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

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

wasa feeling of being overwhelmed with “no chance of getting a good grade.” On the positive side,these students remarked about an improved way to learn and the utilization of many outsideresources as necessities in this modality. Online Course (OLC): The comments replicated most often reflected a feeling ofdetachment and isolation, as well as a feeling of being on their own and learning by themselves.Similar to responses in the face-to face modality, these learners also provided a majority ofnegative comments stating that the courses were more rigorous and required additional time forstudying. Additionally, respondents believed they “learned a lot less” and faculty were viewed asrestrictive with limited access and delayed feedback. The

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

Tagged Divisions

Computers in Education

of the real-life system. Students will alsobuild alternatives to the current system to improve the system's key performance measures. Inaddition, more data will be collected in the future course. This data will help in analyzing theeffectiveness of the CLICK approach across several courses in the IE curriculum. The usabilityof the learning modules will also be revised based on the students’ feedback.AcknowledgmentThe authors would like to thank the National Science Foundation for funding this work underGrant # 1834465. Any opinions, findings, or conclusions found in this paper are those of theauthors and do not necessarily reflect the views of the sponsors. The authors would also like tothank Xing Chen for his help in animating the 3D

Conference Session

Work-in-Progress Posters: Computers in Education Division Poster Session

Collection

2017 ASEE Annual Conference & Exposition

Authors

Oscar Antonio Perez, University of Texas, El Paso; Peter Golding, University of Texas, El Paso; Virgilio Ernesto Gonzalez, University of Texas, El Paso; Mike Thomas Pitcher, University of Texas, El Paso

Tagged Divisions

Computers in Education

PT Work Family Other Students 104 3 33 38 33 Percentage 97.20% 2.80% 30.80% 35.50% 30.80% Table 5. Shows question 5 and the results of the answers received for question 5In addition to results shown in Table 5 reflecting what other commitments students have everyweek; an average of Work/Family/Other commitments was calculated with results showing anaverage of 52.1 hours committed to activities per student. Table 6 shown below displays thestudents’ preference by grouping the answers from question one into two groups. These twogroups being prefer and not prefer

Conference Session

Computers in Education Engineering Division Poster Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

Debarati Basu, Virginia Tech; John Stanton Goldstein Purviance, Virginia Tech ; Darren K Maczka, Virginia Tech; Daniel S Brogan, VIrginia Tech; Vinod K. Lohani, Virginia Tech

Tagged Divisions

Computers in Education

based on the particular device, regardless of the order in which theywere detected. The instruments’ data collected by the python programs were stored in a local MySQLdatabase on the Raspberry Pi. This local database on the Raspberry Pi had seven data tables; twofor the acoustic Doppler current profiler, four for the weather transmitter and one for the waterquality Sonde. Some instruments used multiple tables to store data in a way that reflected howdata was retrieved from them. All of the tables in the local database had an index column thatserved as the primary key, a column with time stamps from the system time and columns of datavalues. The data values were stored as floating point numbers to preserve precision.6.0 System

Conference Session

Instrumentation and Laboratory Systems

Collection

2007 Annual Conference & Exposition

Authors

Hassan Rajaei, Bowling Green State University; Mohammad Dadfar, Bowling Green State University

Tagged Divisions

Computers in Education

t T 3000 i m e 2000 1000 0 4 1 2 3 Basic Aggressive Lookahead Nodes Requested Multiple Queue Figure 7: Nodes Requested versus Waiting Time6.2 Gang Scheduling and BackfillingA policy is evaluated by scheduling criteria which reflect user’s parameters of interest. A fairand quick response time is

Conference Session

Robots in Education

Collection

2009 Annual Conference & Exposition

Authors

Alexander Mentis, United States Military Academy; Charles Reynolds, United States Military Academy; Donald Abbott-McCune, United States Military Academy; Benjamin Ring, United States Military Academy

Tagged Divisions

Computers in Education

, no. 2, pp. 5-9, April 2008.2. Zachary Dodds, “AI Assignments in a CS1 Course: Reflections and Evaluation,” Journal of Computing Sciences in Colleges, vol. 23, no. 6, pp. 262-271, June 2008.3. Barry Fagin, “Using Ada-based Robotics to Teach Computer Science,” in ACM SIGCSE Bulletin, vol. 32, New York, 2000, pp. 148-151.4. Barry Fagin and Laurence Merkle, “Measuring the Effectiveness of Robots in Teaching Computer Science,” in ACM SIGCSE Bulletin, vol. 35, New York, 2003, pp. 307-311.5. Robert W. Hasker, “An Introductory Programming Environment for LEGO MindStorms Robots,” in Midwest Instruction and Computing Symposium, 2005

Conference Session

Computing Technology Session 1

Collection

2017 ASEE Annual Conference & Exposition

Authors

Emre Tokgoz, Quinnipiac University

Tagged Divisions

Computers in Education

responses. The nature of quantitativeresults consist of probabilities that reflect the students’ technology preferences and the variationanalysis of the programming preferences across different research questions. The results presentedin this paper help to determine and understand engineering students’ technology choices forsolving different calculus problems based on their technology education. The participants of thisInstitutional Review Board (IRB) approved research completed the third calculus course of a four-course calculus sequence. This article is a continuation of another IRB approved research that wasconducted by the researcher at a large Midwest U.S. institution.Key Words: Computer programming preference; Undergraduate education

Conference Session

Computing Technology Session 3

Collection

2017 ASEE Annual Conference & Exposition

Authors

Peter J Clarke, Florida International University; Debra Lee Davis, Florida International University; Raymond Chang Lau, Florida International University; Yujian Fu P.E., Alabama A&M University; James D Kiper, Miami University; Gursimran Singh Walia, North Dakota State University

Tagged Divisions

Computers in Education

introduction to the instructors’view of WReSTT-CyLE, one (1) session on using DLOs in WReSTT-CyLE, two (2) sessions on de-signing and conducting a research study, and two (2) sessions on using software testing tools in theclassroom. Additional details of the workshops can be found at http://wrestt.cis.fiu.edu/events.On average for each WISTPC workshops held at FIU, there were 19 applications for the work-shops, 14 applicants attended the workshops, 27 total attendees (including PIs and students) at-tended the workshops, and 18 institutions were represented at the workshops. Based on the surveysconducted at the workshops the attendees found the workshops to be very helpful, relevant to theircourses and interesting. This was reflected in attendees

Conference Session

Computing Technology Session 2

Collection

2017 ASEE Annual Conference & Exposition

Authors

Susan L. Miertschin, University of Houston, College of Technology (MERGED MEMBERSHIP WITH COE); Barbara Louise Stewart, University of Houston; Carole E. Goodson, University of Houston (CoT)

Tagged Divisions

Computers in Education

they need technical support. It isinteresting to note that these findings were consistent among students regardless of their levels ofexperience with online and face-to-face course formats. We might conclude that these aregenerally universal needs for all students, and thus, issues of prompt communication andfeedback may merit solid attention from course designers and faculty members.Value for instructor roles related to technologyOverwhelmingly student responses to the question “What can your instructor do with technologyto better support your academic success?” requested more use of technology. This reflects apositive outlook for the use of technologies to increase learning. Because students saw greatopportunities to enhance their success

Conference Session

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

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Divisions

Computers in Education

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

Conference Session

Computers in Education Division Technical Session 10: STEM Outreach

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

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

Conference Session

COED: Online and Blended Learning Part 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Taylor V. Williams, Purdue University, West Lafayette; Kerrie A. Douglas, Purdue University, West Lafayette; Tarun Yellamraju, Purdue University, West Lafayette; Mireille Boutin, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

Science Foundation (NSF) (PRIME #1544259). Anyopinions, findings, and conclusions or recommendations expressed in this material are those of theauthors and do not necessarily reflect the views of NSF.The authors would like to thank FutureLearn for providing the data and the many reviewers whomade this a much stronger paper.8. REFERENCES[1] R. F. Kizilcec and C. Brooks, “Diverse big data and randomized field experiments in MOOCs,” in Handbook of Learning Analytics, 1st ed., C. Lang, G. Siemens, A. Wise, and D. Gasevic, Eds. Society for Learning Analytics Research (SoLAR), 2017, pp. 211–222.[2] R. F. Kizilcec, C. Piech, and E. Schneider, “Deconstructing disengagement: analyzing learner subpopulations in massive open online

Conference Session

Innovative Use of Technology in K-12 Outreach

Collection

2016 ASEE Annual Conference & Exposition

Authors

Fernando Garcia Gonzalez, Florida Gulf Coast University; Janusz Zalewski, Florida Gulf Coast University

Tagged Divisions

Computers in Education

and immediately start moving towards the next point.As a result the shapes drawn looked deformed. Figure 20 shows a sample drawing from one ofthe teams displaying the word “Hi.”This error cause frustration which is reflected in the surveys the students took at the end of thecamp. However even the distorted drawing they were able to produce resulted in the studentsdisplaying great excitement. Other factors such as a weak grip on the pen and physical play inthe arm’s joints also produced distortion however the students seamed to understand thesecharacteristics. Figure 20: a sample drawing from one of the arms where the arm drew the word “Hi.”The best way to find errors or weaknesses on a software product is to give it to a set of

Conference Session

Technology-Related Educational Research

Collection

2016 ASEE Annual Conference & Exposition

Authors

Krishna Madhavan, Purdue University - West Lafayette; Michael Richey, The Boeing Company; Barry McPherson, The Boeing Company

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

learners work hand-in-hand withindustry experts, academic researchers, and data scientists to elicit the type of design behaviorsthat reflect real world engineering practice in the aerospace industry. This allows us to develop,test, and refine the instrumentation methodology, data architectures, analytics, and visualizationapproaches before interfering with the day-to-day work within an organization. In the context ofour work, a program called AerosPACE was developed not only as a senior capstone course, butalso to serve as a test bed.AerosPACE is an engineering education program developed by a large US aerospace company.The primary goal of this program is to bridge the gap between theory and application, (and tohelp students understand the

Conference Session

General Technical Session

Collection

2015 ASEE Annual Conference & Exposition

Authors

John P. Mullen, New Mexico State University

Tagged Divisions

Computers in Education

: Scatterplot of Average Test Score vs. Class Participation PointsFigure 9 shows the average quiz score, compared to the total of all other points in the course.Both totals were adjusted to 100 points to simplify comparison. There is a surprisingly highcorrelation between the two scores (R = 0.59, P = 0.002). However, this probably reflects the factthat those students who skipped quizzes also tended to skip classes and skipped turning in someassignments. The fact that three students did very well in the quizzes, but got a “C” in the courseindicates that there is no clear cause and effect. Figure 9: Quiz Score vs. Total Non-Quiz Course ScoreStudents who participated in the questions with instructor feedback between attempts

Conference Session

Computers in Education Division Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Bruce W. Char, Drexel University (Computing); Thomas T. Hewett, Drexel University

Tagged Divisions

Computers in Education

for the Page 24.1383.7 week, there were numerous possibilities: knowledge acquisition/review from readings (where the humble true/false question was often good enough), problem-solving using problems similar to ones covered in lab or the readings, exercises that would require result interpretation or reflective thinking, problem-solving that would require adaptation and transference of learning, etc.2. How much time should students expect to the week's autograded work will take, and how will you make your question selection fit within that time budget? Despite its use of autograding, our course emphasizes

Conference Session

Computers in Education Division Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Neelam Soundarajan, Ohio State University; Swaroop Joshi, Ohio State University; Rajiv Ramnath, Ohio State University

Tagged Divisions

Computers in Education

) Fig. 1. Community of InquiryBut it is also appropriate for learning environments that are partly face-to-face and partly on-line. The three principal elements of the CoI model are social presence, cognitive presence andteaching presence. Social presence may be defined as the degree to which participants in thelearning environment feel affectively connected one to another; cognitive presence represents theextent to which learners are able to, via interactions with each other, construct and refine theirunderstanding of important ideas through reflection and discussion; and teaching presence is thedesign of various instructional activities such as lectures as well as activities intended to facilitateinteractions among students to help their

Conference Session

Computers in Education Division Poster Session

Collection

2014 ASEE Annual Conference & Exposition

Authors

Petr Johanes, Stanford University; Larry Lagerstrom, Stanford University

Tagged Divisions

Computers in Education

on a given course. From data gathered across all five courses, wefound that on average students spend 3-4 hours per week on online materials/videos, 1-2hours per week on online quizzes/assessments, and 3-4 hours per week on paper-basedproblem sets (if they are part of the course). (See Figure 1 below.)The total time spent outside of class time is therefore 7-10 hours per week. Given that thesecourses are 3-4 units apiece, this is consistent with the definition of a Carnegie unit, whichstates that 1 unit of academic credit reflects approximately 3 hours of work per week inside oroutside of class. To confirm this conclusion, we calculated the hourly range that each studentreported spending on the course overall, and defined that range as low

Conference Session

Course Development / Curriculum Development

Collection

2015 ASEE Annual Conference & Exposition

Authors

Alisa Gilmore P.E., University of Nebraska, Lincoln

Tagged Divisions

Computers in Education

paper is organized into the following sections: Background: The Need for a MobileRobotics Course, Mobile Robotics Course Goals, Course Innovations, Analysis of StudentFeedback, Reflections, and Conclusion. Page 26.460.2Background: The Need for a Mobile Robotics CourseThe Mobile Robotics course was developed as part of a progression of educational roboticsinitiatives birthed on our campus from 2005 to 2013. A brief overview of these initiatives is firstgiven to provide the motivation and context for the creation of this course and its designelements. Figure 1In 2005, the idea of using robotics to

Conference Session

Innovative Use of Technology I

Collection

2015 ASEE Annual Conference & Exposition

Authors

Zhou Zhang, Stevens Institute of Technology; Mingshao Zhang, Stevens Institute of Technology; Yizhe Chang, Stevens Institute of Technology, School of Engineering and Science; Sven K. Esche, Stevens Institute of Technology, School of Engineering and Science; Constantin Chassapis, Stevens Institute of Technology, School of Engineering and Science

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

. Therefore, after segmentation, these features were extracted by the featureextractor. Then, these features were input into the classifier. Basically, the classifier can recognizethese 3 objects with very high accuracy (89.1% for the digital scale, 91.3% for the pump and98.4% for the Xplorer GLX. The relatively low accuracy of the recognition is attributable to theKinect’s inability to cope with reflective surfaces which reduces the scanning accuracy. (a) (b) Figure 9: Step motor (a) photograph of physical step motor; (b) model in GBVL Page

Conference Session

Computers in Education Division Poster Session

Collection

2016 ASEE Annual Conference & Exposition

Authors

Kenneth A. Ritter III, University of Louisiana, Lafayette; Terrence L. Chambers PE, University of Louisiana, Lafayette; Christoph W. Borst, University of Louisiana, Lafayette

Tagged Divisions

Computers in Education

all informationalicons, the student is then informed to follow the yellow arrows to the solar collectors shown inFigure 6. Figure 6: Left: Area 3, solar collectors. Right: Area 4, boiler.Area 3, Solar Collectors: In this area the student learns about how the solar troughs track the sunthroughout the day to capture the direct sunlight and reflect it to the central absorber tube. Also itis explained in detail how sunlight passes through the transparent glass of the absorber tube, orevacuated tube, and how the heat is transferred to the working fluid. The student is theninstructed to point the solar collectors to capture the direct sun at high noon to collect solarenergy and heat up the working fluid. Once finished the student

Conference Session

Teaching and Advising Tools Using Computers and Smart Devices

Collection

2016 ASEE Annual Conference & Exposition

Authors

Oscar Antonio Perez, University of Texas - El Paso; Virgilio Ernesto Gonzalez, University of Texas - El Paso

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

% 30.80% Table 5. Shows the results of answers for question 5In addition to results shown in Table 5 reflecting what other commitments students have everyweek, an average of Work/Family/Other commitments was calculated with results showing anaverage of 52.1 hours committed to activities per student. Table 6 shown below displays thestudents’ preference by grouping the answers from question one into two groups. These twogroups being prefer and not prefer. Advising System Type System Type at least Preferred not preferred no answer Face 2 Face 87.90% 12.10% 0.00% Mobile 70.10

Conference Session

Computing Technology Session 2

Collection

2017 ASEE Annual Conference & Exposition

Authors

Petr Johanes, Stanford University; Larry Lagerstrom, Stanford University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

personalcomputer in the 1980s and the obvious possibility of using the computer as an automated form oftutor, or as an “intelligent tutoring system” (ITS). [42] An ITS is “any computer system thatperforms teaching or tutoring functions (e.g., selecting assignments, asking questions, givinghints, evaluating responses, providing feedback, prompting reflection, providing comments thatboost student interest) and adapts or personalizes those functions by modeling students’cognitive, motivational or emotional states.” [31] As might be expected, STEM topics – andcomputer science in particular – proved well-suited to these modeling efforts. Not only werecomputer scientists the ones designing the computers in the first place, but they were alsooperating in a

Conference Session

COED: Online and Blended Learning Part 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Swaroop Joshi, Ohio State University; Neelam Soundarajan, Ohio State University; Jeremy Morris, Ohio State University

Tagged Divisions

Computers in Education

student will receive an email from the app askingher to log into the system and answer the question by a deadline, typically 24-36 hours awayfrom the time the homework is posted, with the deadline also being listed in the email. Theapp will require the student to make a specific choice –such as “domain” or “problem” or “so-lution”, and to include a brief justification as part of her answer. We will refer to this as thestudent’s initial submission. Note, these initial submissions are made by individual students andeach reflects the particular student’s (initial/current) conception of the problem. Also, a studentcan log back in any time before the deadline and modify her answer if she wants to. Figure 2shows the initial submission made by one of

Conference Session

COED: Mechanical Engineering-related Topics

Collection

2018 ASEE Annual Conference & Exposition

Authors

Steven F. Barrett, University of Wyoming; Tonia A. Dousay, University of Idaho; Tyler J. Kerr, University of Wyoming; Larry Schmidt, University of Wyoming; Brandon Seth Gellis, University of Wyoming; Jesse Ballard, University of Wyoming

Tagged Divisions

Computers in Education

these efforts to be reflected in faculty and staff participation in the academic year ahead.• Ensuring print quality and overall quality control. 3D printers are the most popular technology housed in the space, and consequently are the machines used most often. As a result, regular maintenance is required to ensure acceptable print quality. In the first semester of operation few visitors knew how to use the software necessary to 3D print objects. Because of this, most 3D printing, including prints for visitors, was completed by staff members. This proved to be challenging for the six staff members for two reasons: 1) print preferences and personal settings varied considerably; and 2) the first printers were largely

Conference Session

Technical Session 2: Embedded Systems

Collection

2019 ASEE Annual Conference & Exposition

Authors

J.w. Bruce, Tennessee Technological University; Ryan A. Taylor, University of Alabama

Tagged Divisions

Computers in Education

manager’s blog [20]reported US$3.98 per LoC for a traditional programming design team that he personally servedas the design architect and manager. Several other studies [19] report software development costsranging from $5-100 per LoC. Lines of Code written per student 2500 2000 1500 LoC 1000 500 0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 YearFigure 2: Average student output for a semester-long effort for 2007-2019Changes in the course’s design requirements are reflected in Figure 2. For example, the designrequirements changed only

Conference Session

Computers in Education Division Technical Session 7: Advanced CS courses

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Divisions

Computers in Education

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

Conference Session

Computers in Education Division Technical Session 7: Advanced CS courses

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

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

Tagged Divisions

Computers in Education

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

Conference Session

Computer Simulation and Animation II

Collection

2008 Annual Conference & Exposition

Authors

Mark Rossow, Southern Illinois University-Edwardsville

Tagged Divisions

Computers in Education

and formulation of generalizations and principles. It would appear thatlearning is best facilitated when impasses are carefully chosen in both design andnumber. Researchers have proposed inserting, in the worked example, prompts such asmultiple-choice questions30. The questions typically are conceptual rather thanquantitative in nature and are designed to force students to reflect upon and generalizetheir ideas about the example being studied. It is interesting to note that such “concept-eliciting questions” play a key role in the work of Steif and colleagues39-40, even thoughtheir focus is on learning through problem solving rather than through studying workedexamples. Indeed, learning through solving problems begins to resemble

Conference Session

Web-Based Education

Collection

2006 Annual Conference & Exposition

Authors

Eugene Ressler, U.S. Military Academy; Stephen Ressler, U.S. Military Academy; Catherine Bale, U.S. Military Academy

Tagged Divisions

Computers in Education

network hardware andoperating system software in good repair and up to date.As shown in the rightmost two columns of Table 4, time spent by contest administrators may bedivided into routine and task-oriented work that may be scheduled or unscheduled. Routine Page 11.547.14work occurs each week from the start of the qualifying round through the completion of finals.Scheduled tasks are generally aimed at preparation for the next contest round. Exceptions are thetasks of the webmaster and software authors, which reflect the effort of initial development.Unscheduled tasks result from unpredictable events such as software bugs and misbehaviors