Conference Session

Software and Programming

Collection

2016 ASEE Annual Conference & Exposition

Authors

Suxia Cui, Prairie View A&M University; Yonghui Wang, Prairie View A&M University; Lin Li, Prairie View A&M University; Xiaobo Peng, Prairie View A&M University; Bugrahan Yalvac, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

project is supported in part by National Science Foundation award # 1229744. The HPCcluster is funded by NSF MRI project with award # 1332566. The evidence based teachingmethod is supported by Department of Education award # P120A140064. Opinions, findings,and conclusions or recommendations expressed in this material are those of the authors and donot necessarily reflect the views of the National Science Foundation and Department ofEducation.Bibliography[1] P. S. Pacheco, "An Introduction to Parallel Programming," Morgan Kaufman, ISBN: 978-0-12-374260-5.[2] D.A. Bader and R. Pennington, ``Cluster Computing: Applications,'' The International Journal of High Performance Computing, 15(2):181-185, May 2001.[3] Retrieved from http://www.top500.org

Conference Session

Computers in Education Division Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Wen Huang, Arizona State University, Polytechnic campus

Tagged Divisions

Computers in Education

supplementary open questions related to participants’ experience in thecollaborative virtual assembly task, their reflections, and feedbacks. The development of these two questionnaires will follow the instrument developmentprocess in the affective domain introduced by McCoach, Gable, & Madura [35]. Specifically, foursteps will be completed in sequence: (1) literature reading and existing similar instruments search;(2) item writing or revision; (3) content validity assessment; (4) face validity assessment. Two orthree researchers in the engineering education and the automotive fields will be invited to assessthe validity of generated items and 3–5 undergraduate students to evaluate whether the instrumentscan be understood for the face

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Lee Kemp Rynearson, Purdue University, West Lafayette; David W Reazin, Purdue University

Tagged Divisions

Computers in Education

methods asan early version of the system was being prepared for use, and it was found that grading on thedigital rubrics was equivalent in speed or faster for all graders versus paper, but the specifictiming data was not retained once the decision to continue with development was made.Therefore, it is difficult to make quantitative statements about the improvements to efficiencyand reliability offered by the new computerized course tools. However, as the new systems offernew capabilities and eliminate certain classes of grading error entirely, some effects can bereported on qualitatively. In the cases, the effects and benefits reflect a consensus of the facultyand grading staff actively involved with the use of the computer tools.Computer Tool

Conference Session

Special Session on Fixed-Point Education

Collection

2007 Annual Conference & Exposition

Authors

David Anderson, Georgia Institute of Technology; Tyson Hall, Southern Adventist University

Tagged Divisions

Computers in Education

Lecture AssessmentMuch of the lecture is in preparation for the laboratory exercises, so in practice, student lab-oratory performance reflects student performance relative to the lecture material. However,lecture material is assessed independently using the following methods.Homework Assignments Fixed–point signal processing involves many concepts that students can practice through homework assignments. These include converting number formats includ- ing Q-format, evaluating filter scaling factors and stability, analyzing through-put and latency for specific structures, and designing and converting various structures such as distributed arithmetic filters.Pre-lab Assignments The pre-lab assignments directly assess and promote those

Conference Session

Web-Based Education

Collection

2007 Annual Conference & Exposition

Authors

James Squire, Virginia Military Institute; Vonda Walsh, Virginia Military Institute; H. Francis Bush, Virginia Military Institute; Gerald Sullivan, Virginia Military Institute; Anthony English, University of Tennessee-Knoxville

Tagged Divisions

Computers in Education

-alone software product and not as a web-basedapplication. Additionally, this data shows that decreasing the time delays inherent to a networkor software application does not improve learning in a proportional manner. From a cost-benefitspoint of view, only changes that result in the near-elimination of network delays to levels lessthan 60 ms are worthwhile. Page 12.1241.9Students’ subjective comprehension are harder to model than either objective comprehension orenjoyment ratings, possibly because a student’s self-confidence is more a function of personalitytraits rather than reflective of the learning experience. The graph is, therefore

Conference Session

Web-Based Education

Collection

2008 Annual Conference & Exposition

Authors

Mahmoud Quweider, The University of Texas at Brownsville; Fitra Khan, U of Texas at Brownsville; Juan Iglesias, The University of Texas at Brownsville

Tagged Divisions

Computers in Education

practices, and more. The vast amount ofapplications developed for the Internet, like the Web, make computer networking an integral partof our daily life. These new trends and applications, including concepts and disciplinesencompassed, have introduced new research and educational requirements demanded by industryand/or society that are reflected in work force demands, employment figures, research grantopportunities, and enrollment in educational programs related to computer networking.Tying in concepts and techniques from networking and distributed processing (NDP) into thecurricula will better prepare students for future work force, and is therefore a major componentof this application. The goal of the lab was to incorporate elements of NDP into

Conference Session

Mobile Robots in Education

Collection

2008 Annual Conference & Exposition

Authors

Anthony Reed, Louisiana Tech University; Taylor Creekbaum, Louisiana Tech University; Matthew Elliott, Louisiana Tech University; David Hall, Louisiana Tech University; Davis Harbour, Louisiana Tech University

Tagged Divisions

Computers in Education

) program under Award No. 0618288. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation.Bibliography1. Cropley D. H. and Cropley A. J., “Fostering Creativity in Engineering Undergraduates,” High Ability Studies, The Journal of the European Council for High Ability, Carfax Publishing, Taylor & Francis Ltd. UK, 11 (2), 2000, 207-219.2. National Academy of Engineering, “The Engineer of 2020.” The National Academies Press, Washington DC, 2004. www.nap.edu3. Parallax, Parallax Home Web Site, http://www.parallax.com/, 2007.4. Kelley, T., Littmann, J., and Peters, T., The Art of Innovation : Lessons in

Conference Session

Instrumentation and Laboratory Systems

Collection

2008 Annual Conference & Exposition

Authors

Jonathan Hill, University of Hartford; Akram Abu-aisheh, University of Hartford

Tagged Divisions

Computers in Education

for any one term to dominate its value must be significantly largerthan the others. To = Ttx 2 + Tf 2 + Trx 2 (4) • To = Overall response time • Ttx = Transmitter response time • Tf = L ⋅ ∆ t = Fiber spreading • Trx = Receiver response timeWe next consider the actual fiber. According to Weinert10, optical dispersion is the spreadingthat occurs to a light pulse as it travels along an optical fiber, as in Figure 5. Here we considerdispersion due to the various optical modes that appear in a plastic fiber. The idea is that a lightray traveling straight down a fiber follows a shorter path and will arrive at the receiver soonerthan a ray that reflects along

Conference Session

Software and Hardware for Educators I

Collection

2009 Annual Conference & Exposition

Authors

Michael Fuller, Auburn University; Chetan Sankar, Auburn University; P.K. Raju, Auburn University

Tagged Divisions

Computers in Education

conclusions or recommendations expressed in this paper are those of theauthors and do not necessarily reflect the views of the National Science Foundation.We thank Mr. K.P. Raghavan, Executive Vice President (Corporate Center), ECC Division, Mr.P. Rengarajan, Senior-Manager, System, and Mr. G.D. Sharma, Vice President, HumanResources, L&T for sponsoring and approving this case study. We also thank Dr.Ramachandraiah Professor, Department of Civil Engineering, Indian Institute of Technology,Madras, for coordinating the local arrangements.References 1. Accreditation Board for Engineering and Technology, Inc., www.abet.org/criteria.html, 2009. 2. Educating the Engineer of 2020: Adapting Engineering Education to the New Century, National

Conference Session

Software and Hardware for Educators III

Collection

2009 Annual Conference & Exposition

Authors

Silas Bernardoni, University of Wisconsin, Madison; Mauricio Rodríguez Alcalá, Skidmore College; Maria Rodriguez Alcala, Paraguay Educa

Tagged Divisions

Computers in Education

training program in preparation for the accelerated growth that is scheduled for theproject.Evaluating Student Learning University students have played an integral part in the Wisconsin OLPC project and alesser but notable presence in the Paraguay deployment. The university students involved in theproject covers a range of majors, focusing mostly on engineering and computer science. Thistrend is seen as a reflection of the project’s nature as well as the choice of academic departments Page 14.1342.8that were chosen to house the XO projects in their respective universities. The Wisconsin OLPCproject is based out of the UW-Madison Engineering

Conference Session

Embedded Computing

Collection

2009 Annual Conference & Exposition

Authors

Michael Swanbom, Louisiana Tech University; Davis Harbour, Louisiana Tech University; Hisham Hegab, Louisiana Tech University; Danny Eddy, Louisiana Tech University

Tagged Divisions

Computers in Education

. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation.If you would like more information, contact:Michael K. Swanbom, Ph.D.P.O. Box 10348Ruston, LA 71272-0046mswanbom@latech.eduOffice (318) 257-3908FAX (318) 257-4630References1. Splitt, F.G., “Systemic Engineering Education Reform: A Grand Challenge.” The Bent of Tau Beta Pi, Spring 2003.2. Sheppard, S. and Jenison, R., “Examples of Freshman Design Education.” International Journal of Engineering Education, 13 (4), 1997, 248-261. Page 14.56.163

Conference Session

Computational Tools and Simulation II

Collection

2009 Annual Conference & Exposition

Authors

Brianno Coller, Northern Illinois University

Tagged Divisions

Computers in Education

controllersomewhere. This challenge required students to think deeper and more creatively. They had todevise their own control architecture and test it conceptually and implement it. Students had todo a lot of tinkering, in a good constructive way. As will be described in a forthcoming article,learning measures related to this exercise were the ones in which we observed mostimprovement.Reflections “Learning is a cycle of probing the world (doing something); reflecting in and on this action and, on this basis, forming a hypothesis; reprobing the world to test this hypothesis; and then accepting or rethinking the hypothesis.”This is one of several fundamental learning principles, proffered by Gee5, for which the mediumof video games may be particularly

Conference Session

COED: EE Topics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Rustin Webster, Purdue University, New Albany; Joseph F Dues Jr., Purdue University

Tagged Divisions

Computers in Education

decades. VR might be able to address them all with its ability to offer anew type of discovery and organic exploration to encourage lifelong learning.  Attention Gap. Attention spans have been decreasing over the past decade with the increase in external stimulation (Statistic Brain Research Institute, 2016). An exception to this is gaming, where it has shown that users are able to engage for extended periods.  Time-Effective Use Gap. Opportunities for a learner to apply the knowledge and/or practice the skills that are being taught are limited.  Pedagogy Gap. Modern pedagogy is not reflective of how the world looks and acts like in the 21st century and shows much resistance to change.Of course, with any new

Conference Session

CoED: Embedded Systems and Robotics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Michael Henry Schulz, The Ohio State University; Evan J. Danish, The Ohio State University; Tyler Wolf Leonhardt, Microsoft Corporation; John William Jackson, Ohio State University; David Joseph Frank, Ohio State University; Richard J. Freuler, The Ohio State University

Tagged Divisions

Computers in Education

took for events on thecourse to be reflected on the course computer’s display. This was caused by the overheadinvolved with creating and sending the messages, and with generating the address for a messagereceiver. Network packets sent via UDP, as in the original framework, are not guaranteed toarrive at their destination nor to arrive in any particular order, and issues involving droppedpackets impacted performance as well.These issues impacted the students because the tasks that their robots completed would notregister as soon as they needed to for the students to adequately progress in the challenge.Additionally, the steep learning curve of the system made it difficult to learn for new developers,which hindered the original intent for a

Conference Session

Technical Session 10: Simulation and Modeling

Collection

2019 ASEE Annual Conference & Exposition

Authors

Stephen W. Crown, University of Texas, Rio Grande Valley; Constantine Tarawneh, University of Texas Rio Grande Valley

Tagged Divisions

Computers in Education

coincidewith the thermodynamics course. The opportunity to see it applied in another course may havepiqued their interest. User's Survey (n = 92) 2 1.5 1 0.5 0 -0.5 -1 -1.5 -2 EASY-TO-USE HOMEWORK NOZZLES HANDOUT ENGINEERING Questions from user's perspective Excel LabView MatLab SciLab Web PageFigure 9: Survey results related to user experience (evaluation of other groups)The survey gave students the opportunity to add additional comments about the project. Arepresentative sample of the feedback is listed in Table 2. The comments reflect many of thesame results already

Conference Session

Computers in Education Division Technical Session 6: Computer Science Freshman Courses

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Joe Michael Allen, University of California, Riverside; Frank Vahid, University of California, Riverside

Tagged Divisions

Computers in Education

theability to pivot among programs each week. To take a closer look at student pivot patterns, weconstructed visual diagrams to represent student workflow. In this section, we show multipleworkflow diagrams to visually represent how students worked on their programmingassignments during various weeks. A key question is "What are some observed pivot patterns?"6.1 Analysis and procedureTo visually represent student workflow, we created GANTT charts for each student for everyweek in the quarter. A GANTT chart shows activities displayed against time. Each activity isrepresented by a bar; the position and length of the bar reflects the start date, duration and enddate of the activity [11]. We chose this representation since GANTT charts allow us to see

Conference Session

Computers in Education Division Technical Session 2: Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Wayne L. Chang, University of Illinois at Urbana - Champaign; Matthew West, University of Illinois at Urbana - Champaign; Craig Zilles, University of Illinois at Urbana - Champaign; David Mussulman, University of Illinois at Urbana - Champaign; Carleen Sacris, University of Illinois at Urbana-Champaign

Tagged Divisions

Computers in Education

supports students’ learning. Learning and Teaching in Higher Education, 1:3–31, 2005.[12] S. E. Harpe. How to analyze Likert and other rating scale data. Currents in Pharmacy Teaching and Learning, 7(6):836–850, 2015. doi: 10.1016/j.cptl.2015.08.001.[13] M. K. Hartwig and J. Dunlosky. Study strategies of college students: Are self-testing and scheduling related to achievement? Psychonomic Bulletin and Review, 19:126–134, 2012.[14] Charles Henderson and Kathleen A Harper. Quiz corrections: Improving learning by encouraging students to reflect on their mistakes. The physics teacher, 47(9):581–586, 2009.[15] G. Herman, K. Varghese, and C. Zilles. Second-chance testing course policies and student behavior. In Proceedings of the

Conference Session

COED: Online and Blended Learning Part 2

Collection

2018 ASEE Annual Conference & Exposition

Authors

Luke S. Lee P.E., University of the Pacific; Hector Estrada, University of the Pacific; Mehdi Khazaeli, University of the Pacific

Tagged Divisions

Computers in Education

textual and verbal descriptions in favor of examples tocomplete problem assignments [8].Amongst instructors, there was a distribution of responses related to content with an emphasis onthe effectiveness of the video content and interacting with the viewer. These responsespotentially reflect the importance instructors place on retaining the attention of the learnerthroughout the video. There were no responses related to creating content that providesderivations or explanations of theory.Instructor PresenceWith 20 total responses (6 student 14 instructor responses), instructor presence was consideredthe third most important feature based on overall responses. Responses related to the instructorpresence category were subcategorized as shown in Table

Conference Session

Technical Session 7: Online and Distributed Learning

Collection

2019 ASEE Annual Conference & Exposition

Authors

Otto Borchert, Missouri Southern State University; Abigail Byram, Virginia Commonwealth University; Debra Mardell Duke, Virginia Commonwealth University; Alex David Radermacher, North Dakota State University; Mourya Reddy Narasareddygari, North Dakota State University; Gursimran Singh Walia, North Dakota State University

Tagged Divisions

Computers in Education

learning objects in other languages and development environments as we findmore collaborators.Another issue with the current version of SEP-CyLE is that students who are using thecollaborative learning engagement strategy aren’t actually collaborating. They are completingthe same problems individually and their group score reflects how many quiz questions eachperson gets right. One enhancement might be creating a system that would require them to workcollaboratively to solve a more complicated problem or to engage in other activities such asreviewing each other’s code.Another problem is the lack of an integrated IDE within SEP-CyLE. We would like to see theability to have students work on small code problems (or eventually entire

Conference Session

Technical Session 3: The Best of Computers in Education

Collection

2019 ASEE Annual Conference & Exposition

Authors

Shaya Wolf, University of Wyoming; Fiona P. Moss, University of Wyoming; Rasana Manandhar, University of Wyoming; Madison Cooley, University of Wyoming; Rafer Cooley, University of Wyoming; Andrea Carneal Burrows Borowczak, University of Wyoming; Mike Borowczak, University of Wyoming

Tagged Divisions

Computers in Education

National Science Foundation (NSF) and National Security Agency(NSA) GenCyber Award #H98230-18-1-0095 (called GenCyber:COWPOKES); 2) The NSF NoyceGrant No 1339853 (called SWARMS); and 3) The US federal Math and Science Partnership grantunder No Child Left Behind (NCLB) (P.L.107F110, Title II, Part B) administered by the WyomingDepartment of Education MSP Grant No. 1601506MSPA2 (called RAMPED). Any opinions, findings,and conclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the NSF, the NSA, or the U.S. government.This work was completed with the help of students from the University of Wyoming through thedirection of the College of Engineering’s CEDAR (Cybersecurity EDucation

Conference Session

Innovative Teaching

Collection

2016 ASEE Annual Conference & Exposition

Authors

David J. Frank, The Ohio State University; Kevin J. Witt, The Ohio State University; Chris Hartle; Jacob J. Enders, The Ohio State University; Veronica Beiring, The Ohio State University; Richard J. Freuler, The Ohio State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

losingcommunication with the RPS system.Beyond the level of accuracy provided, the system does face other limitations. Reflected lightand glare inhibit QR code detection when said glare occurs adjacent to the QR code itself.Detection is also inhibited when QR codes are not perpendicular to the camera. The system canhandle most skewing of QR codes less than 20°, however larger angles result in loss of detectionwhile moving and severe angles can prevent stationary QR codes from being detected at all.CostThe cost of the system for support of one course was approximately $6,000. This estimateincluded the 8020 aluminum structure, the cost of the LabVIEW and NI vision software, thecomputer, and the electronics of the system. The effective cost of the system for

Conference Session

Modeling and Simulation

Collection

2016 ASEE Annual Conference & Exposition

Authors

Luis E Monterrubio, Robert Morris University

Tagged Divisions

Computers in Education

Sophisticated Competent Not yet Competent Codes are properly implemented showing an Codes solve1.2 FEM using understanding of how to displacements, but plots Matlab apply boundary conditions, of deflection of the beam Codes do not solve loads and keeping track of are missing or comments the problem, ABET the degrees of freedom of and conclusions do not comments are Outcome the system. Comments and reflect a good vague a conclusions about the understanding of the differences in accuracy of results. the results are

Conference Session

Data Analysis and Assessment

Collection

2015 ASEE Annual Conference & Exposition

Authors

David B. Knight, Virginia Tech, Department of Engineering Education; Cory Brozina, Virginia Tech; Eric M. Stauffer, Virginia Tech; Chris Frisina, Virginia Tech; Troy D. Abel, Virginia Tech

Tagged Divisions

Computers in Education

, 1-26.13 Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166-183. doi:10.3102/0002831207312909.14 Schunk, D. H., & Zimmerman, B. J. (1998). Self-regulated learning: From teaching to self-reflective practice. New York: Guilford Press.15 Arnold, K. E., & Pistilli, M. D. (2012). Course Signals at Purdue: Using learning analytics to increase student success. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 267– 270). ACM. doi:10.1145/2330601.233066616 Hickey, D. T., Kelley, T. A., & Shen, X. (2014). Small to

Conference Session

Computer-Based Tests, Problems, and Other Instructional Materials

Collection

2015 ASEE Annual Conference & Exposition

Authors

Alex Daniel Edgcomb, University of California, Riverside; Joshua Sai Yuen, University of California, RIverside; Frank Vahid, University of California, Riverside

Tagged Divisions

Computers in Education

theeffectiveness of student’s assessment and peer instruction[7][10][13][14][16]. de Alfaro[7]created a crowdsourced grading tool, CrowdGrader, that allows students to grade andreview their peer's homework submissions. CrowdGrader was found to actively involvestudents in grading other's assignments. O'Neill[14] found that with the use ofcollaborative class lecture notes, students created high-quality lecture notes whenprovided with a lecture skeleton layout. Notes created by the students also reflected howstudents were understanding the content in the course. Kumar[13] studied the effectivenessof an online tutor that provided questions to a student and then graded the student'sanswer with feedback. Students showed a 30-60% improvement from pre-quiz to

Conference Session

General Technical Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Michael Geoffrey Brown, University of Michigan

Tagged Topics

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

Tagged Topics

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

Simulation

Collection

2015 ASEE Annual Conference & Exposition

Authors

Natasha Smith P.E., University of Southern Indiana; Julian Ly Davis, University of Southern Indiana

Tagged Divisions

Computers in Education

the assigned programming projectswere slightly more substantial. Exam metrics reflected this change in emphasis as well. Studentswere more capable of generating global beam stiffness matrices by hand (87%), and slightly morefamiliar with shape functions (70%). However, nearly half of students could not answer a con-ceptual question regarding the difference between a finite element and continuous solution for anelastic bar.It should be noted that both class sizes were small (11 and 15), and that there were differences inexpectations in each group. In 2013, the students were nearer completion of the degree, with moreexperience from upper level courses with a significant programming component. Specifically,45% of the 2013 cohort had taken two or

Conference Session

CoED: Computer Science Topics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Lulu Sun, Embry-Riddle Aeronautical Univ., Daytona Beach; Christina Frederick, Embry-Riddle Aeronautical Univ., Daytona Beach; Li Ding, Embry-Riddle Aeronautical University; Rebecca Rohmeyer, Embry-Riddle Aeronautical University

Tagged Divisions

Computers in Education

are those of the authorsand do not necessarily reflect the views of the National Science Foundation. The authors alsowould like to acknowledge the effort from Ms. Caroline Liron, Dr. Matthew Verleger, whohelped conduct the project in their classes, Dr. James Pembridge who offered suggestions on theproject design and implementation, and the support from the Institution Research at Embry-Riddle Aeronautical University who conducted and collected the survey data for this project.Bibliography1. Bualuan, R. (2006). Teaching Computer Programming Skills to First-year Engineering Students Using Fun Animation in MATLAB,” Paper presented at the 2006 American Society for Engineering Education Annual Conference & Exposition, Chicago, IL.2

Conference Session

Computing Technology Session 2

Collection

2017 ASEE Annual Conference & Exposition

Authors

M T Taher; Usman Ghani, Robert Morris University; Ahmed S. Khan, DeVry University, Addison

Tagged Divisions

Computers in Education

methodology will not only improve students’ learningbut will also offer low-cost and flexible training platform necessary for 21st century students.Even though AUC is a preferable type of feedback compared to KCR, it is more complex andtherefore expensive to develop. Instructional designers are often interested in efficiency. It mightbe expected that the additional steps necessary for AUC would require more study time.References [1] Nahvi, M. (1996). Dynamics of student-computer interaction in a simulation environment: Reflections on curricular issues. Proceedings of the IEEE Frontiers in Education, USA, 1383-1386. [2] Hsieh, S., & Hsieh, P.Y. (2004). Integrating virtual learning system for programmable logic controller