6Van Wie (26946), “Using Reflection to Facilitate Writing Knowledge Transfer in Upper-LevelMaterials Science Courses” by Mallette and Ackler (26638), and “Writing across Engineering:A Collaborative Approach to Support STEM Faculty’s Integration of Writing Instruction in theirClasses” by Ware, Turnipseed, Gallagher, Elliott, Popovics, Prior, and Zilles (26720). Thesepapers were presented in three different sessions (2 in LEES and 1 in chemical engineering); onewas funded by the NSF, while another had significant institutional funding.Many of the papers presented at the 2019 conference exemplify the fourth trend observed in the2016 analysis: collecting data (typically from student evaluations or surveys) for a single course(sometimes even for a
decisions today, related to yourdesign project?”). We found that students reliably accounted for the decisions observed.Based on these subconstructs, we developed Likert statements written as simple concepts [48]with a 7-point bipolar scale, with a middle option to reduce measurement error [49]. Researchsuggests that using item-specific scales, as opposed to the commonplace agree/disagree scale,can improve the quality of responses [50]; we thus avoided agree/disagree scales and focused ondeveloping scales that reflected the construct we sought to measure. For instance, we avoidedscales that focused on frequency (e.g., always to never), as in our discourse analysis, weobserved that even infrequent decisions were sometimes very impactful. This
grades of zero (i.e., incomplete assignments, D), misseddays of classroom instruction (E), and missed days of Discovery (F) by student between schools.N=77 and 53 for Schools A and B, respectively. P-values reflect nonparametric U-tests between schools.Aggregate assessment of classroom performance from both schools presented consistent meanfinal course grades (excluding the 10-15% Discovery portion) of 67% (Figure 2A); given thissimilarity it was determined that further comparative analysis between school cohorts wasjustified. However, performance on Discovery variables was significantly different (p < 0.0001)between school cohorts; School A students averaged 67% (remarkably consistent to their
. Survey responses were first descriptively coded, guided bythe research question. Throughout the coding process, themes were the unit of analysis.Subsections of text within an individual response were deemed to contain essential thought, andthen coded accordingly. This process is in line with utterance coding within verbal qualitativeanalysis [30]. All coding was performed by two researchers, and the researchers reached 100%consensus after discussion in inter-rater reliability (IRR). Focused codes were developed [31], [32] to further interpret Incubator participantunderstandings of teaching and learning. In developing our codes, we asked a more specificquestion: How are BME students’ articulations of teaching and learning reflecting
participants were male, reflecting the demographics of the schoolat the time of the formal meetings.Samples of this size are commonly accepted in qualitative studies investigating social andexperiential phenomena. This size also seems appropriate because we were able to engage almosteveryone who shared the experiences in question. Even in cases where the target population islarger, scholars of qualitative and phenomenological research recommend limiting the sample size.This is done to allow the researcher to delve deeply into the phenomenon and the data. For instance,Dukes (1984) recommended a sample size of 3-10 for phenomenology (cited in Creswell, 2007).A literature review by Guest, Bunce, and Johnson (2006) identified recommendations
. Student artifacts of engagement with this module included a research topic tree, a key word tree, and a written reflection. (See Appendix E.)Assessment Instruments Two assessment instruments were developed by the researches based upon the uniqueneeds of the study. The Final Course Activities Evaluation Rubric was developed to evaluate andprovide a total score relating to whether, or how well, a student could critically evaluate andselect credible and meaningful resources in their research and writing. A second rubric, the 10Supplemental Course Activities Engagement Rubric,was developed in order to better understandhow engaged
strategies for completing the assignment. The third and fourth segments (Peer Review and Self- Review) accelerate learning throughapplication of a rubric and reflection on self-performance. In these segments, studentsdemonstrate an understanding of task requirements by critiquing the work of others. Then,students consolidate their learning gains by reviewing their own submission and reflecting onways to improve. The fifth and last segment collects performance data /peer commentary anddisplays results both to instructors and students. This last segment reinforces learning by givinga composite
ability tomonitor progress towards self-generated goals, and the ability to reflect on performance andmake adjustments and manage time effectively, to comprise the overarching construct of self-regulation in learning [4].Students who are better at self-regulation often outperform those who have not developed theseskills [5]. Although the literature on this topic heavily focuses on students’ use of strategies orperformance, there is a growing body of research focused on students’ backgrounds andunderlying beliefs regarding learning. These individual difference variables may globallyinfluence a student’s disposition, use of strategy, and thus, performance [4, 6]. Although thereare several potential lines of inquiry available, the present study was
been combined together.In addition to the survey, at four times during each semester, a full class period was used toproduce open-ended responses to a reflection prompt (n=16 for Fall 2015 and n=16 for Fall2016, a total of 126 reflections). Reflections prompts were not focused on the canvas (e.g.“Explain a struggle you have had during the design process to this point and describe the variousways you overcame that struggle. What might you abstract that you can use in other designexperiences?”). Lastly, a faculty assessment focus group met on May 21, 2015 and consideredtwo prompts: 1) “I like…” and 2) “I wish…” regarding the course as a whole.As mentioned previously and important to our assessment, Crismond and Adams (2012) proposethat students
process, (d) teamwork and cooperative and collaborativelearning, (e) reflection on how and when these practices could be institutionalized in thecapstone course. Faculty participated in monthly group workshops followed by individualcoaching sessions with two members of the professional development leadership team. Thetwo-member coaching team was comprised of two “experts” – one in the EM and the other inpedagogical practices. The coaching sessions included open-ended questions for facultyreflection on implementation of EM and instructional teaching strategies.Coaching sessions were documented through a Google form, which captured coachingdiscussion details on the following: (i) pedagogy-related topics discussed during the coachingsession, (ii) EM
kind of formal curriculum education is notavailable in the entrepreneurial ecosystem in the general sense (Wang Xuyan et al,2018);participating in competitions is a good way to improve students' entrepreneurialability(Harrington, 2017); the number of graduates who choose to start their own businessescan reflect the output of the entrepreneurship ecosystem in a sense (Beyhan et al, 2017).Synergistic symbiosis mainly refers to the cooperation between organizations in universities.This paper divides synergistic symbiosis into two secondary indicators, namely, theuniversity-school synergy and the teacher-student synergy (Zheng Juan et al.,2017). At leastfor the time being, transforming teachers into entrepreneurs is not the most effective way
consulting with nonprofits, museums, and summer programs. c American Society for Engineering Education, 2019 Creation of an Engineering Epistemic Frame for K-12 Students (Fundamental)AbstractIn implementation of K-12 engineering education standards, in addition to the professionaldevelopment teachers need to be trained to prepare students for future engineering careers,assessments must evolve to reflect the various aspects of engineering. A previous researchproject investigated documentation methods using a variety of media with rising high schooljuniors in a summer session of a college preparatory program [1]. That study revealed thatalthough students had design
several department-specific Comm Labs, 2)Brandeis’s centralized Comm Lab for their Division of Science, and 3) Rose-Hulman’sundergraduate-only centralized Comm Lab for students using a multidisciplinary, co-curricularspace. We then discuss these adaptations with a focus on how our different institutional profilesshape our Comm Lab design. Specifically, we draw connections between institutional data andthe disciplinary focus, scale, and institutional fit of each Comm Lab. We conclude by sharingdata about the Comm Labs’ success, reflecting on the importance of continued data collection,and considering the value of cross-institutional collaboration. Our conclusion reflects both thelimitations of our study and the need for ongoing research. These
. Section V provides a conclusion and implications.II. MethodsThis study was conducted by a combination of a survey of the faculty advisors/counselorscommunity within SWE, and through the analysis of written reflections provided by the authorsof the paper, all of whom are faculty advisors and/or counselors. In 2017, this group of eightadvisors and/or counselors identified factors that contribute to their level of involvement inrunning student organizations. Their individual experiences were shared with respect to their rolein the section’s long-term and short-term goals for the success and sustainability of studentorganizations.The survey was developed based on the goals of the study, with several rounds of review andrevision to ensure that the
: Numbers of papers mentioning "science technology and society” by year, with the emerging time period and the three time periods of high activity that we studied indicated In this study as in most other contexts, STS is a spectrum of concern and activity, not a clearlydelineated body of knowledge or activities. This spectrum is reflected within ASEE in thenumber of different divisions in which papers on STS have been presented. As Figure 2 2 illustrates, STS is taken up as a topic broadly across ASEE with greatest concentrations in (a)Technological Literacy and Technological and
your own business. The next set of 47 questions asked students to show their level ofagreement (on a 7-point Likert scale from “strongly disagree” to “strongly agree”) withstatements that measure three realms and eight dimensions (see Table 2 below for an explanationof each).Finally, students were asked about their experiences with volunteering and a set of demographicquestions (gender, engineering major, year in school, GPA, race or ethnicity, previous engineeringwork experience, first-generation status, religion, and age). The post-test additionally askedstudents to reflect on their experiences in the course and if they would be willing to do afollow-up interview. Table 2: EPRA Realms and Dimensions Realm
will understand the basics of probability, statistics, uncertainty analysis, regression, and correlation; 8. students will be able to write a technical report; and 9. students will understand and be able to communicate the broader context of the course material.These course learning outcomes reflect the nature of the course in Instrumentation andExperimental design that is meant to teach those broad subjects. However, the ideas of signalconditioning, processing and recording, as well as signal characteristics, are all derived out of theelectrical concepts inventory. These concepts in particular overlap with the course learningoutcomes for the course entitled “Mechatronics” which has the following stated course
survey. Since the pre survey wasconducted during the first 1-2 months of the term, they likely reflect both a messaging differencebetween the alternative and the traditional course, as well as incoming beliefs prior to engagingwith the course.When performing a 2-sample independent t-test, only the contrast between impressions ofprofessional programming practice from the subsequent semester interview showed statisticallysignificant differences between alternative and traditional populations, at a 2-tailed alpha level of0.05 (p=.03)When performing a matched pairs t-test on the students in the alternative class who took the preand post survey, only the survey item “This class consisted of” showed a statistically significantdifference between pre
, there is general agreement that students learn by doing. This is reflected inthe aphorism “Tell me and I forget, teach me and I may remember, involve me and I learn”10[which is often misappropriated to Benjamin Franklin, but likely derived from writing of theChinese Confucian philosopher Xunzi (312–230 BC)]. While it is true that information andequations can be learned by reading, memorization, or listening to someone else speak, these arenot the best methods to build intuition. Intuition is built through experience, learned by doing,and reinforced through practice. The processes of learning and doing are inseparable.6 Thecomplexity of topics taught limits the ability for students to “learn by doing” within the time-restricted classroom setting
haveworked through the steps of decoding the disciplines in conversation with technical-expertfaculty.e.g., 32 However, professional communication in “Preparation for Undergraduate Research”is taught by communication instructors – not disciplinary experts – and contains far too manysub-fields – and thus far too many bottlenecks – to manage this model as originally designed.Instead we have developed a different framework - inspired by “Decoding the Disciplines,” buttheoretically informed by RGS - upon which students reflect on their own aspiring-to-expertdomain knowledge, in order to make the rhetorical genre knowledge of their discipline explicit.B. Stage I: Identifying and Communicating ContributionsIn the fall semester, major deliverables (i.e
.--- referencing established and credible information for applications and analyses Reflecting Reflecting for restatement I don’t know. I’m getting 94. It’s Understand (RL) probably a calculation error.--- I’m Analyze saying one of us did something Evaluate mathematically wrong. Soliciting Inviting for collaborations From that can’t you figure out the Understand (SO) frequency
hour experience inwhich they assume roles of leadership in a community, business or an organization. There areseveral major learning objectives of this simulation: i) students are introduced to differentleadership styles and forced to discover that many of the leadership assumptions that hold true inbusiness-as-usual situations are violated in a crisis; ii) students learn how to utilize and allocatelimited resources and make necessary trade-offs; iii) students are exposed to situations in whichthey have to question the ethical implications of their decisions and determine what risks areacceptable and tolerable. Through a post-simulation reflection activity led by volunteer facultyand staff, as well as the local Emergency Services personnel
insectoid robots, etc.). This relaxed introduction to robotics reduces anyreservations that the students might have about the field of robotics. After a welcome phase, ashort lecture is given introducing some of the main themes of robotics and the core researchareas studied by the scientists and robotic engineers at DLR and RWTH Aachen University.A small group size of four to six persons allows for active participation in the six practicalexperiments, of which each group carries out four, and the necessary concentration forhandling the high-tech equipment. Each experiment is followed by a short break, allowing thestudents reflection time to discuss the experiments with their peers. Each experiment startswith a clarification of the educational
2incorrectly deciding enclosed current were common mistakes reflected from students’quantitative written responses15.Students’ Difficulties with Mathematical Problem Solving in EM contextsResearch studies discussed in the previous section have provided insights on students’ commonmisconceptions of EM phenomena. However, conceptual understanding of EM phenomena is notindependent of sophisticated mathematical analysis, especially in upper level EM courses13. Inthese situations, the vector nature of the EM fields and the use of abstract operators can make thestudy of EM phenomena significantly more challenging. The mathematical formalism used tomodel EM phenomena can be much different than straightforward but abstract application ofmathematical rules
places, or community settings. The courseincludes a considerable amount of experiential learning, requiring students to reflect on theirdesign and developmental efforts throughout the semester. Projects which enhance safety,accessibility, or “greener” alternatives to existing devices often serve as potential projects.Each student selects a project from a broad program area such as electricity and electronics,computer systems, or networking. Project topics which bridge multiple program areas orinclude mechanical components are recommended. These projects allow students theopportunity for showcasing their knowledge, skills, and professional work practices.Learning in the capstone course is directed so that it is solution based. Students start off
each other (and to themselves).”3 Thesedefinitions reflect the complex social and communicative processes that need to be unraveled tooffer a complete understanding. While student design contexts differ in important ways fromprofessional practice,4-5 the program-based engineering education context represents animportant space for novice engineers to learn about and develop understandings that will impacttheir future engagement in design. In the context of design, there are many different values, such as innovation or a primaryconcern for safety, that guide design decisions and processes and can impact how designers thinkabout the ethical issues related to their designs and the implications of their “everyday” ethicaldecisions. This is
they implemented the new instructionalplans in the semester following the workshop. Three major themes emerged from inductiveanalysis of interview transcripts. First, all participants reported that the workshop helped thembecome more aware of the importance of incorporating academic integrity into their teaching andwere more reflective on how to effectively discuss this critical issue with their students. Second,after the workshop, participants made several changes in their courses and applied a variety ofstrategies to incorporate academic integrity into four aspects of their teaching: course syllabus,classroom discussion, assignments, and exams. Last, participants discussed several challengeswhen incorporating academic integrity into their
to making it better, faster, or more efficient. • Engineers help shape the future. They use the latest science, tools, and technology to bring ideas to life. • Engineering is essential to our health, happiness, and safety. From the grandest skyscrapers to microscopic medical devices, it is impossible to imagine life without engineering.These and other recommendations to “change the conversation” or “embrace a broader vision” ofengineering bespeak a realization that the profession is not well understood or reflective of thesociety it serves. Organizations in the engineering community have tested female-inclusiveapplications and strategies in outreach and awareness efforts with limited success. The authenticadult (i.e. Baby
as a frameworkfor promoting professional development and community building for graduate students.Building on the themes of the book, this program sought to promote reflection amongparticipants about the choices and actions that women can take to position themselves forsuccess—and encouraged exploration of students’ personal vision of success. Results of pre-and post-tests, along with observational data gathered by the facilitators, indicated that studentswere concerned largely by two topics: concerns about how to balance their career ambition andtheir goals for a fulfilling personal life (whatever that may be), and how to have positive andbeneficial relationship with mentors or advisors. Students also shared their challenges andfrustration
requirements, the process for obtaining eachbadge included at least the following: introduction to the new topic (e.g., participation and animpromptu classroom presentation or discussion, hands-on activity in class); reflections on thedesign and development of the project and on their own learning; application of new materials;and finally, the final project itself accompanied by the narrative/reflection and artifact(s). Whilesome projects were to be completed independently, for others, students were encouraged orrequired to work with peers. In addition, some projects could be in part used to meet sub-competencies across multiple badges. Students completed projects on their own timeframe and inthe order they preferred. While there were soft deadlines