progressing at an accelerated pace in recent years. Most people perceiveAI as creating human-like robots or humanoids, it is more than that. AI is to use neural networktheories to simulate the human thinking processes by computers; to inject the human’s ability toscreening data, provide sound reasoning, to make self-reflection, and self-correction decisions tothe computers. According to TechTarget, artificial intelligence can be broken down into twomain categories: Weak AI (or called Machine Learning category), which is a machine’s ability tobe trained to perform specific tasks. Strong AI (or Deep Learning category) is the machine’sability when equipped with enough cognitive skills, to find solutions to problems on their own.Particular applications
National Science Foundation under GrantsNo. 1360987/1361028. Any opinions, findings, and conclusions or recommendations expressedin this material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.We would like to thank Amelito Enriquez for partnering with us to pursue this work. We wouldalso like to acknowledge the insight and contributions of advisory members Monica Cardella,Holly Matusovich, C. Judson King, and Mark Graham.References Cited 1. U.S. Department of Education, National Center for Education Statistics. (2016). Digest of Education Statistics, 2015 (NCES 2016-014), Chapter 3. 2. http://www.bestcolleges.com/features/49-best-colleges-for-older-students/; accessed: Feb 10
the student perspective and moving beyond traditionalinstitutional reporting begins to elucidate and provide evidence about the “true” engineeringgraduate experience. This increasingly accurate reflection of graduate experiences providesnovel insight into the experiences of students that have been traditionally ignored or unjustifiablylumped in with other students who share the title of graduate student.The initial findings of our qualitative analysis indicate that student perceptions of control and theability to utilize multiple resources to overcome barriers are fundamental to the successfuldevelopment of their identities and motivations. Students’ perceptions of control provide ameans of discerning the difficulty of a given choice or task
cohort, but they also have the PEEPS Support Team (i.e., Engineering Student Supportstaff, engineering faculty, AmeriCorps VISTA member, financial aid staff) available forassistance. We have multiple avenues of inquiry to the PEEPS experiences, such as quarterlycheck-ins (that are also individualized advising sessions), periodic reflections, and a end of theschool year focus group.Therefore, while the PEEPS project enables the cohort members to take certain courses together,study with one another, and socialize together, do they really support each other academicallyand emotionally to make a difference? How do the PEEPS Support Team and PEEPS activitieshelp students, if any? How can we take what we’ve been learning through the PEEPS project
Processing Technical Committee for the IEEE Circuits and Systems society. His research interests are in digital signal processing, speech processing, biometrics, pattern recognition and filter design.Nidhal Carla BouaynayaDr. Kevin D. Dahm, Rowan University Kevin Dahm is a Professor of Chemical Engineering at Rowan University. He earned his BS from Worces- ter Polytechnic Institute (92) and his PhD from Massachusetts Institute of Technology (98). He has pub- lished two books, ”Fundamentals of Chemical Engineering Thermodynamics” and ”Interpreting Diffuse Reflectance and Transmittance.” He has also published papers on effective use of simulation in engineer- ing, teaching design and engineering economics, and assessment of
staff.Furthermore, the statements are reconfirmed at least once annually or removed from thedatabase. This ensures that the statements are not outdated.As stated on the TRB website: An important function of the Transportation Research Board (TRB) is to stimulate research that addresses concerns, issues, or problems facing the transportation community. In support of this function, TRB Technical Activities standing committees identify, develop, and disseminate research need statements (RNS) for use by practitioners, researchers, and others. The RNS on this website have been developed by the technical committees.4To the authors’ knowledge, no other field maintains such an extensive research needs databasethat reflects the
detail todevelop a model that accurately reflects why and how students have difficulty with problemsolving in biomedical engineering design and (2) determine correlations between knowledgeretention and metacognitive awareness with problem solving success.The following research questions will be addressed: 1. How are problem solving schemas developed and used by students in biomedical engineering? How do these schemas differ for high and low performing students? 2. How do students’ problem solving abilities change during and throughout STEM courses? 3. How are students’ misconceptions related to knowledge retention and their mistakes with connecting different parts in problem schemas? 4. How is a students’ metacognitive
; Huggard, M. (2005). Computer Anxiety, Self-Efficacy, Computer Experience: An investigation throughout a Computer Science degree (pp. S2H–3–S2H–7). IEEE. https://doi.org/10.1109/FIE.2005.161224621. Turner, D. W. (2010). Qualitative Interview Design: A Practical Guide for Novice Investigators. The Qualitative Report, 15(3).22. Walther, J., Sochacka, N. W., & Kellam, N. N. (2013). Quality in Interpretive Engineering Education Research: Reflections on an Example Study. Journal of Engineering Education, 102(4), 626–659. https://doi.org/10.1002/jee.2002923. Patton, M. Q. (2014). Qualitative Research & Evaluation Methods: Integrating Theory and Practice (4 edition). Thousand Oaks, California: SAGE Publications, Inc.24
objective measure of the core reasoningskills needed for reflective decision making concerning what to believe or what to do.” [6]Initial Offerings and Course ModificationsThe original concept for the course included a hands-on component using Lego Mindstorms.The original conception also restricted the course to non-engineering majors [8], largely becauseengineering majors were thought to have a considerable advantage working with the LegoMindstorms. The hardware requirement imposed severe constraints on another important coursegoal, online delivery. Ultimately we decided not to implement the hands-on component. Thathad the side benefit of allowing us to open the course to all majors, including engineeringmajors. The course discussion boards have
students, as well as tothemselves. Furthermore, it shows that some of the REU students started to reflect about theeffectiveness of their “teaching” and of ways to further improve the benefit to other students inthe future.Given that the outreach activity took place close to the end of the school year, efforts to get thealready time-strapped elementary school teachers to complete a survey were unsuccessful.However, email feedback from the teachers indicated that they were very happy with theactivities as they saw their students engaged and excited about engineering and hands-onactivities. Efforts will be made in the future to obtain additional assessment data to gage theimpact on the K-5 students.All and all, this was a positive experience for all
IntroductionAlthough there are many standardized questionnaires used to assess students’ self-regulatorybehavior and motivation to learn, the MSLQ is one of the more widely used in general educationresearch [1, 2, 3]. The MSLQ is a self-report instrument specifically designed to assess students'motivational orientations and their use of different learning strategies. . By focusing on the rolesof both motivation and cognition during learning, the MSLQ reflects the research on self-regulated learning, which emphasizes the interface between motivation and cognition [4, 5].Prior research using the MSLQ has found relationships between constructs on its motivationalsubscales such as: intrinsic goals, extrinsic goals, task value, control of learning beliefs, self
global, h. economic, environmental, and societal context i. A recognition of the need for, and an ability to engage in life-long learning j. A knowledge of contemporary issues An ability to use the techniques, skills, and modern engineering tools necessary for engineering k. practice.In addition to ABET student outcomes, learning outcomes listed in the TUEE Phase 1 reportwere considered carefully because they reflect industry perspectives. Outcomes are rated byimportance and by extent to which they are observed in engineering graduates [1]. Becauseneither ABET nor TUEE outcomes were defined in terms that are consistently interpreted, theauthors developed definitions of fifteen top outcomes that
by choosing a different path of study. Phase II of the project begins in Fall 2017with data collection on self-regulated decision making, major fit, and self-regulated learning inorder to map real-world behaviors (major changes) to self-regulated decision-making theory20.AcknowledgementThis material is based upon work supported by the National Science Foundation (NSF) underGrant No. 1554491. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NSF.References1. Pascarella ET, Terenzini PT. Predicting voluntary freshman year persistence/withdrawal behavior in a residential university: A path analytic validation of Tinto’s model. J
addressing students’ metacognitive skills and the ability to self-regulate their learning. To that end, the instructor began the semester with a reflective exercisethat asked students to read Robert Leamson’s (2002) essay “Learning (Your First Job),”comment online about their impressions of the article, and be prepared to discuss in class. Thereflective comments from students regarding this essay were revealing: “These are all things thatwere not explicitly obvious to me as a student and I would have very much liked to have readthis as a freshman.” This piece is especially important as we believe it made an importantdifference in students’ capacity to persevere in this class.The difference in DFW outcomes between the two engineering courses for this
, problem based learning andactive learning approaches, combined with laboratory courses. The use of formative assessmentis reflected in the literature. Enhancement comes in the form of providing supplemental learningopportunities that go beyond the textbook and include teaching assistant (TA) guided instruction,use of web resources and enhanced guided notes. There is a prevalence of leveraging technologyto blend or flip classes. Authentic environments that include interdisciplinary, experiential,collaborate, inquiry, challenge, and service learning are also prevalent.Future WorkA trend analysis of the frequently identified practices may help characterize whether a particulartopic is becoming more or less popular. Additional work to characterize
quiz as seen by students. At the beginning of each class, the instructor poses each ofthe Conceptual Questions from the pre-work assessment to the class, takes a “vote” on it, andthen leads a discussion on the different answers and approaches. These discussions encouragestudents to reflect on the reasoning behind their misconceptions and how it relates to thereasoning behind the actual solutions. Namely, the students and the instructor discuss why some(incorrect) answers appeared attractive and seemed right, and ultimately what is (or should be)the reasoning behind choosing the one correct answer. However, these interactive discussions are rather brief, taking just a very small portion of the class, to enable the other components ofinstruction
number of students obtaining more than 70% of the total points of 50. Figure 2. Students’ performance in Midterms of Spring 2015 and Spring 2016.Discussion of the OutcomesThe purpose of the study was to improve students’ success rate by increasing the percentage ofstudents receiving points 70% or higher, while decreasing the number of students receivingpoints 60% or lower in the Midterms. The results from only the Spring 2016 semester shows thatdividing the course material and assessing the students by three Midterms instead of twoMidterms helped to reach the study objective. Overall, the class performance reflects thefavorable trend of increased percentage of students receiving points 70% to 80
engineering problem. Can partially verify whether a solution meets the given requirements of the problem. Satisfactory: Student can implement a basic solution to a given engineering problem. Can verify whether a solution meets the given requirements of the problem at a basic level. Exemplary: Student can fully implement an advanced solution to a given engineering problem. Can fully verify whether a solution meets the given requirements of the problem at an advanced level.It is important to realize that the Program Outcomes and corresponding performanceindicators are general in nature and not course specific. This requires that each instructorusing the rubric to reflect seriously on the choice of appropriate course
on the analysis of similarresearch practices5. The research involved 1200 students (bachelors and masters), as well as by graduatesof the Kazan National Research Technology University.The studies were carried out usingthe technique of planned behavior (Theory of planned behavior according to which anybehavior reflects the influence of three groups of factors: attitude toward the behavior,subjective norm and perceived behavioral control). The research proved that at the beginning of the training more than 75% of studentsplan to get employed immediately after accomplishing the training, and as few as 10% ofrespondents are willing to work in small-size companies with less than 50 persons in staff.The percentage of students
. The scintillator plate absorbsthis energy and emits light of a known frequency. The plate is wrapped in reflective material, sothe light bounces around until it finds the photomultiplier tube, which absorbs it and emits a signal, Fall 2017 Mid-Atlantic ASEE Conference, October 6-7 – Penn State Berksprocessed by a nearby computer. Data from each computer in the array will be automaticallyanalyzed at QCC. The arrays pursue serious scientific research, and high school studentsparticipate actively in this research. Student research begins with learning practical hands-onlaboratory skills in assembling the detector components. Fermilab has donated the scintillatorplates, pieces of old scintillator panels no longer in use. Fermilab
tools freed up Leslie in the lab space; Leslie didn’t haveto run from group to group assisting each group individually. Her attention to the whole roomand the larger task of inquiry overall could be wider than if she were narrowed in on helpingindividual groups.Leslie held a constructivist stance in inquiry instruction. I believe that Leslie desired studentswork with data from empirical observation and withheld giving away the steps because Lesliethinks learning happens when students construct understandings from experiences,communication, and reflection, indicating a constructivist learning stance. A constructivist stanceis made up of many smaller reasoning resources including perhaps, “knowledge is constructednot given” and others. Leslie
as they apply to K-12 education. In 2013, the Next Generation Science Standards reflected the growing interest in K-12 engineering by integrating it with the science curriculum. In contrast to the prior standards, the NGSS explicitly included engineering as a foundational component of the curriculum, with engineering concepts included in the requirements for each grade level. In fact, the final NGSS document body included over three hundred uses of the word engineering. Taking advantage of recent research into science learning, the standards also propose a new view of teaching science. Whereas the earlier standards heavily emphasized science content knowledge, the new standards took a more holistic view of science. Science education
clarity.Summaries of the survey responses and narrative themes were shared with all of the researchersand reviewed collaboratively to verify our understandings and to increase the trustworthiness ofour conclusions.20In this paper, we have excerpted descriptive data that inform our evaluation by includingresponses suggesting actions that Boise State University, or others, can take to improve thelikelihood that future girls will select and remain on a STEM pathway. The participantdemographic data in Table 2 provides a background to the narrative passages, which are sharedanonymously to protect the confidentiality of our participants. Focus group participants indicatedthey responded to our survey and are assumed to be reflected in the demographics shared
in the ways hands-on activities such as making, technology, and games can be used to improve student engagement.Dr. Kevin D. Dahm, Rowan University Kevin Dahm is a Professor of Chemical Engineering at Rowan University. He earned his BS from Worces- ter Polytechnic Institute (92) and his PhD from Massachusetts Institute of Technology (98). He has pub- lished two books, ”Fundamentals of Chemical Engineering Thermodynamics” and ”Interpreting Diffuse Reflectance and Transmittance.” He has also published papers on effective use of simulation in engineer- ing, teaching design and engineering economics, and assessment of student learning.Dr. David L. Silverstein P.E., University of Kentucky David L. Silverstein is a
, statics and stress, filtration and chemical precipitation, and soon). These engineering concepts are not abstracted from social, political, and economicconsiderations. Rather, engineering is imbued with social context. The RPG offers studentsopportunities to reflect on economic, geographical, economic, and philosophical issues whilelearning the technical skills they need to make informed decisions to address the needs of arapidly expanding population.Introduction and Statement of the ProblemIn 1945, when the French mathematician Jacques Hadamard sought to uncover the thoughtprocesses of mathematicians, he approached Albert Einstein, who suggested that “combinatoryplay seems to be the essential feature in productive thought.”1 For many years
“using mathematics andcomputational thinking”, as well as crosscutting concepts focused on “systems and systemmodels” 11. Engineering design projects provide extensive opportunities to engage in practicescommon to both the CSSM and Framework: defining problems, constructing explanations,developing models, using appropriate tools and attending to precision.Engineering design done well requires an unfamiliar role for many teachers. Teachers must shiftfrom evaluative to interpretive perspectives while moving away from guiding students to correctanswers and toward emphasizing exploration and engagement 12. Teaching practices must fosterstudent reflection on their own reasoning and interpretation of problems 13. Rather than warningstudents when they
-125.5. Carter, J. F., and Van Matre, N. H. (1975) Note taking versus note having, Journal of Educational Psychology 67, 900.6. Von Konsky, B. R., Ivins, J., and Gribble, S. J. (2009) Lecture attendance and web based lecture technologies: A comparison of student perceptions and usage patterns, Australasian Journal of Educational Technology 25.7. Larkin, H. E. (2010) "But They Won't Come to Lectures..." The Impact of Audio Recorded Lectures on Student Experience and Attendance, Australasian Journal of Educational Technology 26.8. Craig, P., Wozniak, H., Hyde, S., and Burn, D. (2009) Student use of web based lecture technologies in blended learning: Do these reflect study patterns, Same places, different
SET, particularly within engineering?1. Miller EJ, Seldin P. Changing Practices in Faculty Evaluation. Academe. 2014;100(3):35.2. Yoder BL. Engineering by the Numbers. ASEE. 2015.3. Beleche T, Fairris D, Marks M. Do course evaluations truly reflect student learning? Evidence from an objectively graded post-test. Econ Educ Rev. Elsevier Ltd; 2012;31(5):709–19.4. Elmore PB, LaPointe KA. Effects of teacher sex and student sex on the evaluation of college instructors. J Educ Psychol. 1974;66(3):386–9.5. Bennett SK. Student perceptions of and expectations for male and female instructors: Evidence relating to the question of gender bias in teaching evaluation. J Educ Psychol
Figure8DwarfMountainPineChallengesandStrategiesdiagram 8The second diagramming example is that of the Cicada. The wings of Cicadas shed dirt andwater while inducing a self-cleaning effect to prevent contamination, erosion, and bacterialaccumulation. The biological structure of these wings also creates an anti-reflective coating.Wings contain thousands of hexagonal sections across the surface. These sections have nipple-like protrusions that hold air pockets between them to prevent the build-up/accumulation ofbacteria, residue, and matter.9 Figure9CicadaChallengesandStrategiesdiagram
will have to cultivate if they are interested in creating a TAP of their own. Our hope isthat TAP will be a pilot for other programs that address this need across the country.AcknowledgmentsThis work is currently supported by the Battelle Engineering, Technology, and Human Affairs(BETHA) Endowment and an Impact Grant from The Ohio State University Office of Outreachand Engagement, a program supporting innovative and scholarly engagement programs thatleverage academic excellence of The Ohio State University in mutually beneficial ways withexternal partners. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the BETHAEndowment or the Office