correctly to only 6 of the 20 questions. Statisticallysignificant differences (p < 0.05) were observed between engineering and non-engineeringstudents on Q#1, Q#2, Q#4, Q#6, Q#7, Q#8, Q#10, Q#12, Q#19. Of these questions withstatistically significant differences, a higher percentage of engineering students respondingcorrectly to Q#1, Q#2, Q#4, Q#6 and Q#7. Interestingly, questions Q#2 and Q#6 pertain toambiguous social interactions which were correctly answered by more than 50% of theengineering students while less than 40% non-engineering students answered these questionscorrectly. And, a higher percentage of the non-engineering students responded correctly toquestions Q#8, Q#10, Q#19 of which two questions (Q#8, Q#10) pertain to social
Iowa State UniversityAbstractAs evidenced by students’ inability to explain their solutions, abstract concepts without directphysical representations in engineering are difficult to grasp because they lack direct sensory,physical, or perceptual referents. In this pilot study, we investigate whether visual aids helpstudents better understand abstract concepts and improve their learning outcomes. Specifically,in the context of the (Q, r) model in the inventory control theory, we first develop visual aids forlearning and teaching, i.e., the animation of line plots that show the evolution of key quantities inthe (Q, r) model over time. We then plan to use a paired t-test to see if there is any differencebetween the students’ scores in the pre-test
after the castingsolidified to prevent shrinkage voids in the casting and is based upon Chvorinov’s Rule.Chvorinov’s Rule for solidification is: t = q(V/SA)2 (1)The solidification time constraint becomes: tr ≥ tc (2)which becomes: qr(Vr/SAr)2 ≥ qc(Vc/SAc)2and can be reduced to: (Vr/SAr) ≥ (Vc/SAc) (3)where: tr = solidification time of the riser tc = solidification time of the metal casting qr = qc= solidification constants for the molding material are equal as both the riser and
class that week. These assignments were collected and a subset of the problems were graded for correctness. Homework solutions were provided after homework was collected. Quiz only (Q): Students were encouraged to complete weekly homework assignments similar to those given for assessment H. Homework was not collected, and students were also given solutions at the time the assignments were assigned. Students then completed an in- class quiz the day the homework assignment was “due,” consisting of one problem very similar to one of the homework problems. Quiz and homework (QH): Students completed weekly homework assignments similar to those given in the other two modalities. The assignments were collected
AENG 100 students was to the statement “There was asense of presence (being there) while learning with VR” (Q#7). This response was expected asthe students did not use the headsets for an immersive experience but rather experienced thelessons on a computer monitor due to COVID challenges. The students of AENG 244 rated thestatement “Using VR helped make memorization easier” (Q#10) the lowest (Fig. 8a). Thisresponse indicated that the lesson was correctly designed, that is, not designed for memorizationbut for understanding. For the impact dimension (Fig. 7b), the lowest average of responses by theAENG 100 students was for the statement “Please indicate the extent to which the use of VR fortopics in this class has improved your knowledge of
policy, which is a mapping from states to actions thatmaximizes the expected future reward.We deploy Q-Learning [24], a common reinforcement learning algorithm where the agent keepsstate-action values Q(s,a) and uses these values to choose the best action to take in each state.The Q(s,a) values are updated through a trial-and-error process and the action with the highestQ(s,a) value is considered the best action to take. Often the state space is large and explicitlystoring Q(s,a) values in tabular form is not feasible. Therefore, approximation methods, rangingfrom linear combinations to deep convolutional neural networks have been used to approximateQ(s,a). Since we aim for effective adaptation, we deploy Q-Learning with linear approximationon
atmosphere or medium defining the GDS W , Wnet , WBW , WUBW ,WECW Power generally or generically, “net” Power (i.e., non-boundary power, usually shaft or electrical), the total Boundary Power, Useful Boundary Power, and the Electrochemical Power zk Mole fraction T0, P0, WUBW and k0 WOUT P0 P0 Q IN
: Questions in First and Second Round Interviews Question Question No. Q.1 (Round Tell me about yourself and any important COVID related experiences you had 1 & 2) during the Fall 2020 semester. Q.2 (Round Explain how and why COVID impacted the functioning and behavior of your 1 & 2) STEM students during the Fall 2020 semester. Q.3 (Round Explain how and why COVID impacted the performance of your STEM 1 & 2) students during the Fall 2020 semester. Q.4 (Round Explain how and why you responded to changes in STEM student behaviors 1 & 2) and functioning during the Fall 2020 semester. Q.5 (Round Explain how and why you responded to changes in the performance of your 1 & 2
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dt QS m RS W hRSW hZWV m INZ cPM, INZ tREL, INZ tREL, Z m INF DA MA cPM, OA tREL, OA tREL, Z DA MA (26)In contrast, the corresponding equation from EnergyPlus with the missing moisture-related termemphasized is reproduced next: d tREL, Z m DA MA Z c PM,Z
, torque T0 and P0 WUBW , angular velocity P0 P0 WOUT opposed Q IN Q l ,in TEFF,IN physical boundary WBW Tl ,in Control Surface (CS) m OUT m IN TEFF,OUT
sectionseach semester.B. ReflectionsThree sections in 2017 engaged in weekly structured reflections focused on feedback, and sixsections in 2018 engaged in weekly structured reflections focused on learning strategies [15]. Inboth semesters, students in these sections earned the course’s standard 2% extra credit offered inall sections by completing these reflections. Reflections included a combination of closed- andopen-ended prompts (Table 1). Note that the number of close-ended prompts differed each weekdepending on the number of learning objectives addressed in the given week of instruction(Table 1: Q4- Q(X-1) in 2017 or Q(2)-Q(Y-3) in 2018). Other prompts remained the same eachweek.While the prompts in both years were intended to have students
are valid for the given data set. To ensurenormality, a Q-Q plot was generated for both the differences in pre-test scores and posttestscores.2. Results and Discussion2.1 Confirmation of Normality Figure 1. Q-Q plot of Posttest scores. Figure 2. Q-Q plot of difference in scores results.The two graphs shown in Fig. 1 and Fig. 2 are Q-Q plots that confirm normality. It is clearthese are normal because all data points fall within the normal range, as illustrated by thedata points falling within the boundary shown by the dotted lines. Because the data isconfirmed to be normal, we can run an ANOVA and an f-test on this data set.2.2 Dependent Variable AnalysisBefore examining the results of
), and self-identity (shyness and confidence toengage in class). In addition, foreign students entering a Mechanics of Materials course havepoor foundational knowledge in subjects like Physics and/or Statics and encounter difficultieslearning in a virtual course delivery model (82% asynchronous and 18% live Q&A sessions).The combination of these challenges exacts a tremendous obstacle to student learning, studentretention, and student persistence.The developed instructional approach uses reduced question sets for homework assignments,which aim to improve the lower-level questioning found in Bloom’s Taxonomy and Costa’sLevels of Thinking and reducing the higher-level questioning. This model helps to decrease thecognitive load that is placed
management courses with bonus points for the in-class problem solving relatedto each topic of the course. The survey questions are presented in Figure 2. The first two questionswere asked to understand the students’ perceptions and attitudes about the course content andalignment. The third question introduced the active learning concept and its effect. Q.1. Did tests reflect the material covered in the class? a. Excellent (5) b. Above Average (4) c. Average (3) d. Below Average (2) e. Very Poor (1) Q.2. Is there a good agreement between the course outline and the course content? a. Excellent (5) b. Above Average (4) c. Average (3
) first to ensure a lack of redundant material and offerings.Curriculum development began on a voluntary, self-paced course taught through an LMS.However, it was decided that a faster approach to serving the faculty was through workshops.Data obtained from feedback and participation from the first Q&A sessions run during March of2020 were analyzed. The department website also had a handful of online videos about Zoom,Blackboard (still the LMS at that time), and Google Classroom, along with recordings ofwebinars, short tutorials, and links to other resources from AI and the Blackboard site. Workshoppresenters looked at web analytics to decide what curriculum should be the priority for the site.Continued evaluation of workshops happened through
different values of d into the above equation and reduce them mod 9.5(-2+0) ≡ -10 ≡ 8 mod 95(-2+3) ≡ 5 mod 95(-2+6) ≡ 20 ≡ 2 mod 9Note that by choosing a composite n (in this case n = 9) we were able to create a congruencewith three solutions vice the single (or rather double) root of the real quadratic equation!Constructing congruences to impede the traditional solution techniquesCase 1 – factoring. If we restrict the leading coefficient a to be equal to 1 in the quadraticcongruences that we construct we can make use of the Integral Root Theorem (a special case ofthe Rational Root Theorem) [5] which states that the rational roots p/q of a given polynomial anxn + an-1 xn-1 + …a1x + a0 = 0with leading coefficient
Water G G Supply F G C S Q
division engineering courses in the Electrical andComputer Engineering department at the University of Texas at Austin. In this study wehave utilized quantitative data such as students’ SI/PLUS session attendance, students’pre-semester GPAs, end-of-semester course grades, and the D’s, F’s, W’s and Q droprates (QDFW rates) for attendees and non-attendees in these programs. Our statisticaldata analysis shows an improvement in both course GPAs and successful coursecompletion for SI/PLUS attendees vs. non attendees. To account for the voluntarynature of these programs, we compared the performance of students with similar pre-semester GPAs to control for the level of preparation of the students. The difference inperformance and successful course
Prompt SRL Phase [21] No. Type While completing PS0N, what actions did you take to Select all Q1 help you attain proficiency with the LOs? Check all that Performance that apply apply. Q2- [Rate abilities with recent learning objectives] (For more 5-point scale Self-Reflection Q(Xa-3) detail, see [25
Analysis & Design q. . q. English I 10 Calculus I 15 Mechanics of Materials 13 English II 10 Calculus II 15 Statics 12 Introduction to 8 Chemistry 15 Structural Analysis 12 Engineering Humanities 7 Physics I 12 Geotechnical Engineering 8 Economics 6 Physics II 12 Dynamics 7 Academic Writing 5 Differential Equations 12 Fluid Mechanics
preliminary Q-Matrix for the test. We will identify students’misconceptions about target concepts by administering open-ended formats of the ECCD to a wide pool ofcircuit students in college [13]. The open-ended format of the test will include question stems with noanswer options provided. Q-Matrix will be developed to map every item on the ECCD with all sub-skillsand cognitive attributes that respondents need to answer items correctly [14]. The Q-Matrix is needed todevelop a multi-dimensional reporting scheme at the second phase of the ECCD project. 6Electric Circuit Concepts Diagnostic (ECCD)4.3 Test Compilation and administration: When the
which the surveys are deployed can impact responserates.AcknowledgementsThe work reported herein was funded, in part, by the Kern Family Foundation. We are grateful to all thefaculty that have deployed the modules in their courses and assisted in the collection of feedback. Specialthanks to Professor Cheryl Li for her on going contribution towards promoting and measuring anentrepreneurial mindset of all our students.References[1]. Engineering Unleashed, “The Framework” https://engineeringunleashed.com/framework (AccessedFeb 1, 2022).[2]. Harichandran, R. S., & Carnasciali, M., & Erdil, N. O., & Li, C. Q., & Nocito-Gobel, J., & Daniels,S. D. (2015, June), Developing Entrepreneurial Thinking in Engineering Students by
included ~10% interactive elements including Q&A and think-pair-share style reflections. • Discussion (50 minutes/week in class). This faculty-led Q&A was essentially an in-class postmortem of the homework assignment from the previous week. • Problem Sets (8 ~ 12 hours/week outside of class). The homework involved a combination of problem-solving and multi-part questions exploring the theoretical basis of thermodynamics. The students were encouraged to work in small teams, but handed-in homework individually. Solutions were posted online, and students received feedback from a TA one week later. • Office Hours (extracurricular). Attendance was extremely variable, but sometimes could expand to a third the class (20 people
programming languages known.The results are shown in Fig. 11. We have observed a positive impact on both genders even thoughmales have more computer knowledge than females. Table 1. Survey QuestionsQ1 What kind of cipher is a Caesar Cipher?Q2 Encryption is when you get ciphertext and turn it into plaintextQ3 What is needed to read encrypted messages?Q4 What is Cryptography used for?Q5 In RSA Algorithm, we select 2 random large numbers ‘p’ and ‘q’. Which of the following is the property of ’p’ and ‘q’?Q6 What text is the scrambled and
videoconference sessions were held twice a week for ERT students and once amonth for online students.Table 2: Activities in the courses included in the study. Modality Pre-class activi- In-class activi- Post-class activities ties ties Lecture None Concept Re- Laboratory (each week) based views Three Graded Programming Q/A Sessions Assignments Worked Exam- ples Group Pro- gramming As- signments Flipped
clear idea about the lab objectives, what to expect and what to do before coming to the in-person lab. Q4 There was a pre-lab exercise and the pre-lab helped me to better prepare for the in- lab, hands-on lab exercise. Q5 If a student answered ‘NA’ for Q 4, then the student was asked Q 5(a) (a) There was no pre-lab exercise. I believe, a small pre-lab exercise would help to familiarize me with the lab topic and prepare me better for the in-lab, hands-on lab exercise. Else, the student is asked Q 5(b) (b) The LTspice simulations in the pre-lab were helpful to get a clear understanding of the lab objectives and what to expect in the hands-on
unitless , U is heat transfer coefficient, A is heat transfer area, and C is thesmallest thermal capacity of the two fluids. 𝑁𝑇𝑈 0.22 𝜀 = 1 − 𝑒𝑥𝑝 { [exp(−𝑐 𝑁𝑇𝑈 0.78 ) − 1]} …………………….. (3) 𝑐where ε is effectiveness, and c is ratio of smallest thermal capacity to largest thermal capacity. q=ɛ*Cmin*(T -T )…………………………………… (4) h,i c,iwhere q is heat transfer rate, ɛ is effectiveness, T is temperature of hot fluid in, and T is h,i c,itemperature
COMB Q IN CCOMB,ACT FCOMBCSYS,0 (5) Q IN,0 It is worth mentioning that the combustor may be replaced by an external heat exchanger (EXHX)in many important applications such as in high temperature gas cooled reactors and similarsystems. In tis case the obvious rating feature is the heat exchange area or the essentially equivalentand easier to calculate overall conductance. In this case the cost model would be such as: F EXHX
speed that is fueling a tremendous increase in demand for computer scienceprofessionals. As a result, the industries and organizations have many open positions that can’tsimply fill them. This is because the institutions of higher education are not graduating career-ready students fast enough to meet this high market demand. To prepare a well-rounded, industryand career-ready student, the above-mentioned activities are very crucial.References[1] “World Final Past Problems”, Accessed March, 2022, https://icpc.global/worldfinals/problems[2] “Explorable Places”, Accessed Feb., 2022, https://www.explorableplaces.com/blog/the-benefits-of-field-trips[3] ”Indeed.com”, Accessed Jan, 2022,https://www.indeed.com/jobs?q=College%20Students%20Paid%20Summer