Conference Session

Online Teaching

Collection

2015 ASEE Annual Conference & Exposition

Authors

Susan L. Miertschin, University of Houston (CoT); Carole E. Goodson, University of Houston (CoT); Barbara Louise Stewart, University of Houston

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

have low TM scores than have strong TM scores.• Among older students (at least 31 years of age), more have strong TM scores than low TM scores. In other age categories, there appears to be a more nearly equal division between low and strong TM scores.• Among the students with the highest GPA, 66% have strong TM scores while 34% have low TM scores. Among students with the lowest GPA, 57% have strong TM scores while 43% have low TM scores. The unexpected direction of difference at the lower end of the GPA scale perhaps reflects a wider range of TM score values and/or the very small n for this GPA category.• Among students who are not employed and those who are employed part-time, higher proportions

Conference Session

Software and Programming

Collection

2015 ASEE Annual Conference & Exposition

Authors

Krista M. Hill, University of Hartford; Ying Yu, University of Hartford

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Diversity

Tagged Divisions

Computers in Education

10.1was the last to include a graphical test bench generator tool. In the Fall 2013 semester weupgraded to ISE version 13.2 and discuss later how despite the introduction of test benches, our Page 26.1252.4students prefer the improved stability of the software.In this paper we consider the usefulness of our tutorial as a reference as well as pedagogy topicsrelated to test benches. In reviewing the literature, Colburn1, Hawkins3, and Kolb7 each outlinephases of the learning cycle model and suggest that experiential learning involves reflection toallow for accommodation of new knowledge. We feel that perhaps the lecture and homework canbe used as

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Xiaobing Hou, Central Connecticut State University; Shuju Wu, Central Connecticut State University; Karen Coale Tracey, Central Connecticut State University

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Diversity

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Computers in Education

reflects the rapid growing IT industry and Page 26.1764.2covers a wide spectrum. The new program's laboratory is under continuous update to enhancestudent's hands-on experience with cutting-edge equipment. Similar to the curriculum design, thelaboratory development benefits significantly from industry help and donation.This paper presents the curriculum and laboratory upgrade. The paper is organized as follows.Firstly, the role of industry is introduced. Then based on the feedback from industry, the updatedNIT curriculum is presented, followed by the upgraded NIT laboratory. Finally, the paperconcludes with the future work.Collaboration With

Conference Session

Best of Computers in Education

Collection

2015 ASEE Annual Conference & Exposition

Authors

Raghavender Goud Yadagiri, NYU Polytechnic School of Engineering; Sai Prasanth Krishnamoorthy, NYU Polytechnic School of Engineering; Vikram Kapila, NYU Polytechnic School of Engineering

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Diversity

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Computers in Education

,24 among other attributes. Ithas been suggested19 that designers of learning environment draw inspiration from game designprinciples to engender active learning, reflection, collaboration, diverse learning opportunities,motivation, etc.As evidenced from the above, there exists a compelling opportunity to integrate the technologyof robotics and student interest in gaming to teach computer programming to K-12 students andto enhance their lateral creativity for creative problem solving.25,26 The idea of constructing andprogramming a physical robot makes the classroom come alive, allowing the students tounderstand that classroom math and science concepts are critical to solve real-world problems.Even as robot games are used to enrich students

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

John C Nesbit, Simon Fraser University; Li Liu, Simon Fraser University ; Qing Liu, Simon Fraser University; Olusola O Adesope, Washington State University-Pullman

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Diversity

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Computers in Education

assignments, asking questions, giving hints,evaluating responses, providing feedback, prompting reflection, providing comments that booststudent interest) and adapts or personalizes those functions by modeling students’ cognitive,motivational or emotional states. This definition distinguishes ITS from test-and-branch tutorial Page 26.1754.2systems which individualize instruction by matching a student’s most recent response againstpreprogrammed, question-specific targets. Complicating matters, there are sophisticatedcomputerized adaptive testing systems, not usually considered to be ITS, that use item responsetheory to model student ability as a

Conference Session

Mobile Devices and Apps

Collection

2015 ASEE Annual Conference & Exposition

Authors

Mohammadjafar Esmaeili, University of Dayton; Ali Eydgahi, Eastern Michigan University; Ilkhomjon Amanov, Eastern Michigan University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

moderate positiverelationship between the variable of Ease of Use and Behavior. In other words, if students findthe usage of a smartphone is easy, they are more willing to use a smartphone in classroom. H7. There is a positive significant relationship between Usefulness and BehaviorThe perception of Ease of Use is another internal factor that reflects the individual willingness toadapt or perform a task if the person feels performing that specific task is easy. Table 13 presentsthe results of the correlation analysis between two factors of perceived Usefulness and Behavior. Correlations Usefulness Behavior Usefulness

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Lulu Sun, Embry-Riddle Aeronautical Univ., Daytona Beach; Yan Tang, Embry-Riddle Aeronautical Univ., Daytona Beach

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Diversity

Tagged Divisions

Computers in Education

. Figure 1 and Figure 2 show snapshots of the concept test question and student responseson PollEverywhere.com from Graphical Communications, and Dynamics courses respectively.Figure 3 shows a snapshot of the open-ended question and student responses from ControlSystems. The lectures were punctuated by multiple-choice conceptual questions or open-endedquestions to test students’ understanding of the material. In the multiple-choice conceptualquestions, often the distracters (incorrect responses) reflect typical student misconceptions.These questions are good indicators of students’ conceptual understanding, especially infundamental courses. The open-ended questions provide the senior-level students an opportunityto improve their critical thinking

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

German Carro Fernandez P.E., Spanish University for Distance Education (UNED); Manuel Castro, Spanish University for Distance Education (UNED) ; Elio Sancristobal, Spanish University for Distance Education (UNED); Francisco Mur Perez, Spanish University for Distance Education (UNED)

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Diversity

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Computers in Education

conducted with teachers from different educational areas with different skills. Theresult was in any case a correct installation of laboratory testing; a robot arm; and the onlydifferences were reflected in a little more time in cases where teachers have less knowledge ofcomputer/electronics.Regarding the use of the system by the students, all of them accessed the system through alogin/password traditional login and they could manipulate and control the robotic or electricalequipment both as a group; leaded by the teacher, or individually in slots of 15 minutes ofduration or through a pre-booking system integrated into SiLaRR and that can be configured bythe administrator and managed using the software.To achieve the universalization of system we

Conference Session

Course Development / Curriculum Development

Collection

2015 ASEE Annual Conference & Exposition

Authors

Wade Fagen-Ulmschneider, University of Illinois, Urbana-Champaign; Cinda Heeren, University of Illinois, Urbana-Champaign; Geoffrey L. Herman, University of Illinois, Urbana-Champaign; Matthew West, University of Illinois, Urbana-Champaign

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Diversity

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Computers in Education

rapidly increasing expectations forstudents’ competencies in computing that went beyond simply word processing andspreadsheets. In response, our “Introduction to Computing” course was reengineered during theSpring 2014 semester with a four-pronged vision: (1) modernizing the curriculum by moving thecourse from a tools-based course to a computing-based course, (2) elevating student engagement,(3) scaling the course for growth, and (4) making the course relevant and accessible to anystudent, regardless of background or technology. Toward modernizing the curriculum, the course met with relevant stakeholders acrosscampus, surveyed top courses from other universities, and reflected on best practices from withinthe community of practice on

Conference Session

General Technical Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Michael Geoffrey Brown, University of Michigan

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Diversity

Tagged Divisions

Computers in Education

of a bibliometricapproach to mapping a network of scholarship. Similarly, bibliometrics account for veryspecific behaviors in scholarly discourse- namely, who a scholar cites in their work andwho a scholar is cited by. Bibliometrics do not reflect the way that these citations areframed in a text, so works that connect two scholars through bibliographic coupling mayreceive different framings (e.g. positive in one article, negative in another) by differentauthors.Research questionsTo that end the following research questions are proposed: 1. What are the most commonly cited articles in the literature on blended learning in engineering education? 2. What network of publication venues forms the basis of the discourse on blended

Conference Session

Course Development / Curriculum Development

Collection

2015 ASEE Annual Conference & Exposition

Authors

Carlotta A. Berry, Rose-Hulman Institute of Technology

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Diversity

Tagged Divisions

Computers in Education

control. The labs with range sensors were themost challenging because they did not have a complete understanding of odometry and sensorerror. For example, specular reflection for sonar or lighting conditions for infrared. Thissometimes made getting the line following, robot following, and obstacle detection to workcorrectly a bit frustrating. There were also some challenges with the robot marco polo and robotcommunication for similar reasons. One solution we found to make the robot communicationmore accurate was the addition of electrical tape on the sensor to narrow the field of view.Although many of the students had never written a technical memo/report before, reviewedtechnical literature, or written a discussion or annotated bibliography

Conference Session

Innovative Use of Technology II

Collection

2015 ASEE Annual Conference & Exposition

Authors

Peter Jamieson, Miami University; Jeff Eaton, Miami University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

more similar, and for the GraphletMatch metric the value willmove upwards towards 1 where 0 reflects no matching.From this figure, it appears that our new metric has a similar behavior to RGF-distance. As notedin our previous work 2 , in many cases student’s seem to be performing better after exam I thenexam II. We have no reason why this is the case, but we are performing additional experiments tosee if we can determine why this is happening. Broadly, it appears that the GraphletMatch metricis as good as RGF-distance with the added benefit of being a true matching of graphlets asopposed to RGF-distance’s measure of approximate structure.Figure 6 shows a similar comparison as previous but with the GranularSimilarity metric and thenew match

Conference Session

Innovative Use of Technology I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Zhou Zhang, Stevens Institute of Technology; Mingshao Zhang, Stevens Institute of Technology; Yizhe Chang, Stevens Institute of Technology, School of Engineering and Science; Sven K. Esche, Stevens Institute of Technology, School of Engineering and Science; Constantin Chassapis, Stevens Institute of Technology, School of Engineering and Science

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

. Therefore, after segmentation, these features were extracted by the featureextractor. Then, these features were input into the classifier. Basically, the classifier can recognizethese 3 objects with very high accuracy (89.1% for the digital scale, 91.3% for the pump and98.4% for the Xplorer GLX. The relatively low accuracy of the recognition is attributable to theKinect’s inability to cope with reflective surfaces which reduces the scanning accuracy. (a) (b) Figure 9: Step motor (a) photograph of physical step motor; (b) model in GBVL Page