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

Best of Computers in Education

Collection

2015 ASEE Annual Conference & Exposition

Authors

Borjana Mikic, Smith College; Al Rudnitsky, Smith College; Annick Jade Dewald; Anjali Karina Desai, Smith College

Tagged Divisions

Computers in Education

temperature differential? Students are encouragedto generate and post their ideas and theories about the topic and build directly on the ideas ofothers. This discourse is supported through a computer- based asynchronous collaborativelearning environment such as Knowledge Forum (KF)10. The workspace preserves an on-goingrecord of the discourse so that participants can return to earlier ideas for reflection, synthesis, andrefinement. In the process, students develop a questioning attitude, learn to identify personal andcollective gaps in knowledge and understanding, become self-directed learners who are capableof bringing in new sources of authoritative information, viewing such information from multipleperspectives in support of theory-development

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

Simulation

Collection

2015 ASEE Annual Conference & Exposition

Authors

Stephanie L. Cutler, Embry-Riddle Aeronautical Univ., Daytona Beach; Wendi M. Kappers, Embry-Riddle Aeronautical Univ., Daytona Beach

Tagged Divisions

Computers in Education

Kolb's four-partexperiential learning framework. “Knowledge construction has four main phases according toKolb’s experiential learning theory (1984) including simulation, reflection, abstraction, andexperimentation”4 (pg. 283). According to Dhulla, Kolb’s ELT “The learning process oftenbegins with a person carrying out an action and seeing the effects of the action; the second step isto understand the effects of the action. The third step is to understand the action, and the last stepis to modify the action given a new situation”19 (p. 111). We then linked these steps to thecomponents of the course under investigation, as seen in Figure 1.According to Kolb17, “immediate or Concrete Experiences are the basis for observations andReflections. These

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

James E. Lewis, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville

Tagged Divisions

Computers in Education

, and accessing and using anotherpersons’ account or electronic identify without explicit permission.Implementation PlanThe plan for providing students with instruction in this area would be to have them work ingroups and do role playing with developed scenarios. Students would do a table top exercise,with different students playing different roles from the scenario. Afterwards the students woulddiscuss and reflect as a group. The groups would then share out information from theirdiscussion and reflections with the whole class. This would allow for a whole class discussion Page 26.1759.7after allowing the students some time to process it in

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

Tagged Topics

Diversity

Tagged Divisions

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

Tagged Topics

Diversity

Tagged Divisions

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

Mobile Devices and Apps

Collection

2015 ASEE Annual Conference & Exposition

Authors

Rachel M. White, Oregon State University; Bill Jay Brooks, Oregon State University; Milo Koretsky, Oregon State University

Tagged Divisions

Computers in Education

studentresponses to open format questions. Students “ink” their responses with pen-enabled Androiddevices, iPads, iPhones, or tablet PCs. Students can respond to in-class questions with words,drawings, graphs, or equations. Creating these responses gives an opportunity to interact withthe subject material and increase metacognition. The instructor gains real-time feedback aboutwhat students are thinking and can address misconceptions and questions10.Mobile apps like InkSurvey help promote active learning by encouraging students to reflect onsubject material and explain concepts in their own words. Studies of more than 5,000 scienceand engineering students found that active learning methods double conceptual learning gains11and give a 25% higher pass rate

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Peter Goldsmith P.Eng., University of Calgary

Tagged Divisions

Computers in Education

. Page 26.1752.2Each module of this virtual laboratory focuses on explicit learner outcomes for a particularcourse. For example, the Planar Mechanisms module, which is the main focus of this paper, is forthe learning and assessment of concepts in a third-year mechanical engineering course on thekinematics and dynamics of mechanisms. The ‘Learning’ and ‘Teaching’ functions in theFLATLAB acronym reflect the student-centered and knowledge-centered components,respectively, of the ASK paradigm.While much of the current research on virtual learning environments focuses on immersive 3Denvironments 2 , FLATLAB takes advantage of the fact that many engineering systems have 2Drepresentations that learners can physically interact with through a 2D visuo

Conference Session

Computer-Based Tests, Problems, and Other Instructional Materials

Collection

2015 ASEE Annual Conference & Exposition

Authors

Dongdong Zhang, Prairie View A&M University; Xiaobo Peng, Prairie View A&M University; Bugrahan Yalvac, Texas A&M University; Deniz Eseryel, North Carolina State University; Uzair Nadeem, Prairie View A&M University; Atiq Islam, Prairie View A&M University; Deron Arceneaux, Prairie View A&M University

Tagged Divisions

Computers in Education

procedures and share themwith each other in groups. They provided feedback to each other’s screencasts and had theopportunity to reflect upon their own screencast design. Different from the traditional andteacher-centered instruction, students in the experimental section took the lead to create theirlearning materials and shared them with their peers. They developed the feelings of belongingand ownership as they created these screencasts. Students were actively involved in thescreencast-making process and motivated to learn. They also received timely feedback fromother students. Students learned from each other and taught each other. In this paper, we discussed the project activities and presented the preliminary results of thefirst

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

Tagged Topics

Diversity

Tagged Divisions

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

Computer-Based Tests, Problems, and Other Instructional Materials

Collection

2015 ASEE Annual Conference & Exposition

Authors

Matthew West, University of Illinois, Urbana-Champaign; Geoffrey L. Herman, University of Illinois, Urbana-Champaign; Craig Zilles, University of Illinois, Urbana-Champaign

Tagged Divisions

Computers in Education

difficulty. The “HW Score” is the score that the student will actually receive for this homework (a constant factor multiplied by the Mastery Score, capped at 100%). The “Do a recommended question” button will take the student to a randomly chosen question with a high recommendation rating, or they can click on a specific question to do it directly.the student has a mastery score that reflects PrairieLearn’s estimate of the student’s ability on thishomework assignment. To increase their mastery score, the student must answer questionscorrectly, in any order they choose. A student can attempt a question as many times as they like(whether answering correctly or incorrectly), but question parameters are randomized on

Conference Session

Simulation

Collection

2015 ASEE Annual Conference & Exposition

Authors

Camilo Vieira, Purdue University; Alejandra J. Magana, Purdue University, West Lafayette; Anindya Roy, Johns Hopkins University; Michael L. Falk, Johns Hopkins University; Michael J. Reese Jr., Johns Hopkins University

Tagged Divisions

Computers in Education

problem solving process.IntroductionComputational Science and Engineering (CSE) has emerged as an important tool to solvecomplex engineering problems1. Engineers need an ability to use computational tools, integratedwith strong problem-solving skills, to tackle complex problems 6, 15, 16. For example, in MaterialsScience and Engineering, a sub discipline called Computational Materials Science3 has beenestablished. This trend is reflected in educational settings too --- there has been a call to integratecomputational tools and methods into different disciplinary engineering curricula sooner andoften2. Aligned with this idea, the department of Materials Science and Engineering at JohnsHopkins University started a novel computational course for its

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

Tagged Topics

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)

Tagged Topics

Diversity

Tagged Divisions

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

Virtual Instruction and Collaboration

Collection

2015 ASEE Annual Conference & Exposition

Authors

Pilar Pazos, Old Dominion University; Nina Magpili

Tagged Divisions

Computers in Education

supporting team processes. The platform is informed by foundational knowledge onteam effectiveness from the industrial and organization psychology field and by social-constructivist learning theory.Theoretical FoundationWorking in teams requires that students learn how to interact with each other, share and processinformation in a collaborative learning environment. There is vast evidence indicating thebenefits of collaborative learning grounded in social-constructivist learning theory10. Socialconstructivist learning theory suggests that learning is largely a social process and that deepunderstanding develops through collaboration and engagement with others11,12. Collaborativework largely reflects the actual environment in engineering-intensive

Conference Session

Innovative Use of Technology I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Rachel Louis Kajfez, Ohio State University; Krista M. Kecskemety, Ohio State University; Max Kross, Engineering Education Innovation Center

Tagged Divisions

Computers in Education

effectiveness of the notebook both in its paper andelectronic form. We recognize that there is the potential for respondents to give only positiveresponses to this type of survey as it may be seen as a reflection of themselves and their work.Specifically, there is the potential for students to report that a tool is useful even when it has Page 26.591.8detrimental effects. We believe the potential for this limitations exists both for the paper andelectronic notebooks reducing its effect in our findings related to comparison; however, it is alimitation that must be considered when examining the results for just the paper or just theelectronic

Conference Session

Course Development / Curriculum Development

Collection

2015 ASEE Annual Conference & Exposition

Authors

Mihaela Vorvoreanu, Purdue University, West Lafayette; Patrick E. Connolly, Purdue University, West Lafayette

Tagged Divisions

Computers in Education

research; evaluation of design solutionslife-long learning project-based research; stretching to new platforms; developing habits for staying abreast of new information (e.g. reading professional blogs)communication skills technical writing; presentation; reports; data presentationcontent mastery and application project based instruction; reflection; design challenges, design critiques Page 26.1656.6technical competencies project based instruction; mentoring; prototyping

Conference Session

Best of Computers in Education

Collection

2015 ASEE Annual Conference & Exposition

Authors

Cameron H. G. Wright P.E., University of Wyoming; Thad B. Welch III P.E., Boise State University; Michael G. Morrow, University of Wisconsin, Madison

Tagged Divisions

Computers in Education

. While the lens system may be able to image certain fine lines and sharp edges in the objectscene, much of this high frequency detail will never be recorded or show up on the monitor screen,due to the worse frequency response of the other MTFs. A realization of such limitations usuallyconstitutes an epiphany for the students.In addition to the Fourier optics and MTF theory approach that takes full advantage of the students’prior knowledge of linear systems theory, the course also includes an algebraic treatment of con-cepts such as aperture, sensor, and pixel size, depth of field, field of view, reflection, refraction, andso forth. Given this, the students obtain a very practical working knowledge of optical engineering(via a single course) that

Conference Session

Data Analysis and Assessment

Collection

2015 ASEE Annual Conference & Exposition

Authors

Cinda Heeren, University of Illinois, Urbana-Champaign; Wade Fagen-Ulmschneider, University of Illinois, Urbana-Champaign

Tagged Divisions

Computers in Education

difficult programming course. The average queue length hovers around 5 Page 26.1296.4students during initial lab hours, but then doubles in each of the last two days of the assignmentFigure 2: Queue usage within a single assignment period.period, to ten and then twenty. The particulars of this example reflect lab availability and acourse policy that awards extra credit for starting early, but the concentrated use of the open labat then end of the window was consistent across assignments, courses, and semesters. In response to this data, one of the courses began to assign more staff to cover the latedate lab hours, but they consequently

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

Tagged Topics

Diversity

Tagged Divisions

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

Virtual Instruction and Collaboration

Collection

2015 ASEE Annual Conference & Exposition

Authors

Thalia Anagnos, San Jose State University; Alicia L. Lyman-Holt, Oregon State University; Sean P. Brophy, Purdue University, West Lafayette

Tagged Divisions

Computers in Education

comparison across the two years.The cohorts for 2013 and 2014 comprised different groups of students and a different set ofresearch sites, with only two students participating in both the 2013 and 2014 REU programs.Results2013 Results – Development and First Use of VPTsThe 2013 data reflect the development of VPTs from a nascent idea to a functional programelement. Thirty of the 36 REU participants completed the online formative assessment survey.The first Likert scale question asked students to identify how effective the VPT activities were inhelping them complete their REU products (Figure 2). The data show the peer reviewinteractions of the VPT were the most effective activity of the VPT teams while regularlyscheduled meetings were somewhat

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

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