Conference Session

Effective Use of Technology in Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Judith Virginia Gutierrez, National Autonomous University of Mexico (UNAM); Frida Diaz Barriga, National Autonomous University of Mexico (UNAM); Nelly Ramirez-Corona, Universidad de las Americas Puebla; Aurelio Lopez-Malo, Universidad de las Americas Puebla; Enrique Palou, Universidad de las Americas Puebla

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Computers in Education

Paper ID #16805Personal Learning Environments: Analysis of Learning Processes, Reflection,and Identity in an Academic ContextMiss Judith Virginia Gutierrez, National Autonomous University of Mexico (UNAM) PhD. Science, Engineering and Technology Education. Postdoctoral Fellow at Universidad Nacional Autonoma de Mexico.Dr. Frida Diaz Barriga, National Autonomous University of Mexico (UNAM) The Mexican researcher and teacher Frida D´ıaz Barriga Arceo serves at the Faculty of Psychology of the National Autonomous University of Mexico. Her academic career includes a degree in Psychology, Mas- ter’s degree in Educational

Conference Session

Software and Programming

Collection

2016 ASEE Annual Conference & Exposition

Authors

Anurag Goswami, North Dakota State University; Gursimran Singh Walia, North Dakota State University

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Diversity

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Computers in Education

ofinspections in software industry (i.e. to save rework cost, effort, and time), academia should alsoprioritize training students with early quality assurance skills (i.e. inspections) during SDLC.Therefore, this research reports the results from a practical training experience to help studentsimprove their understanding of inspection which in turn, would improve their inspectionperformance. This paper presents results of an academic study on the effect of reflection(training) technique on thirteen graduate and twenty-six undergraduate students on theirinspection performance. The participants individually inspected two different requirementdocuments using fault-checklist method and recorded faults pre and post reflection. We analyzedthe impact of

Conference Session

Innovative Use of Technology in K-12 Outreach

Collection

2016 ASEE Annual Conference & Exposition

Authors

Hugo Gomez, University of Texas - El Paso; Mike Thomas Pitcher, University of Texas - El Paso; Hector Erick Lugo Nevarez, University of Texas - El Paso; Pedro Arturo Espinoza, University of Texas - El Paso; Randy Hazael Anaya, University of Texas - El Paso; Oscar Antonio Perez, University of Texas - El Paso; Herminia Hemmitt, University of Texas - El Paso

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Diversity

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Computers in Education

. Through this progression they were able to master most if not all of the challengesand learning outcomes.In this paper we will look at some examples of sessions based on these learning blocks and wewill examine if the camp met the expectations of the campers based on pre- and post-activitiesfor particular learning blocks and the end of camp surveys. We will also look at their level ofengagement during activities as well as how formative assessment was built into the campthrough one of the self-reflection pieces that was part of the process.Materials and MethodsThe primary design strategies for our camp were based on the implementation of learning blocks,which were strongly focused on formative assessment strategies, Blooms Taxonomy

Conference Session

Modeling and Simulation

Collection

2016 ASEE Annual Conference & Exposition

Authors

Elif Miskioglu, Bucknell University; Kaela M Martin, Embry-Riddle Aeronautical University, Prescott

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Computers in Education

Felder-SolomanIndex of Learning Styles (ILS). The learning styles assessment is an open source online tool with44 questions that determines student’s learning style using the Felder-Silverman model oflearning styles.27 The Felder-Silverman model is a multidimensional characterization of learningstyle preferences that attempts to qualify how individuals prefer to perceive, receive, manage,and interpret information. Each of the four dimensions contain two opposing preferences(active/reflective, sensing/intuitive, visual/verbal, sequential/global) and are evaluated on a scalefrom “strong” to “balanced” for a preference within each dimension. The Felder-Silvermanmodel and ILS have undergone several validity and reliability studies.28-31 The ILS has

Conference Session

Technology-Related Educational Research

Collection

2016 ASEE Annual Conference & Exposition

Authors

Swaroop Joshi, Ohio State University; Neelam Soundarajan, Ohio State University

Tagged Divisions

Computers in Education

students usingCSILE focuses on a specified relatively broad problem and begin to build a database of informationabout the topic. There is opportunity for reflection and peer review of each others’ contributions bystudents. More recently, some authors used wikis to allow users to add, modify, or delete contentusing a standard browser, to create a site that thoroughly explores a topic. But, unfortunately, manyof those studies have not produced as good results as expected. For instance, Cole 13 conducted anexperiment in a course on information systems with 75 students; it was organized so that lectureswere in alternate weeks, the other weeks being intended for students to discover new material andpost to the class wiki. Fully one quarter of the

Conference Session

Computer-Based Games and Animations in Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Jacob R Grohs, Virginia Tech; Darren K Maczka, Virginia Tech Department of Engineering Education; Michelle Soledad, Virginia Tech; Kiran Kelsey Bagalkotkar

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Diversity

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Computers in Education

successful performance onwell-structured problems is not a predictor of success on ill-structured problems becausefundamentally different reasoning skills are needed.7 While well-structured problems are oftensolved once an appropriate algorithm has been identified and used, solving ill-structured problemsinvolves skills such as argumentation and reflective design to robustly identify the problem itselfbefore considering potential solutions.9,10 Success in the setting and solving of ill-structuredproblems has been linked to metacognitive strategies,7,9 specific cognitive skills such asanalogical reasoning,11 and epistemological beliefs.12,13 Analogical reasoning is a higher orderthinking process whereby novel problems are interpreted as an amalgam of

Conference Session

Best of Computers in Education Division

Collection

2016 ASEE Annual Conference & Exposition

Authors

Petr Johanes, Stanford University; Larry Lagerstrom, Stanford Center for Professional Development

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Computers in Education

recommendation and into learning personalization.RecommendationsWe include the recommendations below not as an exhaustive guide to all aspects of producingeducational online videos, but rather as a starting primer to create such videos in line with robustfindings and best practices.Recommendation #1: Plan pedagogy before you produce video.In the words of Mayer: “Decisions about how to design a multimedia message always reflect anunderlying conception of how people learn - even when the underlying theory of learning is notstated” (p. 46).19 Therefore, in line with the second and third lenses (learning environment andlearning data), we highly recommend that before producing a video an instructor should clearlyarticulate the learning objectives of the

Conference Session

Effective Use of Technology in Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Myrtede Christie Alfred, Clemson University; Morris Branchell Lee III; David M. Neyens, Clemson University; Anand K. Gramopadhye, Clemson University

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Computers in Education

qualitative research process.5 After several interviews the researcherrevisited the notes from the individual interviews and then compared the notes to identifytrends.6 This process was repeated with every four set of interviews and again at the end of theinterview process. In the research memos, the lead researcher also reflected on theseinterpretations, noting her own thoughts, feeling, and preconceptions about the phenomena beingstudied.After all of the 20 interviews were completed, the researcher defined an initial set of conceptsusing the memos from the interviews as well as the transcriptions. Thoughts, quotes andparaphrased excerpts from the different interviews were grouped based on similarity using aprocess comparable to an affinity diagram

Conference Session

Innovative Use of Technology in K-12 Outreach

Collection

2016 ASEE Annual Conference & Exposition

Authors

Thad B. Welch III P.E., Boise State University; Cameron H. G. Wright P.E., University of Wyoming; Tara N Kimmey; Andres Valdepena Delgado, Boise State University; Sue ORorke, Gifted and Talented Facilitator, West Ada School District ; Morgan Brimstein, Boise State University ; Amy Gabriella Norris; Drew Buckmiller, Boise State University; Ryan Schwartz, Boise State University; Donna R Welch, Boise State University; Rhett James Edwards, Boise State University

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Computers in Education

light.Source: http://9-4fordham.wikispaces.com/file/view/em_spectrum.jpg/244287321/em_spectrum.jpgReveals DifferencesFigure 4. Two identical mugs in the visible spectrum.Figure 5. The two mugs viewed in the infrared spectrum.Figures 4 and 5 illustrate how infrared imaging can be used to see things that areotherwise impossible to see. Figure 4 shows two seemingly identical mugs. However,as shown in Figure 5, the mug on the left has been filled with cold water, and the mugon the right has been filled with hot water. One really interesting aspect of this image isthat we can see the reflection of the heat, the infrared radiation, from the hot mug on thecold mug and on the table.Shows Hot Spots Figure 6: Phone chargersThe picture in Figure 6 is

Conference Session

Best of Computers in Education Division

Collection

2016 ASEE Annual Conference & Exposition

Authors

Osman Yasar, The College at Brockport - SUNY; Peter Veronesi, The College at Brockport - SUNY; Jose Maliekal, The College at Brockport, SUNY; Leigh J Little, The College at Brockport - SUNY; Sounthone E Vattana, The College at Brockport - SUNY; Ibrahim H. Yeter, Texas Tech University

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Computers in Education

findings support effectiveness of computer simulations. Inmany ways simulation has been found to be even more effective than traditional instructional practices.In particular, the literature shows that computer simulations can be effective in: 1) developing sciencecontent knowledge and process skills, and 2) promoting inquiry-based learning and conceptual change.Effectiveness of CMST in education is also well grounded in contemporary learning theories thatrecognize the role of experience, abstract thinking, and reflection in constructing knowledge anddeveloping ideas and skills.16, 22, 27, 38, 61 Cognitive aspects of CMST are being further detailed in a recentarticle by Yaşar67 using a computational model of how the mind learns. Computational

Conference Session

Online, Hybrid, and other Virtual Learning Environments

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kerrie A Douglas, Purdue University, West Lafayette; Brittany Paige Mihalec-Adkins, Purdue University; Nathan M. Hicks, Purdue University, West Lafayette; Heidi A. Diefes-Dux, Purdue University, West Lafayette; Peter Bermel, Purdue University; Krishna Madhavan, Purdue University, West Lafayette

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Computers in Education

instruction to the needs of the intended learners isan undeniably critical component of teaching. Smith and Ragan refer to this process asinstructional design and define it as a “systematic and reflective process of translating principlesof learning and instruction into plans for instructional materials, activities, informationresources, and evaluation” (p. 4).7 Further, Smith and Ragan assert that understanding thelearners, which requires consideration of learners’ needs and goals, is not only necessary butcentral to successful instructional design.7 Regardless of educational platform, instructioncannot be appropriately designed to meet the needs of the learners and ultimately produce thedesired outcomes without a comprehensive understanding of the

Conference Session

Best of Computers in Education Division

Collection

2016 ASEE Annual Conference & Exposition

Authors

Darren K Maczka, Virginia Tech Department of Engineering Education; Jacob R Grohs, Virginia Tech

Tagged Divisions

Computers in Education

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

Conference Session

Teaching and Advising Tools Using Computers and Smart Devices

Collection

2016 ASEE Annual Conference & Exposition

Authors

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

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Diversity

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Computers in Education

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

Conference Session

Computer-Based Games and Animations in Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Frank Vahid, University of California - Riverside; Susan Lysecky, zyBooks, Inc.; Alex Daniel Edgcomb, University of California - Riverside

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Computers in Education

  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

Conference Session

Online, Hybrid, and other Virtual Learning Environments

Collection

2016 ASEE Annual Conference & Exposition

Authors

Ernest M. Kim P.E., University of San Diego; Thomas F. Schubert Jr. P.E., University of San Diego; Cyd Burrows, University of San Diego; Shahra Meshkaty, University of San Diego

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Computers in Education

course.Student perceptions of the use of iPads in the classroom and student attitudes and studentaccomplishments are considered with similar results as reported by Goyings, Klosky, andCrawford [1], and Zhu [2].II. Classroom Instructional MethodsStudents who are in a traditional lecture setting often are so busy trying to capture what is beingsaid at the instant the speaker says it that they do not have the time to reflect upon what is beingsaid. Therefore, they may miss significant topical points because they are trying to transcribe theinstructor’s words. [3][4]. In a flipped classroom, the class-lecture time is replaced by in-classactivities. Lectures and other learning material are delivered so that students are able to view andimmerse themselves in

Conference Session

Innovative Teaching

Collection

2016 ASEE Annual Conference & Exposition

Authors

Lawrence O Kehinde P.E., Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria; Obasegun Tekena Ayodele, IEEE Educational Activities; Olubiyi Olaoluwa Akintade, Department of Electronic & Electrical Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria.; KAZEEM Olaide Olawale, Obafemi Awolowo University, Ile-Ife, Nigeria

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Computers in Education

notbeen done or reported. This work, therefore, focuses on a teaching model that will help studentsexperiment with IoT ideas through some laboratory sessions. Figure 2: Schematic diagram of the setupA number of learning models with corresponding teaching styles have been identified inengineering education [9]. These learning models include;  Sensing and intuitive learning  Visual and auditory learning  Inductive and deductive learning  Active and reflective learning  Sequential and global learning Figure 3: Example of device-to-gateway communication model [3]This work uses the sequential teaching approach to draft quasi-experiments for teaching basicIoT concepts. The aim is to teach IoT in a

Conference Session

Effective Use of Technology in Education

Collection

2016 ASEE Annual Conference & Exposition

Authors

Nina Magpili, Engineering Management & Systems Engineering (EMSE), Old Dominion University; Pilar Pazos, Old Dominion University; Preetham Sathish Ullal, Old Dominion University

Tagged Divisions

Computers in Education

learners surpasses unsupported instruction with regards to the effective transfer ofknowledge.6 Collaborative work largely reflects the actual environment in engineering-intensiveorganizations that use interdisciplinary teams to solve engineering problems. By carefullyconstructing guidance to support the team in the form of tools and guided activities, we canfacilitate and evaluate interactions and then further determine design improvements to ensurethat effective collaboration takes place. The structure and goals of the collaboration tool andinstructional scaffolds aligns with evidence-based research and the foundational knowledge ofteam processes and team effectiveness.14-16 The collaboration tool was built using Google Appsthat are freely

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

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Diversity

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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

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

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Diversity

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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

Innovative Use of Technology in K-12 Outreach

Collection

2016 ASEE Annual Conference & Exposition

Authors

Fernando Garcia Gonzalez, Florida Gulf Coast University; Janusz Zalewski, Florida Gulf Coast University

Tagged Divisions

Computers in Education

and immediately start moving towards the next point.As a result the shapes drawn looked deformed. Figure 20 shows a sample drawing from one ofthe teams displaying the word “Hi.”This error cause frustration which is reflected in the surveys the students took at the end of thecamp. However even the distorted drawing they were able to produce resulted in the studentsdisplaying great excitement. Other factors such as a weak grip on the pen and physical play inthe arm’s joints also produced distortion however the students seamed to understand thesecharacteristics. Figure 20: a sample drawing from one of the arms where the arm drew the word “Hi.”The best way to find errors or weaknesses on a software product is to give it to a set of

Conference Session

Technology-Related Educational Research

Collection

2016 ASEE Annual Conference & Exposition

Authors

Krishna Madhavan, Purdue University - West Lafayette; Michael Richey, The Boeing Company; Barry McPherson, The Boeing Company

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Diversity

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Computers in Education

learners work hand-in-hand withindustry experts, academic researchers, and data scientists to elicit the type of design behaviorsthat reflect real world engineering practice in the aerospace industry. This allows us to develop,test, and refine the instrumentation methodology, data architectures, analytics, and visualizationapproaches before interfering with the day-to-day work within an organization. In the context ofour work, a program called AerosPACE was developed not only as a senior capstone course, butalso to serve as a test bed.AerosPACE is an engineering education program developed by a large US aerospace company.The primary goal of this program is to bridge the gap between theory and application, (and tohelp students understand the

Conference Session

Computers in Education Division Poster Session

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kenneth A. Ritter III, University of Louisiana, Lafayette; Terrence L. Chambers PE, University of Louisiana, Lafayette; Christoph W. Borst, University of Louisiana, Lafayette

Tagged Divisions

Computers in Education

all informationalicons, the student is then informed to follow the yellow arrows to the solar collectors shown inFigure 6. Figure 6: Left: Area 3, solar collectors. Right: Area 4, boiler.Area 3, Solar Collectors: In this area the student learns about how the solar troughs track the sunthroughout the day to capture the direct sunlight and reflect it to the central absorber tube. Also itis explained in detail how sunlight passes through the transparent glass of the absorber tube, orevacuated tube, and how the heat is transferred to the working fluid. The student is theninstructed to point the solar collectors to capture the direct sun at high noon to collect solarenergy and heat up the working fluid. Once finished the student

Conference Session

Teaching and Advising Tools Using Computers and Smart Devices

Collection

2016 ASEE Annual Conference & Exposition

Authors

Oscar Antonio Perez, University of Texas - El Paso; Virgilio Ernesto Gonzalez, University of Texas - El Paso

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Diversity

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Computers in Education

% 30.80% Table 5. Shows the results of answers for question 5In addition to results shown in Table 5 reflecting what other commitments students have everyweek, an average of Work/Family/Other commitments was calculated with results showing anaverage of 52.1 hours committed to activities per student. Table 6 shown below displays thestudents’ preference by grouping the answers from question one into two groups. These twogroups being prefer and not prefer. Advising System Type System Type at least Preferred not preferred no answer Face 2 Face 87.90% 12.10% 0.00% Mobile 70.10