the feedback they received; the intent was to discern if therewas a difference between the Tegrity and Standard written feedback sections in this respect. Thisquestion was utilized in the Fall, 2013, Spring 2014 and Fall 2014 semesters. Forty four studentsin the Tegrity feedback sections and 66 students in the Standard Written feedback sectionsanswered this particular question. It was phrased as follows: Page 26.279.8Answer the following question(s) about feedback and circle all that apply: a. I understood the feedback my instructor gave me. b. The feedback I received conveyed enthusiasm and helpfulness on the part
affectstudent perceptions about the creativity, diversity, and elaboration of their ideas, as well as theirperceptions of the relative difficulty of generating ideas alone or with another person – i.e., in ateam. We begin with some brief background about cognitive style, team ideation, and the use ofperceptions in research, followed by discussions of our research questions, methods, analysis,and results. We close with our conclusions and comments on the limitations of this study and ourplans for future work in this domain.2.0 Background and Previous Work2.1 Cognitive Style and IdeationKirton’s Adaption-Innovation (A-I) theory6 is based on the key assumptions that (a) allindividuals are creative (i.e., generate novelty); and (b) creativity can be
students’ limited programming experience, students are critical ofSECs and require convincing arguments that the taught SECs are relevant.Our pedagogical approach to address these challenges is (a) to run a lab-centered course and(b) to let students see the “real thing” as often as possible.To (a): Lectures introduce concepts and ideas that can later be experienced in carefullydesigned lab sessions. In the labs, we focus on SECs rather than programming by providingstudents with Java programs to be manipulated with tools. Topics covered include: codecommenting with Javadoc, coding standards with Checkstyle, debugging in Eclipse,automated testing with JUnit, test coverage with Emma, automated GUI testing usingsoftware robots, and extreme programming
):508–516, 2012. [3] O. Boubaker. The inverted pendulum: A fundamental benchmark in control theory and robotics. In 2012 International Conference on Education and e-Learning Innovations (ICEELI), pages 1–6, 2012. [4] A. Leva. A hands-on experimental laboratory for undergraduate courses in automatic control. IEEE Transactions on Education, 46(2):263–272, 2003. [5] W. E. Dixon, D. M. Dawson, B. T. Costic, and M. S. De Queiroz. A MATLAB-based control systems laboratory experience for undergraduate students: Toward standardization and shared resources. IEEE Transactions on Education, 45(3):218–226, 2002. [6] B. Aktan, C. A. Bohus, L. A. Crowl, and M. H. Shor. Distance learning applied to control engineering laboratories. IEEE
IP and the contrasting interests in its protection and use. 2. Trade secret (3 weeks) The law of trade secrets introduces students to the major non- statutory protection for IP; this has been a source of protection for software—and might again serve this purpose in light of recent patent cases such as Alice Corp. v. CLS Bank Int’l (2014). a. Existence and protection b. Misappropriation c. Remedies d. Inevitable disclosure 3. Patents (4 weeks) The heart of the course involves the major statutory protection for inventions; the material includes the Constitutional basis for IP protection, the relevant US code, and case law interpreting the statutes with respect to applying and qualifying for
conducted a needs assessment of the faculty, staff, and students. In this study,we investigate current course offerings and ask: 1) What did the lecturers expect students to learn, and what did the students actually learn? 2) How much of current climate related classes are overlaps of previous material as a) listed in the syllabus and b) perceived by students? 3) What do instructors self-report as being needed to manage these topics better?MethodsIn Fall 2014, we interviewed nine faculty members from five departments and two academicadvisors who participated in teaching or recruiting for climate related courses in engineering,architecture, policy, and social sciences. The faculty members ranged from mature lecturers(taught the class
and deleting several variables, the finalcodebook consisted of 28 variables and their associated codes.The two phases of formative coding played an important role in (a) selecting, shaping andclarifying the variables and codes in the codebook, and (b) preparing the reviewers toindependently code the primary research with a high degree of reliability. Table 1 shows asample of the variables and codes in the final version of the codebook.Table 1. A Sample of the Variables and Codes used in the Systematic ReviewResearch Type Design proposal Empirical evaluation Review OtherStudent Model Type Model tracing only Knowledge tracing Constraint-based modeling Bayesian network modeling Expectation
papers were submitted. A stratified sample of 12 papers was selected, based onstudent’s final grade in the course, for coding. The distribution of students electing to completethe optional assignment was fairly evenly spread throughout the course based on final grade,with one exception as shown in Table 1. Only one student received a D for the semester, and thisstudent did not complete the assignment. Table 1. Distribution final course grade and papers selected for coding. Final Grade in Course Total Completed Papers Selected Papers A 62 32 5 B 35 16 3
the first research question (RQ1) (BD). Two prompts focused on identifying ways to improve the experience for undergraduate facilitators related to the second research question (RQ2) (EF). A. What was the goal of your summer program? B. How was the goal of the program achieved? C. To what extent did you as an engineering undergraduate feel that the goal was achieved? D. How did you get involved with the program? E. Describe your experience facilitating your summer program and how it may or may not have impacted your engineering identity F. What were some lessons learned while being a facilitator of the program? Each prompt
. Vancouver, B.C, Canada.Bill Carroll, S. G. (2014). A Hierarchical Project-based iIntroduction to Digital Logic Design Course. Proceedings of the 2014 ASEE Annual Conference. Indianapolis, IN.Burch, C. Logisim. www.cburch.com/logisim.Carroll, B., Geiser, S., & Levine, D. (2014). A Hierarchical Project-based Introduction to Digital Logic Design Course. Proceedings of the 2014 ASEE Annual Conference. Indianapolis. IN.Carroll, C. (2012). Teaching Digital Design in a Programmable Logic Device Arena. Proceedings of the 2012 ASEE Annual Conference. San Antonio, TX.Devore, J., & Soldan, D. (2012). VisiBoole: Transforming Digital Logic Education. Proceedings of the 2012 ASEE Annual Conference. San Antonio
confinement provided tothe soil beneath the bearing area is limited by the passive condition in the soil beyond the lateralextents of the bearing area. The failure surface in this region is characterized by a planar surfaceinclined 45-ϕ/2 above horizontal. Between active and passive zones, there is a transition zonecalled the Prandtl zone in which the failure surface follows the shape of a log spiral. The active,Prandtl, and passive zones are respectively labeled A, B, and C in Figure 5. Page 26.1709.7 ce rfa su ure ail
included as control variables that would allow theresearchers to examine the influence of prior knowledge, frequency of simulation interaction,and perceived preparation.There were also two items on the survey where students were asked to “Select all the skills youfeel MyITLab prepared you for” (simulation preparation) and “Select all of the skills you feltwere on the Excel exam” (application). Each list contained the same 19 skills including: skills a)taught in the simulation (MyITLab) and tested with the application (Excel Exam); b) taught inthe simulation, but not tested for with the application; c) not taught in the simulation, but testedfor with the application; and d) not taught in the simulation nor tested for with the application.These
, Scenario cards, craft suppliesTime Required- 60 minutes for class session.Workshop Procedures- Use of Scenario Cards to walkthrough the design process-This activity is design as a quick overview of the design process from project identification to prototypingand redesign. The participants will select a scenario card that represents current projects in the EPICSProgram. In the design process, one of the most difficult pieces is determining a project that would besuccessful that would: a) meet the needs of a group in the community, b) pique the interest of the studentsand c) deliver the academic content that will fulfill educational requirements. As the teacher participantsare working to create a needs assessment for their community they will
it differs from the first law of thermodynamics analysis, I initially startthe topic with the following example from everyday life. It should be noted that in this paper the italic text represents what the author presents in hislectures in the class. Imagine that there are two professors, Dr. X and Dr. Y, teaching the same course, e.g. AppliedThermodynamics (!). At the end of the semester, both classes end up with the average grade B inthe course. Which professor did a better job? If we just look at the final results and consider them as the parameter to evaluate theperformance of the professors, then both professors are doing equally good (or bad!) job. Thisapproach resembles the first law of thermodynamics analysis or the energy
willensure that it conforms to educational standards as they transform in the future.References1 “Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities.” INCOSE SystemsEngineering Handbook, Ver. 3.2.2, INCOSE-TP-2003-002-03.2.2. October 2011.2 Royce, W. W., “Managing The Development of Large Software Systems.” Proceedings from IEEE WESCON,Pages 1-9, August 1970.3 Boehm, B. W., “A Spiral Model of Software Development and Enhancement,” ACM SIGSOFT SoftwareEngineering Notes, Volume 11 Issue 4, Pages 14-24, August 1986.4 Forsberg, K., and Mooz, H. “System Engineering for Faster, Cheaper, Better.” Proceedings of INCOSE 1999,INCOSE, Brighton, 1999.5 Forsberg, K., Mooz, H., and Cotterman, H., “Visualizing Project
Course – Calculus II -0.4045 0.1546 Grade – A 1.4914 0.1914 Grade – B 1.3151 0.1894 Grade – C 0.6959 0.1957 Grade – D 0.3919 0.2455 Grade – F 0.1231 0.2084 Page 26.1225.5 Grade – P 1.2672 0.2541 Gender
individually watch the corresponding video lecture(s). Thestudent will then be required to log into the CONSIDER system where she will be presented withthe quiz related to the topic. The quizzes will be similar to the example above but, for now, let usassume there is only one question, in particular, item (3) from the example. The student will berequired to make a specific choice (such as “domain” or “problem” or “solution”) and, in addition,will be required to include a brief explanation of her choice.The figure shows the loginscreen and the next screenof the current prototypeof the CONSIDER system,implemented as an Androidapp. Once the student hassuccessfully logged in, thesystem displays the quiz,Fig. 1(b). The student doesnot need to submit the an
joint characteristics, the Z co-ordinate value of the right shoulder(ShoulderRight_Z in Figure 7) was shown the be the strongest attribute for predicting which ofthe functions was being performed by a student. The resulting decision rule is of the form: If ShoulderRight_Z<=0.916808 meters, relative to the fixed position of the AFS, THEN Function A (e.g., hammering a small nail) is being performed If ShoulderRight_Z>0.916708 meters, relative to the fixed position of the AFS, THEN Function B (e.g., hammering a large metal object) is being performedThis prediction could also be used to determine when a student was performing an anomalousaction. I.e., if the instructor has determined that students should be hammering a
students were surveyed throughout the semester as they completed different assignmentsrelated to design of a product. The items of the instrument gauged student perception of theirdevelopment of competencies related to understanding requirements, teamwork competencefrom an individual and team manner, communication, and understanding the design process. Theauthentic design problem that the students addressed in the class required them to use concepts,knowledge, and tools that they have been introduced to during their previous six semesters.In this paper we investigate the following competencies (Table 3): (A) Understandingrequirements of a project (B) Managing a team (team) (C) Managing a team (individual) (D)Communication (E) Understanding design
students arerequired to take part in a year-long capstone program consisting of a one quarter lecture courseand a follow-on two-quarter industry-sponsored capstone project. Feedback from students,alumni and capstone sponsors indicated that: a) students needed better preparation before startingtheir projects, b) we should introduce a realistic mini-project, and c) students should learn andapply project management, time management, teamwork, and communication skills. Theredesigned lecture course of Faust et al.19 has a term-long practicum project that mimics thefollow-on project, requiring completion of a project from concept to test. Here we outline theassessment tools used to quantify the experiential learning of the students engaged on the
mentor 7,14.This paper reports the pilot research study findings of the first author’s dissertation research.The dissertation research study examines the lives and mentoring experiences of ten selectAfrican-American STEM mentors. Study participants are African-Americans PhDs whopossesses at least one STEM degree and have: a) a history of impacting STEM undergraduatestudents as evidenced by their substantial track records for facilitating undergraduate studentsuccess in STEM fields, b) a history of commitment to mentoring underrepresented minorityundergraduates, and c) national acclamation and/or recognition by their peers and prestigiousorganizations and institutions as exemplars for their work with mentoring underrepresentedminorities.This
Expert Systems With Applications (pp. 9939-9945) Vol 39(2012) Elsevier6. http://decoda.univ-avignon.fr/projet.php7. Bechet, F., Maza, B., Bigouroux, N., Bazillon, T., El-Bèze, M., De Mori, R., & Arbillot, E. DECODA: a call-center human-human spoken conversation corpus.8. http://www.wsj.com/articles/metadata-can-expose-persons-identity-even-when-name-isnt-1422558349 Page 26.439.119. http://bits.blogs.nytimes.com/2015/01/29/with-a-few-bits-of-data-researchers-identify-anonymous-people/?_r=010. http://www.sciencemag.org/content/347/6221/536.full?intcmp=collection-privacy11. Speaker Identification by Speech
Education, 37(2), 125-132.7. Andrews, T., & Patil, R. (2007). Information literacy for first-year students: An embedded curriculum approach. European Journal of Engineering Education, 32(3), 253-259.8. Berland, L., McKenna, W., & Peacock, S. B. (2012). Understanding Students' Perceptions on the Utility of Engineering Notebooks. Advances in Engineering Education, 3(2).9. Berndt, A., & Paterson, C. (2010). Global engineering, humanitarian case studies, and pedagogies of transformation. In Transforming Engineering Education: Creating Interdisciplinary Skills for Complex Global Environments, 2010 IEEE (pp. 1-19). IEEE.10. Brophy, S., Hodge, L., & Bransford, J. (2004, October). Work in progress
). a a a a, b 20 b a, b b 15 Average score 10 5 0 1‐1 1‐2 1‐3 4‐1 7‐1 8‐1 8‐2 Semester‐Problem Figure 1. Mean argumentation (Table 1
Prestige: The Experiences of Institutional Striving from a Faculty Perspective," Journal of the Professoriate, vol. 4, pp. 39-73, 2011.[6] M. Nerad, "The PhD in the US: Criticisms, Facts, and Remedies," Higher Education Policy, vol. 17, pp. 183-199, 2004.[7] E. de Weert, "The Organized Contradictions of Teaching and Research: Reshaping the Academic Profession," in The Changing Face of Academic Life: Analytical and Comparative Perspectives, J. Enders Page 26.1608.8 and E. de Weert, Eds., ed Great Britain: Palgrave Macmillan, 2009, pp. 134-154.[8] B. R. Clark, The Academic Life: Small Worlds, Different
Stone. Haptic feedback: A brief history from telepresence to virtual reality. In Haptic Human-Computer Interaction, pages 1–16. Springer, 2001.[21] OAJ Van der Meijden and MP Schijven. The value of haptic feedback in conventional and robot-assisted minimal invasive surgery and virtual reality training: a current review. Surgical endoscopy, 23(6):1180–1190, 2009.[22] Richard Q Van der Linde, Piet Lammertse, Erwin Frederiksen, and B Ruiter. The hapticmaster, a new high-performance haptic interface. In Proc. Eurohaptics, pages 1–5, 2002.[23] N. Hungr, B. Roger, A.J. Hodgson, and C. Plaskos. Dynamic physical constraints: Emulating hard surfaces with high realism. Haptics, IEEE Transactions on, 5(1):48–57, Jan 2012.[24] R.Q. van
the Outreach Chair of the OSU American Society of Engineering Education Student Chapter. His research interests include: (a) technology use, (b) diversity and inclusion, and (c) retention and success, with a particular focus on students in STEM fields. To contact Dr. Long, e-mail long.914@osu.edu.Dr. Joseph Allen Kitchen, The Ohio State University Dr. Joseph (Joey) A. Kitchen is a postdoctoral researcher and program coordinator with the Center for Higher Education Enterprise (CHEE). Dr. Kitchen manages CHEE’s longitudinal, mixed-methods study of college outreach and academic support programs. He earned a Ph.D. in Higher Education and Student Affairs, a Master’s of City and Regional Planning, and a Bachelor’s in
laboratory than a traditionalacademic laboratory. One example is use of professional specifications (e.g. ASTM) as opposedto laboratory manuals. Secondly, multiple field trips to commercial facilities (e.g. Figure 1a)provide students with context for laboratory experiments. A third example is writing assignmentsclosely aligned to professional reports, since most practitioners submit fewer, yet morecomprehensive, reports to clients. Four reports are submitted for all laboratory exercisesperformed (soil/soil stabilization, aggregates, concrete, and asphalt) that also include contentrelated to applications and design. a) Asphalt Concrete Facility b) Example Laboratory Space
perspective with mental models. in 118th ASEE Annual Conference and Exposition, June 26, 2011 - June 29, 2011. 2011. Vancouver, BC, Canada: American Society for Engineering Education.34. Harper, B. and P. Terenzini. The effects of instructors' time in industry on students' co-curricular experiences. in 2008 ASEE Annual Conference and Exposition, June 22, 2008 - June 24, 2008. 2008. Pittsburg, PA, United states: American Society for Engineering Education.35. Padilla, M.A., et al. Drawing valid inferences from the nested structure of engineering education data: Application of a hierarchical linear model to the SUCCEED longitudinal database. in 2005 ASEE Annual Conference and Exposition: The Changing Landscape of
, and flex” tag types9(approximate cost $4 per tag) can operateclose to fluid environment. The Confidex Ironside10 tag ($ 7 per tag) is an industrial typedesigned to be used directly on metal surfaces, see figures 3a and 3b. (a) (b) Figure 3. (a) ALN 9640 and Omni Tags, (b) 9640 & Confidex tags, The individual tags performances were evaluated in the lab environment. A “proximity test”,which determines the reads/s as a function of distance between the tag and the reader antenna, isa good qualitative indicator of their sensitivity (RSS) and performance7. The tested tag wasplaced at a distance from the reader antenna and oriented such