Pedagogy AbstractThe purpose of this work-in-progress (WIP) paper is to report on an ongoing study that used Chiand Wylie (2014)’s Interactive, Constructive, Active, and Passive (ICAP) framework (I > C > A> P) to survey the degree to which LC-DLMs foster cognitive engagement as students learn abouta venturi meter in a fluid mechanics and heat transfer course. Fredricks, Blumenfeld, and Paris(2004) define cognitive engagement as the effort students invest in understanding what they arelearning. Indeed, cognitive engagement is critical for effective teaching and learning inengineering. Although there is research evidence showing that students learn better with hands-onapproaches than traditional
curriculum mapping: supporting competency-based dental education”, Journal of Canadian Dental Association, 74(10) pp.886-889, 2008[7.] Felder, R.M. and Brent, R. “Active Learning: Models from the Analytical Sciences,” ACS Symposium Series 970, Washington DC: American Chemical Society, 2007[8.] Ansari, W.E., Stock, C., Snelgrove, S., Hu X., Parke, S., Davies, S., John, J., Adetunji H., Stoate, M., Deeny P., Philips, C. and Mabhala, A., “Feeling healthy? A survey of physical and psychological wellbeing of students from seven universities in the UK”, International Journal of Environmental Research and Public Health, 8(5) pp. 1308- 1323, 2011[9.] Shallcross, D.C., “Career preferences for undergraduate
think up as many possible ways tohandle it as I can until I can’t come up with any more ideas” to what is shown in Table 1. Table 1 – Questions of the EM-PSI Item Engineering Modified PSI (EM-PSI) Subscale 1 When I face a complex problem, I first define exactly what the problem goal(s) is. AAS 2 When a solution method to a problem was unsuccessful, I do not examine why it did not work. AAS 3 If my first effort to solve a problem was unsuccessful, I become unsure about my ability to PC
consequences of the scenario to a broader scope than thespecific situation. They look at how situations like this affect not only the people at that specifictime, but also after the fact and how it affects the community as a whole.C. Compartmentalizing (5): S ubjects agree that there is an issue related to diversity/inclusion,but it is irrelevant to the decision at hand. Often saying things like “In general, this isinappropriate. In this situation…”E. Equivocating (1): Subject is focused on having a back-and-forth with themselves, oftenbouncing between two (or more) alternate perspectives. Usually in a “can’t decide” scenario, butcan become prevalent through the questioning process.S. Solution-Focused (2): Students tend to craft their own
available resources.References[1] Foor, C., Trytten, D., McClure, L., Waldren, S. and T. Combrink. (2006) “I wishSomeone Would’ve Told Me: Undergraduate Engineering Students offer Advice to IncomingStudents.” Proceeding of the 2002 American Society for Engineering Education AnnualConference, Chicago, IL, July. Paper ID: 1381[2] Romkey, L. (2008) “The First Year Transition: Challenges and Solutions for Students,Instructors and administrators.” American Society for Engineering Education AnnualConference. June 22-25, 2008, Pittsburg, PA. Paper ID: 2127[3] Bradley, S and Bradley, W. (2006) “Increasing Retention by Incorporating TimeManagement and Study Skills into a Freshman Engineering Course.” Proceeding of the 2002American Society for Engineering
shifts in emphasis over the years, animportant one being the 1950’s government funding of fundamental, as opposed to “applied”research; with a subsequent (further) shift away from hands-on experiences and towardsengineering science as the curriculum core [1]. Heavy loading of first year programs with mathand science has implications for persistence and recruitment of global learners [2] and certainunderrepresented minorities such as females [3]. Felder and Brent [4] caution against a “trustme” approach to education in which students may have to persist for months or years before theysee why what they’ve been taught is important. The proposed case-studies move instructionfrom deductive to inductive [5], with the goal of deeper retention and
advancestudents’ understanding and mastery of the material.references:[1] Jensen, D., & Kellogg, S. (2010, June), Improving Conceptual Understanding In ProbabilityAnd Statistics Paper presented at 2010 Annual Conference & Exposition, Louisville, Kentuckyhttps://peer.asee.org/16816[2] Wilson, R (2002, July), What Does This Have to Do with Us? Teaching Statistics toEngineering Students Paper presented at ICOTS 2010 Annual Conference, Cape Town SouthAfrica. http://iase-web.org/documents/papers/icots6/5e1_wils.pdf[3] Reeves, K., & Blank, B., & Hernandez-Gantes, V., & Dickerson, M. (2010, June), UsingConstructivist Teaching Strategies In Probability And Statistics Paper presented at 2010 AnnualConference & Exposition, Louisville
We formed divisions as per entrance examination scores and allocated better teachersto divisions with poor performers. The teachers were asked to follow the mastery approach i.e.focus more on understanding. We kept the same divisions for all courses. s based on consistentstudent evaluations of teaching effectiveness and performance of their students in universityexaminations. Kulik et al. [12] did meta-analysis of findings from 108 controlled evaluationsto conclude that mastery learning programs have positive effects on the examinationperformance of students in colleges. Further, they found that the effects appear to be strongeron the weaker students in a class, and they also vary as a function of mastery procedures used,experimental designs
Preschool TeacherCandidates", Universal Journal of Educational Research, vol. 4, no. 11, pp. 2533-2540, 2016.[8] D. Jonassen, J. Strobel and C. Lee, "Everyday Problem Solving in Engineering: Lessons forEngineering Educators", Journal of Engineering Education, vol. 95, no. 2, pp. 139-151, 2006.[9] S. Loyens, J. Magda and R. Rikers, "Self-Directed Learning in Problem-Based Learning and itsRelationships with Self-Regulated Learning", Educational Psychology Review, vol. 20, no. 4, pp. 411-427,2008.[10] M. Gick and K. Holyoak, “The cognitive basis of knowledge transfer”, Transfer of learning:Contemporary research and applications, Elsevier, pp. 9-46, 1987.[11] D. Jonassen, "Instructional design models for well-structured and III-structured problem
and bottom three motivational attitudes along with the student’s rating.Further, it depicts the average intrinsic and extrinsic scores allowing the student to comparehis/her motivation with that of the whole class. Finally, there is a short summary explaining thestudent’s motivational attitudes category together with the attitude items with which s/he wasleast and most motivated. Example report cards for students intrinsically and extrinsicallybalanced, predominantly intrinsic, and predominantly extrinsic in nature are shown in Figs. 1-3.Figure 1 is an example report card for an intrinsically and extrinsically balanced student with anaverage intrinsic score of 7.4 and average extrinsic score of 8.1. This student provided the lowestrating for
process, the ISE-2 project team will compare student reports of engagement and classroom climate in classrooms taught by ISE-2 faculty versus comparison classes. A survey for junior students was also administered in Spring 2017 and will be administered in the Spring semesters of subsequent years. This survey broadly examines student engagement and classroom climate in the College of Engineering. The goal is to determine if there are changes in juniors’ experiences pre-/post-implementation of ISE-2. Student engagement in the classroom is measured by the Student Experience in the Research University Survey (SERU-S)2. Classroom climate is measured by the Critical Incidents Questionnaire (CIQ)3, items from the Diversity
Recruitment, Mentoring and Retention through the Aerospace and Industrial Engineering (ASPIRE) Scholarship Program1. IntroductionThe overarching goal of the Aerospace and Industrial Engineering (ASPIRE) Scholarshipprogram is to improve recruitment and retention of aerospace engineering (AE) and industrial(IE) engineering students. With support from the NSF S-STEM program, the ASPIRE programprovides scholarships to academically talented, full-time AE and IE students with demonstratedfinancial need. The ASPIRE program enhances the educational experience of ASPIRE studentsthrough mentoring and networking events. The objectives of the ASPIRE program are to: • Prepare students for the workforce. • Provide educational
engagement of industry mentors with the students has increased the number ofinternships with the region. The interaction of students in competitions motivates the students totake on more challenging projects in STEM areas than they would engage in with traditionalcourses. Finally, having students carry out lessons and activities builds self-confidence andspeaking skills.References1. Jolly, Campbell, and Perlman, “Engagement, Capacity and Continuity: A Trilogy for StudentSuccess” (GE Foundation, September 2004)2. Chun-Mei Zhao and George D. Kuh, “ADDING VALUE: Learning Communities and StudentEngagement”, Research in Higher Education, vol. 47, 2006, pp 89-1093. Georgiopoulos, M., Young, C., Geiger, C., Hagen, S., Parkinson, C., Morrison-Shetlar, A
Engineering Education, vol. 104, no. 1, pp. 74–100, 2015.[6] J. C. Hilpert, J. Husman, G. S. Stump, W. Kim, W. T. Chung, and M. A. Duggan, “Examining students’ future time perspective: Pathways to knowledge building,” Jpn. Psychol. Res., vol. 54, no. 3, pp. 229–240, 2012.[7] E. Godfrey and L. Parker, “Mapping the Cultural Landscape in Engineering Education,” Journal of Engineering Education, vol. 99, pp. 5–22, 2010.[8] E. Crede and M. Borrego, “From Ethnography to Items: A Mixed Methods Approach to Developing a Survey to Examine Graduate Engineering Student Retention,” J. Mix. Methods Res., vol. 7, no. 1, pp. 62–80, Aug. 2012.[9] B. E. Lovitts and C. Nelson, “The Hidden Crisis in Graduate Education: Attrition From Ph.D
research is needed.AcknowledgementsThe authors thank the reviewers for their helpful comments and suggestions. We would also liketo gratefully acknowledge the NSF for their financial support (through the DUE-1744407 grant).Any opinions, findings, and conclusions or recommendations expressed in this Report are thoseof the authors and do not necessarily reflect the views of the National Science Foundation; NSFhas not approved or endorsed its content.References[1] S. Freeman et al., “Active learning increases student performance in science, engineering, and mathematics,” PNAS, vol. 111, no. 23, pp. 8410-8415, June 10, 2014.[2] M. H. Dancy and C. Henderson, “Experiences of new faculty implementing research-based instructional strategies,” AIP
are typically notassociated with engineering by middle schoolers, a reality that this game confronts. This allowsAlgae City to have a greater audience and get a wider variety of people interested in algae andengineering. Future work involves testing this game with subject groups of various ages rangingfrom 5th to 8th grade, gathering feedback, and then making any necessary changes to the gamebased off that feedback. In the end, Algae City aims to challenge, excite, and educate the playerwith the overarching goal of promoting STEM education.References[1]. T. S. Online, “Students taking up STEM subjects on decline last 10 years,” Nation | The StarOnline, 15-Jul-2017. [Online]. Available:https://www.thestar.com.my/news/nation/2017/07/16/students
A. Bergman, T. Kf Caughey, Anastassios G. Chassiakos, Richard O. Claus, Sami F. Masri, Robert E. Skelton, T. T. Soong, B. F. Spencer, and James TP Yao. (1997). "Structural control: past, present, and future." Journal of engineering mechanics 123, no. 9: 897-971.[6] Spencer Jr, B. F., and S. Nagarajaiah. (2003). "State of the art of structural control." Journal of structural engineering 129, no. 7: 845-856.[7] Mahin, S. A., P. B. Shing, C. R. Thewalt and R. D. Hanson. (1989). "Pseudodynamic test method-current status and future directions." J. Struct. Eng. 115 2113–28.[8] Shing, P. B., M. Nakashima and O. S. Bursi. (1996). "Application of pseudodynamic test method to structural research." Earthq. Spectra 12 29–56.[9
Paper ID #22817Evaluating Learning Engagement Strategies in a Cyber Learning Environ-ment during Introductory Computer Programming Courses – an EmpiricalInvestigationMrs. Mourya Reddy Narasareddygari I am Ph.D student at North Dakota State University. My research work is to see how different Learning strategies affect the student learning.Dr. Gursimran Singh Walia Gursimran S. Walia is an associate professor of Computer Science at North Dakota State University. His main research interests include empirical software engineering, software engineering education, human factors in software engineering, and software quality. He is a
a 5-point rubric yielding total scores between 0 and 16for each. Cohen’s d (effect size) was calculated ([3]: (µ1-µ2)/s), and average post-quiz scoreswere compared by paired t-test or repeated-measures ANOVA. Students’ self-recorded videoswere coded for the quality of their interactions as described by [1]. Two factors were varied: (1) the scaffolding (instructions) given to the students and (2)whether students watched a dialogue video or monologue video. Statistical analyses of thenumber of interactive episodes for each group are performed (by coding interactions observed inthe students’ self-recorded videos) to test the hypothesis that students watching dialogue videoshave more interactive episodes and higher learning gains than
+ gz2 = a constant (1)Where: P: the pressure of the fluid (Pa, PSI) ρ: the density of fluid (Kg/m3, lbm/ft3 ) v: the velocity of the fluid relative to the airfoil (m/s, ft/s) g: the magnitude of acceleration for body (m/s2, ft/s2) z: the height at that point (m, ft) The subscripts 1 and 2 represent different points along the same streamline of fluid flow.When a car turns, a force must accelerate the car towards the center of the turn.AERODYNAMIC OVERVIEWThere are many different aerodynamic effects taking place on a car at different locations. For somelocations the car is producing lift while others the car is experiencing down-force. Figure 1, shows a
Aims: Assessement of a University Capstone Course.," The Journal of General Education, vol. 53, no. 3/4, pp. 275-287, 2004.[5] T. Bailey, J. C. Calcagno, D. Jenkins, T. Leinbach and G. Kienzl, "Is Student-Right-to-Know All You Should Know? An Analysis of Community College Graduation Rates," Research in Higher Education, pp. 491-519, 2006.[6] R. W. Marx, P. C. Blumenfeld, J. S. Krajcik and E. Soloway, "Enacting Project-Based Science," The Elementary School Journal, vol. 97, no. 4, pp. 341-358, 1997.[7] M. Sadat-Hossieny and M. Torres, "NKU-Mazak Corp. Joint Senior Project Program," in 21st ASEE Annual Conference, Indianapolis, 2014
STEM transfer students exist. Programs such as summer bridge programs, mentoring,tutoring, learning communities, and other activities are fairly common at the undergraduate levelin STEM fields, and many of these programs have historically been funded by NSF STEP and S-STEM programs. Few systematic studies of interventions have been conducted, however. Localassessment data, typically published in conference papers and reports, support the efficacy of theseinterventions; however, no systematic reviews of the considerable literature have been found. Tosignificantly and positively impact representation of Hispanic scientists and engineers, we need acomprehensive synthesis to (a) develop patterns of successes and failures of Hispanic STEMtransfer
-billion-devices-will-be-connected-to- the-internet-by-2020-2013-10#ixzz3QWI7CyZh, (viewed on February 1, 2015)[2] R. Piyare, Internet of Things: Ubiquitous Home Control and Monitoring System using Android based Page 26.1770.11 Smart Phone, International Journal of Internet of Things, Vol. 2 No. 1, 2013, pp. 5-11. doi: 10.5923/j.ijit.20130201.02.[3] G. Kortuem, F. Kawsar, D. Fitton, and V. Sundramoorthy, "Smart objects as building blocks for the internet of things," Internet Computing, IEEE, vol. 14, pp. 44-51, 2010.[4] D. Lowe, S. Murray, E. Lindsay, and D. Liu, Evolving remote laboratory architectures
* Averaging 1.5 FDA approvals per year† 2007: 19 NMEs [lowest since 1983] 1000’s of samples 2008: 21 NMEs [29% new-in-class] Balancing complexity of biology against 2009: 24 NMEs [17% new-in-class] heterogeneity of patients Maybe…but can it be more efficient?*Paul et. al, Nature Rev. Drug Discovery, March 2010; † Leigh Anderson, Clin Chem, 2010National Institutes of Health (NIH):27 Institutes and CentersNHGRI NIA NIDA
/xcell/Xcell32.pdf ,text [22], which was an outgrowth of the research presented https://en.wikipedia.org/wiki/Xilinxhere [1]. [10] https://www.xilinx.com/products/silicon-devices/fpga/artix-7.html Thus based on written student surveys and observing the [11] https://www.xilinx.com/products/design-tools/vivado/vivado-general delight of students when building the projects, we webpack.htmlbelieve this approach (spiral model plus themed labs across [12] Brown, S. and Vranesic, Z., Fundamentals of Digital Logic withthe four years), and
2017 and 2018. In addition, two student teams presented their work at the 2017ASEE Zone II Conference and one team, composed of engineering students and an art student,presented a design solution at the spring 2018 ASEE SE Conference.Project Substantiation and ImportanceIn the 1980’s, research introduced that disability is socially created rather than rooted in theindividual [1]. More recent studies indicate that persons with disabilities may move through aprocess of seven types of identities: isolated affirmation, apathy, resignation, situationalidentification, affirmation, crusadership, and normalization [2]. Studies also indicate that the arts,including the visual arts, can be a tool to aid transition through these identities to enhance
science and technology as well as students approach to the technological designprocess. These areas will be explored more fully in future papers. References[1] X. Chen, “STEM Attrition: College Students’ Paths into and out of STEM Fields. Statistical Analysis Report. NCES 2014-001.,” Natl. Cent. Educ. Stat., 2013.[2] C. Dweck, Mindset: The new psychology of success. Random House, 2006.[3] D. S. Yeager and C. S. Dweck, “Mindsets That Promote Resilience: When Students Believe That Personal Characteristics Can Be Developed,” Educ. Psychol., vol. 47, no. 4, pp. 302– 314, Oct. 2012.[4] A. Rattan, K. Savani, D. Chugh, and C. S. Dweck, “Leveraging Mindsets to Promote Academic Achievement Policy
retention in our engineering program over time. 2018 ASEE Mid-Atlantic Fall Conference, October 26-27, 2018 – Brooklyn Technical High SchoolReferences1. S. Sorby, “Educational Research in Developing 3-D Spatial Skills for Engineering Students,” International Journal of Science Education, vol. 31, no. 3, 2009, pp. 459-480.2. Norman, K.L., Spatial visualization – A gateway to computer-based technology. Journal of Special Educational Technology, XII(3), 1994, pp. 195–206.3. Smith, I.M., Spatial ability - Its educational and social significance. London: University of London, 1964.4. J. Wai, D. Lubinski, and C. P. Benbow, “Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its
Session ETD 475the attack and prevention were successful or not. Proper action should be immediately takenwhen the message shows an attack is happening. The student should implement the defensemechanism against that attack at once because s/he will keep losing points if other studentslaunch the same attacks. Figure 2. Score and Message Board3.3. Graphic user interface (GUI)A graphic user interface (GUI) application is designed for each student to log into his/herlearning environment. The main menu of the application includes a set of InfoSec activities andeach includes two labs: attack and defense. Each lab features a series of actions that requirestudents to complete their attack (defense) task. Each defense lab in
role model(s) who are scientists/engineers I want to earn more money I love creating/designing I am passionate about STEM Other Fig. 7: Interest in pursuing Engineering and/or Science careers, pre-camp survey Fig. 8: Student’s perception of learning outcomes post-camp survey assistants (TA’s), out of which three were instructors and had extensive