in terms of the themes and overarching goals. Faculty have varying levelsof input into and interaction with the execution of the strategic plan with the majority of theirfocus concentrating on the day-to-day operations of their research and academic programs.Faculty well-being surveys can reflect the status of the faculty views on their collectiveexperiences in an institution; some issues raised in these surveys can be addressed in targetedcollege of engineering faculty development initiatives.The purpose of this paper is to describe the process of how an established college of engineeringfaculty development office at North Carolina State University integrated the findings of aqualitative faculty well-being survey and programmatic faculty
eliminate any issues a minority of students had because they could not ask questionswhen watching video lectures. The overall depth and quality of questions generally reflected thestatus of the course as being outside the core interests of the students, who were mostlyMechanical Engineering majors.Note that the use of something like Piazza seems to be critical to making flipped classroomswork. Students need to know that they have a mechanism for asking questions, no matter whereor when they are working. Also, it encourages students to help one another. There is littlecompetition for grades in these courses because standards are clear and students are remindedover and over that our goal is that, someday, everyone will earn an A. Piazza also provides
personalized feedback. 5)Reflection allows students to think about how their pre-existing ideas about a topic have evolvedand expanded through completing the learning block. In this study, we examined the impact ofthe “Idea Generation” and “Concept Development” learning blocks. Each learning block takesapproximately 6 hours to complete and is built on pedagogical best practices that combines self-study with remote feedback [29]. It focuses on a student-centered teaching approach developedaround the constructivist learning theory [30], which allows content sharing online without timeand location limitations [31]. The learning blocks are built around the best practices in teachingand learning to promote active engagement, which is essential for success
intheir home country their entire life. A follow-up ANOVA was run between the two variables andthey were found to be predictive of each other. Over 80% of those who spoke English as asecond language and said that had lived outside of their home country said that the United Stateswas the country they had lived in for more than 6 months outside of their home country. Asmany of this subset of respondents came from different countries, they may not have deemedtheir responses as unethical when reflecting on the ethical underpinnings of their home country.As this subset of students also learned English as a second language, a limited vocabulary andlack of fluency in English may have negatively impacted their ability to answer the writtenresponses, or
4.00 0.79 0.003 I plan to use technology in my future career 3.00 4.33 0.57 0.057 I am interested in careers that use technology 2.60 4.20 0.89 0.016 I plan to use engineering in my future career 2.77 4.11 0.71 0.000 I am interested in careers that use engineering 3.00 4.44 0.55 0.005As can be seen in Table 4, the change in student STEM career interest as reflected in all but onequestion was significant. There was an upward trend in the low interest students’ interest incareers in STEM fields. The only question that was not significant is “I plan to use technology inmy future career” with a p-value of 0.057. The same
. Delaine is a co-founder and past president of the Student Platform for Engineering Education Development (SPEED) and has served two terms as an executive member of the International Federation of Engineering Education Societies (IFEES) as a Vice President for Diversity & Inclusion. He is investigating university-community engagement as empow- erment settings and working to further the research agenda of the global community of practice within Diversity and Inclusion in Engineering Education. His research laboratory aims to support an inclu- sive, global pipeline of STEM talent and to unify the needs of the engineering education stakeholders in order for engineering education to more accurately reflect societal
similar teaching styles.In Fall 2016, during the first stages of the re-design, two junior faculty members were added, and everyone waslearning and sharing experiences. All four were in general agreement about all class activities and assessments (thathad not been modified), however, were adjusting to the changed format as well as building the class activities onlya few days ahead. There was not much time for reflection during the semester.In Fall 2017, a junior faculty member replaced one of the original instructors on the DE team. In the summer of2017, the three junior faculty members attended a 2-day institute on active learning. The institute challenged themto explore new learning spaces and to strive for more student-student collaboration
. entrepreneurial mindset (e.g., Fry,2011; Kriewall and Mekemson, 2010; Condoor and McQuilling, 2009; Bilan et al., 2005).Finally, educators are thrusting experiential exercises into the curriculum, i.e. methods teaching(Cadotte, 2014; Greene and Neck, 2011). From our perspective, this mixed modality approachoffers students a dynamic learning environment and an equally exciting opportunity for facultymembers to conduct research related to student experiences and behaviors.In this dynamic classroom setting, which includes historical context, reflection on one’s mindset,process learning, and methods teaching, we developed a relevant research question, which is thebasis for this paper: Does an entrepreneurial mindset assessment predict a student’s behavior
as line, rectangle, and textbox primitivesfrom PyGame. Note that the process in the example is isometric, or constant volume. Thediagram reflects this fact in that the position of the piston has not risen or fallen. As the problemparameters change, that affects not only the data values shown in the figure but also the positionof the piston accordingly.Figure 7: Formatted output of problem descriptionAs was mentioned previously, rarely does automatically generated text not require some amountof human intervention in the form of additional post-processing to correct grammar mistakes, topossibly correct formatting, or to add a human flair or poetry to otherwise mechanical prose.Conclusions and Recommendations for Future WorkThe method outlined
design of the VR teachingmodule to be more immersive and visualized. The current VR module is a semi self-paced tutorial.Concurrent research (Phase III) is being conducted to investigate how well students understand thequeuing theory concept using this updated VR teaching module versus traditional classroomlecture. Data is currently being collected using a different set of students with the same conceptualquiz but taught the topic in a traditional classroom manner (control group). Afterwards, we plan toprovide a comparative analysis of both approaches, control group versus experimental group anddisseminate the results.. The sections discussed below only reflects how well the students performusing the VR training module (experimental group
havebeen generally positive. The authors will use results of future surveys to assess the success ofthis project and to improve student engagement. AcknowledgmentsThe research presented in this paper is partly supported by the Kern Family Foundation grantentitled “Implementation of Innovation and Entrepreneur Mindset Concept into Mechanics ofMaterials”. We would like to acknowledge and appreciate the supports by Dr. Massoud Tavakoliand Dr. Mohammad Torfeh, principal investigators of the grant at Kettering University. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the sponsoring organizations. References[1] J. Baqersad, P. Poozesh
, underprepared students). As many of theseprograms look to go online to help them grow, it is important to encourage deeper learning,engagement and community for ALL learners, not just those in physical classrooms. While theresearch suggests that similar learning outcomes can be achieved in both traditional face-to-faceclasses and online courses [4] [5], online courses require more of a proactive approach to helpthem reach levles of engagment and learning that more naturally take place in the on-groundsetting.Danaher proposes that there are seven constructs by which an online engineering course can beassessed for quality. They are information, interface, support, engagment, collaboration,reflection and autonomy [6]. The DFO approach brings these
evaluations usingCATME; (3) surveys during the CP experience; and (4) surveys in post-requisite courses. Thecomparison of these assessments provides cross-sectional and semi-longitudinal results. Notexplicitly indicated here are other forms of formative and summative assessment including:retention; grades; teaching evaluations; student and professor reflections. As students worked to complete the milestones previously highlighted in Table 3, thecompleted assignments were assessed by the instructor in a timely manner, and numerousopportunities were given for students to receive verbal and written feedback, inside and outsideof class. In most cases students’ work indicated increasing understanding of thermodynamics,enhanced capabilities of
participate in policy making [2], be more inventive and improve economiccompetitiveness [3], and, most importantly, leverage different aspects of engineering to nurturethe interest of the youth, especially girls and underrepresented minorities to pursue engineeringstudies and career [4]. Public outreach is an important component of the national STEM educationecosystem and is reflective of the reality that there are ample opportunities for the public to knowabout science and technology outside of formal classroom settings [5]. In the USA, a majority ofthe public (62%) encounters science at informal science venues [6] such as festivals, fairs,exhibitions, summer camps, hands-on workshops, and online resources developed for STEMoutreach. These programs
-related identities in a variety of ways including those we categorized as each of the threedimensions of communities of practice.When considering the joint enterprise dimension of communities of practice, we recognized thatour datasets included 83 artifacts that were evidence of this dimension. Artifacts that we codedas referring to NSBE communities as family or “fam”, and those in which young adults publiclyacknowledged ties between the multiple communities where they held identities, illustrated thejoint enterprise dimension. Hashtags such as #FoYoMama and #NSBEFam, and various heartemoji were elements of those artifacts. Artifacts that reflected awareness of the importance offinancial matters to members of these communities of practice
information through a series of courses taken byundergraduate students also needs to be studied. These issues are addressed in ongoing studieswhich will be reported later. Further, the scalability of this approach will also be studied in otherengineering schools in the future. Although this study focuses on the tools, course content,elements of structure and process of learning, it does not specifically address the role andinfluence of faculty on the learning environment.Acknowledgements: Support for this work is provided by the National Science Foundation Award No. DUE1504692 and 1504696. Any opinions, findings, and conclusions or recommendations expressedin this paper are those of the authors and do not necessarily reflect the views of the
results in lower performance averages by students compared to PSVT:R problems forthis population. It is expected, based on Reusch et al.’s results [22], that there is a higherdifficulty level on the MCT problems used. This, in turn, may have been reflected by themoderate increase in EDA when we consider dividing this value by the time expended on theMCT problem-set as can be estimated from the two Figure 3 graphs (e.g., 0.05microSiemens/minute for MCT). The preliminary results of this pilot study corroborate thesefindings by suggesting a higher normalized arousal (or mean range-corrected EDA/timed event)found in these types of problems compared to PSVT:R (0.13 microSiemens/minute) and Staticsproblems (0.01 microSiemens/minute) (Figure 3).Parallel
measured in the cognitivedomain, attitudes most often are a reflection of one’s value system and, as such, outcomes relatedto attitude should be measured in the affective domain. Duczyminski [15] points out that,regardless of topic, affective outcomes are often closely related to deeper levels of thinking.Students engaged in a subject who recognize its value, can exhibit a change of attitude, andultimately achieve a consistent behavior. A number of academics have recognized the need tosupplement cognitive learning with the attainment of affective outcomes to promote deeperlearning and have incorporated specific learning strategies to accomplish this [16],[17],[18].Bielefeldt [18], for example, used project based learning and project based service
Foundation under DRL GrantNumbers 1615019 and 1614496. Any opinions, findings, conclusions, orrecommendations presented are those of the authors and do not necessarily reflect theviews of the National Science Foundation.References[1] "Tapping America's potential: The education for innovation initiative," Business Roundtable, Washington, D.C.2005, Available: http://www.tap2015.org/about/TAP_report2.pdf.[2] "An American imperative: Transforming the recruitment, retention, and renewal of our nation’s mathematics and science teaching workforce.," Business Roundtable, Washington, D.C.2007, Available: http://www.bhef.com/solutions/anamericanimperative.asp.[3] Rising Above the Gathering Storm: Energizing and Employing America
, the shared Redshirt model consists of seven mainprogrammatic elements that are designed to improve the engagement and rates of retention andgraduation of students underrepresented in engineering and computer science. These elementsare “intrusive” academic advising and support services; an intensive first-year academiccurriculum; community-building; programming to develop career awareness and identification;mentoring by an engineering or computer science faculty member; financial support, includingthe NSF S-STEM scholarships; and second-year academic support. There is flexibility acrossinstitutions in how these core components are implemented, reflecting distinctions in theadministrative structure, resources, and student populations at each
consumer is, however, unharmed bythe product’s color despite not being happy about it.Value systems are influenced by many factors, including upbringing, geographic location,historic time, life experiences, reflective thought, education, knowledge, and even prejudices.What might have been considered safe in the 1950s is not considered safe today and what is nowconsidered safe may not be regarded as safe in the 2030s. To drive this point home, the courseincludes a historic review of various changes in the safety of food [7], consumer products [8],and automobiles [9]. D. Product-Safety ConceptsWhen either establishing or assessing the safety of a product, the engineer must know what theproduct is intended to do. Strangely enough, this is not
first-year students (n=353) just beyond the mid-point of their first-year.The Workload Measurement Survey (WMS) was administered weekly, and was distributed byemail to groups of 20 first-year students from each program throughout the first semesters inYears 1 (2016) and 2 (2017) of our study. These twenty students were selected at random fromeach of our 8 engineering programs each week; surveys were distributed at the end of the weekfor a twelve-week fall semester in order to encourage reflection and responses based on thatparticular week of study. In 2016, the survey received a response rate of 26.87% with acompletion rate of 77.88%; in 2017, the response was 46.27% and presented a completion rate of77.87%. This survey explored the perceived
Science Foundation (NSF) (PRIME #1544259). Anyopinions, findings, and conclusions or recommendations expressed in this material are those of theauthors and do not necessarily reflect the views of NSF.The authors would like to thank FutureLearn for providing the data and the many reviewers whomade this a much stronger paper.8. REFERENCES[1] R. F. Kizilcec and C. Brooks, “Diverse big data and randomized field experiments in MOOCs,” in Handbook of Learning Analytics, 1st ed., C. Lang, G. Siemens, A. Wise, and D. Gasevic, Eds. Society for Learning Analytics Research (SoLAR), 2017, pp. 211–222.[2] R. F. Kizilcec, C. Piech, and E. Schneider, “Deconstructing disengagement: analyzing learner subpopulations in massive open online
research guides specifically dedicated to chemical pricing.The presence or absence of certain sources on a research guide is often governed by perceivedpatron needs and what resources are licensed by the library. If a librarian is not familiar with theneed (or has no requests), they are not likely to include such information. Furthermore, librariesmay have policies that restrict the types and organization of research guides, leaving littlediscretion for a librarian to create chemical pricing research guide or even a chemical pricing tab.On the other hand, the presence or absence of chemical pricing guides may just be a reflection ofthe resources needed and used at a given institution.Many of the sources mentioned by Maizell8 and Reichardt15 remain
GPA. In the follow-up interviews, the students consistently praised SITE for: Working in teams Working with students of different backgrounds Exposure to other fields Meeting faculty on a close basis Working on projects with real applications Integrating material learned in courses to solving complex problems Opportunity to think about careers in industry Good for the resume At this early stage in their educational careers, SITE represented one of the first times that many of these students were able to engage in and reflect upon these important aspects of STEM training. The following highlights some markers of positive impact on students: 22% of students
participation equivalent to asingle 3 or 4-credit course. Building upon this credit structure, some academic units have establishedcredit-use policies that incentivize multiple semesters of participation in VIP [5]. However, whethercurricular incentives yield higher persistence has not been examined.The VIP model has been adopted by twenty-six colleges and universities, and at the Georgia Institute ofTechnology (Georgia Tech), additional departments continue to adopt and refine curricular policiesregarding the program. This expansion demands reflection on how policies affect student persistence inthe VIP program, and how other factors may contribute. We hypothesize that different Georgia Techcredit-use policies affect student persistence in different
categories reflected, and grew out of the previous presentation rubric, but with specificpoints now guiding student preparation, peer assessment, and instructor assessment, equally.The Content area was reworded to address the points from the Target rubric, so that the studentswere given the expectation that their critical thinking process needed to be demonstrated duringtheir oral presentation as well as during the writing. The other points addressed technical aspectsof the presentation including: organization, visuals/slides, timing, speaking, and nonverbalcommunication. The full IOP Rubric is given in Appendix B.The student poll of rubric effectiveness (see appendix A) indicates that 83% of respondentsAgreed or Strongly Agreed that they found the
, which in turnprovides control signals to the motors controlling the launching mechanism. For objectdetection, the two obvious choices are ultrasonic sensors, and infrared sensors. Ultrasonicsensors can provide very accurate ranging information, and since they use sound instead of light,they are not adversely affected by direct sunlight [10]. Accurate ultrasonic sensors do tend to bemore expensive than infrared sensors, however.Infrared sensors do have the capability of providing accurate ranging information, but they runinto problems when used in direct sunlight [10]. Additionally, since light reflects differently offdifferent surfaces and different colors, the range reading can differ between two objects whichare the same distance away from
biomedical engineering not seen from the classroom, allowing me to become more aware of the possibilities I may want to pursue in the future.”While most students focus on the positive benefits of the course, few comment on anyapprehension or anticipated challenges. A written assignment completed before clinic rotationsincludes a student reflection on “Fears and Concerns”. Table 5 lists the most common responsesfrom the engineering students. The course syllabus and handbook include topics addressingthese issues and may have influenced the students’ responses.Table 5 - Common answers to “Fears and Concerns” Questions Common Answers • Overwhelmed by
of learning and engagement in a makerspace environment.Our analysis revealed the instrument had acceptable levels of reliability (above .65 and below.95), whichwe maintain makes the instrument suitable for assessing student perceptions and engagement inmakerspaces. Further, the acceptable reliability indicates students are answering the items consistentlywhich further reflects alignment of the items to our four constructs of interest.We were able to provide an additional level of assurance that our instrument is aligned with ourassessment goals through our analysis of the students’ responses in conjunction with their individualcharacteristics. The only association with student individual characteristics we found to be predictive ofthe survey