reading/language research: Vol. 5, Literacy through family, community, and schoolinteraction (pp. 261-276). Greenwich, CT: JAI Press. [19] Henderson, A. T., & Berla, N. (1996). A new generation of evidence: The family is critical to studentachievement. Washington, DC: Center for Law and Education[20] Kellaghan, T., K. Sloane, B. Alvarez, and B. S. Bloom. "A process-based approach for homes." The homeenvironment and school learning: promoting parental involvement in the education of children (1993): 136-143.[21] G. Valdes, G.; Con Respeto: Bridging the Distances Between Culturally Diverse Families and Schools: AnEthnographic Portrait. Teachers College Press, 1996.[22] Clark, R (1983), Family Life and school achievement: Why poor black children
. Unfortunately, the instructors had no practical way ofoverseeing how specific students were distributed between the two sections. Table 2demonstrates that the control group, on average, had significantly higher grade point averages incourses completed through the summer of 2013.Table 2: Grade point averages in courses completed prior to the start of the Fall 2013semester (4.0=A, 3.0=B, 2.0=C, 1.0=D).Section Mean GPA Standard DeviationExperimental Group (n=26) 3.21 0.55Control Group (n=26) 3.42 0.38In total, 53 students enrolled in PCP I for the Fall 2013 semester: 27 in the experimental groupand 26 in the control group. One of the “experimental” students withdrew from the
projectlearning, (b) early prototyping that accelerates and improves the quality of final designs, (c)formal communication (oral and written) that allows clients to easily integrate design projectresults, and (d) cadre of graduate student mentors with exceptional technical leadership skills.Program operation outcomes include: (a) annual planning, oversight, and assessment thatproduces yearly improvements, (b) project results that delight all stakeholders, leading to follow-on projects in subsequent years, and (c) minimal cost to produce results, leading to increasedfinancial resources for infrastructure.Infrastructure development outcomes include: (a) locally produced, web-based design tools,rubrics, and quick references for just-in-time professional
animals in elementary school. In 2012 7th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1–6).[3] Braun, V., &Clarke,V.(2006). Using thematic analysis in psychology. Qualitative research in Psychology.[4] Bujak, K. R., Radu, I., Catrambone, R., MacIntyre, B., Zheng, R., & Golubski, G. (2013). A psychological perspective on augmented reality in the mathematics classroom. Computers & Education, 68, 536–544. doi:10.1016/j.compedu.2013.02.017[5] Chang, Y.-J., Chen, C.-H., Huang, W.-T., & Huang, W.-S. (2011). Investigating Students’ Perceived Satisfaction, Behavioral Intention, and Effectiveness of English Learning Using Augmented Reality. In Proceedings of the 2011 IEEE
Biomaterials. Liverpool: Liverpool UniversityPress; 1999.2. Polymer Characterization Techniques.247-56.3. Ratner B, Hoffman AS, Schoen FJ, Lemons JE. Biomaterials Science: AMultidisciplinary Endeavor. Biomaterials Science: A Introduction to Materials in Medicine. SanDiego: Elsevier Academic Press; 2004. p. 1-9.4. Moss A. Use of Selected Medical Device Implants in the United States. Hyattsville, MD:National Center of Health Statistics, 1988.5. Black J, Shalaby SW, LaBerge M. Biomaterials Education: An Academic Viewpoint.Journal of Applied Biomaterials. 1992;3:231-6.6. Vanderbilt N, Texas, and Harvard-MIT Engineering Research Center.http://www.vanth.org/curriculum/curr_bio_domains.asp.7. Saterbak A, editor Laboratory
to the most striking data.For example: ü 69% of 170 respondents agree or strongly agree with the statement “The course material has been interesting to me.” ü 70% (of 170) non-EE students are satisfied or very satisfied with this EE course ü 55% (of 153) students report increased interest in EE due to taking this course ü 62% (of 153) non-EE students report increased motivation to apply EE to their fields ü 79% (of 153) non-EE students report increased confidence in applying EE to their fields.The authors anticipate several types of applications for their findings: A. Fine-tuning of the teaching strategies and the logistics in this course. B. Verification of these findings in the future semesters (with different
. In each class, halfof the students completed Part 1 on paper and Part 2 on the computer, while the other half ofstudents did the reverse. Part 3 of each examination can be considered as the remaining 50-60%of each test and was completed in the same mode for both versions (A and B). Most of Part 3was completed on paper; however, some questions required the use of a computer. The resultsfrom Part 3 were not considered in this test mode study. The test breakdown is representedschematically in Figure 1, and represents the same structure of all three examinations used in thisstudy.Question phrasing and order on the same part (1 or 2) were identical, regardless of testing mode.The paper portions were created to be as aesthetically similar as
team project experiences. These student-based assessments can be used in defining student performance grades for the project if desired.The Peer Evaluation Template can be easily adapted for use in an industrial or business setting tohelp project managers motivate team members to enhance project outcomes through increasedinvolvement in team activities, while simultaneously improving team dynamics andcommunication with team members and other stakeholders.References1. Barkley, B., & Saylor, J. (2001). Customer-driven project management. New York, NY: McGraw -Hill.2. Bonebright, D. A. (2010). 40 years of storming: A historical review of Tuckman's model of small group
earlier activities related toChapters 5, 7 and 8 of the course textbook30). Groups were comprised of 4 students and weremostly self-selected; the same self-selected teams were used to complete all group activities(e.g., homework assignments and in-class group activities). Page 24.1332.6 (a) (b) Figure 2: (a) Ideal and (b) Real Pendulums Description: An ideal pendulum (shown in
Paper ID #10282Feasibility of interactive eTextbooks with computationally intense contentDr. Jacques C. Richard, Texas A&M University Dr. Richard got his Ph. D. at Rensselaer Polytechnic Institute, 1989 & a B. S. at Boston University, 1984. He was at NASA Glenn, 1989-1995, taught at Northwestern for Fall 1995, worked at Argonne National Lab, 1996-1997, Chicago State, 1997-2002. Dr. Richard is a Sr. Lecturer & Research Associate in Aerospace Engineering @ Texas A&M since 1/03. His research is focused on computational plasma modeling using spectral and lattice Boltzmann methods for studying plasma turbulence
-program survey of students' intended major, while Table 3-B summarizes the post-programsurvey results. Cumulative results for the five years (column labeled “Total”) indicate that thelargest increase in the number of students' intended major is in Civil Engineering (+2), followedby Electrical Engineering (+6), and Mechanical Engineering (+4). The largest decrease is inEngineering (-19), followed by Undecided (-6). The large decrease in the number of studentswho initially declared a “general” Engineering major shows that after participating in SEI, thesestudents have been able to identify a specific engineering field of interest to them. These resultsalso indicate that after participating in the program and gaining an understanding of the
Anatomy, Biology, Environmental Science, and even Spanish. Participantsreceived 20 hours of professional development credit.The program was structured into two workshop sessions. The first session, during the summer of2012, consisted of three days of hands-on instruction. It focused on several instructional topics,including (a) Overview of Cloud Services, (b) Storing and Sharing Data in the Cloud, (c) Cloudsin Education and Collaboration in and out of the Classroom, (d) Cloud-based Tools for Real-timeCollaboration, (e) Course Management using Piazza, (f) Standards-based Lesson Planning andPost-workshop Assignment, (g) Creating a Lesson Plan, and (h) Using Public Data SetsAvailable in Amazon’s Cloud. At the end of the three-day workshop
Paper ID #9294Toward a Conceptual Model: African-American Male Students’ Motivation,Persistence and Success in Community CollegesMrs. Olgha B Davis, North Carolina State University Olgha B Davis is currently a doctoral student at the Department of Leadership, Policy and Adult and Higher Education at North Carolina State University. She obtained a Bachelor’s degree in Biomedical Engineering from Boston University in 1998. She worked in the software industry for 7 years, focusing on modeling and simulating automotive, aerospace and biological systems. She returned to graduate school and earned her Master’s degree in
Encyclopedia of Education (Third Edition). P. Peterson, E. Baker and B. McGaw. Oxford, Elsevier: 112-118.Baker, R. S. J. D. and K. Yacef (2009). "The State of Educational Data Mining in 2009: A Review and Future Visions " Journal of Educational Data Mining 1(1).Hall, M., E. Frank, G. Holmes, B. Pfahringer, P. Reutemann and I. H. Witten (2009). "The WEKA Data Mining Software: An Update." SIGKDD Explorations 11(1).Johnson, L., S. Adams-Becker, M. Cummins, V. Estrada, A. Freeman and H. Ludgate (2013). NMC Horizon Report: 2013 Higher Education Edition. Austin, Texas, The New Media Consortium.Macfadyen, L. P. and S. Dawson (2010). "Mining LMS data to develop an "early warning system" for educators: A proof of concept." Computers & Education
-source content.!Table 1. A simplified list of 8th Grade Core Curriculum Standards for Physical Sciences. A. Properties of Matter C. Forms of Energy 5.2.8.A.1 Matter 5.2.8.C.1 Solar Energy 5.2.8.A.2 Substances are composed of elements 5.2.8.C.2 Energy Transfer 5.2.8.A.3 Solids, Liquids, and Gases 5.2.8.A.4 Periodic Table !D. Energy Transfer 5.2.8.A.5 Chemical Properties 5.2.8.D.1 Conservation of Energy 5.2.8.A.6 Properties of Metals 5.2.8.D.2 Energy Flow 5.2.8.A.7 Acid-Base Reactions !B. Changes in Matter !E. Forces and Motion
Behavioral Sciences, pp1313-1318.6. Daft, R. L. & Lengel, R. H. (1986). Organizational Information Requirements, Media Richness and Structural Design. Management Science, 32(5), Organization Design, pp554-571.7. Driscoll, M. P. (2012). Psychological foundations of instructional design. In R. A. Reiser & J. V.8. Gagne, R. M., Driscoll, M. P. (1988). Essentials of Learning for Instruction. 2nd Ed. Prentice-Hall, Englewood Cliffs, NJ.9. Kelly, M., Collette, L., McGrath, M., Cannon, G. (2009). A Multi-Method Study to Determine the Effectiveness of, and Student Attitudes to, Online Instructional Videos for Teaching Clinial Nursing Skills. Nurse Education Today, 29, pp292-300.10. Kozma, R. B. (1994). The Influence
. Page 24.692.12References 1. NSF Advanced Funding Search. Retrieved December 26, 2013 from http://www.nsf.gov/funding/advanced_funding_search.jsp. 2. Borrego, M., & Cutler, S. (2010). Constructive Alignment of Interdisciplinary Graduate Curriculum in Engineering and Science: An Analysis of Successful IGERT Proposals. Journal of Engineering Education, 99(4), 355-369. 3. McNair, L. D., Newswander, C., Boden, D., & Borrego, M. (2011). Student and Faculty Interdisciplinary Identities in Self-Managed Teams. Journal of Engineering Education, 100(2), 374-396. 4. Lattuca, L. R., Knight, D. B., & Cortes, C. M. (2011). Working as a Team: Enhancing Interdisciplinarity for the Engineer of 2020. Proceedings
use photos, images, graphics, or word-art in your 3 slides. No more than 3 slides (1 for each question). Your first slide should highlight 1 to 3 things. These can be projects/accomplishments that are current or in the past; do not try and highlight your entire career/CV. b) Retreat Assignment 2012: be prepared to present (3-5 minutes maximum) your answer to the following question: What inspires you? Feel free to be creative in how you communicate this answer. You could show a single or small number of Power Point slides that might include photos, figures, or other ways of conveying what inspires you. You could bring music to share. You could tell a story or read a poem. Again, feel free to be
). Providing support for faculty who wish to shift to a learning-centered paradigm in their higher education classrooms. Journal of the Scholarship of Teaching and Learning, 3(3), 69-81. 7. Labov, J. B., Singer, S. R., George, M. D., Schweingruber, H. A., & Hilton, M. L. (2009). Effective practices in undergraduate STEM education part 1: examining the evidence. CBE-Life Sciences Education, 8(3), 157-161. 8. Lock, J. V. (2006). A new image: Online communities to facilitate teacher professional development. Journal of Technology and Teacher Education, 14(4), 663-678. 9. McKenna, A. F., Johnson, A. M., Yoder, B., Chavela Guerra, R. C., and Pimmel, R. (in preparation). Evaluating virtual
0% 75% 25% 100% 60% h 0% 0% 0% 0% Exemplary i 0% 67% 33% 100% 50% Acceptable j 0% 0% 0% 0% Unsatisfactory k 7% 63% 33% 102% 40% 30% 20% 10% 0% a b c d e
instructor, and the group's repeatability of the error (on the specificassignment) is plotted in Figure 2. Page 24.26.5 Figure 2. Plot of the probability distribution functions.For the study, the values of the coefficients from Equation 3 and the weights, , from Equation 1are shown in Table 1. These values were optimized by using the data discussed in the followingsections. Content Priority Prior Experience Repeatability Coefficients i=1 i=2 i=3 a 0 1 0 b
. Assessment and EvaluationWe will formulate an external advisory team for evaluating our progress and suggesting changes asneeded. The team members will be selected from academia, industry, business, and community. Theexternal and internal evaluation and assessment team will be also a part of this advisory team. The short-term assessment and evaluation report will include: (a) students’ grades and progress towards their degrees; (b) students’ progress in their learning of computer technology; and (c) students’ attendance and participation in the project’s academic enhancement activities.Students will evaluate all program activities regarding the relevance and presentation of information,pointing out the program’s strengths
, Conceptualisation in Visuospatial Reasoning Tasks: A Case for Exploring, in Engineering Design Graphics Division 68th Mid-Year Conference. 2013: Worcester, MA.5. Sweller, J., J.J.G. vanMerrienboer, and F.G.W.C. Paas, Cognitive Architecture and Instructional Design. Educational Psychology Review, 1998. 10(3): p. 251-296.6. McGilchrist, I., The Master and His Emissary: The Divided Brain and the Making of the Page 24.314.6 Western World. 2009, England: Yale University Press.7. Tversky, B., Functional Significance of Visuospatial Representations, in The Cambridge Handbook of Visuospatial Thinking, P. Shah and A. Miyake
science,mathematics, and the physical and social sciences. As a result, engineers and scientists are better able topredict and optimize systems affecting almost all aspects of our lives and work, including ourenvironment, our security and safety, and the products we use and export. Other benefits include, but arenot limited to:(a) having one-on-one contact with the instructor, (b) improving qualifications, whether for graduateschool or for industry, and (c) increasing self-esteem. The CSET-STEM Scholars will use the trainingmodules used in the computer technology course and in the NSF/HBCU-UP program at XYZ State.Some of these courses and modules are (a) Web programming (b) Game Programming and GraphicalProgramming, and (c) Application software
resolve them, andwhat issues remained after the discussions. The timeline for the activity is tentative and will beadjusted as we gain experience with the system. (a) Login (b) Quiz Figure 1: Initial ScreensSince many students use smartphones regularly, we are implementing our system to be accessibleboth on smartphones as well as via the desktop. Figure 1 displays the initial screens as seen onan Android device. The login screen is standard and authenticates the user. Once the student haslogged in, he/she will see the current quiz, as in Fig. 1(b). The student will then be able to submit 2 It is not clear that it should be
study consisted of undergraduate students using the lectureLess application intwo different engineering courses taught by two different teachers. The first course (Course A)was a simulation elective consisting of 17 × seniors (~20 yrs of age; 1 female, 16 male) enrolledin either engineering or operations research. The second course (Course B) was a projectmanagement course consisting of 16 × seniors (~20 yrs age; 2 female; 14 male) enrolled in oneof our institution’s engineering programs. Two students were enrolled in both courses. The pilotstudy was blocked into 5 sessions–two administered in Course A, and three administered inCourse B. These sessions were scheduled in the middle to latter half of the semester. Thesessions were selected to
Letter Enhancing the "to complement observations […] survey data were 2011 Comparison A Quality… collected"; "a synthesis of the findings" Incorporating a No 2011 no discussion of why MM was used B Systems… Justification AEE Service
experience. Update the exercise in order to incorporate any new tools and techniques that become available to students. The exercise, no matter how effective as it is, can never be viewed as a finished product—one must always be ready to adapt it to suit new circumstances and learning goals. Page 24.523.14A note concerning Appendices:For those who wish to incorporate the Archimedes-screw exercise directly into their own classes,or to adapt the project for their own use, in Appendices A and B we have included the detaileddrawings and instructions that we distribute to students, as well as specific schedules, notes, andlists of parts
. A log-scale-basedrelationship should be established from the macroscale to the atomic scale to help studentsunderstand the scale and range of the nanoscale. An example of a team beginning to establishthis log-scale relationship can be seen in Figure 3.B. Representations of ScaleThe majority of student teams presented content that demonstrated the concept of scale, butmany of them only incorporated the absolute numeric dimensions of objects (i.e. Quantitative Page 24.609.12Absolute). Magana, Brophy, and Bryan (2012) considered this the highest level of studentunderstanding in Gagne’s taxonomy (i.e. mathematical reasoning), 14 but this study
of project students.The proposed project addressed the following research questions:a. Is the level of audience awareness and interaction (aai) higher for the project students than forthe control group?b. Is the level of message coherence and focus (mcf) higher for the project students than for thecontrol group?c. Is the level of message delivery effectiveness (mde) higher for the project student than for thecontrol group?These questions generated the criteria by which we would evaluate the students’ oralpresentations. Both the questions and the criteria were generated in a July 2011 meeting, duringwhich, after much discussion, the faculty team determined that audience awareness andinteraction, message coherence and focus, and message