choosing a language with a simpler syntax, herewe separate two tasks that we know individually demand a high level of cognitive load fornovices: learning problem-solving strategies, and learning programming techniques.AssessmentOften times assessment becomes the weak point of a learning system. Designing good assessmentis hard,56,57 and often good assessment can require significant time on the part of the instructor.Because of this, assessment is often simplified, lowering the effectiveness of the entiresystem.If our course objective is to teach learners to solve problems with programming, then an idealassessment would be to give students a problem to solve, ask them to write a program to solve itas well as reflect upon the patterns they used in
few days later and included the two itemsshe had requested. The salary was not quite the level Sarai had hoped for, but given her interestin remaining in the region and her success in receiving funding for both of her requests, shedecided against negotiating for a higher salary. All in all, the negotiation workshop had, in hereyes, paid off. Without it, she reflected, she would have just accepted the verbal offer withoutarticulating what else she needed to help her succeed in this new position.Administrative Level NegotiationsCase 3: College level budget negotiationState U had just hired a new provost. He was a biologist and one of his platforms was to launch anew STEM program. The university had, however, been weathering budget crises for
(3) face-to-face but taught in parallel with the online section. 600 500 400 300 Other 200 Reform 100 0Figure 2: Calculus I enrollment by semester.Total students “captured” by the reform project, as a percent of enrollment is shown in Figure 3.It appears to be stabilizing in the low to mid 70’s, which currently reflects the portion of calculusthat Boise State University has chosen to offer as honors, online, or face-to-face but parallel toonline. 100% 90% 80% 70% 60% 50% 40
-intentional‘general distribution requirements’ of the university [that] are not necessarily tailored to meet theneeds of students”6 nor a thoughtfully comprised liberal core for holistically prepared engineers.Is this student response instigated and nurtured by a cultural devaluation of non-technicalcoursework that is reflected in minimal non-technical requirements filled with choice? Surely thepresence of faculty, advisors and deans unenthusiastic about the added value of exploration ofhumanities and social sciences topics impacts the climate of perception towards liberal educationin engineering colleges; programs that emphasize the integration of the humanities and socialsciences with engineering need faculty champions, broad and overt institutional
carrysomewhat different meanings), peer review is often associated with Peter Elbow’s teacherlesspedagogy of the 1970s, shifting the responsibility for feedback from the instructor to thestudent.2The literature refers to numerous benefits from peer review. Topping et al. suggest that peerreview can create “an enhanced sense of ownership and personal responsibility.”4 Peer feedbackmay also support student engagement and reflection in their learning.5 In fact, some researchsuggests that students may actually get as much or more from student critiques of their work asfrom instructor feedback.3 In addition, work in peer review also proposes that students can learnfrom giving as well as receiving feedback.4,5 Topping et al. lists a wide array of
environment19.In more recent work, these benchmarks are replaced with engagement indicators that arecategorized into four themes: academic challenge, learning with peers, experiences with facultyand campus environment48. The course material delivery framework outlined in this paper 1focuses on some of these benchmarks including higher order learning, reflective and integrativelearning and learning strategies (all under the “academic challenge” theme).There have been several research efforts over the past many years to improve engagement inengineering classrooms. These include the use of a technology-centered classroom20, formationof learning
“engineering students have so much to learn before they can actuallystart practicing in the field, safely, that a formal rigorous engineering education at the Bachelorslevel is inescapable.”9 However, because competency in soft skills is also critical to theprofession, it is essential to look beyond textbook learning. A National Science Foundation studyrecommends engineering faculty engage students in “collaborative problem-solving, analysis,synthesis, critical thinking, reasoning, and reflections to real-world situations,” and that “newlearning approaches must be put to use that heighten practical learning and allow students todemonstrate the application of their studies to real-world situations.”10 Interestingly, theproposed revision to Criterion 3
Paper ID #14971Measuring Student Response to Instructional Practices (StRIP) in Traditionaland Active ClassroomsMr. Kevin A. Nguyen, University of Texas, Austin Kevin Nguyen is currently a Ph.D. student in the Science, Technology, Engineering, and Mathematics (STEM) Education department at University of Texas at Austin. He has a B.S. and M.Eng in Environ- mental Engineering both from Texas Tech University. As an engineering education researcher, he has worked on projects regarding self-reflection, teamwork, active learning, and participatory science com- munities.Dr. Maura J. Borrego, University of Texas, Austin
whichincluded (i) 6, (ii) 9, and (iii) 2 questions for each of the three sections. Comparatively, the end-term survey had 19 questions of (i) 11, (ii) 4, and (iii) 4 questions. All the original questionsfrom sections (i) and (iii) were maintained and supplemental questions were added. Section (ii)was modified to reflect class activities that had occurred since the mid-semester survey. Specificquestions will be discussed in greater detail in the following section analyzing student feedback.Summary of Student FeedbackEighteen of the twenty students enrolled in the DBE course consented to participate in theresearch study, sharing their assessment of this new curriculum. The remainder of this sectionaggregates both the responses from Likert scale rating
developing skills and understanding where the abilities and tools for learning gainedfrom various life stages (e.g., childhood) and various sources (e.g., schooling) provide a contextand resource for learning and performing in later life.8 Lifelong learning capability is seen whenan individual or group reflects on the current situation and resolves to address a problem, toshare an idea, or to do research and further study to gain a better understanding of the situation.Thus, lifelong learning happens serendipitously in the workplace, at home, and at play, as part ofdaily living.Some authors have written on the role of technology in lifelong learning. Idrus and Atansuggested that life-wide learning hinges on technology mediated communication
conflicts between members (and how these were resolved). ii. Team strategy: This component examined whether ECE students had a particular strategy to ensure they were successful at maintaining their microgrids, generating revenue, and successfully fending off (or minimizing the impact of) cyberattacks. iii. Team preparedness: This aspect focused on whether ECE students were prepared, knew the various elements of the Grid Game, and understood what different cyberattacks did to their systems. iv. Methodological issues: This section asked CJ students how they felt about doing handson research, any difficulties they experienced in observing and interviewing ECE students, and also reflections on what
Acreditación)In addition to the assessment results obtained, the outcome leader uses input from three differentsources for the analysis: the course card, the course syllabus, and the reflective memo. Thecourse card contains the key competencies to be developed, the general objectives and thegeneral learning strategies. The course syllabus contains the detailed course learning goals andlearning units. The reflective memo contains the faculty self-assessment report about learningstrategies and explains how learning strategies support the achievement of competencies andlearning goals. The student outcome leader and faculty involved in the courses associated withthe outcome discuss the assessment findings and identify improvement opportunities and
fit within Zimmerman’s model of self-regulated learning. Students are encouragedto arrive with forethought, engage in performance, and reflect at the end of the tutoring session,time permitting. Additionally, tutors are trained on Gardner’s intelligences, learning styles, and thinkingstyles. Tutors are provided ample material and training to understand how to engage a studentbased on their demonstrated intelligences, learning styles and thinking styles. Trainingemphasizes to tutors that students receive and process information in a variety of ways. As peertutors they have the opportunity to create and increase learning opportunities for students15. Thetraining these tutors receives impacts their feedback efficacy16.III. Results and
statement development) Creative thinkers properties (pressure, Identify the problem: Access to water at the volume, temperature) center in problem scoping session Thoughtful team light properties Using the problem statement develop the workers (radiation, reflection, solution process to translate written refraction, insolation), statement into solution model electricity basics, Design (Design process methodology) (current, voltage, resistance), solar Apply design process to generate ideas, geometry (daylight model, analyze predict and build the time), solar panel solution product, characteristics
variability in the data14. However, this instrument did notinclude several characteristics of the FTP cone types identified in our subsequent qualitativework. The study described in this paper attempts to further refine our survey instrument bycreating items that quantitatively capture latent constructs reflected in our qualitative findings .MethodsUsing an instrument in research that does not assess what the researchers are presuming tomeasure can lead to incorrect results and wrong decisions18. In refining the MAE survey, carewas taken in the process of choosing factors, developing items, and testing for validity andreliability.Developing ItemsFactors were chosen based on the results from our previous qualitative research. Code categoriesthat were
involved in an organization that expanded beyond the confines of their campusprovided the students with access to a larger community of black engineers. As reflected inprevious quotes, this created a sense of belonging in engineering. These students created anatmosphere of acceptance and affirmation for themselves, but it expanded to the campus and waslikewise, recognized by NSBE regional. This acceptance outside of their university providedthem with a greater sense of integration into a larger engineering community. “I think from, at least when I was on regional level and looked to award my chapter with an award with participating in a community event that was hosted in Indianapolis, and also of course, in Michigan in Detroit, I
arepeated comparative research approach. The assessment methods analyzed in this study as compared to past studiesincluded both subjective (indirect) and objective (direct) measures. The indirect measureincluded a pre and post questionnaire (before and after project experience) in which thewording was slightly modified based on the reflections of the instructor and informed bythe continuous improvement process. Additionally, video lectures/documentaries of real-world construction projects were shown to the students followed by assessment of thestudents. Such assessments included a post-questionnaire that included assessment oflearning outcomes and objective based questions, which were graded. The direct measuresincluded homework grades, in
use inboth course and student outcomes assessment. The most recent FCAR methodology consists ofthe FCAR which is generated by faculty members at the end of the semester. The FCARprovides one or two pages of summative information related to the courses taught by eachfaculty member during that semester. The FCAR generally contain the following information: • Course Description • Course Outcomes • Class Grade Distribution • Course Outcomes Assessment • Student Outcomes Assessment • Reflection • Proposed Action ItemsThe main idea is to capture the reflection and proposed action items for improvement of coursestaught at the grass-roots by the responsible instructors. Hence, the assessment information isprocessed by the
encourage post-lab reflection on the results and to address Learning Objective 6,students are also required to submit individual assignments the week after the lab session. Inthese reports, students are asked to discuss the results from both the standard tensile tests andnanowire simulations and to complete a simple problem related to calculating the Schmid factorfor FCC slip. Specifically, the following questions are asked:1. How does the yield stress of a copper nanowire compare to the yield stress of copper sample? Why is there a difference or similarity in strength? Hint: refer to your group worksheet.2. How does the Young’s modulus of a copper nanowire compare to that of the macroscale copper sample? Why is there a difference or similarity
andconversion or use) of these by any one sector or nation requires a commensurate reduction in useby another.However, project sustainability that is assessed through triple-bottom-line accounting is deficientin one key dimension – the role of technology.If the engineering is poor, irrespective of how much effort is placed to ensure that the other threeparameters are addressed, the proposal will fail. Through “engineering” we address the technicalaspects of a proposal – which in turn are a reflection of the design and the materials used.Further, if the structure has a designed life span, provision should be made to consider whatshould happen to the materials and the site on demolition. In light of this, Buckeridge22introduced the concept of the “4 Es
University 44 6 Total 77 17 Percentage 81.91% 18.09% Male Female Figure 2: Distribution of Male and Female StudentsData AnalysisStatistical analysis was performed using an independent sample t-test to determine themean values of all five categories of survey questions using SPSS22 software20. Theindependent t- test was used to evaluate the three different hypotheses listed in theprevious section. A t-test’s statistical significance indicates whether or not the differencebetween two groups’ averages most likely reflects a “real” difference in the populationfrom which the groups were sampled.Results and DiscussionDescriptive
would probably be less likely to recognize its value. These observationsby the students about their perceptions before and during the travel could in part be due to thedomestic nature of the project. They may have perceived the travel experience to be less valuablebecause of staying in the U.S. and merely traveling to another part of the country. Even so, theyall agreed that, based on what they learned upon project completion, they value the travel muchmore and would take the time in the future to meet design colleagues face-to-face and completesite visits, if funds were available.ConclusionsWe have reflected on the findings of the interviews, on their observations of learning while theprojects were under way, and observations from prior inter
provides HTML on the left, and the rendered web page on the right. The student can change the HTML, by modifying text, adding bold, inserting header text, and more, and then press "Render HTML" to see how the changes are reflected in a new webpage. 9 Subsequent images show similar tools for CSS and Javascript. 10 Integrated basic word processing and spreadsheet applications Many computing technology courses have lab components that teach
- Lean Systems - Final project report and presentationThreaded DiscussionsThe online threaded discussion provides students an opportunity to participate in virtualconversations at any time and any location. It can help students synthesize knowledge intounderstanding of the weekly course learning objectives. Evidence showed threaded discussionsincreased the amount of time students spent on class objectives comparing to face-to-facediscussion as in an onsite class. And the students appreciated the extra time for reflection oncourse issues4. It was also reported that online threaded discussion can improve critical thinking5.A study at Athabasca University 6 found online
profilesAs shown in Figure 2, the instrument consists of seven scales to measure fourteen majorpreferences. These fourteen categories reflect an individual’s systems thinking capacity indealing with complex system problems. The first pair, level of complexity (C-S) describes anindividual’s comfort zone for engaging complex system problems. The second pair, level ofautonomy (G-A), describes an individual’s inclination in dealing with integration of multiplesystems or internal systems. For instance, (G)-type systems thinkers focus more on applying aglobal perspective and treat the system as an integrated unit. The third pair, level of interaction(I-N), describes what type of scale an individual would choose to work with. The fourth pair,level of
part of further simulation process. Fig. 3 – The Cloud Manufacturing frameworkThe system part responsible for modeling interaction includes simulation based on DEVSformalism. Data defines interaction between devices and produces predictiveenvironment for the next steps of the process. Thus system holds information aboutphysical devices and provides decision making support, analytics and prediction. Virtualclones of the environmental nodes on the previous level are modeled as atomic parts of theDEVS model [12]. The simulation process is described in details below. SimulationThe cloud manufacturing framework reflects current system state in the cloud. Suchrepresentation allows to monitor and control the devices
that may improve the students’ performanceand help them graduate on time. One possible future work is to identify the bottleneck coursesand investigate the paths that lead to failing or passing them.AcknowledgementsThis work was supported in part by NSF Grant# 1447489. We would like to thank ourinformants for participating in the field studies reported here. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.References[1] Pandey, U. K. and Pal, S. (2011), “A Data Mining View on Class Room Teaching Language”, (IJCSI)International Journal of Computer Science Issue, Vol. 8, Issue 2, 277-282, ISSN:1694-0814[2
• 16 Analog pins • 14 Pulse Width Modulation pins • 128 KB of Flash Memory • 5V Operating VoltageUltrasonic Sensor:The four HC-SR04 Ultrasonic Modules [13] mounted to the four sides of the truck offer a collisiondetection system by sending out a short burst of ultrasonic sound. These sounds reflect off fromthe surrounding environment and then return back to the sensor. By measuring the time that it takesfor the echo to return, the distance between the sensor and the nearest object are calculated. Thespecifications are as follows: • Operating Voltage: 5V • Operating Current: 15mA • Effectual Angle: <15° • Ranging Distance: 2cm - 400cm / 1” - 13ft 3 • Measuring
learn about functions, procedures and test-benches. Theyspecifically develop a test-bench to verify the 4-bit ripple carry adder functionality using the ripplecarry design (and its associated full adder module) that they developed in lab 2. This latter lab isimportant because it allows the students to reflect back on a previous lab exercise and enables thereinforcement of previously acquired knowledge. In all of the above mentioned labs, the studentsnot only simulate the design, but also synthesize and implement the design, generate the bit stream,and download it onto the board in order to demonstrate its functionalities.The second laboratory module also consists of four structured labs starting with lab 5. This modulefocuses on sequential
that has the potential to revolutionize how weassess student achievement in higher education. Acknowledgements This work was made possible by a grant from the National Science Foundation (NSF DUE-1503794). Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author and do not necessarily reflect the views of the National ScienceFoundation. Bibliography 1. Postman, N. 1992. Technopoly: The surrender of culture to technology, Alfred A. Knopf, New York, NY.2. Sadler, D. 2005, “Interpretations of criteria-based assessment and grading in higher education,” Assessment & Evaluation in Higher Education, 30(2), 175-194.3. Broad, B. 2000, “Pulling you hair out: Crises of