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

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Computers in Education

Nebraska, Lincoln Tareq Daher earned his Bachelors in Computer Science from Mutah University in Jordan. He pursued a Master’s of Instructional Technology at the University of Nebraska –Lincoln while working as the co- ordinator for the Student Technology Program on the UNL campus. Currently, Dr. Daher works as the director for the Engineering and Computing Education Core (ECEC) at the University of Nebraska – Lincoln. Dr. Daher collaborates with engineering faculty to document and research the integration of in- novative instructional strategies and technologies in their classrooms and designs and delivers professional development programs for faculty in the college.Dr. Markeya S. Peteranetz, University of Nebraska

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

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Computers in Education

Research Scientist with the Computer Vision and Image Processing Laboratory. His research interests include image analysis, machine learning, face recognition, and facial expressions and emotions recognition. He has authored over 40 papers in journals and conferences.Islam Alkabbany, University of LouisvilleDr. Marci S. DeCaro, University of Louisville Marci DeCaro is an Associate Professor in the Department of Psychological and Brain Sciences at the Uni- versity of Louisville. Dr. DeCaro earned a PhD in cognitive science from Miami University in 2009 and a US Department of Education-funded postdoctoral fellowship at Vanderbilt University from 2009-2011. She directs the Learning and Performance Lab at the University of

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

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Computers in Education

Paper ID #29988Work in Progress: Student Perception of Computer Programming WithinEngineering Education: An Investigation of Attitudes, Beliefs, andBehaviorsDr. Kelly S Steelman, Michigan Technological University Dr. Kelly Steelman is an Associate Professor in the Department of Cognitive and Learning Sciences and an Affiliated Associate Professor in the Department of Mechanical Engineering and Engineering Mechanics at Michigan Technological University.Dr. Michelle E Jarvie-Eggart P.E., Michigan Technological University Dr. Jarvie-Eggart is a registered professional engineer with over a decade of experience as an environ

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

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Computers in Education

administrative appointments. She has ex- perience in teaching at the undergraduate and the graduate level. In addition to her academic work, Dr. Erdil worked as an engineer in sheet metal manufacturing and pipe fabrication industry for five years. She holds B.S. in Computer Engineering, M.S. in Industrial Engineering. She received her Ph.D. in Industrial and Systems Engineering from Binghamton University (SUNY). Her background and research interests are in quality and productivity improvement using statistical tools, lean methods and use of information technology in operations management. Her work is primarily in manufacturing and healthcare delivery operations.Dr. Ronald S Harichandran P.E., University of New Haven Ron

Conference Session

Computers in Education Division Technical Session 8: Modulus Topics

Collection

2020 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

digital, weregularly process our signals in their digital or discrete form.Returning our discussion to the derivative operator, a student who has learned thefundamentals of the Laplace transform should recognize the derivative, d/dt as theLaplace independent variable s. In most texts, s= σ + jω , and for a discussion of thefrequency response, setting σ = 0 results in the classic result, s = jω . At this point, aSignals & Systems student should be able to recreate Figure 1. This should be recognizedas the magnitude only display of a Bode plot for the response of an ideal integrator, 1/s,and an ideal differentiator, s.Figure 1. The frequency response (magnitude only) of an ideal integrator, 1/s, and anideal differentiator, s. This is a portion

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Edward E. Anderson, Texas Tech University

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Computers in Education

reviewed. Review of Nodes 3 and 1 is marginal in thesense that a review is determined by the context of the current node and its assessment. Forexample, node 8 is not directly related to node 3, but is indirectly related through node 6 and nodirect review is needed. Node 1, like nodes 5 and 7, is on the edge of this knowledge domainand no assessment can be made beyond this node(s). As additional knowledge domains becomeavailable, they can be interconnected through appropriate links. Figure 5: Typical KnowNet Student Review Scenario (R - Reviewed and N = Not Reviewed)This brute force approach to an intelligence tutor assures that any missing knowledge will becovered through the search. But it is not terribly efficient as demonstrated by the shaded

Conference Session

Computers in Education Division Technical Session 11

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Milo Koretsky, Oregon State University

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Computers in Education

studentsshouldn't be afraid to ask questions. Sometimes, ideas around status, popularity, or competenceprevent students from asking questions. This fear limits the opportunity for students to usestudios as an environment to learn and grow.” We also see general shifts in beliefs, e.g., from amore “transmission-based” conception of learning to a more constructivist view.ReferencesBlosser, P. (2000). How to Ask the Right Questions. National Science Teachers Association.Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational researcher, 18(1), 32-42.Campbell, T., Schwarz, C., & Windschitl, M. (2016). What we call misconceptions may be necessary stepping-stones toward making sense of the world

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Bryan Weber, University of Connecticut

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Computers in Education

and procedures for handling assessments.References [1] ABET | ABET accreditation. [Online]. Available: https://www.abet.org/. [2] Criteria for Accrediting Engineering Programs, 2019 – 2020 | ABET, en-US. [Online]. Available: https://www.abet.org/accreditation/accreditation- criteria/criteria-for-accrediting-engineering-programs-2019-2020/. [3] N. E. Adams, “Bloom’s taxonomy of cognitive learning objectives,” Journal of the Medical Library Association : JMLA, vol. 103, no. 3, pp. 152–153, Jul. 2015, issn: 1536-5050. doi: 10.3163/1536-5050.103.3.010. [4] B. S. Bloom, Taxonomy of Educational Objectives: The Classification of Educational Goals, 1st ed. Longman, 1956. [5] C. C. Bonwell and J. A. Eison, Active

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

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Computers in Education

Game 2. Apply team communication strategies 1. Explain concepts of project scheduling Project Virtual 2. Create project management https://psu.box.com/s/79h0o2y Management Construction Desktop plans osbb25bk1ggzionus9o5mzdgk Lecture Topic Simulator 4 3. Evaluate scheduling choices and factors

Conference Session

Computers in Education Division Technical Session 8: Modulus Topics

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Aneet Dharmavaram Narendranath, Michigan Technological University

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Computers in Education

matrix, K1, possesses all the properties that make it an unconstrainedstructure. Stiffness matrices that are extracted from commercial packages may also be used andthis can be done in the future (please see summary section). The logic to identify these wouldremain the same. At the time of writing of this work-in-progress paper, a fundamental,one-dimensional spring element problem is used to provide a stiffness matrix.nSize =34;K1 = r e p m a t (K, n S i z e ) ;The second matrix (K2) is K1 with it’s non-zero elements replaced by -rand*rand. This is not astiffness matrix as it lacks the property of being symmetric and having non-zero, positive diagonalelements.K2 = K1 ;K2 ( any ( K2 ( : ) ) ) = −r a n d . ∗ r a n d ;The third matrix (K3) is a

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

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Computers in Education

functions) was easier in Coral than it 2.86would have been in C++I think learning Coral first made C++ easier to learn 2.75I think my C++ code is neater/cleaner because I learned Coral first 2.52I struggled with Coral's syntax 1.31I struggled with C++'s syntax 2.41I would have preferred to learn C++ through the whole course, without Coral 1.97I think learning Coral first caused me to struggle more with C++ syntax than I would haveotherwise

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Fadi Castronovo, California State University, East Bay; Jesus Oliver Ph.D., California State University, East Bay; Andrew Stanciulescu, California State University, East Bay

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Computers in Education

, additional experimentalprocedures, such as mixed designs, will be developed to capture and mitigate for any ordereffects.7. Acknowledgements The authors’ work was generously supported by the Association of Public and Land-grantUniversities, the National Science Foundation, and the CSU East Bay College of Science.Bibliography[1] C. C. Bonwell, “Active learning: Creating excitement in the classroom,” George Washington University, Washington D.C., 1, 1991.[2] S. Freeman ​et al.,​ “Active learning increases student performance in science, engineering, and mathematics,” ​Proc. Natl. Acad. Sci.​, vol. 111, no. 23, pp. 8410–8415, 2014.[3] S. D. Johnson and R. M. Fischbach, “Teaching Problem Solving and Technical Mathematics through

Conference Session

Computers in Education Division Technical Session 9: Pedagogical Tools

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Dylan Keifer Finch, Virginia Tech; Stephen H. Edwards, Virginia Tech

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Diversity

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Computers in Education

unique to Duke?," Duke Chronicle, 24 October 2017. [Online]. Available: https://www.dukechronicle.com/article/2017/10/with-large-classes-and-waitlists-compsci- feels-growing-pains-but-are-those-pains-unique-to-duke. [Accessed 1 January 2020].[5] G. V. Glass and M. L. Smith, "Meta-analysis of research on class size and achievement," Educational evaluation and policy analysis, vol. 1, no. 1, pp. 2-16, 1979.[6] L. E. Winslow, "Programming pedagogy - a psychological overview," SIGCSE Bull., p. 17–22, 1996.[7] N. Bosch, S. D’Mello and C. Mills, "What emotions do novices experience during their first computer programming learning session?," in International Conference on Artificial Intelligence in Education, 2013.[8] E. J. Kim and K

Conference Session

Computers in Education Division Technical Session 7: Advanced CS courses

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Zachary Michael Steudel, Baylor University; Cynthia C. Fry, Baylor University

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Computers in Education

[14]. Code-level hardening is also employed tomake it difficult for attackers from easily discovering vulnerabilities in the code, as well as to protectthe program owner’s intellectual property [15].Hardening can also refer to practices that make the original source code of an application moredifficult to understand. This is generally defined as code obfuscation. The practice of codeobfuscation in modern software engineering dates back to the 1980’s, with small competitions heldto transform simple C code into confusing, abstract puzzles difficult for humans to parse andunderstand [16].Since the 1980’s, literature on code-level obfuscation has been consistent but generally sparse. Thisfield of research is relatively small, with no more than

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Luis Felipe Zapata-Rivera, Embry-Riddle Aeronautical University; Maria M. Larrondo-Petrie, Florida Atlantic University; Catalina Aranzazu-Suescun, Latin American & Caribbean Consortium of Engineering Institutions

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Diversity

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Computers in Education

some of thefields defined by LOM (Learning Object Metadata) [8] and add new fields that are specificallyrelated to online laboratories such as: title, type_of_lab a, activity(s), among others. Table 1presents the data that the professor who creates it gives us so the system can classify it in one ofthe galleries. Field Name Field data Description Mandatory / type Optional title String Unique title for the lab Mandatory purpose String Description of the purpose of the lab Optional topic(s) String[] Topics covered 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

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Computers in Education

of 2014, the J. B. Speed School of Engineering (SSoE) at the University of Louisville(UofL) commenced an endeavor to renovate the school’s existing course(s) focused onintroducing first-year students to the profession and fundamentals of engineering, resulting in atwo-course sequence that all first-year SSoE students are required to take. The first component ofthis sequence, Engineering Methods, Tools, & Practice I (ENGR 110), is structurally analogousto the previously existing introductory course and is primarily focused on introduction to andpractice with fundamental engineering skills. The second component, Engineering Methods,Tools, and Practice II (ENGR 111), is a makerspace-based course primarily focused onapplication and

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

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Computers in Education

, and experience with computer simulation and video games in general. The survey was collected before the assignment at the start of the semester. 2. Reduced Instructional Materials Motivation Scale (RIMMS): This instrument is a 12-item questionnaire to assess the level of student motivation. Motivation is measured by four factors: attention (A), relevance (R), confidence (C), and satisfaction (S). Each factor has 3 items in the questionnaire [30]. This questionnaire was collected immediately after finishing Figure 2: A logic of the simulation model of the park with food stand the assignment. The assignment was completed in eleven days. Both groups complete the RIMMS questionnaire. 3. Knowledge test

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

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Computers in Education

, and Kyle Weingartner.References [1] The 2015 Gordon Research Conference on Visualization in Science and Education. https://www.grc.org/ visualization-in-science-and-education-conference/2015/. Accessed: 2019-10-16. [2] J. Barnes and P. Hut. A hierarchical O(n log n) force-calculation algorithm. Nature, 324(6096):446, 1986. [3] M. Bastian, S. Heymann, and M. Jacomy. Gephi: An open source software for exploring and manipulating networks. In Proceedings of International AAAI Conference on Weblogs and Social Media, 2009. [4] F. Beck, M. Burch, S. Diehl, and D. Weiskopf. A taxonomy and survey of dynamic graph visualization. Computer Graphics Forum, 36(1):133–159, 2017. [5] J. Berry. Improving discrete mathematics and algorithms

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

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Computers in Education

Society of Engineering Education (ASEE 2018), 2018. [5] Cynthia Bolt-Lee and Sheila D Foster. Examination retakes in accounting: increasing learning by writing after the exam. Language and Learning Across the Disciplines, 4(2): 40–46, 2000. [6] S. K. Carpenter, N. J. Cepeda, D. Rohrer, S. H. K. Kang, and H. Pashler. Using spacing to enhance diverse forms of learning: Review of recent research and implications for instruction. Educational Psychology Review, 24:369–378, 2012. [7] I. Clark. Formative assessment: Assessment is for self-regulated learning. Educational Psychology Review, 24:205–249, 2012. doi: 10.1007/s10648-011-9191-6. [8] J. C. F. de Winter and D. Dodou. Five-point Likert items: t test versus Mann-Whitney

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

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Diversity

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Computers in Education

can vary by regions because of their proximity togeographic locations close to AI sectors (e.g. Pittsburgh or Silicon Valley) that have a highimpact on the communities/culture. Therefore, there is a necessity to expand this study with alarger population of participants from various ethnic backgrounds, professions and regions.AcknowledgmentThis research is funded by the National Science Foundation NSF DUE #1941782. Any opinions,findings, or conclusions found in this paper are those of the authors and do not necessarily reflectthe views of the sponsor.References(1) Nadelson, L. S.; Seifert, A. L. Integrated STEM Defined: Contexts, Challenges, and the Future; Taylor & Francis, 2017.(2) Boston, M. D.; Smith, M. S. A ‘Task-Centric

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Burford J. Furman, San Jose State University; Salman Ahsan, San Jose State University; Eric Wertz, self/EduShields

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Diversity

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Computers in Education

/262274614_Simply_Python_for_CS0/links/54de78c40cf296663786a2a1/Simply-Python-for-CS0.pdfArora, S. A. S. (2018, September 5). Learn Python: Tutorials for Beginners, Intermediate, andAdvanced Programmers. Retrieved January 11, 2020, from https://stackify.com/learn-python-tutorials/.Ateeq, M., Habib, H., Umer, A., & Rehman, M. (2014). C++ or Python? Which One to Beginwith: A Learner's Perspective. In 2014 International Conference on Teaching and Learning inComputing and Engineering (pp. 64–69). (Available:https://www.researchgate.net/publication/271425337_C_or_Python_Which_One_to_Begin_with_A_Learner's_Perspective)Bell, C. (2017). MicroPython for the Internet of Things: A Beginner’s Guide to Programmingwith Python on Microcontrollers. Apress. https://link.springer.com

Conference Session

Computers in Education Division Technical Session 10: STEM Outreach

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Afrin Naz, West Virginia University Institute of Technology; Mingyu Lu, West Virginia University Institute of Technology; Chase Broyles, West Virginia University Institute of Technology; Isabel Barrio Sanchez, West Virginia University Institute of Technology

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Diversity

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Computers in Education

expecting to graduate in Spring of 2020. He has been working with high school computer science curriculum and is an advocate for Computer Science classes in all West Virginia schools. Recently, he has been working with middle school students in an after-school program focusing on exposure to STEM topics and experiences.Ms. Isabel Barrio Sanchez, West Virginia University Institute of Technology Isabel Barrio S´anchez is a college student at West Virginia University Institute of Technology. She is currently a Junior pursuing a Mathematics major and Computer Science and Economics minors. She has been working as a middle school and high school mentor for three years. Alongside the Computer Science department at WVU Tech and

Conference Session

Computers in Education Division Technical Session 9: Pedagogical Tools

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Thiago Fernandes Leao, Purdue University Northwest; Jiliang Li P.E., Purdue University Northwest; Jinyuan Zhai, Minnesota State University, Mankato

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Computers in Education

, 2004.5. S. R. Davies, “Spreadsheets in structural design”, Longman Publishing Group, 1996.6. E. Zaneldin and S. Ashur, “Using spreadsheets as a tool in teaching construction management concepts and applications”, American Society of Engineering Education (ASEE) Annual Conference, pp. 22-25, 2008.7. E. Zaneldin and B. El-Ariss, “Using spreadsheets and vba for teaching civil engineering concepts," J. Education, Informatics and Cybernetics, vol. 2, no. 1, pp. 28-36, 2011.8. K. W. Wong and J. P. Barford, “Teaching excel vba as a problem-solving tool for chemical engineering core courses", Education for Chemical Engineers, vol. 5, no. 4, pp. e72-e77, 2010.9. T. L. Chambers, “Teaching engineering analysis using vba for excel", in

Conference Session

Computers in Education Division Technical Session 8: Modulus Topics

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

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Computers in Education

curriculum.IntroductionSince 2006 the popularity of computational thinking (CT) - skills for solving problems byadopting the theoretical concepts of computer science - has been increasing substantially,leading to an increase in the amount of research and experiments on the CT method. Yet,there are limited numbers of inquiry investigate approaches to incorporated CT into acurriculum. Betül Czerkawski researched ways to integrate CT across all curriculum, throughsurveying instructional CT designers. She constructed the survey using the ADDIEinstructional design model. One of her findings showed that the Mind Map(s) (MM) strategycan establish a better connection between CT and instructional design [1]; however, verylittle research existed to investigate the correlation

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Robert L. Avanzato, Pennsylvania State University, Abington

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Computers in Education

educators to developadditional resources for MATLAB and ROS programming of low-cost robot manipulators thatare effective in the classroom and laboratory. These results also have significance to theintroduction of modern robotics concepts, including industrial robots and intelligentmanufacturing, into lower division engineering courses, K-12 and STEM activities.7.0 References[1] https://www.ros.org/ [Accessed April 26, 2020][2] S. A. Wilkerson, J. Forsyth, C. Sperbeck, M. Jones, and P. D. Lynn, “A Student Project using RoboticOperating System (ROS) for Undergraduate Research,” 2017 ASEE Annual Conference & Exposition,Columbus, Ohio, June 2017. Available: https://peer.asee.org/27515 [Accessed April 26, 2020][3] A. Yousuf, W. Lehman, M. A. Mustafa

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

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Computers in Education

Paper ID #30621Effectiveness of Using Guided Peer Code Review to Support Learning ofProgramming Concepts in CS2 Course: A Pilot StudyDr. Tamaike Brown, State University of New York at Oswego Assistant Professor of Computer Science, Department of Computer Science, State University of New York at OswegoDr. Gursimran Singh Walia, Georgia Southern University Gursimran S. Walia is Professor of Computer Science at Georgia Southern University. His main research interests include empirical software engineering, software engineering education, human factors in soft- ware engineering, and software quality. He is a member of the IEEE

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

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Diversity

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Computers in Education

/1HYl9xzr43RKMbV-AN76fu6t5utNTnUUl.[4] G. S. o. computing, "hasobkw," [Online]. Available: http://hasobkw.net/pages/degrees.aspx.[5] R. Al-Nakib, "Education and democratic development in Kuwait: Citizens in waiting," in Chatham House Research Paper 7 , 2015.[6] data.worldbank, "data.worldbank," [Online]. Available: https://data.worldbank.org/indicator/SP.POP.0014.MA.IN?end=2018&locations=KW&name_desc=true& start=1960&view=chart.[7] howtostem, "STEM education around the world," [Online]. Available: http://howtostem.co.uk/blog/stem- education-around-world/.[8] F. Russell, J. L. Weese and N. H. Bean, "ncreasing Student Self-Efficacy in Computational Thinking via STEM Outreach Programs," in Proceedings of the

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Dawn McKinney, University of South Alabama; Alex Daniel Edgcomb, Zybooks; Roman Lysecky, University of Arizona; Frank Vahid, University of California, Riverside

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Computers in Education

survey responses, a p-value < 0.005 (= 0.05 / 10 tests)is interpreted as significant.R was used for all analysis [29]. The Internal Review Board approved this study.7. ResultsThe pass rate in Fall 2017 (passive learning textbook) was 78% (57 of 73 students), which wassignificantly lower (p-value = 0.04) than 91% (69 of 76 students) in Fall 2018 (active learningtextbook). Of the students who did not pass, 10 changed majors in Fall 2017, and 2 changedmajors in Fall 2018.Course grades are shown in Table 1. Fall 2018's homework average was 88 out of 100 points,which is interpreted as significantly higher (p-value < 0.001) than Fall 2017's homework averageof 71. Of the grade categories, homework most utilized the textbooks and respective

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

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Computers in Education

years between 2014 - 2016. Section 6 discusses the most recent changes between2017. Section 7 concludes.2. Other styles of online classesThis section briefly details some of the other styles of online classes that are being used. Theintention of this work is not to say that these other online structures are "worse" than what we aredoing at our university, but rather should be used as a point of comparison for the other optionsof teaching an online class.2.1 Massive Online Open Courses (MOOCs)A MOOC is an online course with the option of free and open registration, a publicly sharedcurriculum, and open-ended outcomes [1]. MOOCs have been around since the late 2000's andstill remain popular today. Universities such as Stanford, Harvard, MIT

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

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Computers in Education

., Reeping, D. & Spingola, E.: “A Taxonomy for Introduction to Engineering Courses,” International Journal of Engineering Education, Vol. 35, No. 1, 2018.2. Honor Code Policy and Manual, URL: https://honorsystem.vt.edu/honor_code_policy_test.html, accessed 2/1/20203. A Theory for Detecting Software Similarity, URL: https://theory.stanford.edu/~aiken/moss/, accessed 2/1/2020.4. Roth, N.L. and McCabe, D.L., "Communication Strategies for Addressing Academic Dishonesty," J. College Student Development, vol. 36, n. 6, 1995, pp. 531-541.5. McCabe, D.L. and Makowski, A.L., "Resolving Allegations of Academic Dishonesty," About Campus, March-April, 2001, pp. 17-216. Carpenter, D., Harding, T., Finelli, C., Montgomery, S