AC 2011-2844: INFLUENCING THE ACADEMIC SUCCESS OF UNDER-GRADUATE FIRST-YEAR ENGINEERING STUDENTS THROUGH A LIV-ING LEARNING COMMUNITYJacqueline Q. Hodge, Texas A&M University Jacqueline Hodge is a native of Giddings, Texas and currently the Project Manager for the Engineering Student Services & Academic Programs Office (ESSAP) at Texas A&M University (TAMU). In her cur- rent position, Jacqueline is responsible for Retention and Enrichment Programs for engineering students. Jacqueline graduated from TAMU with a Bachelors of Science degree in Mechanical Engineering. While obtaining her degree, Jacqueline was involved with several community service activities such as the Boys & Girls Club of Bryan, Help
AC 2012-4319: ENGAGING FRESHMAN IN TEAM BASED ENGINEER-ING PROJECTSMs. Lacey Jane Bodnar, Texas A&M University Lacey Bodnar is a master’s of engineering student in water resources engineering at Texas A&M Uni- versity. Her undergraduate degree was from the University of Nebraska, Lincoln in 2010. She currently works for the Engineering Student Services and Academic Programs Office and is pleased to be involved in managing exciting freshman engineering projects.Ms. Magdalini Z. Lagoudas, Texas A&M UniversityMs. Jacqueline Q. Hodge, Texas A&M University Jacqueline Hodge is a native of Giddings, Texas and currently the Project Manager for the Engineering Student Services & Academic Programs Office
AC 2011-913: UNDERGRADUATE ACADEMIC EXPERIENCE FOR FIRST-YEAR ENGINEERING STUDENTS THROUGH A SUMMER BRIDGE PRO-GRAMJacqueline Q. Hodge, Texas A&M University Jacqueline Hodge is a native of Giddings, Texas and currently the Project Manager for the Engineering Student Services & Academic Programs Office (ESSAP) at Texas A&M University (TAMU). In her cur- rent position, Jacqueline is responsible for Retention and Enrichment Programs for engineering students. Jacqueline graduated from TAMU with a Bachelors of Science degree in Mechanical Engineering. While obtaining her degree, Jacqueline was involved with several community service activities such as the Boys & Girls Club of Bryan, Help One Student To
safety, and sustainable infrastructure.Mr. Edward Stephen Char Jr., Villanova University BS EE Villanova University 1996 MS EE Villanova University 1998Dr. John Komlos, Villanova University Page 26.27.1 c American Society for Engineering Education, 2015 ✁✂✄☎ ✁✂✆✄✝☎ ✁✂✞✟✂✠☎✠✡ ☛✠ ☞ ✌✄✂✍☎✎✡✏✑☞✝☎✒ ✓☛✄✝✡✏✔☎☞✄ ✕✠✖☛✠☎☎✄☛✠✖ ✗✘✙✚✛✜✚✢✣✚✤ ✥✦✚✛✦✜✚✧ ★✢✩ ✪✫✫✚✫✫✬✚✢✭✮✯✰✱✲✳✴✱✵✶✷✷✸✹✺✻✸ ✼✹✶✻✽✾✿✶❀❁ ✽❂❃✸✾❄✽❅ ✺✹ ✸ ✹✽❆ ❇✾✺❈✽❉❀❊❃✸✿✽❅ ✸❇❇✾✺✸❉❋ ●✺✾ ❀❋✽ ✾✽❍■✶✾✽❅ ●✶✾✿❀❊❁✽✸✾ ✽✹❏✶✹✽✽✾✶✹❏❑▲▼❑◆❖❑◗❑ ❖ ❘❙❙❚❯ ❱❲❖❳ ❑❨ ❩❖◆❳❱❬❭❑❪◆ ❑▲▼❑◆❖❑◗❑ ❨❪❳ ◆❑▼❫◆❱❑❴ ❖ ❱❲❑ ❘❙❵❙ ❛❜❝❝ ❛❞❪❡ ❢❫❩❑◆❑◗❑❣❤✐❥❦❦❧♠♥♦♣q rs❦ t
engineering students. The first objective of this study is to explore theengineering epistemological beliefs among students in introductory engineering courses, using aunique methodological approach, Q methodology. The second objective is to examine whethersuch epistemological beliefs are related to student academic outcomes among first yearengineering students.This study focuses on students in introductory engineering courses for two reasons. First,introductory STEM (including engineering) courses are often large, posing difficulties forinstructors and students to closely examine and discuss concepts and knowledge covered in thecourses. Students’ epistemological views in these courses can be potentially used to relate tostudents’ course performances
modifications have been made on a regular basis.Table 4. Mentor evaluation of students in a team6 Draft Average grade Q. 2. Q. 3. Q. 4. Q. 6. score from Q. 1. Work Do Informed Q. 5. Listened out of 5 mentorStudent Meeting before team team if Contributed to team from (NG toname attendance meetings tasks absent in meetings mates Q 1-6 A+) AverageFigure 2 shows the 2008/2009 winners of the prize for the top team in the module along
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
. Furtherinvestigation of the histograms and Q-Q plots of GPAs for each category of homeworkcompletion confirmed the appropriateness of using a nonparametric test to compare thedistributions of GPA between homework completion categories to answer RQ1. For RQ1 theTwo -Sample Kolmogorov-Smirnov Test, which is based on the empirical distribution function, Page 26.845.6was used to test for a difference in the distributions of GPA for the different categories ofhomework completion. The test was run in MatLab using the KSTEST2 function. Cliff’s deltawas used as a nonparametric measure of effect size. The MatLab program written to calculateCliff’s delta is in the
Learning Outcome III Learning Outcome IV Q 1 2 3 4 5 Mean Q 1 2 3 4 5 Mean Q 1 2 3 4 5 Mean Q 1 2 3 4 5 Mean 1 24 22 1 2 0 1.61 3 23 20 5 0 1 1.69 4 11 26 9 3 0 2.08 5 18 27 3 1 0 1.73 2 33 15 0 0 1 1.39 6 22 25 2 0 0 1.59 9 15 22 10 2 0 1.98 8 27 19 3 0 0 1.51 13 29 19 1 0 0 1.43 7 27 21 1 0 0 1.47 10 27 20 2 0 0 1.49 15 25 20 3 0 1 1.61 14 5 6 4 16 18 3.73 12 25 22 1 1 0 1.55 11 22 24 1 1 1 1.67 20 32 16 1 0 0 1.37 17 13 28 8 0 0 1.90 19 23 22
) coupler link; frame link B) ground link; frame link C) ground link; coupler link D) coupler link; side link7. Omitted8. Grashof’s Criterion is ___________ when S is the length of shortest link, L is the length of longest link, and P and Q are lengths of the intermediate links. A) (S + L) - (P + Q) B) S + L ≤ P + Q C) (S +L)² - (P + Q)² D) S² + L² ≤ P² + Q² Page 13.393.129. Some four-bar linkages have dead points (or toggle points), which occur when two moveable links ___________. A) create a 45˚ angle B) create a 90˚ angle C) line up D) move continuouslyElectrical Engineering10. The
support model [1]. TheSupplemental Instruction (SI) program provides optional, non-remedial sessions designed todeliver content review and additional practice opportunities while developing transferable studyeffectiveness skills to benefit the student in all coursework at the institution.Results from other studies have revealed that regular session attendance positively impactedexam scores, overall course grades and DFWQ% (Ds, Fs, Q-drops, Withdraws) rates, and thatparticipants had an overall favorable perception of the SI program [1]-[5]. Some works havesought to determine factors that affect attendance in SI sessions, by using qualitative data onstudents attitudes to predict behaviors of attendance [6], [7]. This work in particular found
negativeskewness, as confirmed through visual inspection of the Normal Q-Q plot and histograms of theGPAs. However, since both the University of Cincinnati and University of Louisville had similarskewness (-1.222 and -1.018, respectively) we chose to continue with the independent t-testanalysis toward our decision toward maintaining the two datasets. The results of the independent samples t-test indicated a significant difference,t(694.7)=4.325, p
freshman engineering class: (i) Prior knowledge survey, (ii)Nanotechnology video assigned as a homework assignment, (iii) In-class Q/A session assisted byTablet PC and DyKnow technologies, (iv) Hands-on activities, (v) Video presentation on ananotechnology experiment, (vi) Homework assignments on nanotechnology concepts, and (vii)Post-module surveyPrior Knowledge Survey: The Spring ’08 prior knowledge survey (see Appendix 1) wasimplemented on a voluntary basis and more than 50% students responded (see Figure 2). Studentresponses indicated similar type of misconceptions as were observed in the Spring ’08 pilot.Nanotechnology video presentation: Students were assigned to review a nanotechnology videothat was developed by a nanotechnology expert (i.e
-university test was administered before the start of the program, and the post-testwas administered at the end of the first-year year. The data for Case 2 was collected in2014/2015 where the pre-university test was administered before the start of the program and themid-test was administered midway through first-year.The sample size in both cases was approximately 200 students for the pre-university test, with aslightly reduced group size due to attrition (approximately170) for both the mid and post-testscenarios. A summary of the results for each case is provided in Table 1. The data in Table 1 iscollated in terms of question number (Q), question type (Type), percent correct for the sampleconsidered both pre, mid and post-test, the number of
review of the current literature revealed no one standard for comparing students according totheir attendance to multiple exam reviews. Considering the lack of a consistent n-value for examreview attendance, we defined the “exam” group as students attending 2 or 3 collaborative mockexam reviews and the “no exam” group attending 1 or none. We considered attending one examreview as not receiving the intervention, as the student would have completed the structured,timed retrieval practice only once, which would most likely not produce significant learninggains.Definitions Used in StudyThe following terms utilized in this study are defined according to the authors’ and theuniversity’s use: ● Q-Drop: students may leave a course after the 12th
provideinstructional guidance for faculty and staff in the future. We collected survey responses for EE306 students, but had extremely limited responses for EE 307E (a course with only 22 students),so we are only able to report on the metacognitive interventions in EE 306.IV. Definitions Used in StudyThe following terms utilized in this study are defined according to the authors’ and theuniversity’s use: ● Q-Drop: students may leave a course after the 12th class day with a “Q” noted on their transcript [17]. ● QDFW% rates: the percentage of students in the course who Q-dropped the class, made a D, F, or withdrew (and received a W on their transcript), in comparison to the whole student population for that course. ● SI group: students who
all survey items.The item prompts are presented in groups so that the text fits better on the pages. The groupingalso reveals patterns in prompts. Although presented in groups, the prompts are given in the orderpresented to the survey takers. Note that Tables 10, 11, and 12 contain preamble text in the tablecaptions. The preambles were presented as an introduction to the respective group of Likert scaleitems.The tables of prompts have the same column headings. The first column is “Q #”, which is theitem label assigned by the Qualtrics software. Those item labels are also tags for identifying andselecting items in the R code used for statistical analysis, but otherwise the item label is notsignificant. The second column labeled “Rev.” is a 1
c h n i q u e s i n a
course. ● Q-Drop: students may leave a course after the 12th class day with a “Q” noted on their transcript [11]. ● Low Socioeconomic Status (SES): parental income reported as below $40,000. ● First Generation: neither parent of the student has completed a bachelor’s degree or higher. ● Underrepresented Minority (URM): federal ethnicity reported as Latino/Hispanic, Black, Multi-Racial, Hawaiian/Pacific Islander, or Native American [12].Design and ImplementationSI is an international model of academic support targeting large and historically difficult classes.Developed at the University of Missouri-Kansas City in 1973, SI’s peer
- content/uploads/2012/01/EUR-ACE_Framework-Standards_2008-11-0511.pdf.(13) Passow, H. J. J. Eng. Educ. 2012, 101, 95. Page 26.1177.10(14) Brett, J.; Behfar, K.; Kern, M. C. In The Essential Guide to Leadership; Harvard Business Review, 2009; pp. 85–97.(15) Halverson, C. In Effective Multicultural Teams: Theory and Practice; Halverson, C. B.; Tirmizi, S. A., Eds.; Springer, 2008; pp. 81–110.(16) Pelled, L. H.; Eisenhardt, K. M.; Xin, K. R. Adm. Sci. Q. 1999, 44, 1.(17) Watson, W. E. Acad. Manag. J. 1993, 36, 590.(18) Horwitz, S. K. Hum. Resour. Dev. Rev. 2005, 4, 219.(19) Manning, M. L.; Lucking, R. Clear
ScienceFoundation.AppendixFigure 2 shows the plots for the comparison groups. The histograms and Q-Q plots show that thedistribution of the cumulative GPA does not follow the Normal distribution. The results of thenormality tests presented in Table 9 also confirm that. Table 9. P-value of Normality test methods for cumulative GPA for C-Groups Jarque Shapiro- Anderson- Kolmogorov- Groups/ Method Bera (J-B) Wilk (S-W) Darling (A-D) Smirnov (K-S) Not 1&2 6.338e-13 4.612e-06 2.986e-06 0.08832 PELL-Eligible 3 <2.2e-16 <2.2e-16 <2.2e-16 1.048e-07 1&2 2.174e-07 7.481e-05
noted on their transcript up to the 12th class day. ● Fail: a student earning below a D- has failed a course. ● Q-Drop: students may leave a course after the 12th class day with a “Q” noted on their transcript [13]. Design and ImplementationI. Course Content and Student EnrollmentThe objectives of the Introduction to Electrical Engineering (EE 302) course are to introduce thefreshman student to the basics of electrical engineering through the study of DC circuits.Students learn all the basic laws that govern circuits such as the power conservation law,Kirchhoff’s current and voltage laws, and Ohm’s Law, followed by
to design examples andexercises that meet the specific needs of each classroom. In order to better understand thedifferences between classrooms, students from two different classrooms (named“Classroom 1” and “Classroom 2”) were submitted to the same following question duringan electrochemistry lesson:Consider the following overall reaction for a battery: 2 Ag+ + Sn → 2 Ag + Sn2+What is the reaction quotient (Q) for this redox process?a) [Sn2+].[Ag]2/[Ag+]2.[Sn] b) [Sn2+]/2[Ag+]c) [Sn2+]/[Ag+]2 d) [Ag+]2/[Sn2+]The correct answer to the question above is letter c): Q = [Ag+]2/[Sn2+].Although it seems to be a very easy question, is was possible to
), 1541–1547.[5] Mazumder, Q. H., Karim, R. M. (2012). Comparative Analysis of Learning Styles of Students of USA and Bangladesh, Paper no: AC2012-5075, 119th ASEE Annual Conference, June 10-13, 2012, San Antonio, TX, USA[6] Sadi, O. & Uyar, M. (2013). The relationship between cognitive self-regulated learning strategies and biology achievement: A path model. Procedia-Social and Behavioral Sciences; 93 (2013), 847-852.[7] Crede, M., & Philips, A. L. (2011). A meta-analytic review of the motivated strategies for learning questionnaire. Learning and Individual Differences; 21 (2011), 337-346.[8] Puteha, M., &, Ibrahimb, M. (2010). The usage of self-regulated learning strategies among form four students in
whichversions of all first year classes are being developed for this MOOC environment with options toreceive college credit from Arizona State University (ASU). Through this program, learners cantake a course completely for free in the “audit track” which allows them access to all coursematerial, but does not provide instructor grading of assignments or any kind of “verified”certificate of completion. For these students, the course is treated much like a traditionalMOOC, but with the benefit of an instructional team that includes professors who monitor andparticipate in discussion boards and host live “Q&A” video sessions throughout the course. Theinnovative aspect of this course is that there is a parallel track that students can opt into
evaluated by the authors. Session 1 Session 2 Presentation Q&A Presentation Q&A 0.4286 0.9333 0.7241 0.5926 no input 4 8 10 12 -1 8 0 2 0 0 4 2 4 11 1 23 29 23 16 Observation: 1. The value of 0.4286 indicates the results could have been better but was still a worthwhile effort. Recall the value could go negative. Note there 23 out of 39 students indicated the
and non-value added steps in a manufacturing process. 6. Identify metrics to measure, improve, and control in a manufacturing process. 7. Utilize principles of lean and Six Sigma to improve productivity and quality of a manufacturing process. 8. Differentiate between a push system and a pull system for a sequential manufacturing process. 9. Evaluate manufacturing models for strengths and weaknesses in terms of quality, productivity, and communication. 10. Compare manufacturing models in terms of effectiveness and profitability. 11. Write a cohesive group lab report based on different information and observations from each group member.Materials and ResourcesThe Q&P lab uses the Mr. Potato Head toy for
effect on students’ academic achievement. The overall effect was d = 0.35 (CI = [0.02,0.68]). This effect is statistically significant since the 95% confidence interval of the overalleffect does not contain a zero, also known as a zero effect. The statistically significant Q value of63.69 (df = 15, p < .001) indicated that the effects were not homogenous and were groupedaccording to some moderating variable. We grouped the studies by the engineering dimensions:design, project development, and control training. Two studies [4] [18] provided ten effects ondesign aspect of first-year engineering education. The effect on design was d = 0.53 (CI = [0.30,0.76]). This effect was statistically significant. One study [20] provided five effects for
. The second semester is mechanics and the third semester is electricity and magnetism.BackgroundThe following chronology was constructed with guidance from the large southwestern universitySenior Associate Dean for Academic Affairs during an interview with the author.In spring 2016, the Physics Mechanics course multi-semester revealed a trend of a failure/q-droprate approaching 30%. This is a foundational course for engineering students, and, as a result,many engineering students were opting to take this course at other colleges and transfer the hoursor abandoning their engineering vision completely. To investigate the sources and ramificationsof this alarming failure/q-drop rate, at the direction of the Dean of Engineering, a facultycommittee