts of digital logic circuits,including combinational and sequential logic. The accompanying lab requires students to use 74series IC chips and breadboard prototyping.. (a) (b
7.961 Step 2: Final Regression with only task and process conflict Variable B SE B β Intercept 5.254* 0.297 _ Task Conflict -0.376* 0.173 -0.244 Process Conflict -0.458* 0.174 -0.327 2 R 0.235 2 F for change in R 11.988Note: B is unstandardized beta, SE B is the standard error for the unstandardized beta, and β isthe standardized beta. *p < .05. This data comes from a total of 81 observations.Discussion The most immediate
help students to bettercomprehend engineering problems. To evaluate this hypothesis, a few visualization methodswere implemented in the flipped classroom including:a) Instructor built simple foam models to show design details and potential loadings and stresses.Figure 1 shows sample foam models used in Mechanics of Materials course. The instructordisplays and interacts with the foam models during lectures to visually show deformation andfailure modes. More than 80% of students reflected in SET data that these foam models veryhelpful in their learning. However, they suggested that letting them to interact with the modelswill be more beneficial. (a) (b) Figure 1. Foam models to
populations; (a) students whomatriculate in an Engineering field and persist within their field, (b) students who start in a non-engineering field and switch and graduate from an engineering major, and (c) students who startin an engineering major and opt out engineering and graduate from a non-engineering major. Inthis work-in-progress we will focus on main statistical analysis of these three groups.CategorizationThe dataset was categorized into groups of majors to allow comparison among different fields ofstudies. The breakdown of each groups of majors is shown in Table 1. The Major groupings usedin this study is based on National Science Foundation definitions [16].Term DefinitionArts & History, Communications, Journalism
and Scientists, New York: CRC Press,2012.[11] J. Schmidhuber, “Deep Learning in Neural Networks: An Overview,” Neural Networks vol.61, pp. 85-117, 2015.[12] A. Almasri, A. Ahmed, N. Al-Masri, Y. A. Sultan, A. Y. Mahmoud, M. I. Zaqout, A. N.Akkila and S. S. Abu-Naser, “Intelligent Tutoring Systems Survey for the Period 2000-2018”,IJAER vol 3(5), pp 21-37, 2019.[13] B. P. Woolf, Building Intelligent Interactive Tutors Student Centered Strategies forRevolutionizing E-Learning, New York: Morgan Kaufman, 2009.[14] Y. A. Cengel, M. A. Boles and M. Kanoglu, Thermodynamics An Engineering Approach,New York: McGraw-Hill, 2019.[15] M. J. Moran, H. N. Shapiro, D. D. Boettner and M. B. Bailey, Fundamentals of EngineeringThermodynamics, New York: Wiley
. Furthermore, they will have a solid understanding of how the pieces of thetheory fit together and how the tools of mathematics support the problem-solving process. Themastery objectives for dynamics are given in Table 1. Table 1. Dynamics Mastery Objectives. This table give a brief description of the 16 mastery objectives for Dynamics. The objectives are the common strands that form the problem-solving approach for all dynamics problems. A.1. Geometry and problem setup F.1. Vector algebra and calculus A.2. Initial conditions F.2. Integrate over spatial domain A.3. Modeling and constraints G. Conservation of momentum B. Describe
-based activities and virtual laboratories, all of which have been shown to improvestudent learning. This wealth of educational materials stored on the CW has resulted in broadadoption by the chemical engineering community, with over 1200 faculty and 30,000 studentusers to date. We now seek to expand this tool for use by mechanics instructors and to study itsadoption by this community.Project ObjectivesThe objectives of our IUSE project are to:1. Extend the use of the Concept Warehouse (CW) to Mechanical Engineering (ME) and grow by 50,000 student users from diverse populations. To achieve this objective, we will: a. Develop content [at least 300 new ConcepTests] for Statics and Dynamics. b. Continue development of ME research-based
years in which motivation and identity are so important to persistence. Our study addressesthis question by measuring motivational constructs in a cohort of mechanical engineering studentsmultiple times across several different course contexts.MethodsData was collected from students in three concurrent Mechanical Engineering courses during theFall 2019 semester (“Course A”: Introductory Fluid Mechanics, “Course B”: Mechanics ofMaterials, and “Course C”: Mechatronics). These three courses have been targeted by ourlearning initiative because they reach every student enrolled in the mechanical engineeringprogram (courses A and B are required while course C is taken by almost all students to satisfy amajor requirement), and because we have
learning in a lecture-based engineering class,” in Proceedings of the 32nd Annual Frontiers in Education Conference, 2002, vol. 1, pp. T2A-9-T2A-15 vol. 1.[11] D. R. Brodeur, P. W. Young, and K. B. Blair, “Problem-based learning in aerospace engineering education,” in Proceedings of the 2002 American Society for Engineering Education Annual Conference and Exposition, 2002, pp. 16–19.[12] D. Broman, K. Sandahl, and M. Abu Baker, “The Company Approach to Software Engineering Project Courses,” Educ. IEEE Trans., vol. 55, no. 4, pp. 445–452, 2012.[13] S. Jayaram, L. Boyer, J. George, K. Ravindra, and K. Mitchell, “Project-based introduction to aerospace engineering course: A model rocket,” Acta Astronaut., vol. 66
. The head of the capstone design course together with the teachingaffair office and instructors continuously improve the syllabus. The 2020 spring syllabusconsists of a detailed description of how to conduct the outcome-based design of the course. This reform of capstone design course is featured by the following characteristics: a)Completing practical design task with engineering background through teamwork torealize the transformation of teaching method from closed to open, from knowledge toability; b) Introducing enterprise into capstone design and training students to view andsolve problems from multiple perspectives through solving practical engineering problemssponsored by industry; c) Establishing a multi-channel industry-university
” technique, where the higher of the two attempt scores,by question, was kept and summed together for a final “superscore.” An example of how the finalscores are calculated is shown in Table 1 below, where a “1” represents a conceptually correctsolution to a problem and a “0” represents a conceptually incorrect solution. Table 1: Mean exam scores. Question Exam A Exam B Superscore 1 1 1 1 2 1 0 1 3 0 1 1 4 0 0 0 5 1 0 1
were assigned equal weights for scoring. The participants weregiven at most 40 minutes to respond to the test through the assistance of one of the researchers.The survey was held online throughout the Fall 2019 semester.The concept inventory aims at inquiring the respondents about the following basic concepts: 1. What do they understand about circuit elements that store energy? 2. How do they differentiate: a. A capacitor and an inductor? b. Energy storage and energy source? c. Energy storage and load? 3. How do they analyze: a. A first-order circuit? b. A second-order circuit? c. A higher-order circuit where the source is an AC signal? d. Circuit transformation where the
met. Each interview lastedabout 15 to 30 minutes. Once the interviews were transcribed, each question response wasanalyzed. Thematic coding was performed to determine patterns between the instructors and toestablish any themes of the instructor’s experiences. The main focus of this study was tounderstand how VOH affected the course design and student learning. Institutional ReviewBoard (IRB) approval was issued prior to the beginning of the study.A recording of a session in one of the classes can be viewed here:https://boisestate.techsmithrelay.com/kJY4ResultsProfessor A taught Circuit Analysis and Design in Electrical and Computer Engineering,professor B taught Heat Transfer in Mechanical Engineering, and professor C taught twosections of
engineers,” Proc. IEEE, vol. 88, no. 8, pp. 1367–1370, Aug. 2000.[3] P. K. Imbrie, S. J. Mailer, and J. C. Immekus, “Assessing team effectiveness,” in ASEE Annual Conference and Exposition, Conference Proceedings, 2005, pp. 831–837.[4] H. J. Passow, “Which ABET Competencies Do Engineering Graduates Find Most Important in their Work?,” J. Eng. Educ., vol. 101, no. 1, pp. 95–118, Jan. 2012.[5] ABET, “Engineering Programs,” 2019.[6] R. Guimerà, B. Uzzi, J. Spiro, and L. A. N. Amaral, “Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance,” Science (80-. )., vol. 308, no. 5722, pp. 697 LP – 702, Apr. 2005.[7] S. Wuchty, B. F. Jones, and B. Uzzi, “The Increasing Dominance of
. Forthe brevity of this paper, a longer description of each model, its final projects, and incentives areprovided in Appendix B. A summary of the major differences between the models is provided inTable 2 with a more detailed explanation of the rationale between iterations provided inAppendix B. While there are differences across the cohorts, all cohorts shared four majorcomponents: (1) college credit, (2) AP calculus support, (3) college advice, and (4) industrypanelists.Table 1. Demographic Characteristics of Students Participating in the Project by Cohort Cohort 1 Cohort 2 Cohort 3 2013-2014 2014-2015 2017-2018Racial/Ethnic Category
littleattention to connecting the concept to reality. The paper focuses on two sets of examples: 1. Examples that are unrelated to time. These include (a) discontinuity in space, forexample water levels at different sides of the locks in Panama Canal, sharp change in elevationof sidewalks (known as curbs), length of unused paper towel or toilet paper, change in brightnesslevel from light to shadow and between intensity level of pixels in a digital image, (b) numericaldisplays, such as an abrupt change in the numerical display of an elevator’s floor, change indigital display of radio frequencies, (c) switch-based devices such as light switches, (d) audiofrequencies, such as audio frequencies of piano keys, and (e) cartoon-based and non
diagram Pie chart * examples: breakfast, travel, class, etc.Figure 6. Bloom’s question category 6A (create a diagram based on examples using your data) and student deliverable for 8 amclass.A lecture on the theme of communication included a discussion of the history of genetics. GregorMendel’s study of pea plants showed that one in four pea plants had purebred recessive alleles,two out of four were hybrid and one out of four were purebred dominant. Students were asked tocomplete a Punnett square and answer a question based on the results (Figure 7). Please fill in the Punnett square (used to make genetic predictions) below and answer Q1: Q1: If B is for brown
-2f6bbca45f14.html[10] J. Bossart and B. Neelam, “Women in Engineering: Insight into Why Some EngineeringDepartments Have More Success in Recruiting and Graduating Women.” American Journal ofEngineering Education, vol. 8, no. 2, Dec. 2017.[11] A. Siani and C. Dacin. “An Evaluation of Gender Bias and Pupils’ Attitude towards STEMDisciplines in the Transition between Compulsory and Voluntary Schooling.” New Directions inthe Teaching of Physical Sciences, vol. 13, no. 1, 2018.[12] E. Lee. “Effects of South Korean High School Students’ Motivation to Learn Science andTechnology on Their Concern Related to Engineering.” Educational Sciences: Theory andPractice, vol. 17, no. 2, 2017.[13] R. Christensen, G. Knezek, and T. Tyler-Wood. “Gender Differences in