Conference Session

Computers in Education Division Technical Session 11

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Milo Koretsky, Oregon State University

Tagged Divisions

Computers in Education

particularly focus on what prevents students from being able to integrate and extend the knowledge developed in specific courses in the core curriculum to the more complex, authentic problems and projects they face as professionals. Dr. Koretsky is one of the founding members of the Center for Lifelong STEM Education Research at OSU. American c Society for Engineering Education, 2020 Work-in-Progress: An Online Journal Tool with Feedback for a Learning Assistant Program in EngineeringOverviewThis work-in-progress paper presents the development and pilot implementation of a computer-based reflection tool used in a Learning Assistant (LA) Program in

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Tamaike Brown, State University of New York at Oswego; Gursimran Singh Walia, Georgia Southern University; Alex David Radermacher, North Dakota State University; Maninder Singh, St. Cloud State University; Mourya Reddy Narasareddygari, Rider University

Tagged Divisions

Computers in Education

systematically check forprogramming errors when reading source code on line-to-line basis.Research methodology: We designed and implemented four different PCR sessions over thecourse of four weeks in one CS2 classroom. During each week, students were given a piece ofcode covering a specific data structure and were asked to review and find errors in the code. Theprovided code pieces were seeded with five categories of errors: initialization/declaration,method call/ definition, array/linkedList/trees/, output and flow of control. We analyzed datagathered from the guided PCR sessions, reflection sessions conducted after each PCR session,work conducted by students (assignments, quizzes, and exams completed as part of the course),and a feedback survey

Conference Session

Computers in Education Division Technical Session 3: Digital Learning Part I

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Zhiyi Li; Stephen H. Edwards, Virginia Tech

Tagged Divisions

Computers in Education

ability and skill can be improved through practice and hardwork 7 . Edwards et al. designed and implemented a suite of fifteen indicators to reflect students’progress and effort based on students’ submissions 8 . These indicators span different aspects ofstudents programming activities and measure positive trends of students’ effort. Another exampleeffort is that Goldman developed daily missions tasks based on these indicators in Web-CAT.Students were provided the opportunities to accomplish daily missions tasks to win rewards suchas extra submission energy 11 .Studies indicate that gamification can motivate and engage students in their learning process 20 16 .Especially Toth et al. integrated Role-Playing Game (RPG) elements into computer

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Joseph A. Lyon, Purdue University, West Lafayette; Aparajita Jaiswal, Purdue University, West Lafayette; Alejandra J. Magana, Purdue University, West Lafayette

Tagged Divisions

Computers in Education

traditional lecturing with assigned homework andquizzes, with the lab section of the course being the time for modeling projects and the seniordesign project.Learning DesignThe final learning design was developed based on modeling-based learning. The development ofa four-phase process from these frameworks has previously been reported on [citation blindedfor peer review]. The four phases of the modeling process that students used during theirmodeling activities were: (1) planning the model, (2) building the model, (3) evaluating themodel, and (4) reflecting on the model. Table 1 below overviews the tasks that students didduring each phase of the modeling process.Table 1. Overview of learning design for the modeling projects during the course. Phase

Conference Session

Computers in Education Division Technical Session 4: Digital Learning Part II

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Kelly S. Steelman, Michigan Technological University; Michelle E. Jarvie-Eggart, Michigan Technological University; Kay L. Tislar, Michigan Technological University; Charles Wallace, Michigan Technological University; Nathan D. Manser, Michigan Technological University; Briana C Bettin, Michigan Technological University; Leo C. Ureel II, Michigan Technological University

Tagged Divisions

Computers in Education

, and software developer drive his research exploring how humans can better understand, build, and use software. His work has been funded by the National Science Foundation, Google, Microsoft Research, and the U.S. Department of Defense. Dr. Wallace’s Agile Communicators project, supported by an NSF IUSE award, seeks to build an en- hanced curriculum for computing programs that emphasizes inquiry, critique and reflection, grounded in authentic software development settings. Tools in this project include process oriented guided inquiry learning, automated feedback to students through an intelligent tutoring system, case studies in software communication, and guided reflective exercises on team communication. As part

Conference Session

Computers in Education Division Technical Session 11

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Shaya Wolf, University of Wyoming; Rafer Cooley, University of Wyoming; Mason Johnson, University of Wyoming; Andrea Carneal Burrows Borowczak, University of Wyoming; Mike Borowczak, University of Wyoming

Tagged Divisions

Computers in Education

coding) and soft skills (such as problemconcept interpretation. solving and teamwork). Lastly, using these results, volunteers can enhance future opportunities. • Students were asked to reflect on their learning individually to provide an Individual indication of their progress interest level, and content knowledge. This was Reflection done through drawings, worksheets, and surveys. Conclusions & Future Work

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Fadi Castronovo, California State University, East Bay; Robert Schaffer, Mission College; Varsha Reddy Kandi

Tagged Divisions

Computers in Education

, the students are grouped in pairs and are challenged to solvepuzzles in VR. However, only one student can wear the headset, while the other has a manualwith the solution to the puzzle. The students need to communicate with each other to solve thepuzzle. At the end of the VR game, the students need to reflect on the challenges that theyencountered and how they can improve their team communication. To support the Project Management lecture topic, the ​Virtual Construction Simulator 4(VCS4) ​game was selected. The game is “​a simulation game that teaches students the dynamicnature of the construction process and frequent changes to construction schedules” [​ 31]​. Thegame was selected because of its extensive supporting instructional

Conference Session

Computers in Education Division Technical Session 2: Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

D. Cenk Erdil, Sacred Heart University; Darcy Ronan, Sacred Heart University

Tagged Divisions

Computers in Education

, each section spends two weeks in a particular laboratory,and moves on to the next one. All sections then have a one-week common group meeting for reflection andgeneral exposure to school-wide programs (advising, major declarations, student programs, etc.). In the secondrotation, each section spends one week in a particular laboratory. The semester ends with another commongroup meeting for overall feedback, and interdisciplinary activity involving all programs.The rotation-based course includes a number of targeted modules in each section to address the above goalscollectively. Each module is described below.Computer Science and Information Technology: Mainly based on Code.org’s Computer Science Principles(CSP), and the background story on

Conference Session

Computers in Education Division Technical Session 2: Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Eddie Davis, SUNY Farmingdale

Tagged Divisions

Computers in Education

Hat)Fig 3: Instructor Encouraged Student Participation (Fall 2018 without Top Hat)One of the primary expectations of this research was that if students participated in classmore, their learning would increase and this would be reflected in their final grades. Ananalysis of the class average grades before and during the Phase I pilot did not reflect anincrease in student’s average grades. (Fig 4)Fig 4: Average Grades (In Percent)7. Summary of Key Findings and Future ResearchSince the deployment, there have not been any significant quantitative impact achievedby using Top Hat. Student participation in the end of semester surveys is not mandatory.Even though students were strongly encouraged to participate. The participation duringthe Phase I

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Caeley Ashtyn Joy Gibbs, Queen's University

Tagged Divisions

Computers in Education

operations in thechemical processing plant. The second design problem will present a plant troubleshootingscenario and examine the students’ ability to develop a solution to solve the problem that iscausing issues in the processing plant. At the end of the course the study participants will begiven an exit survey to evaluate the perception of their design abilities. Six months after thecourse has ended, participants will be asked to complete a longitudinal survey to reflect on howthey believe the course has impacted their chemical engineering process design competency.4.2 Phase TwoIn this phase the course will be executed with a VR component integrated into the coursedeliverables. The research will look at approximately 100 participants that are

Conference Session

Computers in Education Division Technical Session 11

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

James C. Squire P.E., Virginia Military Institute; Gerald Sullivan P.E., Virginia Military Institute; Tom McCormick, Virginia Military Institute

Tagged Divisions

Computers in Education

reach statisticalsignificance, and curiously they show the opposite of what appears to be the objective truth; thecohort that used the continuous applications believed they understood less than the students thatused the discrete applications (Figure 3). This may reflect the Dunner-Kruger paradox thatexplains the cognitive bias which occurs when low-ability people lack the framework to assesstheir abilities accurately, and high-ability people overestimate the abilities of others [12],[13].Figure 3: Comparison of the students’ self-assessment of their subject mastery before theycompleted the objectively-scored portion. It is noticeably below the objective scores, andsurprisingly show a generally opposite trend from their actual understanding in

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

James E. Lewis, University of Louisville; Brian Scott Robinson, University of Louisville; Nicholas Hawkins, University of Louisville

Tagged Divisions

Computers in Education

integration of the fundamentals learned in ENGR 110. Included amongstnumerous skills institutionally-identified as “fundamental” was programming, hence all SSoEengineering students – regardless of discipline – are exposed to edification in the basics ofprogramming.Associated programming curriculum developed for this sequence was heavily influenced by adesire to reflect the varying nature of programming applications throughout industry and theengineering profession. In other words, it is virtually impossible to expose students to all of thepossible programming “styles” and dozens of varying programming languages rampant in themodern work force. Accordingly, pedagogy throughout both ENGR 110 and 111 has beendesigned to expose students to multiple types

Conference Session

Computers in Education Division Technical Session 2: Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

James Christopher Foreman, University of Louisville; Aly Farag, University of Louisville; Asem Ali, University of Louisville; Islam Alkabbany, University of Louisville; Marci S. Decaro, University of Louisville; Thomas Tretter, University of Louisville

Tagged Divisions

Computers in Education

classroom, both the instructor and student can objectivelyobserve this metric. Instructors can use the metric to tailor delivery of the course material,spending more or less time on concepts, and move away from ineffective teaching methodsand towards effective methods. Students, given this knowledge of their own engagement,can reflect on why they may be disengaged, potentially become motivated to improve theirengagement, and communicate effectively with the instructor to seek assistance. Once theproblem of disengagement is identified and associated with specific classroom activities andconcepts, both the student and instructor can work together towards a successful learningoutcome.1.3 How Measuring Engagement Facilitates Better Evaluation of

Conference Session

Computers in Education Division Technical Session 5: Online Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Kenneth Reid, Virginia Tech; Max Mikel-Stites, Virginia Tech

Tagged Divisions

Computers in Education

group given the timing of the assignments. This is reflected primarily in theshared work unique to students, and not Chegg.com-tied submissions. Of the twenty Chegg.com-tiedsubmissions, nine were related to track 2 students and eleven to track 1 students, implying that there wasnot an increased use in Chegg.com throughout the semester, and that the increase in cases was due toother factors. This could also indicate that the known availability of solutions in the students’ peer groupwas the primary factor, and that students who used Chegg.com were already aware of it (and likely usingit) prior to the assignment. The bulk of the cases were pairs of students, with an average incident size of2.38 students. Based on this, while cross-track sharing

Conference Session

Computers in Education Division Technical Session 9: Pedagogical Tools

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Martin Imre, University of Notre Dame; Wenqing Chang, Xi'an Jiaotong University; Shuzhan Wang, Beijing University of Posts and Telecommunications; Christine P. Trinter, University of Notre Dame; Chaoli Wang, University of Notre Dame

Tagged Divisions

Computers in Education

layouts. To further deepen the learning effect, we allowadjusting parameters for a subset of the layouts so that users can gain instantaneous feedback.P4: Comparison. When studying multiple related concepts, it is often helpful to compare their respective strengthsand weaknesses. For graph visualization, the primary choice lies in the selection of a particular layout to draw agiven graph. GraphVisual supports simultaneous visualization of two different graph layouts of the same data set intwo side-by-side display panels, allowing students to make easy comparison through brushing and linking (i.e., theselection made in one view is dynamically reflected in the other view). Furthermore, the two display panels reactsynchronically to interactions such

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

Computers in Education Division Technical Session 3: Digital Learning Part I

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Fitratullah Khan, University of Texas, Rio Grande Valley; Mahmoud K Quweider, University of Texas, Rio Grande Valley; Ala Qubbaj, University of Texas, Rio Grande Valley; Emmett Tomai, University of Texas, Rio Grande Valley; Liyu Zhang, University of Texas, Rio Grande Valley; Hansheng Lei

Tagged Divisions

Computers in Education

example, recently RPi 4 isavailable with 4 GB RAM which has facilitated taking on computationally-intensive machine visionand cybersecurity projects. Table I shows the key concepts targeted in each course. As mentioned earlier CSCI 4390 is anexception where students may choose to do an RPi based project, therefore, there are no establishedkey concepts targeted for CSCI 4390. It should be noted that key concepts shown do not reflect allthe topics covered in the course in which an RPi is used. Once RPi is part of a course, it is used bythe student for most of the projects assigned in the course. Therefore, an RPi is used in a targetedcourse for many more topics than shown in the table. TABLE I Key Concepts in Targeted Courses Course

Conference Session

Computers in Education Division Technical Session 3: Digital Learning Part I

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Byul Hur, Texas A&M University; Ana Elisa P. Goulart, Texas A&M University; Logan Porter, Texas A&M University; Nripendra Sarker, Texas A&M University; Mike Willey, Texas A&M University

Tagged Divisions

Computers in Education

department itself. This growth has been reflected to this graph. To compare the data for thetwo Fall semesters of 2018 and 2019, the numbers of students in Fall 2019 have been almost twotimes bigger than the ones in all three listed courses. Figure 5. Enrolled students who have taken embedded system integration track courses from Fall 2018 to Spring 2020.The total numbers of the listed courses are not small. However, they are divided by the multiplelaboratory sections. In each laboratory section, there are 16 to 20 students or less. The numbersof sections from Fall 2018 to Spring 2020 are shown in Figure 6. As the enrolled students havebeen increased, the numbers of lab sections also have been increased

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 2

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Conrad Tucker, Carnegie Mellon University; Kathy Schmidt Jackson, Pennsylvania State University, University Park; John Jongho Park, Penn State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

made strong statements such as “AI projects human needs or intentthrough computational reduction to serve human needs” and that AI is, “an automated method tospeed and improve decisions and outcomes to advance benefits to society.” These positivestatements were surprising since the second day of the workshop was dedicated to AI ethics,security and privacy. One possible explanation could be the optimism shared by workshopparticipants pertaining to AI and its potential to have positive impact in STEM and society.Participants’ AI definitions did reflect that although they didn’t have a common definition of AI,they recognized the role of computers and machines in expanding human knowledge andcapabilities. None of the participants parsed AI into

Conference Session

Computers in Education Division Technical Session 5: Online Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Maria-Isabel Carnasciali, University of New Haven; Nadiye O. Erdil, University of New Haven; Ronald S. Harichandran, University of New Haven; Jean Nocito-Gobel, University of New Haven; Cheryl Q. Li, University of New Haven

Tagged Divisions

Computers in Education

– Introduces a number of methods that can lead to new business ventures, including recognizing societal trends and market gaps, and discovering different ways to develop solutions to societal needs. 12. Innovating to Solve Problems Under Organizational Constraints – Introduces different types of innovation and problem-solving techniques in order to create a portfolio of practical solutions that reflect organizational boundaries and constraints. 13. Innovative Client-Centered Solutions Through Design Thinking – Describes two human- centered design thinking cycles and teaches how to apply design-thinking skills to a client-centered challenge. 14. Learning from Failure – Describes the difference between

Conference Session

Computers in Education Division Technical Session 5: Online Teaching and Learning

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Alisa Gilmore P.E., University of Nebraska, Lincoln; Tareq Daher, University of Nebraska, Lincoln; Markeya S. Peteranetz, University of Nebraska, Lincoln

Tagged Divisions

Computers in Education

due to using a different browser that did not allow editing of during class compared to earlier semesters. Instead, stepped pdfs but was faster to log in. In part, this was a work-around to through solution steps as the solutions were already sigiificant WiFi connectivity issues that were experienced in the prepared. classrooms this semester. The instructor observed that in 2018, students did not understand the Empasized student reflection on considering the

Conference Session

Computers in Education Division Technical Session 10: STEM Outreach

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Safia Malallah, Kansas State University; Salah Alfailakawi, Kansas State University; Joshua Levi Weese, Kansas State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

plugging the resistors into ablinking LED circuit to determine the relationship between LED brightness and resistorstrength. The weak resistor showed a bright LED, while the strongest resistor displayed nolight. Each lesson in the MMC was designed to highlight the microcontroller's software forspecific CT skills. Students trained to read circuit diagrams by plugging the expected pins onthe Arduino board; most circuit activities in MMC are comprised of LED lights and buttons.Ultrasonic sensors were introduced within the Arduino IDE, and text-based programminglanguage was used to teach students how to reflect the Scratch structure. As a result, studentslearned to correlate how the blocks programming corresponds to real-world coding. On

Conference Session

Computers in Education Division Technical Session 7: Advanced CS courses

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Sabahattin Gokhan Ozden, Penn State Abington; Omar M. Ashour, Penn State Erie, the Behrend College; Ashkan Negahban, Pennsylvania State University, School of Graduate Professional Studies

Tagged Divisions

Computers in Education

concepts for the first time. Therefore, it was necessary to: (a) use a familiar context such as a food stand with which most students have some experience with; and, (b) keep the complexity level of the system relatively low to focus on learning database-related concepts rather than on understanding the underlying dynamics of a com- plex system/simulation. For advanced database courses, it is recommended to use contexts with more complex entities and relations that may not have simple visual representations (e.g., database design for human resource management or medical records). This would further enhance how the I-SBL module reflects a future professional context.This paper presents a first attempt to develop

Conference Session

Computers in Education Division Technical Session 7: Advanced CS courses

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Cynthia C. Fry, Baylor University; Kevin Kulda, Baylor University; Gennie Mansi, Baylor University

Tagged Divisions

Computers in Education

inserted comments in the code aboutnew patterns and functions that they discovered. Upon finding suspect segments of code, stu-dents modified the contents of the executable and observed the effects to see if the problem waseliminated. They reverted back to the previous version of the executable if the modificationshad unexpected or undesired results. Finally, students implemented and tested their additional modifications. In the previousstage, students had been deliberate in taking notes and discussing various features to alter.Therefore, they simply explored the different ideas they liked most. In BinaryNinja, once theexecutable was altered, the graphical view would immediately reflect the result of the alterationon the program’s flow. Students