results collected from a microphone andUSB data acquisition system and discuss any discrepancies. Table 1. We organized the learning objectives into three categories: enduring understanding (EU, highlighted), important to know and do (IKD), and worth being familiar with (WF). Topic Learning Objective Priority Assessment Critique data visualizations and descriptive statistics for HW1, 3, 5-7, 9, 11- EU clarity and appropriateness 13; P1-3; Q Data
questions about what they learned from the program, if the programchanged their goals/plans, and their satisfaction with the program. The pre-survey also gathereddemographic information and background academic information.Table 2: Questions from the pre-survey administered at the start of each summer program. Pre-Survey Question Question Type Participant identification (Student ID Number, Year, Faculty Text boxes and Lists Mentor) Participant background academic information (Major, GPA, etc.) Text boxes and Lists Participant demographic information (Gender, Race and Ethnicity) Select from lists Q: What interested you about this summer program? Open-ended comment Q
teachers may ask students when exploring the Report Card and relatedactivities are as follows: • Q: Which of these infrastructure types do you see and/or use in your daily activities? o Activities: A discussion with students could include the infographic “How Much Infrastructure Do You Use Before Noon?” Students choose one category of infrastructure to explore in more detail through creation of a short report, a photo collage of that infrastructure type (younger students), Teachers lead a field trip around their community and have students identify the different infrastructure components around them
users were also required to judge the realism of the model in comparison toimages provided as well as perceptions on the usefulness of the model.SoftwareEach software package used in this project is presented to provide deeper understanding of theeducational module developed. Choosing the appropriate software for 3-D representation was Q c American Society for Engineering Education, 2017 PAPER ID: 18690one of the key factors that aided in the development of the paper. Whereas most 3-D modellingsoftware programs have the capacity to represent the model, not all of them will represent thetrue characteristics of
in the sketch.Following the online performance, however, the facilitators, like sports analysts, recap thesituation and ask the student audience to comment regarding how they feel. The students respondusing the Zoom Q&A feature to enter comments and questions which are addressed by thefacilitators. Instead of bringing student audience members into the Zoom team, the actors areinterviewed, on-screen and in character, and asked how they feel about what happened, why theydid what they did, and how they think their actions made the other characters feel. The studentaudience is encouraged to ask questions of the characters using the Q&A feature and to “upvote”questions to help determine which questions have the most audience interest
0% Content-Specific Questions Yes No Page 26.415.7Content Questions and Keywords used to evaluate responses Questions Keywords Tissue, engineering, creating, regenerating, growing, organic matter, making, cell function, Q-1: What is tissue engineering? building, forming, examining, manipulating
democratization of manufacturingand programmable electronics. The design experience in the class provides students an outlet forexercising their creativity at the highest level of Bloom’s taxonomy. ∗A web-based, private beta version was provided to students in the Fall 2015 to assist them with their projects.Figure 5: A few pictures of the projects from the Final Robot Design Project Demo day, Fall 2015;see complete gallery of pictures at https://goo.gl/photos/WhYmy4kxFoStwNQz7References1 Shen, Q., Al-Smadi, Y. M., Martin, P. J., Russell, K., and Sodhi, R. S., 2009, “An extension of mechanism design optimization for motion generation”, Mechanism and machine theory, 44(9), pp. 1759–1767.2 The National Academy of Engineering, 2005, Educating the
engagementwith the instrument. An expert in the field was tasked with taking the assessment to establish abaseline for the amount of time reasonably required to complete the EERI thoughtfully. Thechange in score was calculated for each individual, and histograms, Q-Q Plots and theShapiro-Wilks test were used to evaluate the normality of this data [9]. A paired pre/post t-testwas employed to evaluate the differences in the EERI scores from the first to the fourth year.This test was chosen for its effectiveness in comparing two related samples.ResultsInitially, the P score, which measures postconventional thinking based on universal good, had amean pre-score of 60.62 (SD = 17.59). Over four years, it decreased to a mean post-score of57.24 (SD = 19.37
ofresearch, (4) an interactive tour of the conference hardware competition which provides concreteexamples of cutting edge research, (5) a small group Q&A with graduate students engaged inresearch, and finally (6) a panel discussion with diverse research faculty committed to post-secondary engineering education. The challenges associated with this approach to outreach, theadvantages of incorporating a STEM intervention into a technical research conference, andsuccessful methods for locating a group of underserved students are discussed. In addition, thescale and impact of the intervention are evaluated through open-ended and quantitative surveys.The survey results document the positive student reaction to this intervention. The positivestudent
taken) Participant demographic information (Gender, Race / Ethnicity) Select from lists Q: What interested you about this summer program? Open-ended comment Q: What do you expect to learn and experience in this summer program? Open-ended comment Q: How do you expect this program to help your academic career? Open-ended comment Q: Rate your agreement with the following statements: 5-point Likert scale (strongly I am interested in the field that I am studying. agree = 5, agree = 4, neutral I am interested in a career in STEM. = 3, disagree = 2, strongly I am confident that I am prepared
, disciplines, individuals with complementaryValue across multiple levels of activity and engagement. etc. skill sets, expertise, etc. q. Integrates/synthesizes different kinds of knowledgeFirst Year Engineering Experience (FYEE) Conference August 6 – August 8, 2017, Daytona Beach, FL W1A-1 Session W1AThe three
have time to answer them all. I was wondering maybe we should have had a shorter presentation and longer Q & A section. I'm not sure if the students would have enjoyed and learned more with a longer Q & A section. I think if we were given some more time, we could have had the kids do an activity relating to engineering, which could be beneficial. (Note: this comment referred to the amount of time at the school) A similar activity, but with local high schoolers, would be a good opportunity to use more interesting/complex experiments.These and other comments show that the REU students not only enjoyed the experience, butwalked away from the outreach activity seeing benefits to both the K-5
,Introjected, and Identified w ere obtained from further categorization of Extrinsic Motivation.Each subscale is measured by 4 items. Further separation of Amotivation was not done in theoriginal study and so it remains its own subscale with 4 corresponding items. Motivation ismeasured by the Academic Motivation Scale which is created from the aggregation of the sevensubscales. (see Appendix A; Q2: 1-10, Q3: 1-10, Q4: 1-8). Table 1 Academic Motivation (AMS) and Corresponding Items Academic Motivation Scale Intrinsic Motivation Extrinsic Motivation Amotivation Know Q2: 2, 9, Q3: 6, Q
or are considering becoming parents.Summary of ideas to be explored and discussed:Raising children is one of the most challenging and opportunity-filled experiences most peoplewill take on in their lives. Raising children as a member of the Academy brings an additionallayer of complexity. This panel will present challenges and opportunities encountered by thepanelists while raising children and trying to succeed in the Academy. The panelists will alsoprovide concrete, achievable strategies that have worked for them to overcome those hurdles andhow they have leveraged opportunities available to them. The session will allow time for Q&Aduring which audience members can share their own challenges and success strategies with thebroader group
g r a m s .T w o - a n d f o u r - y e a r s c h o o ls h a v e e x p lo r e d v a r io u s c o n n e c tio n s . In S a m u e l, e t. a l. [ 9 ] th eu n iv e rs ity g a v e th e tw o - y e a r s tu d e n ts a c c e s s to th e ir e q u ip m e n t. T h is c o lla b o r a tio n a ls o h a din s tr u c to r s jo in tly c r e a te a m o d u le to b e u s e d in b o th c u r r ic u lu m s . H o w e v e r , th e s tu d e n ts o n lyw o rk e d w ith o th e r s tu d e n ts in th e ir p r o g r a m . T h e s tu d e n ts d id n o t w o r k to g e th e r a c ro s s s c h o o ls .A C a lifo rn ia c o lla b o ra tio n [1 0 ] re v is e d s e v e ra l c o u rs e s a t b o th th e c o m m u n ity c o lle g e a n d th eu n iv e rs ity to in c o r p o r a
industry. The repeated cycle of training new hires due to labor turnover may affectorganizational and project performance. Construction firms should seek tactical human resourcesinitiatives to attract new hires, develop old hires’ skills, and retain talent in their workforce. Thisstudy investigates the differences in human dimensions of individuals engaged on construction jobsites. The aim of this paper is to identify distinctive human dimensions of skilled trades workers,essentially required for job transition within the construction industry. This study adoptedHEXACO personality inventory, Emotional Intelligence, and Q-DiSC behavioral diagnostics todetermine personality trait differences and peculiarities between 133 project managers workingfor
1.0 0.5 0.0 Incorrect WT Pre-‐Video Q Correct WT Pre-‐Video Q Marble Machines Wind Tubes Figure 8. Performance on Wind Tubes related posttest items, clustered by condition and performance on WT pre-video question. Wind Tubes tinkerers performed the best, if they got the pre-video question correct.Data analyses on the marble-related posttest questions showed a similar trend, but were lessclear-cut (see Fig 9). ANOVA revealed a
or deductive coding. This manual theming was supplemented using theNVIVO software to identify common words and phrases leading to any additional or missedthemes. Throughout this process, discussions and checks were conducted with the research teamfor agreement on final themes. Table 1: Interview questions with faculty Question Question No. Q.1 Tell me about yourself. Q.2 Explain how and why COVID pandemic impacted the functioning and behavior of your STEM students. Q.3 Explain how and why COVID pandemic impacted the performance of your STEM students. Q.4 Explain how and why you responded to changes in STEM student
the student population responded that they are more satisfied with KACIE incomparison to other courses. The other half had the opinion that they are satisfied with KACIEjust like any other course. Finally, nearly all responded that KACIE sheets were useful for betterunderstanding and learning the concepts. TABLE IV STUDENT SURVEY DATA TABLE Completely Somewhat Disagree (%) agree (%) agree (%) Q.1 The supplementary videos provided helped to 50 50 0 understand the course material in better manner Q.2 These videos equipped
sample sizes increase, the distribution of the sample mean differencesapproaches normality, even when the underlying data is not perfectly normal (Ghasemi &Zahediasl, 2012).To ensure the data met this assumption, the Shapiro-Wilk test was employed to assess normality.The Shapiro-Wilk test is frequently used in real-world applications across various fields,including educational and psychological research, to evaluate whether data significantly deviatesfrom a normal distribution (Razali & Wah, 2011). This approach helped ensure the validity of thesubsequent t-tests, providing confidence that the assumptions of the statistical models wereadequately met.Figure 4: LAESE Factor scores - Histograms and Q-Q plotsfigure 5: CPSES Factor scores
showedan increase in student engagement. However, it was inconclusive whether the homeworkcompletion grade was affected by the pedagogy. The results also showed that the homework hada weak positive correlation with exam performance.The present paper further aims to assess the efficacy of the pedagogy by examining studentengagement and student performance across multiple cohorts of the course. Learningmanagement system tools, like chat and polling, were previously shown to be effectivequalitative methods for overcoming the passive learning behavior exhibited by EFL students.Thus, a comparison by cohort and in aggregate were performed for the following: studentparticipation at each synchronous Q&A session using the chat feature, student polling
Method: Measures search * high scores represent high levels of the respective variables Ø Perceived Support-Organization (6-point Likert Scale), Supervisors, Coworkers, Family (4-point Likert Scale) Ø Perceived Organizational Climate (5-point Likert Scale) Ø Workplace Incivility (5-point Likert Scale) Ø Workplace Microaggressions (6-point Likert Scale) Ø Work-family Conflict (5-point Likert Scale) q Engineering Task Self-Efficacy (6-point
-agree (or True) or D-disagree (or False) is given in front of each question.Q#4: I would rather bet 1 to 6 on a long shot than 3 to 1 on a probable winner. (A)33% of Freshmen and Sophomores agreed to the statement while 77% of Juniors and Seniorsagreed with this statement (p < 0.0002)Q#5: The way to understand complex problems is to be concerned with their larger aspects insteadof breaking them into smaller pieces. (A)32% of Freshmen and Sophomores agreed to the statement while 77% of Juniors and Seniorsagreed with this statement (p < 0.0002)Q#6: I get pretty anxious when I am in a social situation over which I have no control. (D)58% of Freshmen and Sophomores disagreed to the statement while 27% of Juniors and Seniorsdisagreed with this
equations are converted to a set of algebraic equations using a weighted integral statement (e.g., weak-form Galerkin and least-squares formulation). For example, a weak-form Galerkin formulation of the governing equations, Eq. 1–2, can be stated as: find the solution {u, p} ∈ S h such that for all {w, q} ∈ V h the following equation is satisfied: Z ∂u w· ρ + ρu · ∇u − ρg − (∇ · w)p dΩ Ω ∂t Z − ∇q · u dΩ + (suitable stability terms) ZΩ = {w · (−pI + τ ) · n
historically minoritized groups. Both the surveyquestions that were used to study emerging themes of self-advocacy in the graduate students, andfocus group questions have been presented to the engineering education research community atconferences and one-on-one meetings to get feedback from the broader community on thethemes of self advocacy and the questions. The focus groups will be conducted in Summer 2023and all students in the GREATS program will be invited to participate.Table 1. Focus group questions Question 1: Q.1 Can you describe your graduate-program trajectory story? Why did Background, you choose to pursue a graduate degree in science/engineering? Why Motivation, and did you choose and/or apply to the
, industry or government collaboration, and/or travel.Discussion topics will also include process requirements of applying, conducting, anddocumenting the outcomes of the sabbatical.The suggested layout of the panel session is: • 5-minute introduction of panel topic and panelists • Overview of each panelist’s sabbatical activity (5 minutes each) • Brief whole group Q&A session to engage audience and panelists • Small group activities with documentation of Q&A: o What resources did you find helpful in planning your sabbatical? o What was the timeframe of planning, applying for, conducting, and documenting your sabbatical? o What were the requirements of your sabbatical
”To achieve the second goal, we implemented a Q&A forum inside canvas and used Pizza featuresto manage it (Fig. 3). Students are encouraging to participate in the forum, but no grade is assignto this to avoid competitiveness. All participants can vote for the best answer and the highest-ranking answer will show always on top. We create a forum for each one of the mainlabs/assignments on the course, this way student can quickly find help on the project they areworking on. Fig 3 Q&A ForumResultsTo evaluate the benefits of this project we used some of these educational technologies indifferent classes. Introduction to Programming in the Computer Engineering Department, aNumerical Analysis class in
(Equations (1)-(3)) in Simulink,and the last one for the introduction of the MFC model; 3) the project problem statement showingthe detail of the MFC models and the model parameters. All these materials were sent to studentsvia email, and the videos were uploaded onto YouTube for students to watch. dc A q = (c A,i - c A ) - kc A (1) dt V dT w (-DH R )k UA = (Ti - T ) + cA + (T - T ) (2) dt rV rC rVC c k = k0 exp(- E / RT
xj= 0.49 𝜇m The total amount of dopant introduces into the substrate Q(t) is given by √4𝐷𝑡 Qt = Cs= 2.9 * 1015 atoms/cm2 √𝜋 Example 2.3.2 Drive-In Calculate the junction depth xj of the sample in example 2.3.1 after Drive-In at1100°C for 4.5 hours. 𝑄𝑇 −𝑥 2 C(x,t)= exp( ) √𝜋𝐷𝑡 4𝐷𝑡 2𝐶𝑠 √𝐷𝑡 5.18∗1015 Qt =( )predep = √𝜋 √𝜋 5.18∗1015 Where Cs’(t) = = 2.5*1019/cm3 𝜋√(𝐷𝑡)𝑑𝑟𝑖𝑣𝑒−𝑖𝑛