Conference Session

COED: Autograding and Autoadvising

Collection

2018 ASEE Annual Conference & Exposition

Authors

Mike Thomas Pitcher, University of Texas, El Paso; Peter Golding, University of Texas, El Paso; Pedro Arturo Espinoza, University of Texas, El Paso; Crystal Fernandez-Pena, University of Texas, El Paso; Celena Arreola, The University of Texas, El Paso; Hugo Gomez, University of Texas, El Paso; Hector Erick Lugo Nevarez, University of Texas, El Paso; Randy Hazael Anaya, University of Texas, El Paso; Diane Elisa Golding, University of Texas, El Paso; Kelsi Marie Oyler, Engineering Leadership; America Fernandez, University of Texas, El Paso; Helen Elizabeth Geller, University of Texas, El Paso; Luis Carlos Jimenez, University of Texas, El Paso; Jennifer Arreola, University of Texas, El Paso; Andrea Annette Duenez; Karla Alejandra Ayala

Tagged Divisions

Computers in Education

providing reflection, mentoring, and professional growth. 2) The timing of the process was geared towards the class registration process and its deadlines and not the student’s calendar of professional development. The current process takes place near the end of each semester when students are most focused on final exams, projects, and finishing up course work in general rather than their future development and growth. 3) Within the Engineering Leadership department, the department has grown and gained students and faculty with diverse interests and backgrounds. This has created an advising process that requires modifications to maintain the individualized feel that originally existed but was lost as the

Conference Session

COED: Gamification and Introducing Students to Programming

Collection

2018 ASEE Annual Conference & Exposition

Authors

Mourya Reddy Narasareddy Gari, North Dakota State University; Gursimran Singh Walia, North Dakota State University; Alex Radermacher, North Dakota State University

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Diversity

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Computers in Education

how the SEP-CyLE cyber-learning environmentwould impact the performance of students when team formation is based around groups that areassigned to work on projects outside of SEP-CyLE. Also, we are working with courseinstructors to develop a larger set of LOs that would help overcome some of the knowledgedeficiencies of students and would enable increased usage of SEP-CyLE in introductoryprogramming courses.10. Acknowledgements:This work is supported in part by the National Science Foundation under grants DUE-1225742and DUE-1525112. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.11. References:[1] R. Alex

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

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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

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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

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Diversity

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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

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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

Computed Simulation and Animation

Collection

2007 Annual Conference & Exposition

Authors

Bill Genereux, Kansas State University, Salina

Tagged Divisions

Computers in Education

ofthought ignores the realities and interconnectedness of the world. Some writers such as PeterBlewett have expressed dissatisfaction with “professional programs that treated humanities andsocial sciences as an after-thought at best and an onerous irrelevancy at worst.” 2 Others call foreach discipline to recognize and appreciate the value of disparate fields of thought. “Scientistswould doubtless be better people if they were culturally literate, and ditto for humanists if theywere scientifically informed.” 3The importance of a broad based education is reflected in current ABET curriculum Page 12.959.2requirements for engineering and engineering

Conference Session

Programming for Engineering Students

Collection

2007 Annual Conference & Exposition

Authors

Tammy VanDeGrift, University of Portland

Tagged Divisions

Computers in Education

opportunity to make several decisions and takeownership of their learning path while constructing solutions to the programming assignments.This relates to problem-based learning5, where students are given problems to solve and theyseek the necessary material, digest it, and apply it to solve the problem. A third learning theorythat informed the creation of the programming assignments is that of metacognition1,2. Learnersmust be aware of their own cognitive system and monitor their own learning process and style.The assignments were devised to have a tandem written summary, where students have anopportunity to reflect upon the learning process while (hopefully) providing a hook formetacognitive activity.2.2 Programming AssignmentsNine programming

Conference Session

Robots and K-12 Computer Applications

Collection

2013 ASEE Annual Conference & Exposition

Authors

Cheryl D. Seals, Auburn University; Earl B. Smith, Georgia Southern University

Tagged Divisions

Computers in Education

the influx and progression of K-12students through graduate school in programs that lead to computing careers. This material isbased in part upon work supported by the National Science Foundation under Grant NumberCNS-0540492. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.Bibliography1. Fiegerman, S. (2010). The Dumbest States in America. Jan 21, 2010. Retrieved from http://www.mainstreet.com/slideshow/lifestyle/smartest-dumbest-states.2. Shahami, M. (2008). Overview of the New Undergraduate Computer Science Curriculum. Stanford Research Institute, http://www.stanford.edu/class/cs298

Conference Session

Computers and Learning

Collection

2013 ASEE Annual Conference & Exposition

Authors

Khalid W Khawaja, American University in Dubai

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Computers in Education

Colleges ,Volume 22 Issue 4, April 2007, p 252-259.3. Marilee J. Bresciani, Megan Moore Gardner, and Jessica Hickmott. DemonstratingStudent Success : A Practical Guide to Outcomes-Based Assessment of Learning andDevelopment in Student Affairs. s.l. : Stylus Publishing, 2010. 9781579225155.4. Sarah Earl, Fred Carden and Terry Smutylo. Outcome Mapping : Building Learningand Reflection into Development Programs. Ottawa, ON, CAN : IDRC Books, 2001.5. Closing the Training Loop with Enterprise Technologies and Solutions. Khawaja, KhalidW. Bonn, Germany : IBIMA, Managing Information in the Digital Economy: Issues andSolutions, 2006, pp. 716-719.6. A Task-Centered Instructional Strategy. Merrill, M. David. 1, 33-50, s.l. : Journal ofResearch on Technology

Conference Session

Online Learning

Collection

2013 ASEE Annual Conference & Exposition

Authors

Petronella A James-Okeke, Morgan State University; Craig J. Scott, Morgan State University; Yacob Astatke, Morgan State University; Jumoke Oluwakemi Ladeji-Osias, Morgan State University; LaDawn E. Partlow M. Eng., Morgan State University; Kofi Nyarko, Morgan State University

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Computers in Education

assessment report (FCAR). Faculty Course Assessment Report (FCAR)The faculty course assessment report (FCAR) is utilized by Faculty to summarize course levelobservations and actions. The FCAR (Figure 6) can be automatically generated for any courseand serves as a record for all qualitative and quantitative information for the course and related Page 23.88.11outcomes that are assessed. This report contains a breakdown of how well the course satisfied itsassigned outcomes, as well as information on the modifications made to the course, the studentfeedback, reflections, proposed actions, and grade distribution. Changes to any course can betracked

Conference Session

Topics in Computer Science and Programming

Collection

2012 ASEE Annual Conference & Exposition

Authors

Rajeev K. Agrawal, North Carolina A&T State University; Zachary Kurmas, Grand Valley State University; Venkat N. Gudivada, Marshall University; Naser El-Bathy P.E., North Carolina A&T State University; Cameron Seay, North Carolina A&T State University

Tagged Divisions

Computers in Education

conclusions. Page 25.950.22. Sorting AlgorithmsSorting algorithms can be classified by the following features:  Computational Complexity of Comparisons  Computational Complexity of Swaps  Memory Usage  Recursion  Stability  General Method Used (e.g. Merging)The sorting algorithms used in game development should reflect the best combination of all thesefeatures. A game may use several different sorting algorithms depending on the amount and typeof data, and the degree to which that data is partially sorted.2.1 Heap Sort: “The Heap Sort is well known as the hacked sort because heaps were nevermeant to

Conference Session

Computers in Education Poster Session

Collection

2010 Annual Conference & Exposition

Authors

J. Wey Chen, Southern Taiwan University

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Computers in Education

instructional steps will be integrated into the Bayesian model toserve as a guiding framework to develop a rich and flexible web-based environment for Teachingand Learning Computer Programming languages.The Cognitive TheoryIt is widely known that programming, even at a simple level, is a difficult activity to learn. Why isthis so? Are novice difficulties really inherent in programming or are they related to the nature ofthe programming tools currently given to novices? Bonar and Soloway14 presented evidence thatcurrent programming languages do not accurately reflect the cognitive strategies used by noviceprogrammers. Instead, Bonar and Soloway14 have found that novice programmers possessknowledge and experience with step-by-step specifications in

Conference Session

Laboratory Applications of Computers

Collection

2014 ASEE Annual Conference & Exposition

Authors

Abul K. M. Azad, Northern Illinois University; Pramod P. Kaushik, Northern Illinois University

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Computers in Education

(Transforming Undergraduate Education in Science,Technology, Engineering, and Mathematics) project, award number DUE-1140502. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation.References[1] Pretz, Kathy, A new IEEE group is taking on the quest to connect everything, IEEE The Institute, October, 2013. (http://theinstitute.ieee.org/technology-focus/technology-topic/exploring-the-impact-of-the-internet- of-things)[2] Gunkel, David, Communication and Artificial Intelligence: Opportunities and Challenges for the 21st Century, Communication +1, 1(1), 2012.[3] Lowe, D., Murray, S., Lindsay, E., and

Conference Session

Simulation

Collection

2011 ASEE Annual Conference & Exposition

Authors

Seung Youn Chyung, Boise State University; Joe Guarino, Boise State University; Marion Scheepers, Boise State University, Department of Mathematics; Rey DeLeon, Boise State University, Mechanical & Biomedical Engineering Department; Charles Adams, Boise State University; Paul Williams, Boise State University

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Computers in Education

” grant and the “CloudComputing Services in Education” grant from Hewlett Packard. Any opinions, findings, andconclusions expressed in this material are those of the authors and do not necessarily reflect theviews of Hewlett Packard.Bibliography1 MathWorks, Inc. (1994-2010). MATLAB. http://www.mathworks.com/products/matlab/2 Prabhu, G. S., & Shankar, P. M. (2002). Simulation of flat fading using MATLAB for classroom instruction. IEEE Transactions on Education, Vol. 45, No. 1, 19-25.3 Shiakolas, P. S., Chandra, V., Kebrle, J. , & Wilhite, D. (2002). Engineering design, analysis, and simulation for education using MATLAB via the World Wide Web. II. Representative examples - System simulation and planar mechanism

Conference Session

Computers in Education Poster Session

Collection

2011 ASEE Annual Conference & Exposition

Authors

Chris Smaill, University of Auckland; Colin Coghill, University of Auckland

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Computers in Education

teachers: students of senior physics are by no means guaranteed a teacher whomajored in physics. Such students are most likely disadvantaged in terms of both subjectskills and inclination to further study. The American Society for Engineering Education,reflecting the nation‟s anxiety over the situation in the U.S., in 2003 established a K-12 &Pre-College Engineering Division (website available at http://k12division.asee.org/).Many universities are now funding outreach programs to increase the number of engineeringundergraduates 4-15. Ideally, such outreach programs should have two positive outcomes:participating students should be both better prepared for and better informed aboutengineering careers. The University of Auckland‟s (UoA‟s

Conference Session

Hardware Applications

Collection

2011 ASEE Annual Conference & Exposition

Authors

Gary Spivey, George Fox University

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Computers in Education

http://engr.georgefox.edu/Chirps.Acknowledgements This material is based upon work supported by the National Science Foundation under GrantNo. 0720526. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation. Page 22.1432.12References1 G. Spivey, B. Harder, , “Starting a Multidisciplinary Senior Capstone Design Course”, 2007 Capstone Design Conference, June 2007, Boulder, CO.2 D. Heer , R. Traylor, T. Thompson., and T. Fiez,, “Enhancing the Freshman and Sophomore ECE Student Experience using a

Conference Session

Computers in Education General Technical Session I

Collection

2011 ASEE Annual Conference & Exposition

Authors

Robert P. Taylor, University of Alabama; Keith A. Woodbury, The University of Alabama

Tagged Divisions

Computers in Education

-ins, and other assistance is gratefully acknowledged.DisclaimerAll opinions, findings, and conclusions or recommendations expressed herein are those of theauthors and do not necessarily reflect the views of the National Science Foundation.Bibliography 1. Dent, T., Woodbury, K.A., and Taylor, R., 2008, “Microsoft Excel Heat Transfer Add-in for Engineering Courses,” AC 2008-933, 2008 ASEE Annual Conference and Exposition, June 22-25, Pittsburgh PA. 2. Chappell, J., Taylor, R., and Woodbury, K.A., 2008, “Introducing Excel Based Steam Table Calculations into Thermodynamics Curriculum,” AC 2008-1398, 2008 ASEE Annual Conference and Exposition, June

Conference Session

Computers in Education General Technical Session II

Collection

2011 ASEE Annual Conference & Exposition

Authors

Deborah Walter, Rose-Hulman Institute of Technology

Tagged Divisions

Computers in Education

to the first-time or non-experience student. A list of the most used “How-To” videos, their length, and a description of the information conveyed is described in Table 1.The number of hits is the number of times (since fall 2010) that the videos have been accessed;this reflects the relative popularity of the topic.Basic “How-To”Tutorials Video Description Number Length of hits (m:ss)How_to_Breadboard 1:45 Explains the connections in a standard breadboad 65How_to_measure_R_with_DMM 1:00 A digital multimeter is used to

Conference Session

Programming for Engineering Students

Collection

2010 Annual Conference & Exposition

Authors

John Baker, University of Kentucky; Vincent Capece, University of Kentucky; Keith Rouch, University of Kentucky

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Computers in Education

concatenated into a single video recording using theediting features available in Camtasia Studio.Two of the examples recorded were classical problems found in most textbooks. One was thedevelopment of the Rayleigh pitot-tube relation and its use to determine the test section velocityin a supersonic wind tunnel. The second was the regular reflection of an oblique shock wavefrom a wall.The other two problems supplemented the examples found in the textbook used for this course.The solution for one dimensional flow with friction and a normal shock wave was presented forone of the problems. This illustrated the solution of a problem with multiple compressible flowfeatures. The other example problem considered was the solution of a normal shock wave for

Conference Session

Signal Processing Education

Collection

2010 Annual Conference & Exposition

Authors

Robert Santucci, Arizona State University; Tushar Gupta, Arizona State University; Mohit Shah, Arizona State University; Andreas Spanias, Arizona State University

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Computers in Education

estimate the acoustic impulse response h(n) from theloudspeaker to the microphone including the reflection paths. A digital replica of the echo signaly(n) is estimated by filtering the received far end signal with estimated AIR w(n) which is thensubtracted from the observed microphone signal. The AEC is usually realized on a digital signalprocessor (DSP) which implies digital-to-analog conversion of the received far-end signal andanalog-to-digital conversion of the microphone signal. Since the echo path is unknown and,moreover, can change during the operation time, the linear filter has to be realized adaptively. Estimated room impulse response 0.7

Conference Session

Best of Computers in Education Division

Collection

2012 ASEE Annual Conference & Exposition

Authors

Barry E. Mullins P.E., Air Force Institute of Technology

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Computers in Education

professionals six to eight years after their initial cyberspace training. Cyber 300 isdesigned to provide a broad background at the strategic level in “cyber concepts, includingcapabilities, limitations and vulnerabilities and their associated application and employment injoint military operations”19.6. AcknowledgementsThe author acknowledges the funding and support of the Center for Cyberspace Research. Theviews expressed in this article are those of the author and do not reflect the official policy orposition of the United States Air Force, Department of Defense, or the U.S. Government.7. References1. D. Drummond, A new approach to China, http://googleblog.blogspot.com/2010/01/new-approach-to- china.html, last accessed 6 January 2011.2

Conference Session

CoED General Technical Session II

Collection

2012 ASEE Annual Conference & Exposition

Authors

Robert P. Brazile, University of North Texas; Kathleen Swigger, University of North Texas; Matt Ray Hoyt, University of North Texas; Brian Lee, University of North Texas; Brandon Nelson, University of North Texas

Tagged Divisions

Computers in Education

, it should bepossible to study the patterns among the participating instructors and identify the compatiblecourses. To address this issue, we need to obtain instructor data over several semesters tounderstand which courses and projects were successfully executed.6. AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant No.0705638. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation. We also wish to thank the students who participated in the study, and the manycolleagues (in all four countries who helped make this research possible.7. References[1] P

Conference Session

Topics in Computer Science and Programming

Collection

2012 ASEE Annual Conference & Exposition

Authors

James Dean Palmer, Northern Arizona University; Eck Doerry, Northern Arizona University

Tagged Divisions

Computers in Education

program, creating formative andmutually-supportive friendships that create a support structure that helps students succeed in ourprogram. Page 25.1291.2In this paper we will describe the funding, design, and evolution of the Digital Carnival concept,and reflect on the surveys and participation data collected over the five years since launching theDigital Carnival initiative. The results show that gaming represents a unique crosscut of thestudent population and that these students are not well served by other extracurricular activities.This suggests that gaming can be an important part of student socialization, which can be

Conference Session

Computers in Education Division Poster Session

Collection

2012 ASEE Annual Conference & Exposition

Authors

Katherine G. Nelson, Arizona State University; Jenefer Husman, Arizona State University; Refika Koseler; Stuart Graham Bowden, Arizona State University

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Computers in Education

author(s) and do not necessarily reflect thoseof the National Science Foundation or Department of Energy. Page 25.1495.11

Conference Session

Computer Hardware

Collection

2014 ASEE Annual Conference & Exposition

Authors

Johné M. Parker, University of Kentucky; Stephen L. Canfield, Tennessee Technological University; Sheikh Khaled Ghafoor

Tagged Divisions

Computers in Education

authors and do notnecessarily reflect the views of the National Science Foundation.  Bibliography[1] Canfield, S. L, and Abdelrahman, M. A., 2009, “Enhancing the Programming Experience for Engineering Students through Hands-on Integrated Computer Experiences” Proceedings of the 2009 ASEE Southeastern Section Annual Conference, Marietta, GA, April.[2] National Academy of Sciences. “Undergraduate science and engineering teaching needs improvement.” ScienceDaily, 21 May 2012. Web. 29 May 2012[3] Bransford, J. D., Brown, A., & Cocking, R., 2000, How People Learn: Mind, Brain, Experience and School, Expanded Edition, Washington, DC: National Academy Press.[4] Committee on How People Learn, A Targeted Report for Teachers, How

Conference Session

Computers and Learning

Collection

2013 ASEE Annual Conference & Exposition

Authors

Pramod Rajan, Laboratory for Innovative Technology & Engineering Education (LITEE); P.K. Raju, Auburn University; Chetan S Sankar, Auburn University College of Engineering

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Computers in Education

thoseof the authors and do not necessarily reflect the views of the National Science Foundation. .References1. Games for Scientific and Engineering Education ( 2007). Communications of the ACM, 50(7)2. Dabbagh, N., & Menasce, D.A. (2006). Student perceptions of engineering entrepreneurship: An explanatorystudy. Journal of Engineering Education.3. Raytheon Company. Retrieved from http://investor.raytheon.com/phoenix.zhtml?c=84193&p=irol-newsArticle&ID=1631503&highlight=4. Connolly, T. M., Boyle, E. A., MacArthur, E., Hainey, T., Boyle, J. M. (2012). A systematic literature review ofempirical evidence on computer games and serious games. Computers & Education, 59(2),661-6865. Dym, C., Agogino, A., Eris, O., Frey, D., &

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

Tagged Divisions

Computers in Education

.NBT.1 Recognize that in a multi-digit whole num- 4 ber, a digit in one place represents ten times what it represents in the place to its right. Highest out-degree 1.0A.6 Add and subtract within 20; 2.0A.2 Fluently 1; 2; 3; 3; add and subtract within 20; 3.OA.7 Fluently multi- High School ply & divide within 100; 3.OA.9 Identify arithmetic patterns; G-CO.4 Develop definitions of rotations, reflections, and translations Highest incoming rank 9 (17 vertices) Highest outgoing rank 9 (6 vertices)nine; Figure 4 visualizes this path. Note that in our visualization, arrows point

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

concepts in an incremental manner to helpstudents progress, while still enabling a less-prepared student many opportunities to practice. Anexplanation provides the student feedback, guides the student through the level, and adapts to thegiven question and answer provided.As more classes become virtual and instructors need to cope with larger groups of learners moreefficiently, auto-grading and self-assessment as a result, have become very important.Self-assessment promotes students’ skills of reflective practice and self-monitoring, andincreases students’ motivation and confidence. This homework activity style encouragesself-assessment especially with the use of activities where students receive immediate feedbackon each question. Even when a

Conference Session

Computers in Education 3 - Modulus I

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Roxanne Moore, Georgia Institute of Technology; Sunni Haag Newton, Georgia Institute of Technology; Meltem Alemdar, Georgia Institute of Technology; Sabrina Grossman, Georgia Institute of Technology; Jason Freeman, Georgia Institute of Technology; Jason Brent Smith, Georgia Institute of Technology; Tom Berry, Amazon Future Engineer

Tagged Topics

Diversity

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Computers in Education

worked on the project only at home.Less than 1/3 of students had made music using a computer prior to the competition, and fewer(16.4%) had used the EarSketch platform prior to the competition. In terms of their coursework,nearly all students (94.5%) reported being currently enrolled in a computer science or technologyrelated course, and a large portion of students (89.0%) reported that they had previously taken acomputer science or technology related course.Students’ Feedback on the Competition: Students were asked to reflect on various aspects of thecompetition. On eight of these ten items, average student responses fell between the “Agree” and“Strongly Agree” scale points, indicating generally positive feedback about most aspects of