]). TABLE I. LITERATURE DEFINITIONS OF MENTORING Definition Source “a collaborative process in which mentees and mentors take part in reciprocal and dynamic activities [7, p. 35] such as planning, acting, reflecting, questioning, and problem-solving” “a form of teaching where faculty members provide advice, guidance, and counsel in the areas of academic, career, and personal (psycho-social) development, which can occur either individually or [11, p. 48] in small groups” “a dyadic, hierarchical
, to incentive effort on this quiz andensure our results reflect knowledge rather than other learning strategies.This is the first study to examine the use of exploratory learning in undergraduate engineeringmathematics. We randomly assigned students to experimental condition, and used the exact sameactivities across conditions—just switching the order of activity and instruction. These featuresstrengthen the causal conclusions we can make about the benefits of exploring before instruction.We plan to replicate and extend these findings with new samples and new topics, withadjustments to the procedures as needed (e.g., requiring students to complete the Geogebra™activity).To our knowledge, this is also the first study to use an online
,” which includes processing prior experiences to direct future choices.Schön and Rose’s definitions enumerate on the temporal aim of reflection. This study will focuson this temporal aim of reflection as it is closely tied to individual’s values of reflection.Our current work is framed by Expectancy-Value Theory (EVT) (Wigfield & Eccles 2000,Eccles & Wigfield 2002) focusing specifically on how individuals value their current reflectionactivities. Task value is influenced by utility value, attainment value, intrinsic value, and cost.Utility value refers to the perceived usefulness of the task towards achieving an individual’sfuture plans or goals. Attainment value refers to the importance of doing well on a particulartask. Intrinsic value
support, and moving to the whiteboard to show initiative.We will also conduct post-event focus group interviews with the three winning teams and askteams to provide additional insight regarding the collected video data. We will choose five toseven critical moments of teams captured in the video and ask participants to explain or elaborateon their experience, thought processes, and interactions. In this way, we plan to explore someways that deep-level diversity attributes impact participants’ micro-level behaviors that buildcollaboration, transcending individual differences. The matching focus group data with videodata will aid in identifying critical patterns of behavior.Our research team expects to develop insights about team learning processes
: http://www.bls.gov/careeroutlook/ [Accessed Feb. 3, 2019].[5] National Research Council, Successful K-12 STEM education: Identifying EffectiveApproaches in Science, Technology, Engineering, and Mathematics. Washington, DC: NationalAcademies Press, 2011.[6] National Research Council, A Framework for K-12 Science Education: Practices,Crosscutting Concepts, and Core Ideas. Washington, DC: National Academies Press, 2012.[7] NGSS Lead States, Next Generation Science Standards: For states, by States. Washington,DC: National Academies Press, 2013.[8] National Science and Technology Council, Federal Science, Technology, Engineering, andMathematics (STEM) Education: 5-year Strategic Plan. Washington, DC: Committee on STEMEducation, 2013.[9] National
understanding by exploring engineering students’ researchexperiences through an interweaving of quantitative survey data and connected qualitativeinterviews. By integrating quantitative and qualitative data, we can better understand students’researcher identities and ultimately better support their research academic and career choices.Introduction and BackgroundUndergraduate research experiences (UREs) give students the opportunity to understand what itis like to be a researcher while enhancing their metacognitive and problem-solving skills [1].Exposure to UREs can help prepare students for a thesis-based graduate program and, morebroadly, can help them clarify their career plans and goals. UREs have been shown to increasestudents’ confidence in their
.225 Passive .1102 10.838 525 .000* Out-of-class .729 .270 In-class .269 .256 Disengaged -.0709 -7.277 536 .000* Out-of-class .340 .250Future WorkWhile we have shown the SCCEI measures modes of cognitive engagement inside and outside theclass distinctly, work remains to clarify the meaning of these constructs to students and educators.We plan to continue this work both quantitatively and qualitatively. We have proposedinterviewing students with respect to their
ability to solve most problems, even if no solution is immediately apparent to me. PSC 9 Many problems I face regularly are too complex for me to solve without assistance. PSC 10 When starting a problem, I tend to try the first solution method I think of to solve it. AAS 11 When deciding on a solution method, I do not consider the chances of success of each method AAS versus the time investment required to implement each method. 12 When I make a plan to solve a problem, I am almost certain that I can make it be successful. PSC 13 I try to predict the overall outcome
issues identified broadly inengineering education community has not yet been made, so comparisons currently are limited.However planned future use of consensus reports to identify issues should enable ad hocjudgements of how EER is achieving policy impacts and identification of relevant concernsexpressed by administrators.Bibliography[1] A. Campanini, “Bologna Process,” in International Encyclopedia of the Social & Behavioral Sciences: Second Edition, 2015.[2] H. Blumer, “Symbolic interactionism: Perspective and method,” in The methodological position of symbolic interactionism, Oakland, CA: University of California Press, 1986.[3] C. Groen, D. Rutledge, and L. McNair, “An Introduction to Grounded Theory: Choosing and
. This core groupof eleven faculty members prepared for a leadership role in the communication project byattending a CxC-sponsored Faculty Institute during the summer of 2005. The engineering teamreceived a comprehensive orientation to the campus-wide CxC program and explored how theirparticipation could lead to the integration of communication goals in the COE curriculum. Theyworked on their individual syllabi, as well as college-wide plans for a COE CommunicationStudio. They shared their ideas about an engineering graduate’s need for communication skillsand their newly-revised syllabi with faculty members representing all colleges, who provided aninterdisciplinary audience for their perspectives. In many cases, the necessary communication
: topic sentence. Paragraph Order Contributes to an Demonstrates a Ineffective or inconsistent Random effective argument; clear plan Points: reinforces the content Transitions Effective and varied Transitions are used Mechanical and/or Transitions are absent (between sentences) transitions greatly consistently repetitive transitions for the most part. assist audience in throughout reading the paper. Points:MECHANICS & LINGUISTICS Word Choice
promote student learning and allow for the on-goingassessment of a set of student outcomes our College intends for our graduates.The Accreditation Board for Engineering and Technology (ABET) expects institutions tohave detailed student learning objectives in place that are consistent with the institutions’mission and with ABET’s criteria 16. With the assistance of an external board made up ofa broad cross section of industry leaders, The Pennsylvania State (Penn State)University’s College of Engineering has developed a set of attributes that address theinclusion of the new demands for professional skills17. Along these same lines, the PennState College of Engineering strategic plan includes the mission to prepare students tobecome World Class
order to plan for future work.GS04 My team made use of incremental goals (i.e., we set short term goals) in order to complete course assignments on time.GS05 My input was used to set our team goals.GS06 This team helped me accomplish my individual goals for this course.The second questionnaire is a 10-item Likert-scale peer evaluation instrument developed tomeasure three team effectiveness factors based on how a student evaluates each individual onhis/her team. Among the 10-item Likert-scale peer evaluation, there is one single item on its owndedicated to measure the general opinion of each specific team member on their whole teameffectiveness is designated TECT. The team effectiveness measured by the 9-item is designatedas
possible solutions without limiting ideas (at this phase)3. Determine ‘best’ solution using a (iv) development by reasoning of the bearings pre-defined analysis technique of the suggestion4. Plan and implement the solution (v) further observation and experiment leading to its acceptance or rejection; that is, the5. Evaluate results conclusion of belief or disbeliefTable 1 Comparison of Problem Solving and a "Complete Act of Thought"It is not enough, however, simply to add to the curriculum assignments that draw uponcritical thinking skills. A tool for assessing those skills is also necessary, to provide bothguidance to students on their current skill
Engineering Education. 94:2, 207-213.14. Light, Richard J., Judith D. Singer, and John B. Willett (1990) By Design, Planning Research on Higher Education. Harvard University Press, Cambridge, 296p.15. Van de Ven (2000) “Professional Science for a Professional School: Action Science and Normal Science” Breaking the Code of Change, chapter 19, edited by Michael Beer and Nitin Nohria. Harvard Business School Press. Boston, 512p.16. van Someren, Maarten W., Yvonne F. Barnard, and Jacobijn A.C. Sandberg (1994) The Think Aloud Method: A Practical Guide to Modelling Cognitive Processes. Academic Press, London, 218p.17. Camacho, M., and Good, R. (1989) “Problem Solving and Chemical Equilibrium: Successful versus
academic plan. Courses that provide a self-pacedcomponent along with in-class contextual math applications may be a solution. Further researchinto these student groups will be conducted as population sizes allow. ReferencesAdams, Carolyn D., "Development of the Self-Advocacy Measure for Youth: Initial Validation Study with Caregivers of Elementary Students with Attention-Deficit/Hyperactivity Disorder" (2015). Graduate Theses and Dissertations. http://scholarcommons.usf.edu/etd/5445Alarcon, G. M., & Edwards, J. M. (2012). Ability and Motivation: Assessing Individual Factors That Contribute to University Retention. Journal of Educational Psychology, 105(1), 129- 137Ayotola, A., Adedeji, T. (2009
pretest (n=130, unpaired t-test, p<0.0001, 35+11 vs26+12). There was no significant difference between any of the exam grades or final coursegrade (77+8 vs 75+7, p>0.2) for students who had completed AP biology versus students whohad not had AP biology.Figure 3b: The combination of individual learning and classroom activities benefited everystudent such that they all achieved the course learning objectives prior to each of the exams.Molecules and Cells is a required four-credit course in the Johns Hopkins University ABETaccredited BME program. Students are told on the first day of the course that they should plan tospend ten to twelve hours on the course each week between attending the three lectures andThursday section, completing the
experience and identify common criteria for comparisons. Using the assignment,the rubric, and their background and experience thus far, the judges reached consensus tocontinue making judgments with a specific emphasis on: 1) student evidence for justifyingdesign decisions, 2) detailing of design plans, and 3) action based upon design analysis whilemaking the judgments. Using these common criteria each judge was asked to complete 10 additionalcomparative judgments. All judges completed at least 10 additional judgments with one judgeopting to continue judging through 22 additional comparisons. The resulting rank order ofstudent work was recorded and a reliability statistic representing the repeatability of theconcluded rank order was
critically examines the design, project plan, analysis results, etc. every weekduring the team meetings. This provides essential feedback to the students during differentphases of the project. These meetings also afford the instructor an opportunity to closely observeteam dynamics and intervene, if necessary. All team members perform peer evaluations to assessthe performance of other members two times during the semester. These peer evaluations areanonymously reported back to the students. For Spring 2016, the 2016 IEEE SoutheastConference Hardware Competition project was used as the course project and assigned to all theteams in both the sections. The main deliverables for this course in Spring 2016 were robotdesign and project demonstration at the
by the class it wascombined with, typically 30 minutes. Next, this same process was repeated with any classesdedicated to material review in preparation for major assessments, to include the finalexamination. The next step in restructuring was to combine complementary lessons in a fashionthat did not overwhelm students with new material. While the previous actions were relativelysimple to execute across all course subjects, this particular step relied heavily on instructorknowledge of the curriculum and individual lesson plans. Not surprisingly, decisions made atthis juncture appear to be the most identified for potential changes during end of course facultyreviews. Instructors with little or no familiarity of course progression found
University c American Society for Engineering Education, 2019 WIP: Assessing the Creative Person, Process, and Product in Engineering Education.Introduction: why assess creativity?This work-in-progress paper investigates different instruments for assessing individual creativity,an essential tool to engineers. Historically, the basis for most modern engineering curricula canbe traced to the 1955 ASEE recommendations on engineering curricular, aka the Grinter report[1] that recommends “an integrated study of engineering analysis, design, and engineeringsystems for professional background, planned and carried out to stimulate creative andimaginative thinking […]”. The National Academies of
Católica de Chile (PUC). (2018). IDI 2015: Antro-Diseño course syllabus. Santiago, Chile: author.Rittel, H. W., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy sciences, 4(2), 155-169.Rosenthal, G. (2004) "Biographical Research," in C. Seale, G. GoboJ. Gubrium, and D. Silverman (eds.), Qualitative Research Practice. London: SAGE. pp. 48-65.Schraw, G., Bendixen, L. D., and Dunkle, M. E. (2002). Development and validation of the Epistemic Belief Inventory (EBI). In Hofer, B. K., and Pintrich, P. R. (eds.), Personal Epistemology: The Psychology of Beliefs About Knowledge and Knowing, Erlbaum, Mahwah, NJ.Vigotsky, L. (1931). Historia del desarrollo
problem directions. Designing task Designing the task's complexity (i.e., how many steps or how much advanced complexity planning is needed for an adequate response). Providing scaffolds Designing the way a problem is broken into sub-tasks or the provision of extra guidance or hints. Expecting length Expecting responses to be an approximate length. Expecting openness Expecting a range of acceptable answers. Expecting task Designing the dependence of separate tasks within a problem. dependence Expecting Designing the extent to which students will likely need to provide explanation interpretability to interpret their responses. Expecting depth of
works closely with the departmental leadership to manage the undergraduate program including: developing course offering plan, chairing the undergrad- uate curriculum committee, reviewing and approving course articulations for study abroad, serving as Chief Advisor, and representing the department at the college level meetings. She is also engaged with college recruiting and outreach; she coordinates three summer experiences for high school students visit- ing Bioengineering and co-coordinates a weeklong Bioengineering summer camp. She has worked with the Cancer Scholars Program since its inception and has supported events for researcHStart. Most re- cently, she was selected to be an Education Innovation Fellow (EIF
undergraduate students in the College of Arts and Sciences (COAS) ofwhich N=1,330 are identified as STEM students. These students will be provided with theinitial 12-question survey. Data analysis will identify student perceptions and will allow forimplementation of programs ranging from faculty mentorship to faculty outreach.To further assess relationships identified, the research team plans to organize focus groups withstudent participants. For example, if lack of awareness is the greatest issue preventing studentsfrom participating in URE, then steps to remediate this can be taken, such as the need forgreater publicizing of campus research opportunities. Once we know more about time usage,we will address time management in terms of studying and
. Confidence values were tabulated as a percentage for eachquestion, and students who self-reported that they attended at least 9 of their years of K-12schooling were flagged for subgroup analysis. This was the only demographic data taken, andnames or other confidential information were not collected. This study complied with theapproved IRB research plan; students’ responses did not affect any grades in the course.Control questionsThe first multiple-choice graphical-literacy question for each session was randomly selectedfrom pool of three control questions. The three control questions were selected from 8th grademathematics questions included in the 2015 and 2016 National Assessment of EducationalProgress (NAEP) multiple-choice question banks [9
identify ways to elicit or remindstudents to use multiple strategies. One limitation of this study was that we used one-minutechunks in the data analysis, which did not give high granularity, but was necessary to simplifythe analysis. For future work, we plan to explore students’ four design strategies usage with abigger sample size and for a longer time. We might also include a second intervention toencourage students’ optimum design strategy usage that might result in better designperformances.AcknowledgmentResearch reported in this paper was supported in part by the U.S. National Science Foundationunder the award DRL #1503436. The content is solely the responsibility of the authors and doesnot necessarily represent the official views of the
Educational Planning, Developing Research Report, and Understanding School Culture. Mr. Beigpourian currently works in the CATME project, which is NSF funding project, on optimizing teamwork skills and assessing the quality of Peer Evaluations.Dr. Matthew W. Ohland, Purdue University-Main Campus, West Lafayette (College of Engineering) Matthew W. Ohland is Associate Head and Professor of Engineering Education at Purdue University. He has degrees from Swarthmore College, Rensselaer Polytechnic Institute, and the University of Florida. His research on the longitudinal study of engineering students, team assignment, peer evaluation, and active and collaborative teaching methods has been supported by the National Science
). Bridging the research-to-practice gap: Designing an institutional change plan using local evidence. Journal of Engineering Education, 103(2), 331-361. http://dx.doi.org/10.1002/jee.20042Fraser, J. M., Timan, A. L., Miller, K., Dowd, J. E., Tucker, L., & Mazur, E. (2014). Teaching and physics education research: Bridging the gap. Reports on Progress in Physics, 77(3), 032401.Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of educational research, 74(1), 59-109.Friedrich, K., Sellers, S., & Burstyn, J. (2007). Thawing the chilly climate: Inclusive teaching resources for science, technology, engineering, and math. To
that the 11items we developed should load unto three factors indicative of social capital as illustrated inFig. 1. We conducted three stages of modelling analyses to test the viability of our hypothesisusing students’ response to the survey. In this section, we discuss our findings and plans toimprove items on the instrument going forward.In the first stage our analysis, we conducted a CFA to test our hypothesized factor loading.Students’ responses to items on the survey did not seem to support the model however. Hence,we resorted to conducting an EFA to determine how many latent factors explains participants’responses to items on the survey in the second stage of our analysis. The correlation matrix fromour EFA analysis showed that a variable