thecurriculum as a whole and for individual courses (including its place in the ABET continuousimprovement criterion), the specific lessons learned after the first 3 years of implementation, thechanges to be made for the next 3 year cycle, and conclusions on how these experiences may betransferred to other programs. A mixed-methods approach is used to evaluate this first cycle ofimplementation and assessment, include comparing expected vs. actual/measured: (a) coursesevaluated in a given semester; (b) student artifacts; and (c) program learning outcomes.Introduction and BackgroundDuring the period 2013-14 and 2014-15 academic years, Texas A&M University’s civilengineering department undertook a curriculum transformation project base its program
, basic knowledgeabout college education, educational degree expectations and plans, difficulty in cultural andsocial transitioning process, and family income and support” [3]. Likewise, Terenzini et al. [4]describe first generation students to have following attributes compared to their non-firstgeneration peers: a) have low family income; b) belong to underrepresented population group;and c) have “weaker cognitive skills in math, science, and critical thinking”. The authors alsofound a significant difference between the FG and Non-FG students with respect to their overallcollege experience. Their findings showed that the FG students had taken fewer number ofcredits hours, studied fewer hours, worked longer hours, and had overall lower academic
Paper ID #23246Insights on Retention of Underrepresented Minority Electrical and Com-puter Engineering Transfer Students (Experience)Dr. Samuel Paul Merriweather, Texas A&M University Dr. Samuel Merriweather currently serves as the Texas A&M University System Louis Stokes Alliance for Minority Participation (TAMUS LSAMP) Associate Director through the Texas A&M Engineering Experiment Station (TEES), a part of the Texas A&M University System. He obtained bachelor and mas- ter of science degrees in industrial engineering at Georgia Institute of Technology and a PhD in industrial engineering at Texas A&M
.), determine all other parameters in a moist air. Determine the flow rate of incompressible fluid in a pipe or duct accounting for all friction and head losses. b Estimate the energy required to maintain this flow. c Determine steady-state and transient heat transfer via conduction, convection, and radiation. Determine the unique aspects in the physical properties of food and biological materials and describe their d importance to specific applications Prepare a systems diagram of processes identifying all inputs, outputs, and external factors affecting the e system. f Understand how food is produced. g Perform an energy balance on a system and determine efficiency. h Exhibit a
) increasing student engagement, success, and retention, and (b) ultimately seeing greater increases for underrepresented minority (URM), women, and first-generation students. Ten faculty teaching first- and second-year Engineering courses participated in the first cohort of ISE-2 in Summer 2017, which consisted of three workshops and six informal “coffee conversations”. At the conclusion of the workshops, each faculty was tasked with completing a teaching plan for the Fall 2017 semester, to incorporate the strategies and knowledge from ISE-2 into the courses they plan to teach. Focus groups with the ISE-2 faculty were conducted in Fall 2017 to obtain feedback about the faculty development program. Classroom observations were
executionAccording to Bringle and Hatcher [1], service-learning is defined as a “course-based, creditbearing educational experience in which students (a) participate in an organized service activitythat meets identified community needs, and (b) reflect on the service activity in such a way as togain further understanding of course content, a broader appreciation of the discipline, and anenhanced sense of personal values and civic responsibility” (p. 112).” Service-learning has beenproven to benefit students in many ways. More specifically, service learning has been found toenhance students’ collaboration skills [2], civic engagement, interpersonal skills [3], [4], andtheir ability to apply knowledge to problem-solving [5].Our service-learning course was
find chemical information: A guide for practicing chemists, educators, and students (3rd ed.). New York: John Wiley & Sons.[9] ICIS. (2018). About us. Retrieved from https://www.icis.com/about/[10] Johnson, O. (2018). The price reporters: A guide to PRAs and commodity benchmarks. Abingdon, UK: Routledge.[11] Spectrum Chemical. (2017). Chemicals. Retrieved from https://www.spectrumchemical.com/OA_HTML/Chemicals.jsp?minisite=10020 &respid=22372[12] Raizada, T. (2017). MEG. ICIS Chemical Business, 291(26), 32.[13] Lord, C. (2000). Guide to information sources in engineering. Englewood, CO: Libraries Unlimited.[14] Osif, B. A. (2012). Using the engineering literature. Boca Raton: CRC Press.[15
she played 2 years of women’s basketball at Bevill State Community College in Fayette AL and her last 2 years at the University of West Georgia in Carrollton GA. She was a 4 year Academic All American.Dr. Sarah B. Lee, Mississippi State University Sarah Lee joined the faculty at Mississippi State University (MSU) after a 19 year information technology career at FedEx Corporation. As an assistant clinical professor and Assistant Department Head in the Computer Science and Engineering Department, she is co-founder and co-director of the Bulldog Bytes program at MSU that engages K-12 students with computing and provides professional development to K-12 teachers in computer science and cybersecurity. She is the PI for the
. Three separate andindependent groups of students are recruited for the study. Group distribution is shown as a Venndiagram in Figure 1. Group A is presented with written literature to review before the flight. Theliterature defines the functions of the flight simulator, flight controls, aircraft principles,instruments and the required mission details. They are then asked to fly the mission with minimalassistance during the flight portion. They are free to ask questions during the flight. Group B is notpresented with any literature for review before the flight. A short presentation is given to them thatdescribes the flight controls, basic instruments and the mission. Their first real exposure to theflight is when they get on the simulator and
professionals and action researchers successfully draw out narratives and stories from underrepresented groups who may be reluctant to share their experiences? What are some best practices for sharing results from a project that investigates these experiences in depth? How can the results of qualitative research best inform practice and policy as it relates to underrepresented groups? Share advantages and limitations of qualitative methods for academic affairs professionals and others. Share multiple methods for recruiting small sample interview participants. Provide methods for eliciting narratives from underrepresented groups Practice applying innovative data collection techniques to your
graduated and gone to work – at a plastic formingcompany wanted to build a thermoforming machine and conduct material experiments onthermoformed specimens. His co-op experience clearly gave rise to interest in this project.A plan solidified with first-semester (spring) objectives for the four students to: 1. Design/build a 3D printer and thermoforming machine that could produce specimens for material testing a. Three students responsible for the 3D printer b. One student responsible for the thermoforming machine 2. Design an experimentation procedure for 3D printed and thermoformed materials 3. Produce a variety of specimens that could be tested, primarily in tensionThe option remained for a second semester (summer
Paper ID #22126Revising the Civil Engineering Body of Knowledge (BOK): The Applicationof the Cognitive Domain of Bloom’s TaxonomyDr. Decker B. Hains, Western Michigan University Dr. Decker B. Hains is a Master Faculty Specialist in the Department of Civil and Construction Engi- neering at Western Michigan University. He is a retired US Army Officer serving 22 years on active duty with the US Army Corps of Engineers and taught at the United States Military Academy at West Point (USMA). He earned a Bachelor of Science degree in Civil Engineering from USMA in 1994, Master of Science degrees from the University of Alaska
fellow of the ASEE and IEEE and is active in the engineering education community including serving as General Co-Chair of the 2006 Frontiers in Education (FIE) Conference, on the FIE Steering Committee, and as President of the IEEE Education Society for 2009-2010. She is an Associate Editor of the IEEE Transactions on Edu- cation. She and her coauthors were awarded the 2011 Wickenden Award for the best paper in the Journal of Engineering Education and the 2011 Best Paper Award for the IEEE Transactions on Education. In Spring 2012, Dr. Lord spent a sabbatical at Southeast University in Nanjing, China teaching and doing research.Dr. Joyce B. Main, Purdue University-Main Campus, West Lafayette (College of Engineering
square-foot concrete structure) [18]. Thestructure, called a barracks hut or B-Hut, was printed as a result of a three year Army Programcalled the “Automated Construction of Expeditionary Structures.” It uses an additivemanufacturing process to “print” semi-permanent structures in a theater of operation. The abilityto use concrete, for all the walls, in exception of the wooden roof sourced from readily availablematerials, reduces logistical requirements for the U.S. Army. Structural [19], and thermal [20]studies have been performed to predict the best mixture for the structure and the most energy-efficient building in terms of energy.A methodology for building construction has been developed (Figure 2). This methodology isbased on three steps
) Leadership Award in 2010. At the University of Alabama, Fridley has led efforts to establish several new programs including new undergraduate degree programs in construction engineering, architectural engineering and environmental engineering, a departmental Scholars program allowing highly qualified students an accelerated program to earn their MSCE in addition to their BS degree, the interdisciplinary ”Cube” promoting innovation in engineering, and the cross-disciplinary MSCE/MBA and MSCE/JD dual-degree programs.Dr. Decker B. Hains, Western Michigan University Dr. Decker B. Hains is a Master Faculty Specialist in the Department of Civil and Construction Engi- neering at Western Michigan University. He is a retired US
muscle force. The tab applies the reaction force to keep theas lifting and moving objects. The positions and angles of arm stationary when loaded.joints and end-points are found using direct and inversekinematics, which often requires the application of the law ofsine and cosine. FIGURE 1 EXAMPLES OF MUSCULOSKELETAL FORCE VECTORSTwo-link arm apparatusA human arm and bicep muscle model is used to demonstrate (a) (b)the application of vectors in engineering and applications of FIGURE 3the law of sine and cosine to find muscle length, muscle (A) TWO-LINK ARM APPARATUS (B) WEIGHTSattachment angle, and end position distance
leverageinstitutional data to improve the STEM undergraduate education system, in particular at the stageduring which students take foundational courses taught in large class sizes: RQ1: What data do STEM faculty teaching large foundational classes for undergraduate engineering identify as being useful so that they may enhance students’ experiences and outcomes a) within the classes they teach, and b) across students’ multiple large classes? RQ2: How can looking across data sets at different levels (i.e., within-course and across courses) change faculty members’ attitudes or behaviors related to teaching undergraduate classes? RQ3: How can looking across data sets at different levels produce insights
Paper ID #242602018 CoNECD - The Collaborative Network for Engineering and ComputingDiversity Conference: Crystal City, Virginia Apr 29First-Year Experience (FYrE@ECST): Pre-Physics Course (WIP)Ni Li, California State University Los AngelesDr. Gustavo B Menezes, California State University, Los Angeles Menezes is an Associate Professor in Civil Engineering Department at CalStateLA. His specialization is in Environmental and Water Resources Engineering. Since becoming part of the faculty in 2009, Menezes has also focused on improving student success and has led a number of engineering education projects. He is currently the PI
withoutany additional instructor workload. (b) Remediation group activities (a)increased Remediation groups motivated my understanding of me5.2 Student Perceptions to become concepts more which prepared I was
factor analysis with a promax (non-orthogonal) rotation was then run withthe newly shortened set of items. From theory, we would expect three factors (attainment STV,utility STV, and intrinsic STV), so a three-factor analysis was run first. Results from the threefactor maximum likelihood analysis are provided in Appendix B. We note that all items meetrecommendations for minimum loading of 0.32 onto a factor [38], except for the item that asked“I am interested in learning how to communicate with people from different backgrounds”.However, factor correlations ranged from -0.51 to -0.81, indicating that two of the factors arehighly correlated. Therefore, the three factor solution is not appropriate based on our data.Additionally, we could not
cycle. Educational research review. 14(2015), pp. 47-61. 4. Barron B, Darling-Hammond L. Teaching for Meaningful Learning: A Review of Research on Inquiry-Based and Cooperative Learning. Book Excerpt. George Lucas Educational Foundation. 2008. 5. Kuhlthau CC, Maniotes LK, Caspari AK. Guided inquiry: Learning in the 21st century: Learning in the 21st century. ABC-CLIO; 2015 Oct 13. 6. Hmelo-Silver CE. Problem-based learning: What and how do students learn? Educational psychology review. 16(2004), pp. 235-266. 7. De Jong T., van Joolingen W.R. Scientific discovery learning with computer simulations of conceptual domains, Review of Educational Research, 68 (1998), pp. 179-202 8. Blumenfeld P
-centered and learner-oriented [3], [9], [10].Bransford, Brown, and Cocking (2000) reported that an effective learning environment includesthe following four characteristics: (a) knowledge-centeredness, (b) learner-centeredness, (c)assessment-centeredness, and (d) community-centeredness [3]. A knowledge-centeredinstruction develops conceptual understanding and organization of the knowledge in the field. Ina learner-centered environment, students’ pre-conceptions and alternative conceptions areexplored prior to teaching, and the instruction focuses on what students know, what they want toknow, and how they will use the knowledge. Assessment centeredness provides frequentopportunities for formative feedback over the course of the learning, and the
. 17 References[1] S. J. Poole , and J. F. Sullivan. "Assessing K-12 pre-engineering outreachprograms," Frontiers in Education Conference, vol. 1, pp. 11B5-15, 1999.[2] J. J. Kuenzi, "Science, technology, engineering, and mathematics (STEM) education:Background, federal policy, and legislative action." 2008.[3] S.Y .Yoon, M. Dyehouse, A. M. Lucietto, H. A.. Diefes‐Dux, and B. M. Capobianco, "Theeffects of integrated science, technology, and engineering education on elementary students'knowledge and identity development," School Science and Mathematics, 114, no. 8, pp.380-391,2014.[4] T. J. Moore, and K. M. Tank,"Nature-‐Inspired Design: A PictureSTEM Curriculum forElementary STEM Learning," 2014.[5] T
question: From the principal’sperspective, what high school level local and contextual factors contribute to the variation inenrollment into 4-year University engineering programs?Site and Participant DescriptionThree schools are under investigation in this WIP study: High School A (HSA), High School B(HSB), and High School C (HSC). The case site that encompasses these three high schools is aprimarily rural geographic region. U.S. Census (2016) indicates the county containing these highschools has a population of approximately 80,000 - 120,000 and a median household income of$40,000 - 60,000. Ranges were reported instead of the actual values to obscure the identity of thecounty. Based on the ranges of secondary school size provided by Grauer (2012
STEM: Unpackingthe STEM Identity Work of Historically Underrepresented Youth in STEM,” ICLS Proceedings.pp. 418-425, 2016.[8] Jay L. Lemke, “Across the Scales of Time: Artifacts, Activities, and Meanings in EcosocialSystems,” Mind, Culture and Activity, vol. 7, no. 4, pp. 273-290, 2000. doi:10.1207/S15327884MCA0704_03[9] Joseph L. Polman and Diane Miller, “Changing Stories: Trajectories of Identification AmongAfrican American Youth in a Science Outreach Apprenticeship,” American EducationalResearch Journal, vol. 47, no. 4, pp. 879-918, Dec. 2010.[10] Heidi B. Carlone, Catherine M. Scott and Cassi Lowder, “Becoming (Less) Scientific: ALongitudinal Study of Students’ Identity Work from Elementary to Middle School Science,”Journal of Research in
Paper ID #242722018 CoNECD - The Collaborative Network for Engineering and ComputingDiversity Conference: Crystal City, Virginia Apr 29On Becoming a ”Transfer Institution”: Research on a Community Collegethat Supports Diverse Black Students in their Transfer AspirationsDr. Bruk T Berhane, University of Maryland, College Park Dr. Bruk T. Berhane received his bachelor’s degree in electrical engineering from the University of Mary- land in 2003, after which he was hired by The Johns Hopkins University Applied Physics Laboratory (JHU/APL) where he worked on nanotechnology. In 2005 he left JHU/APL for a fellowship with the
Paper ID #23568Examining the Replication – or Mutation – Processes of Implementing a Na-tional Model for Engineering Mathematics Education at a New SiteDr. Janet Y. Tsai, University of Colorado, Boulder Janet Y. Tsai is a researcher and instructor in the College of Engineering and Applied Science at the University of Colorado Boulder. Her research focuses on ways to encourage more students, especially women and those from nontraditional demographic groups, to pursue interests in the eld of engineering. Janet assists in recruitment and retention efforts locally, nationally, and internationally, hoping to broaden the
learningprocess. By checking learning outcomes and gathering feedback from the learners via surveysor forums it will be possible to improve the MOOC based on evidence.Figure 2. Theoretical framework for the design and evaluation of MOOC's - Grover et al. [29]This framework was used during the development of the math MOOC. This development wasa cooperation between the math lecturers, IT, and pedagogical supporters. The course consistsof four modules (ILE – Content), which are divided in numerous subsections. The modulesare enumerated below: Elementary arithmetic’s A Elementary arithmetic’s B Trigonometry, Geometry, Equations, Inequalities, & Linear systems Derivatives & IntegralsEvery module contains video’s, step
, S. K.Sensor nodes sense the interested physical information based on the specific applications.Following that, the physical information is converted into a serial of raw data. Then, the raw data ispassed to the local intelligent electronics devices (IEDs) to process. After that, the processed datais sent to the sink node. The sink, in turn, passes the corresponding instructors to the sensor nodesaccording to the received information. The main characteristics of the WSNs can be generalizedas 4:a) Network topology is specified based on the users’ requirements;b) Applications are diverse based on the sensors varieties in sensor field;c) Traffic characteristics is relatively unique based on the protocols used in the whole network;d) Available
Recommendations,” Perspect. Psychol. Sci., vol. 10, no. 6, pp. 721–726, 2015.[5] ABET, “Accreditation Changes | ABET,” 2018. .[6] B. O’Reilly, “Alan Alda Promotes Improv As Means To Better Science Communication,” The East Hampton Press & Southhampton Press, 2016. [Online]. Available: http://www.27east.com/news/article.cfm/East-End/481096/Alan-Alda-Promotes-Improv-As- Means-To-Better-Science-Communication. [Accessed: 01-Dec-2016].[7] R. Bernstein, “Communication: spontaneous scientists,” Nature, vol. 505, no. 7481, pp. 121– 123, 2014.[8] P. Agre, “Toward a critical technical practice: Lessons learned in trying to reform AI,” Soc. Sci. Tech. Syst. Coop. Work Gt. Divide Erlbaum, 1997.[9] M. Ratto, “Critical making: Conceptual and