Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Anu Aggarwal, University of Illinois Urbana Champaign

Tagged Divisions

Computers in Education

semester. Somestudents also secured A+ grade, as compared to no A+ grades in the previous semester. In thecurrent semester, there were no F or C grades, only 10% secured D grade. In the previoussemester, B grade was the most common, some C, D and F grades were also assigned. Overall,there was better student performance in the semester. Fig. 2 Student grades for the course (ECE425) with and without online delivery.This led to better instructor evaluation as compared to the previous semester.9. Improvements made in future semesters based on lessons learntEven though teaching during Spring 2020 semester was successful as far as better student andinstructor performance was concerned, several different platforms like zoom, course

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sunay Palsole, Texas A&M University; Jeff Chernosky, Texas A&M University; Randy McDonald, Texas A&M University Engineering

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Diversity

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Computers in Education

/08923640701341679[12] J. Lee, “An exploratory study of effective online learning: Assessing satisfaction levels ofgraduate students of mathematics education associated with human and design factors of anonline course,” International Review of Research in Open and Distance Learning, vol. 15, no. 1,pp. 111–132, 2014, doi: 10.19173/irrodl.v15i1.1638[13] L. Chen and D. Ph, “A model for effective online instructional design,” LiteracyInformation and Computer Education Journal, vol. 6, no. 2, pp. 1551–1554, 2015.[14] P. Ralston-Berg, J. Buckenmeyer, C. Barczyk, and E. Hixon, “Students’ perceptions ofonline course quality: How do they measure up to the research?” Internet Learning Journal, vol.4, no. 1, pp. 38–55, 2015.[15] B. Thornton, J. Demps, and A. Jadav

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sunay Palsole, Texas A&M University; Jaskirat Singh Batra, Texas A&M University; Xi Zhao, Texas A&M University

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Computers in Education

. Retrieved 03/05/2021 https://coi.athabascau.ca/coi- model/5. Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243-12896. Shelton, B. E., Hung, J. L., & Lowenthal, P. R. (2017). Predicting student success by modeling student interaction in asynchronous online courses. Distance Education, 38(1), 59-69.7. Picciano, A. G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous learning networks, 6(1), 21-40.8. Sher, A. (2009). Assessing the relationship of student-instructor

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

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

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Computers in Education

Paper ID #33207Lemons into Lemonade!Dr. Thad B. Welch, Boise State University Thad B. Welch, Ph.D., P.E. received the B.E.E., M.S.E.E., E.E., and Ph.D. degrees from the Georgia Institute of Technology, Naval Postgraduate School, Naval Postgraduate School, and the University of Colorado in 1979, 1989, 1989, and 1997, respectively. He was commissioned in the U.S. Navy in 1979 and has been assigned to three submarines and a submarine repair tender. He has deployed in the Atlantic Ocean, Mediterranean Sea, and the Arctic Ocean. From 1994-1997 he was an Instructor and Assistant Professor teaching in the Electrical

Conference Session

Computers in Education 2 - Programming 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Nabeel Alzahrani, University of California, Riverside; Frank Vahid, University of California, Riverside

Tagged Divisions

Computers in Education

design skills in novice programmers using the SOLO taxonomy,” In Proceedings of the 2016 ACM Conference on International Computing Education Research, 251–259.[46] Brian Hanks and Matt Brandt. 2009. “Successful and unsuccessful problem solving approaches of novice programmers,” ACM SIGCSE Bulletin 41, 1 (2009), 24–28.[47] Nelishia Pillay and Vikash R. Jugoo. 2006. “An analysis of the errors made by novice programmers in a first course in procedural programming in Java,” Preface of the Editors 84, (2006).[48] Nancy Cunniff, Robert P. Taylor, and John B. Black. 1986. “Does programming language affect the type of conceptual bugs in beginners’ programs? A comparison of FPL and Pascal,” ACM SIGCHI Bulletin 17, 4.

Conference Session

Computers in Education 9 - Technology 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Efthymia Kazakou, zyBooks, A Wiley Brand; Alex Daniel Edgcomb, zyBooks, A Wiley Brand; Yamuna Rajasekhar, zyBooks, A Wiley Brand; Roman Lysecky, University of Arizona; zyBooks, A Wiley Brand; Frank Vahid, University of California, Riverside

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Computers in Education

). Eachlevel typically builds on earlier levels, so earlier levels must be completed first.As shown in Figure 1, a homework activity contains:(a). A title describing the activity at a high level.(b). An area displaying the questions of the current level and fields for the student to answer.(c). A bar showing each level of the activity. Blue, filled-in levels are the completed levels, andthe grayed out levels are the incomplete levels.(d). A “Check” button validating students' answers when pressed.(e). A “Next" button proceeding to the next higher level once the current level is successfullycompleted. If the answer is incorrect, clicking “Next” provides a new question of similardifficulty for the current level.(f). An explanation for the given answer

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Joseph Maloba Makokha, Stanford University

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Computers in Education

America's AUGMENT D. B. Neill[47] healthcare system - from disease detection to building predictive models for treatment - thereby improving the quality and lowering the cost of patient care. The broad use of machine learning makes it important to understand REPLACE Sharif, M., the extent to which machine-learning algorithms are subject to Bhagavatula, S., attack, particularly when used in applications where physical Bauer, L., & security or safety is at risk. We investigate a novel class of attacks on Reiter, M. K.[48] facial biometric systems: attacks that are physically realizable and inconspicuous, that allow an attacker to evade recognition or

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Larysa Nadolny, Iowa State University of Science and Technology; Md Imtiajul Alam, Iowa State University of Science and Technology; Michael Geoffrey Brown, Iowa State University of Science and Technology; Monica H. Lamm, Iowa State University of Science and Technology

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Computers in Education

areas of study and directions for future research. Thus, the purpose of this contentanalysis is to explore (a) the thematic trends of ASEE gaming conference papers over time and(b) the semantic relationships between concepts.MethodsContent Analysis MethodologyContent analysis is a research procedure for making reproducible and valid interference byanalyzing text or other media 11 . This definition is relatively similar to the description provided byHolsti nearly five decades ago, as ”any technique for making inferences by objectively andsystematically identifying specified characteristics of messages” (p. 14) 12 . Content analysis haspreviously been conducted by time-consuming manual processing, such as hand coding text. Withthe development of

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

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

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Computers in Education

Paper ID #34200Work in Progress: Remote Instruction of Circuitry in a MultidisciplinaryIntroduction to Engineering First-year CourseDr. James E. Lewis, University of Louisville James E. Lewis, Ph.D. is an Assistant Professor in the Department of Engineering Fundamentals in the J. B. Speed School of Engineering at the University of Louisville. His research interests include paral- lel and distributed computer systems, cryptography, engineering education, undergraduate retention and technology (Tablet PCs) used in the classroom.Dr. Nicholas Hawkins, University of Louisville Nicholas Hawkins is an Assistant Professor in the

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Gulustan Dogan, University of North Carolina Wilmington; Yang Song, University of North Carolina Wilmington; Damla Surek, Yildiz Technical University

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Diversity

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Computers in Education

patternrecognition are introduced in Pattern Recognition Module, as seen in Figure 2a. Abstraction is theprocess of filtering out, or ignoring, the characteristics of patterns that are not needed in order toconcentrate on those that are. Abstraction is also introduced as a module, as seen in Figure (a) Introduction page (b) Decomposition page Figure 12b. (a) Pattern Recognition page (b) Abstraction page Figure 2In CT, we refer to a step-by-step set of instructions as algorithms. An algorithm is a step-by-steplist of instructions that, if followed exactly, will solve the problem under

Conference Session

Computers in Education 10 - Technology 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Jeffrey Todd McDonald, University of South Alabama; Dawn McKinney, University of South Alabama; Todd R. Andel, University of South Alabama

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Computers in Education

for this lecture, but with more focus on cybersecurityconcepts and correlation with course activities. The lecture is always done toward the end of thesemester, as students are working on a course project that involves design and implementation ofa 3-bit CPU. Figure 7 shows the desired (end-product) of the course project which could be builtup using constitute components. From semester to semester, the various “functions” andopcodes of the CPU change. Figure 7: Example 3-bit CPU from PETGUI Component and Gate-Level DefinitionThe example in Figure 7 shows that two 3-bit numbers (A,B) are input along with a 2-bit opcode,which chooses 1 of 4 potential functions: NEGATE(A), AND(A,B), COMPARE(A,B), andADD(A,B). The PETGUI guest lecture

Conference Session

Computers in Education 8 - Video Technology

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Dule Shu, Carnegie Mellon University; Christopher Doss, RAND Corporation; Jared Mondschein, RAND Corporation; Denise Kopecky, Challenger Center; Valerie A. Fitton-Kane, Challenger Center; Lance Bush, Challenger Center; Conrad Tucker, Carnegie Mellon University

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Computers in Education

spread,” Technovation, vol. 25, no. 3, pp. 213–222, 2005.[2] O. B. Adedoyin and E. Soykan, “Covid-19 pandemic and online learning: the challenges and opportunities,” Interactive Learning Environments, pp. 1–13, 2020.[3] G. E. Prestera and L. A. Moller, “Facilitating Asynchronous Distance Learning: Exploiting Opportunities for Knowledge Building in Asynchronous Distance Learning Environments.,” 2001.[4] R. Blair and T. M. Serafini, “Integration of education: Using social media networks to engage students,” Systemics. Cybernetics, and Informatics, vol. 6, no. 12, pp. 28–31, 2014.[5] N. Buzzetto-More, “Student attitudes towards the integration of YouTube in online, hybrid, and web-assisted courses: An examination of the impact

Conference Session

Computers in Education 10 - Technology 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Christian E. Lopez, Lafayette College; Omar Ashour, Pennsylvania State University; James Devin Cunningham, Carnegie Mellon University; Conrad Tucker, Carnegie Mellon University

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Computers in Education

. 29, pp. 935–946, 2010.[9] B. N. Geisinger and D. R. Raman, “Why They Leave: Understanding Student Attrition from Engineering Majors,” This Artic. is from Int. J. Eng. Educ., vol. 29, no. 4, pp. 1–12, 2013.[10] C. Lopez, O. Ashour, and C. Tucker, “An introduction to CLICK: Leveraging Virtual Reality to Integrate the Industrial Engineering Curriculum,” ASEE Annu. Conf. Expo., no. June, pp. 1–12, 2019.[11] Z. Merchant, E. T. Goetz, L. Cifuentes, W. Keeney-Kennicutt, and T. J. Davis, “Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis,” Comput. Educ., vol. 70, pp. 29–40, 2014.[12] A. Brown and T. Green, “Virtual Reality: Low-Cost Tools

Conference Session

Computers in Education 9 - Technology 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Chelsea L. Gordon, zyBooks, A Wiley Brand; Roman Lysecky, University of Arizona; zyBooks, A Wiley Brand; Frank Vahid, University of California, Riverside

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Computers in Education

autograding of programming assignments,” in Proceedings of the 49th ACM Technical Symposium on Computer Science Education, SIGCSE, pp. 278-283, Feb 21 2018.[4] H. Keuning, J. Jeuring, and B. Heeren. “Towards a Systematic Review of Automated Feedback Generation for Programming Exercises,” in Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE '16, pp. 41-46, Jul 2016.[5] J. Moghadam, R.R. Choudhury, H. Yin, and A. Fox, “AutoStyle: Toward Coding Style Feedback at Scale,” in Proceedings of the Second (2015) ACM Conference on Learning @ Scale, pp. 261-266, Mar 14, 2015.[6] T. Daradoumis, J.M. Puig, M. Arguedas, and L.C. Liñan, “Analyzing students' perceptions to improve the

Conference Session

Computers in Education 1 - Programming 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Astrid K. Northrup P.E., Northwest College; Raymond Edward Floyd, Northwest College; S. Renee Dechert, Northwest College; Andrea Carneal Burrows Borowczak, University of Wyoming

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Computers in Education

Paper ID #33670Coding is the New Coal: A History of Integrating Computer Science AcrossWyoming’s K-12 CurriculumProf. Astrid K. Northrup P.E., Northwest College Astrid Northrup earned her B.S. degree in petroleum engineering from the Montana College of Mineral Science and Technology (Montana Tech) in 1984 and her M.S degree in petroleum engineering from Mon- tana Tech in 1986. She also earned a Certificate in Land Surveying from the University of Wyoming in 2005. She is a registered Professional Engineer in Colorado and Wyoming. She worked in the petroleum industry as a reservoir engineer and as a private consultant

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Shamsul Arefeen, Texas Tech University; Tim Dallas P.E., Texas Tech University; Heather Greenhalgh-Spencer, Texas Tech University

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Diversity

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Computers in Education

delivers education to resource limitedregions around the world in a cost-effective way. The minimized form-factor, utilizing a pico-projector powered by a foldable solar panel, makes the system deployable to any region. Theeducational content is typically stored on standard micro-SD cards and USB drives. Access to awireless network allows the pico-projector to use online resources. SPDCB is also a stand-alonesolution which can deliver education in remote settings where grid-connected electrical powerand modern classroom facilities are absent. Figure-1 shows the components of the system whichare briefly described below: A. Solar Photovoltaic Panel: This foldable solar panel offers 21 Watts of power to charge the external battery. B

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Arinjoy Basak, Virginia Polytechnic Institute and State University; Todd Patrick Shuba, Virginia Polytechnic Institute and State University; Jianqiang Zhang, Virginia Polytechnic Institute and State University; Sneha Patel Davison, Virginia Polytechnic Institute and State University; David A. Dillard, Virginia Polytechnic Institute and State University; Jacob R. Grohs, Virginia Polytechnic Institute and State University; Nicole P. Pitterson, Virginia Polytechnic Institute and State University; Clifford A. Shaffer, Virginia Polytechnic Institute and State University

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Computers in Education

Study on Faculty Perceptions of Teacher-Student Interaction in Foundational Engineering Courses,” in The 2nd Annual Teaching Large Classes Conference, 2016.[2] K. VanLehn, J. Wetzel, S. Grover, and B. Van De Sande, “Learning how to construct models of dynamic systems: an initial evaluation of the dragoon intelligent tutoring system,” IEEE Trans. Learn. Technol., vol. 10, no. 2, pp. 154–167, 2016.[3] K. VanLehn et al., “The Andes physics tutoring system: Five years of evaluations,” 2005.[4] K. A. Ericsson, R. T. Krampe, and C. Tesch-Römer, “The role of deliberate practice in the acquisition of expert performance.,” Psychol. Rev., vol. 100, no. 3, p. 363, 1993.[5] J. R. Grohs, T. Kinoshita, B. J. Novoselich, and D. B

Conference Session

Computers in Education 10 - Technology 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Tristan M. Ericson, York College of Pennsylvania

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Computers in Education

frequency domain (right).5. Data used to support lessons learnedAll available evidence related to the lessons subsequently presented is provided in theappropriate section. The supporting data includes (a) student response to courseevaluations/surveys conducted by York College of Pennsylvania without professor involvement,(b) student performance on MATLAB/Simulink assignments (grades) compared to other courseevaluation tools (homework and quizzes), (c) student performance (course grades) as Iimplemented changes throughout successive course offerings, and (d) hours invested inMATLAB/Simulink assignment support across five years. No available data was unused; anyevidence pertaining to the lessons is presented. In

Conference Session

Computers in Education 5 - Online and Distributed Learning 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Tiffanie R. Smith, Lincoln University; Susan Ellen Safford, Lincoln University; Chidera Iguwe; Mofoluwasho Akinlade

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Diversity

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Computers in Education

Paper ID #34195Ashmun Express: A Mobile-based Study Application for STEM StudentsDr. Tiffanie R. Smith, Lincoln University Dr. Tiffanie R. Smith is currently an Assistant Professor of Computer Science at Lincoln University of PA. She received her Ph.D. in Human-Centered Computing from the University of Florida in the Department of Computer and Information Sciences and Engineering in 2019 . She received her B.S. in Computer En- gineering from North Carolina A&T State University in 2013. Her research interests include educational technologies, embodied learning, culturally relevant education, and broadening minority

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Rahman Adekunle; John Kofi Eshirow Jr., University of Virginia; Jacob Lam Herring, University of Virginia; Sin Lin, University of Virginia; Rider W. Foley, University of Virginia

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Diversity

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Computers in Education

Paper ID #33704Research-practitioner Partnerships Supported by the Computer Science forAll Program: A Systematic EvaluationRahman AdekunleMr. John Kofi Eshirow Jr., University of Virginia John Eshirow is a first-generation fourth-year student at the University of Virginia majoring in Systems Engineering with a concentration in Economic Systems and a minor in Engineering Business. Originally from the Bronx, he grew to have a passion for understanding and developing the intersection of business, engineering, and technology. In the future, John hopes to be an investor and strategic advisor to companies whose mission is

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

James Kretzschmar, University of Wyoming; Robert F. Kubichek, University of Wyoming; Cameron H. G. Wright P.E., University of Wyoming; Steven F. Barrett, University of Wyoming; Jeffrey R. Anderson, University of Wyoming

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Computers in Education

Paper ID #33080Implementation of Hands-on, Home-based Laboratory for Two ElectricalEngineering Courses (A Pilot Study)Dr. James Kretzschmar, University of Wyoming Colonel, USAF (ret) Amateur Radio (FCC license: AE7AX) Member: IEEE, ASEE, ARRLDr. Robert F. Kubichek, University of Wyoming Robert Kubichek received his Ph.D. from the University of Wyoming in 1985. He has held positions at Boeing, the BDM Corporation, and the Institute for Telecommunication Sciences (NTIA). He taught at the University of Wyoming for 29 years and retired in 2020. His research and teaching focus has been communications and digital signal

Conference Session

Computers in Education 2 - Programming 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Petra Bonfert-Taylor, Dartmouth College; Simon Ethan Oster, Dartmouth College

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Diversity

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Computers in Education

Paper ID #32496Work in Progress: A Seamless, Customizable e-Book for IntroductoryProgramming CoursesProf. Petra Bonfert-Taylor, Dartmouth College Petra Bonfert-Taylor is the Associate Dean for Diversity and Inclusion and a Professor and Instructional Designer at the Thayer School of Engineering at Dartmouth College. She received her Ph.D. in Mathe- matics from Technical University of Berlin (Germany) in 1996 and subsequently spent three years as a postdoctoral fellow at the University of Michigan before accepting a tenure-track position in the Mathe- matics Department at Wesleyan University. She left Wesleyan as a tenured

Conference Session

Computers in Education 9 - Technology 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Mahgol Nowparvar, Pennsylvania State University ; Xing Chen, Pennsylvania State University ; Omar Ashour, Pennsylvania State University ; Sabahattin Gokhan Ozden, Pennsylvania State University Abington; Ashkan Negahban, Pennsylvania State University

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Computers in Education

reality (VR), augmented reality (AR), and mixedreality (MR), use computerized environments and objects to simulate a “real” user experience[2]. There is a wide range of research on the effectiveness of immersive technologies ineducation. For example, several papers suggest immersive technologies to enhance specificlearning outcomes in engineering by enabling remote/online teaching and providing a flexibleand safe virtual environment [3]. Furthermore, immersive technologies can facilitate teachingand learning of design concepts (e.g., 3-dimensional design for a new product) while enhancingstudents’ interactions, creativity, and spatial skills [3].(a) Discipline breakdown for PBL. (b) Discipline breakdown for VR

Conference Session

Computers in Education 6: Best of CoED

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Luwen Huang, Massachusetts Institute of Technology; Kayla M. Bicol; Karen E. Willcox, University of Texas at Austin

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Computers in Education

can be represented by vectors. A.3 Find the components of a vector by subtracting the coordinates of an initial point from the coordinates of a terminal point. Cluster: Perform operations on vectors. B.4.A Add vectors end-to-end, component-wise, and by the parallelogram rule. Un- derstand that the magnitude of a sum of two vectors is typically not the sum of the magnitudes B.4.A Given two vectors in magnitude and direction form, determine the magnitude and direction of their sum .. .The next step in creating the network model is to draw prerequisite relationships betweenMicro-Standards. Focusing on one grade band at a time, we review the Micro-Standards withinthe given grade band. We determine whether a given Micro-Standard is a

Conference Session

Computers in Education 6: Best of CoED

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sherif Abdelhamid, Virginia Military Institute; Yousef Jalali, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

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Computers in Education

to single-author papers during the last 14years, as shown in figure 3.a. Additionally, the analysis revealed an overall increase inmulti-institution publications. Figure 2: Annual number of publications in ASEE conference proceedings 1996 - 2020. (a) (b) Figure 3: Proportion of (a) multi-author and (b) multi-institution publications compared to total publications in the ASEE conference proceedings from 2006 to 2020.A mapping of the ASEE publications to geographic locations was carried out. The schoolinformation was extracted from the author’s affiliation. A geocoding process was conducted totransform the text-based description or the name of the

Conference Session

Computers in Education 8 - Video Technology

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Markus Iseli, University of California, Los Angeles; Tianying Feng, University of California, Los Angeles; Gregory Chung, University of California, Los Angeles; Ziyue Ruan; Joe Shochet, codeSpark; Amy Strachman, codeSpark

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Diversity

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Computers in Education

for PathDist happens either when PathDist does not reduce(character got stuck on its path to the goal) or when PathDist drops steeply (character took ashortcut and misses some gems).The observable behavior of abstraction is defined as adding a command and changingparameters at once, or as neglecting distractors or details (see Table 2 below). Examining thevisualizations, we originally expected that (a) some students would add all commands and thenchange their parameters at once and that (b) other students would change the parameter aftereach added command. However, it could be seen that the second behavior (b) was prevalent, andthat the first behavior (a) would only occur if there was a misconception present. Figure 4 showsan example of the

Conference Session

Computers in Education 1 - Programming 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Pat Ko, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University; Jonathan G. Harris, Northern Gulf Institute; Jamie Lee Dyer, Mississippi State University; Yan Sun, Mississippi State University

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Computers in Education

model; we present the same information to all teachers, and rely on each teacher tocreate lessons and adapt the material to be appropriate for their students. The primary content themes and subthemes for the summer program are: 1. Energy and Mass a. Temperature b. Convection and Vertical Motion 2. Water in the Atmosphere a. Atmospheric Moisture b. Clouds and Precipitation 3. Distribution and Movement of Air a. Pressure and Wind b. Global Circulation Patterns 4. Atmospheric Disturbances a. Mid-Latitude Cyclones and Fronts b. Tropical Cyclones Every subtopic is split into a series of short lectures

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Julian Ly Davis, University of Southern Indiana; Thomas McDonald, University of Southern Indiana; Bradley Lane Kicklighter, University of Southern Indiana

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Computers in Education

of testingin an LMS that could be done much better to suit our individual needs. In this paper, we discusssome of the types of questions that we use in Blackboard Exams and some of the computer toolsthat we use to create them. We discuss some of the successes as well as some tricks of the tradethat we use to address our objectives. Finally, we discuss some additional tools that we use tomitigate cheating. This paper covers subjects such as: 1) Different types of Blackboard questions a. Calculated Formula b. Multiple Choice c. Fill in the Blank d. Fill in Multiple Blanks 2) Software tools to help write questions (e.g.) a. Mathematica b. Excel c. Visio 3

Conference Session

Computers in Education 4 - Online and Distributed Learning 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Sherif Abdelhamid, Virginia Military Institute; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education

) (b) (c) (d) Figure 5: Linguistic features variability in the instructional videos across different computer science topics based on (a) lexical diversity, (b) transcripts readability, (c) count of difficult words, and (d) normalized count of similes.Finally, we realized that instructors who used more similes and metaphors in their videos had ahigher tendency to use more words that express cognitive processes (e.g., cause, know, think);see figure 6. Several studies have identified the underlying cognitive processes involved in usingfigurative language [41, 42, 43]. (a

Conference Session

Computers in Education 7 - Modulus 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Ahmed Ashraf Butt, Purdue University at West Lafayette; Saira Anwar, University of Florida; Muhsin Menekse, Purdue University at West Lafayette

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Diversity

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Computers in Education

asked to reflect on their experiences using the followingquestion:How often have you been in courses where some educational technology tools, especiallymobile applications, have been used? Tell us something about your experience. a. Please state the name of the application(s) or other technology tools (e.g., Clicker, CATME, Socrative, Any quiz software, etc.). b. What you liked about that application(s) and why? c. What you didn’t like and why? d. Were those applications academically relevant? If yes, why, if no, why not?Data AnalysisThe study focuses on exploring the students’ perceptions of using educational technology toolsin postsecondary STEM classrooms. To inform our study, we employed