Course Introduction - Spring 2022

Resources

• Slides
• Previous Versions

Video Script

[Slide 1]

Hello and welcome to the Computational Core program!

My name is Emily Alfs-Votipka, and I’ll be one of the instructors for this program. My contact information is shown here, and is also listed on the syllabus.

[Slide 2]

There are many other instructors and TAs for this program that you may interact with or see in the tutorial videos. They all have been instrumental in the development of this program.

[Slide 3]

In this course we will primarily use a K-State email group (cc110-help or cc110-help@ksuemailprod.onmicrosoft.com ) to communicate. Email sent to this address is forwarded to all instructors and TAs. Our replies to you will also be shared amongst the instructors and TAs so we all have access to the assistance you have already received. We will respond to you within a business day So a question emailed Friday night may not receive an answer before Monday.

If you wish to pose a discussion topic to you classmates, you should use the discussion feature in Canvas. Please note that asking a question on a discussion forum is not the same as emailing cc110-help; we will certainly monitor the discussion channels, but not with the same speed as the “help line”. Please read and adhere to the guidance on Netiquette in the syllabus for all electronic communications.

[Slide 4]

In addition to email and Canvas, we’ll be using the online learning platform Codio for most of the programming tutorials and projects in this program. We’ll also discuss how to use Codio later in this module.

[Slide 5]

The Computational Core program consists of several courses, and each course contains a number of learning modules. There are about 30 modules in this course. Each module will usually consist of some lecture material and quizzes, and there are a few modules which include a programming component. The modules themselves are gated, which means that you must complete each item in the module in order before continuing. In addition, the modules enforce prerequisite requirements from other modules. For CC 110 you must complete them in order starting with module 0, the enroll module should be completed first, but is not a prerequisite.

You are welcome to work on this course at any time during the week as your schedule allows, provided that you complete each module before the listed due date. There will be roughly two modules due each week. The modules are self-contained, and nearly all of the grading in this course is completed automatically through Canvas and Codio. So, you can complete modules at any time before the due date, and once a module is complete, you may immediately start on the next one.

[Slide 6]

Looking ahead to the rest of this introductory module, you’ll see that there are a few more items to be completed before you can move on. In the next video, we’ll discuss a bit more information about navigating through this course on Canvas and using the Codio learning environment.

[Slide 7]

One thing we highly encourage each of you to do is read the syllabus for this course in its entirety, and let us know if you have any questions. My view is that the syllabus is a contract between me as your teacher and you as a student, defining how each of us should treat each other and what we should expect from each other. We have made a few changes to the standard syllabus template for this program, and those changes are clearly highlighted. Finally, the syllabus itself is subject to change as needed as we adapt this program to meet the needs of its students, and all changes will be clearly communicated to everyone before they take effect.

[Slide 7]

One very important part of the syllabus that every student should read is the late work policy. First off, each module has a due date, and you may work on that module at any time before it is due, provided you have met the prerequisites. As discussed before, you must do all the readings and assignments in a module in listed order before moving on, so you cannot jump ahead. A module is considered completed when all items have been completed.

For the purposes of grading, we will use the date and time that the confirmation quiz was submitted at the end of each module to determine when the module was completed. This is due to the way that Codio handles automated grading, as it may resubmit previously graded assignments if an error in the module is corrected, making a previously completed assignment appear to be submitted late.

If any work is submitted after the due date, a penalty of 10% of the total points possible in that assignment will be deducted for each day it is late, up to a maximum of 3 days. After 3 days beyond the due date, you will receive a 0 on the assignment. Please refer to the full late policy in the syllabus for more information about how late work is handled in this course.

Finally, even if a module is late, it still must be completed before you can move on to a later module. So, it is very important to avoid getting behind in this course, as it can be very difficult to get back on track. If you ever find that you are struggling to keep up, please don’t be afraid to contact either the instructors or GTAs for assistance. We’d be happy to help you get caught back up quickly.

In this program, the standard “90-80-70-60” grading scale will apply, though I reserve the right to curve grades up to a higher grade level at my discretion. Therefore, you will never be required to get higher than 90% for an A, but you may get an A if you score slightly below 90% if I choose to curve the grades.

This is intended to be a completely online, self-paced course. There are no mandatory scheduled course times. All of the content is available online, so you can work whenever and wherever you want. It could be a 3-hour block once a week, or a few minutes here and there between classes. It’s really up to you and your schedule. However, remember that each module may require 4 to 6 or more hours of work to complete, so make sure you have plenty of time available to devote to this course.

Also, a vast majority of the grading in this course will be handled automatically through Canvas and Codio. This means that you’ll be able to receive feedback directly from those systems as soon as you submit your work. You may also contact the instructors and GTAs for additional tips and feedback regarding your work, but depending on the number of students in the program, we may not be able to review every student submission directly.

In addition, due to the flexible online format of this class, there won’t be any long lecture videos to watch. Instead, each module will consist of a guided tutorial and several short videos, each focused on a particular topic or task. Likewise, there won’t be any textbooks required, since all of the information will be presented in the interactive tutorials through Codio. Finally, since we are using Codio as our learning platform, you won’t have to deal with installing and using a clunky integrated development environment, or IDE, just to learn how to program. Codio helps make learning to program quick and painless by moving everything to the web.

For this course, the only supplies you’ll need as a student are access to a modern web browser and a broadband internet connection. No other special hardware or software is necessary!

Finally, as you are aware, this course is always subject to change. This is a relatively new program here at K-State, and we’re always working on new and interesting ideas to integrate into the courses. The best advice I have is to look upon this graphic with the words “Don’t Panic” written in large, friendly letters. If you find yourself falling behind, or not understanding seek our help via cc110-help.

So, to complete this module, there are a few other things that you’ll need to do. The next step is to watch the video on navigating Canvas and Codio, which will give you a good idea of how to most effectively work through the content in this course.

To get to that video, click the “Next” button at the bottom right of this page.

Navigating Canvas & Codio

Resources

• Codio Documentation

Video Script

This course makes extensive use of several features of Canvas which you may or may not have worked with before. To give you the best experience in this course, this video will briefly describe those features and the best way to access them.

When you first access the course on Canvas, you will be shown this homepage. It contains quick links to the course syllabus and Piazza discussion boards. This is handy if you just need to jump to a particular area.

Let’s walk through the options in the main menu to the left. The first section is Modules, which is where you’ll primarily interact with the course. You’ll notice that I’ve disabled several of the common menu items in this course, such as Files and Assignments. This is to simplify things for you as students, so you remember that all the course content is available in one place.

When you first arrive at the Modules section, you’ll see all of the content in the course laid out in order. If you like, you can minimize the modules you aren’t working on by clicking the arrow to the left of the module name. I’ll do so, leaving the introductory module open.

As you look at each module, you’ll see that it gives quite a bit of information about the course. At the top of each module is an item telling you what parts of the module you must complete to continue. In this case, it says “Complete All Items.” Likewise, the following modules may list a number of prerequisite modules, which you must complete before you can access it.

Within each module is a set of items, which must be completed in listed order. Under each item you’ll see information about what you must do in order to complete that item. For many of them, it will simply say view, which means you must view the item at least once to continue. Others may say contribute, submit, or give a minimum score required to continue. For assignments, it also helpfully gives the number of points available, and the due date.

Let’s click on the first item, Course Introduction, to get started. You’ve already been to this page by this point. Many course pages will consist of an embedded video, followed by links to any resources used or referenced in the video, including the slides and a downloadable version of the video. Finally, a rough video script will be posted on the page for your quick reference.

While I cannot force you to watch each video in its entirety, I highly recommend doing so. The script on the page may not accurately reflect all of the content in the video, nor can it show how to perform some tasks which are purely visual.

When you are ready to move to the next step in a module, click the Next button at the bottom of the page. Canvas will automatically add Next and Previous buttons to each piece of content which is accessed through the Modules section, which makes it very easy to work through the course content. I’ll click through a couple of items here.

At any point, you may click on the Modules link in the menu to the left to return to the Modules section of the site. You’ll notice that I’ve viewed the first few items in the first module, so I can access more items here. This is handy if you want to go back and review the content you’ve already seen, or if you leave and want to resume where you left off. Canvas will put green checkmarks to the right of items you’ve completed.

Continuing down the menu to the left, you’ll find the usual Canvas links to view your grades in the course, as well as a list of fellow students taking the course.

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Where to Find Help

Resources

• Slides
• K-State IT Help Desk - Email helpdesk@ksu.edu
• K-State Online Canvas Help
• Instructure Canvas Guides
• Codio Documentation
• Codio Support
• K-State Libraries
• K-State CS Support
• K-State CS Advising
• K-State Engineering Student Services
• K-State Office of Student Life
• K-State Report It

Video Script

[Slide 1]

As you work on the materials in this course, you may run into questions or problems and need assistance. This video reviews the various types of help available to you in this course.

[Slide 2]

First and foremost, anytime you have a questions or need assistance in the Computational Core program, please email the appropriate help group. It is the best place to go to get help with anything related to this program, from the tutorials and projects to issues with Codio and Canvas. For example, if you are enrolled in CC315 and have questions, from your KSU email, you would type cc315-help and hit tab to auto-complete the email.

[Slide 3]

If you have any issues working with K-State Canvas, K-State IT resources, or any other technology related to the delivery of the course, your first source of help is the K-State IT Helpdesk. They can easily be reached via email at helpdesk@ksu.edu . Beyond them, there are many online resources for using Canvas, all of which are linked in the resources section below the video.

[Slide 4]

If you have any issues using the Codio platform, you are welcome to refer to their online documentation. Their support staff offers a quick and easy chat interface where you can ask questions and get feedback within a few minutes.

[Slide 5]

If you have issues with the technical content of the course, specifically related to completing the tutorials and projects, there are several resources available to you. First and foremost, make sure you consult the vast amount of material available in the course modules, including the links to resources. Usually, most answers you need can be found there.

Of course, as another step you can always exercise your information-gathering skills and use online search tools such as Google to answer your question. While you are not allowed to search online for direct solutions to assignments or projects, you are more than welcome to use Google to access programming resources such as StackOverflow, language documentation, and other tutorials. I can definitely assure you that programmers working in industry are often using Google and other online resources to solve problems, so there is no reason why you shouldn’t start building that skill now.

[Slide 6]

Next, we have grading and administrative issues. This could include problems or mistakes in the grade you received on a project, missing course resources, or any concerns you have regarding the course and the conduct of instructors and your peers. Since this is an online course, you’ll be interacting with us on a variety of online platforms, and sometimes things happen that are inappropriate or offensive. There are lots of resources at K-State to help you with those situations. First and foremost, please email your instructor as soon as possible and let them know about your concern, if it is appropriate for them to be involved. If not, or if you’d rather talk with someone other than your instructor about your issue, I encourage you to contact either your academic advisor, the CS department staff, College of Engineering Student Services, or the K-State Office of Student Life. Finally, if you have any concerns that you feel should be reported to K-State, you can do so at https://www.k-state.edu/report/ . That site also has links to a large number of resources at K-State that you can use when you need help.

[Slide 7]

Finally, if you find any errors or omissions in the course content, or have suggestions for additional resources to include in the course, email the instructors. There are some extra credit points available for helping to improve the course, so be on the lookout for anything that you feel could be changed or improved.

[Slide 8]

So, in summary, the content and links in the modules should always be your first stop when you have a question or run into a problem. For issues with Canvas or Codio, you are also welcome to refer directly to the resources for those platforms. For questions specifically related to the projects, use the courses help group. For grading questions and errors in the course content or any other issues, please email the instructors for assistance.

Our goal in this program is to make sure that you have the resources available to you to be successful. Please don’t be afraid to take advantage of them and ask questions whenever you want.

What You'll Learn

Resources

• Slides
• Code.org Quotes

Video Script

Finally, before embarking on this program, let’s take a brief minute to review what you’ll learn by the time you complete the program.

Of course, the biggest and most impactful outcome will be learning how to write computer programs. Throughout the Computational Core program, you’ll learn either the Java or Python programming language, and get to a point where you are quite proficient with your language of choice. You’ll be capable of building your own programs from scratch to meet many of the challenges you’ll encounter in your career or elsewhere. This skill alone will set you well above your peers.

There are many additional benefits beyond just learning how to write programs. For starters, programming involves a large amount of problem solving and computational thinking, and these courses will help sharpen you skills in both areas. In addition to programming, you’ll also learn about software engineering methods that will help you build better programs, but also data structures and algorithms that will make your code more efficient and useful as it manipulates and stores data. Of course, you’ll also pick up some new math and logic skills, as both are vitally important to understanding computer code. Lastly, we’ll spend a bit of time discussing how computers actually work, so you can see how your code actually gets a computer to perform the tasks you desire.

Finally, you may be asking yourself why this is important. I could absolutely bring out large numbers of statistics stating how many computer programming jobs are available right now, and how we have a distinct lack of capable graduates to fill these positions. I could also talk about how much more money you could make as a computer programmer than in many other fields. But, instead, I think it is best to just present this quote from Stephen Hawking, one of the most brilliant people to ever live:

Whether you want to uncover the secrets of the universe, or you just want to pursue a career in the 21st century, basic computer programming is an essential skill to learn. - Stephen Hawking

This is just one of the many great quotes encouraging you to learn computer programming from Code.org. I highly recommend checking out their quote archive whenever you need additional inspiration.

That should cover all of the background information you’ll need before you start this program. The rest of this module includes the full course syllabus and a few assignments that you should read through before beginning the course, but you don’t have to do anything else for them right now. Finally, this module wraps up with a quick quiz making sure you are 100% ready to take this course.

Best of luck to you on your adventure through this program!

How to Learn Programming

Resources

• Slides
• The Science of Learning Programming from Nathan Bean’s CIS 400 Textbook
• The Power of Believing You Can Improve | Carol Dweck - TED Talk on Mindsets and the Power of “Yet”
• The New Science of Learning: How to Learn in Haromony with your Brain by Terry Doyle and Todd Zakrajsek - Great Book on Learning
• Constructivism on Wikipedia - Article about Jean Piaget’s Learning Philosophy
• Toward a Developmental Epistemology of Computer Programming by Raymond Lister - Introduces the Stages of Learning to Program

Video Script

Before we launch into the course itself, I wanted to take a few minutes to share some information with you regarding what we know about how students learn to program. This isn’t just anecdotal evidence from computer science teachers like me, but theories and research from education researchers who study how humans learn new skills and abilities throughout their lives.If I had to summarize all of this information in as few words as possible, I’d simply say “do the work.” Learning to program is difficult, and the only way to really get good at it is through constant practice and learning. However, that greatly oversimplifies the information that I want to share, and I’m hoping that you’ll find some helpful takeaways from this video that you can incorporate into your learning process.

Before I begin, I want go give all the credit to Nathan Bean for developing this information as part of his CIS 400 course. He graciously allowed me to use his hard work here, and I encourage you to check out his original version, which is available at the URL shown on this slide.

The statement “do the work” is a shorter version of a very common quote from educators, which is “the person doing the work is the person doing the learning.” I couldn’t find a solid reference for who said it first, so I’ll just attributed it to various educators throughout time. This really highlights one of the biggest struggles many students run into when learning to program. There are so many guides online, and the answer to many simple problems can be found through a quick Google search. You can just copy and paste the code, and then your program works. However, did you really learn how to write that program and what it does, or just how to find a quick answer? While this may be a useful tactic from time to time, if you rely too much on other people to do your coding, you really won’t learn it yourself. This is just like learning to shoot free throws on a basketball court or beating your best time in a speedrun - you can’t just watch someone do it and expect to do it yourself (believe me, I’ve tried). So, if you aren’t doing the work, you aren’t really learning.

Next, let’s address a major myth in computer science. I’ve heard this many times: “some people are just natural born programmers, and others simply cannot learn to program.” And yes, on the surface, it may appear to be this way. Some students just seem to have a knack for programming, and you may sit and struggle and not really get anywhere. However, there is no innate skill or ability that makes you good at programming.

Instead, let’s reframe what it means to learn programming. At its core, programming is learning to write steps to solve problems in a way that a computer can perform those steps. That’s really what we are doing when we learn programming.

So, we must focus on learning how to write those steps with the proper exactitude and precision so that they make sense, and we must understand how a computer functions to be able to program that computer effectively. So, when you see someone who is good at programming, it’s not because they are good at some esoteric skill that you’ll never have - they just know how to express their steps properly and know enough about how a computer works to make their program do what they want. That’s really it! And, to be honest, after a single semester of learning to program, you’ll have all the skills you need to do both of those things! If you know how to make conditionals, loops, functions, and use simple variables and arrays, that’s really all you need. Everything else that comes after that is just refining those skills to make your programs more powerful and your coding more efficient.

So, how do we learn these skills? Well, there are a couple of important pieces we need to make sure are in the right place first. For starters, we need to have the correct mindset. Many times I’ll see students struggle to learn how to program, and they’ll say things like what you see on this slide. “Its too hard.” “I don’t understand this.” “I give up.” Statements like this are the sign of a “fixed mindset,” and they can be one of the greatest blockers preventing you from really learning to program. Just like learning any other skill, you have to be open to instruction and willing to learn, or else you’ve failed before you even started.

Instead, we want to focus on building a growth mindset. In the TED talk by Carol Dweck that is linked below this video, which I encourage you to watch, she talks about the power of “yet.” We can turn these statements around by simply adding positive power of “yet” - “I don’t understand this yet.” “I love a good challenge.” “I’ll keep trying until I get it.” Going into a programming project with a mindset that is open to growth and change is really an important first steps. When I feel like I’m getting a fixed mindset, I like to think about how difficult it would be to teach a child to tie their shoes if they don’t want to learn. As soon as I realize that, it is pretty easy to recognize that same problem in myself and work to correct it.

So, once we have our growth mindset, how do we actually learn to program? To understand that, let’s dive a bit into the world of educational theory and the work of Jean Piaget. Piaget was a biologist and psychologist who studied how young children acquired new knowledge, and he helped pioneer the concept of Constructivism, one of the most influential philosophies in education. You can read more about Constructivism in the links below this video.

One particular thing that Piaget worked on was a theory of genetic epistemology. Epistemology is the term for the study of human knowledge, so genetic epistemology is the study of the origins, or genesis, of that knowledge. Put more clearly, it’s the study of how humans create new knowledge. This concept was inspired by research done on snails - he was able to prove that two previously distinct species of snails were actually the same by moving snails from one habitat to another and observing how they modified their behaviors and how their shells grew to match the snails in the new habitat. Put clearly, the snails displayed an altered behavior based on their environment. They tried to exist in equilibrium with their environment by adapting their behaviors to fit what they now experienced in the word.

Piaget suspected that something similar happens when humans try to learn something - the brain tries to adapt itself to maintain an equilibrium in its environment, which in this case is the existing knowledge it contains. So, when the brain is exposed to new ideas, it must somehow adjust to account for that new information. Piaget proposed two different mechanisms for how this occurs: assimilation and accommodation. In assimilation, new knowledge can be added to existing structures in the brain. For example, if you are exposed to a new color, such as periwinkle, you can see that it falls somewhere between blue and violet, two colors you already know. So, you can assimilate that new knowledge into the existing knowledge without a major disruption to your mental structure of existing colors. Accommodation, on the other hand, happens when your brain must radically adapt to new information for which no existing structures exist. This can be very difficult, and can lead to a lot of struggle and frustration when trying to get “over the hump” on a new subject. Think about learning algebra or a new language for the first time - you really don’t have anything you can use to help understand this new material, so you just have to keep at it until those new structures are formed in your brain.

Unfortunately, to achieve accommodation, your brain simply has to build brand new structures to store and represent all of this new information, and that process is difficult and takes time. Put another way, it takes significant stimulus, usually in the form of doing homework, struggling with difficult problems and wrestling with the new information to try and understand it all, to create enough disequilibrium in your brain that, coupled with a growth mindset, will allow accommodation to occur. However, when all the pieces are in the right place, and you work hard and have a growth mindset, then…

EUREKA! The structures will form, and you’ll get over that huge hurdle, and things will start falling into place. It may not happen all at once, but it does happen (you’ve probably had it happen to you several times already - think about some eureka moments from your past - were they related to learning a new skill?). Of course, there’s a good chance that your brain might form a few incorrect structures in the process, so you’ll have to overcome those as you continue to learn. I still struggle to spell some words because my brain formed incorrect structures when I was still learning. But, if you continue to work hard and be open to learning, you’ll eventually sort those errors out as well.

Let’s look at one other concept in education, which is called stage theory. Piaget identified four stages that children go through as they learn to reason about the world. Those four stages are shown on this slide. In the sensorimotor stage, the child is just using their senses to interact with the world, without any real understanding of what will happen when they perform an action. This is best represented by babies and toddlers, who touch and taste everything in their surroundings. Next, the preoperational stage is represented in young children as they start to think symbolically about the world, using pictures and words to represent actions and objects. They then progress to the concrete operational stage, where they can begin to think logically and understand how concrete events happen. They can also start to think inductively, building the general principles of the world from their specific experiences. For example, if they observe that cooked spaghetti is better than raw spaghetti, they might reason that other foods like potatoes are better cooked than raw. Finally, the last stage is the formal operational stage. This stage is represented by the ability to work fully with an abstract work, formulating and testing hypotheses to truly understand how the world works and predict how new items will work before experiencing them firsthand.

Many later researchers built upon this model to show that adults learn in much the same way. They also discovered that the stages are not rigid, and you may exhibit behaviors from multiple stages at any given time. This is called the “overlapping waves” model, and is shown here in this diagram. So, as you learn new skills, you may be at the operational stage in some areas, but still at the preoperational stage in other areas. This explains why some concepts may make sense while others don’t for a while - you just have to keep going until it all fits together.

So, how can we apply all of this information to programming? One theory comes from the work of Lister and Teague, who proposed a developmental epistemology of computer programming. Put another way, they applied this theory to computer science education, and gave us a unique way to think about the different stages of learning to program.

At the sensorimotor stage, we’re just getting the basics. So, when given a piece of code and asked to trace what it does, we still make lots of errors and get the answer incorrect. If we want to get a program to work ourselves, it usually involves a lot of trial and error, and many times when it does end up working we don’t even know exactly why it worked that time, but we’re building up a baseline of information that we can use to construct our mental model of how a computer works.

As we progress into the preoperational stage, we become better at tracing code correctly, but we still struggle to understand what the program itself does. We see each line of code as a separate instruction, but not the entire program. A great analogy is reading a recipe that calls for flour, water, salt, and yeast. Will it make bread? Biscuits? Pie crust? We’re not sure yet, but at least we can recognize the ingredients. To solve problems at this stage, we typically will randomly adjust pieces of our code that we don’t quite understand and see what it does, trying to form a better idea of the importance of each line in the code.

Eventually, we’ll get to the concrete operational stage. At this stage, we can construct our own programs, but many times we are simply piecing together parts that we’ve used before and performing some futile patches and bugfixes as we refine the program. We can also work backwards to figure out what a program does from execution results, but we still aren’t very good at deducing the results from the code itself. However, we’re starting to work with abstraction, though we tend to simplify things to a level that we are more comfortable with.

Finally, we’ll reach the formal operational stage. At this stage, we can comfortable read and understand code without executing it, quickly seeing what it does and how it works without fully tracing it ourselves. We can also start to form hypotheses for how to build new programs and code, and reason about whether different approaches would work better or worse than others. This is the goal stage for any programmer! Once you have reached this stage, then you’ll feel totally at home working in code and developing your own programs from scratch.

So, how can we enable ourselves to be the best learners we can be? There is lots of interesting research in that area, best summarized in the book “The New Science of Learning” that is linked below this video. Let’s go through a few of the big concepts.

First, getting ample and regular sleep is important, because it allows your brain to build those knowledge structures we discussed earlier and store the memories from the day in long-term storage. Without enough sleep, your brain is unable to process memories offline and make them ready for retrieval later on, an important step in learning. Also, consuming large amounts of caffeine or alcohol can disrupt your sleep patterns, so keep that in mind before you pour that next cup of coffee or go out partying. You can also take advantage of modern technology to help you track your sleep - most smart watches and smartphones today can help with that!

Likewise, regular exercise is important to both your physical and mental health. When you exercise, especially aerobic exercise that gets your heart rate up, your body releases neurochemicals that help your brain cells communicate. In addition, just getting up and moving around regularly helps keep your body healthy, so take regular breaks, and consider getting a standing desk for some extra benefits.

Research also shows that engaging your senses is an important part in learning. This is why we, as teachers, try to vary our lessons with pictures, videos, activities, and more. It is also the basis of the cognitive apprenticeship style of learning that we use, which you can learn more about in the links below this video. We show you the code we are writing, engaging your sense of vision, while talking about it so you are also listening, and then you are writing your own version, using your sense of touch. You can build upon this by using your senses while you learn by taking notes during a lecture video, building concept maps, and even printing out and writing on your code and these lecture scripts. All of these processes help engage different parts of your brain and make it that much easier to build new knowledge structures.

Looking for patterns is another important way to understand programming. There are many common patterns in computer programs, such as using a for loop to iterate through an array, or an if-else statement to determine if a particular variable is set to a valid value. By recognizing and understanding those patterns, we can more quickly understand new programs that use slightly different versions of the same code. Humans are naturally very good at pattern recognition, and it is one of the reasons why we see the same code structures time and time again - not because they are the only way to accomplish that goal, but because that structure is commonly used across many programs and therefore is easier to understand.

There is quite a bit of research into how memories are formed and how we can adjust our studying habits to take advantage of that. For example, cognitive science shows that the parts of our brain responsible for memory creation are active up to one hour after a learning experience has ended, such as a lecture video or activity. So, instead of jumping to the next task, you may want to take a little while to reflect on what you just did and let it sink in before moving on. Likewise, to build strong memories, it is important to constantly recall the memory or use the skills you’ve learned to strengthen their structures in the brain. This is why teachers like to throw in a few questions from a previous exam or quiz every once in a while - it helps strengthen those structures by forcing you to recall information you’ve learned previously. On the other hand, many students try to “cram” a bunch of information right before an exam, only to forget it soon after because it wasn’t recalled more than once. As you progress further, we’ll continue to come back to concepts you’ve already learned and build upon them, a process called elaboration that helps reinforce what you’ve already learned while building new, related knowledge.

Finally, it is important to remember that we must give our brains the space it needs to focus on the task at hand. Multitasking while learning, such as watching YouTube or Twitch, chatting with friends, or listening to a lecture video while coding can all reduce your brain’s ability to form strong memories and do well. In fact, research shows that individuals who try to multitask tend to make 50% more errors and spend 50% more time on both tasks. So, instead of giving yourself distractions, try to find things that will help you focus better - there are some great playlists online for music without lyrics that can help you focus or code better, and you can easily mute notifications on your phone and on your computer for an hour or so while you work.

So, let’s summarize what we’ve covered here. First, and most importantly, remember that you can learn to program, just like the many students who have done it before you. However, it can be difficult and frustrating at times, and it will take lots of hard work on your part to make it happen. That means that you’ll need to read and write a lot of code before it really starts to make sense. In short, you must do the work to learn to program.

That said, you can help make the process easier by getting good sleep, exercising regularly, and engaging fully with all of the content in the course. That means you’ll need to take your own notes, maybe draw some diagrams, and annotate code you write and code you read to help you understand it. While you are working, try not to multitask so you can focus. If you are given some code to include in your program, don’t copy/paste it - rewrite it, and make sure you completely understand what each line does. Finally, take some time to read code written by others! GitHub is a great place to discover all sorts of code and see how others write code. If you want to write good poetry you have to read lots of good poetry, and the same goes for coding.

With that in mind, I hope you are able to make the best of this course and continue to develop your programming skills. If you are interested in this topic and would like to know more about things you can do to be a better learner, let us know! As you can imagine, teachers like me love to talk about this stuff, so don’t be afraid to ask. Good luck!

CC 110 Syllabus - Spring 2024

CC 110 - Introduction to Computing - Spring 2024

Previous Versions

Instructor Contact Information

• Instructor: Safia Malallah
  I use she/her pronouns. Feel free to share your own pronouns with me, and I’ll do my best to use them!
• Email: Safia@ksu.edu  and CC cc110-help@KSUemailProd.onmicrosoft.com >
  Please avoid using the Canvas email functionality; instead, contact me directly at this email address. Canvas emails don’t always reach my inbox reliably.
  I’d like to emphasize that I make an effort to respond to emails within 24 “business hours” (if you don’t receive a reply within 24 hours, please don’t hesitate to reach out again). Specifically, on Fridays, I can only respond until I need to attend to my kids, which means you can anticipate my reply on Monday. Therefore, it’s a good practice to reach out with your questions well in advance to ensure you have enough time to receive my response.
  
• Office Hours:
  

• Time : Check the calendar below to locate my name and the type of the office hour. It could be in person, hybrid, or online. Please check the type regularly as it could change throughout the semester
  
• In person: DUE 2161
  
• Online : https://ksu.zoom.us/my/safiamalallah
  

Preferred Methods of Communication:

• Email: Please use “cc110-help” (cc110-help@ksuemailprod.onmicrosoft.com if not on web-mail) for all communication regarding these courses as it allows instructors and TAs to provide a clear and detailed response, as well as easily store and record communication for reference later. You should receive a response within one business day, and hopefully much sooner. Note emailing the instructor or teaching assistants directly may result in longer wait times for your support.

TAs Contact Information

• TA: Carrie Aponte (she/her)
  
• Email: cgaponte@ksu.edu  and CC cc110-help@KSUemailProd.onmicrosoft.com >
  
• Online Office Hours: T/TH 12pm-2pm:
  https://ksu.zoom.us/my/carrie.aponte

Office Hours

Course Schedule

online

Prerequisites

• None

How to Get Help in this Course

CC 110 can be an interesting course due to the large amount of material covered and much of the material is brand new to students. Therefore, you are encouraged to seek help whenever you feel you are being overwhelmed or don’t understand a topic. You are not alone! Most students in CC 110 have never studied anything relating to computer science before, so it is new to everyone. The instructors and TAs are always willing to help students with any questions you may have about the class or other issues related to Computing Science. So please, don’t be afraid to ask questions. Get help early and often!

Here are the 4 recommended ways to get help on CC 110:

• Review the course materials posted on K-State Canvas and the course website
• Send assignment questions to the CC 110 Help email (cc110-help@ksuemailprod.onmicrosoft.com )
• Visit your professor’s office hours, or the office hours for your TA if available
• Schedule a one-on-one meeting with your professor/TA
• Tutoring center: They offer both online and in-person support. You can access online tutoring through the Computational Core website at the following link: https://www.k-state.edu/aac/tutoring/appointment.html

Course Overview

An overview of the history of computers and programming. Famous historical figures and their impact in modern computing. Introduction to major topics in computer science such as artificial intelligence, high performance computing, cryptography, big data, cyber security, robotics, and more. Brief experience with computer programming concepts.

Course Description

This course serves as a primary introduction to modern computing and programming by reviewing historical figures and events and the impact they had on modern technology. Students are exposed to a variety of topics in computer science, and gain hands-on experience with some of these topics through the use of some basic programming skills. The goal of this course is to show students the wider world of computing and technology beyond programming, building a broad foundation for later courses to build upon.

Learning Objectives

By the end of this course, each student will be able to:

• Describe the history of Computing Science and list some of the important devices, innovations, and people that got us to where we are today.
• Relate Computing Science to a variety of other disciplines and describe how they are interconnected with each other.
• Apply and use Computing Science tools and techniques to solve real-world problems.
• Research and learn about new ideas and areas in Computing Science and share those ideas with others.
• Develop a personal understanding of how Computing Science affects his or her own life.
• Understand many different subject areas within Computing Science and how they are changing our understanding of the field.

Major Course Topics

• The history of computer science and early computing machines
• The basics of binary representation, Boolean logic, data encoding, encryption, and error checking
• Computational thinking, programming, and algorithm design
• The history and technology behind the internet and how it affects our world
• Computer science areas such as artificial intelligence, human-computer interaction, high performance computing, data science, robotics, and more
• Cybersecurity in a modern, interconnected world
• Other disciplines related to computer science
• Experience with basic programming concepts

Course Structure

These courses are being taught 100% online, and each module is self-paced. There may be some bumps in the road as we refine the overall course structure. Students will work at their own pace through a set of modules, with approximately one module being due each week. Material will be provided in the form of recorded videos, online tutorials, links to online resources, and discussion prompts. Assignments may also include portions which will be graded manually via Canvas or other tools.

Grading

In theory, each student begins the course with an A. As you submit work, you can either maintain your A (for good work) or chip away at it (for less adequate or incomplete work). In practice, each student starts with 0 points in the gradebook and works upward toward a final point total earned out of the possible number of points. In this course, each assignment constitutes a portion of the final grade, as detailed below:

• 80% Lectures & Quizzes
• 20% Discussions

Letter grades will be assigned following the standard scale:

• 90% - 100% → A
• 80% - 89.99% → B
• 70% - 79.99% → C
• 60% - 69.99% → D
• 00% - 59.99% → F

Late Work

Since this course is entirely online, students may work at any time and at their own pace through the modules. However, to keep everyone on track, there will be approximately two modules due each week. Each graded item in the module will have a specific due date specified. **Any assignment submitted late will have that assignment’s grade reduced by 10% of the total possible points on that project for each day it is late. Late assignments will not be accepted if they have been submitted more than 3 days after the due date, unless a special reason is provided and prior approval for an extension has been obtained before the due date.

** This penalty will be assessed automatically in the Canvas gradebook.

The following table outlines the highest possible score that a module can earn based on when it is complete

Even if a module is not submitted on time, it must still be completed before a student is allowed to begin the next module. So, students should take care not to get too far behind, as it may be very difficult to catch up.

Finally, all course work must be submitted on or before the last day of the semester in which the student is enrolled in the course in order for it to be graded on time.

If you have extenuating circumstances, please discuss them with the instructor as soon as they arise so other arrangements can be made. If you find that you are getting behind in the class, you are encouraged to speak to the instructor for options to make up missed work.

Incomplete Policy

Students should strive to complete this course in its entirety before the end of the semester in which they are enrolled. However, since retaking the course would be costly and repetitive for students, we would like to give students a chance to succeed with a little help rather than immediately fail students who are struggling.

If you are unable to complete the course in a timely manner, please contact the instructor to discuss an incomplete grade. Incomplete grades are given solely at the instructor’s discretion. See the official K-State Grading Policy for more information. In general, poor time management alone is not a sufficient reason for an incomplete grade.

Unless otherwise noted in writing on a signed Incomplete Agreement Form , the following stipulations apply to any incomplete grades given in Computational Core courses:

1. Students may receive at most two incompletes in Computational Core courses throughout their time in the program
2. Students will be given 6 calendar weeks from the end of the enrolled semester’s finals week to complete the course
3. Any modules in a future CC course which depend on incomplete work will not be accessible until the previous course is finished
4. For example, if a student is given an incomplete in CC 210, then all modules in CC 310 will be inaccessible until CC 210 is complete
5. Students understand that access to instructor and GTA assistance may be limited after the end of an academic semester due to holidays and other obligations
6. If a student fails to resolve an incomplete grade after 6 weeks, they will be assigned an ‘F’ in the course. In addition, they will be dropped from any other Computational Core courses which require the failed course as a prerequisite or corequisite.

Recommended Texts & Supplies

To participate in this course, students must have access to a modern web browser and broadband internet connection. All course materials will be provided via Canvas and Codio. Modules may also contain links to external resources for additional information, such as programming language documentation.

Subject to Change

The details in this syllabus are not set in stone. Due to the flexible nature of this class, adjustments may need to be made as the semester progresses, though they will be kept to a minimum. If any changes occur, the changes will be posted on the Canvas page for this course and emailed to all students.

Academic Honesty

Kansas State University has an Honor and Integrity System based on personal integrity, which is presumed to be sufficient assurance that, in academic matters, one’s work is performed honestly and without unauthorized assistance. Undergraduate and graduate students, by registration, acknowledge the jurisdiction of the Honor and Integrity System. The policies and procedures of the Honor and Integrity System apply to all full and part-time students enrolled in undergraduate and graduate courses on-campus, off-campus, and via distance learning. A component vital to the Honor and Integrity System is the inclusion of the Honor Pledge which applies to all assignments, examinations, or other course work undertaken by students. The Honor Pledge is implied, whether or not it is stated: “On my honor, as a student, I have neither given nor received unauthorized aid on this academic work.” A grade of XF can result from a breach of academic honesty. The F indicates failure in the course; the X indicates the reason is an Honor Pledge violation.

For this course, a violation of the Honor Pledge will result in sanctions such as a 0 on the assignment or an XF in the course, depending on severity. Actively seeking unauthorized aid, such as posting lab assignments on sites such as Chegg or StackOverflow, or asking another person to complete your work, even if unsuccessful, will result in an immediate XF in the course.

Use of AI text and code generators such as ChatGPT and GitHub Copilot in any submission for this course is strictly forbidden unless explicitly allowed by your instructor. Any unauthorized use of these tools is considered plagiarism.

We reserve the right to use various platforms that can perform automatic plagiarism detection by tracking changes made to files and comparing submitted projects against other students’ submissions and known solutions. That information may be used to determine if plagiarism has taken place.

Authorized Aid

All graded work is individual effort. You are authorized to use:

1.  course’s materials,
   

2.  direct web-links from this course
   

3.  the appropriate languages documentation (https://docs.python.org/3/  or https://docs.oracle.com/javase/ Links to an external site.)
   

4.  Email help received through  110 help email, CC - Instructors, GTAs
   

5.  Zoom/In-person help received from Instructors or GTA
   

6.  ACM help session (an on campus only resource) Most Tuesdays in EH 1116, 6:30PM. 
   

7.  Tutors from the Academic Assistance Center or provided by K-State Athletics 
   

Use of on-line solutions whether for reference or code is prohibited. Use of previous semester’s answers, whether your own or another student’s is prohibited. Use of code-completion/suggestion tool’s, other than those we have installed in the Codio editor, is prohibited.

AI Prohibited

This course assumes that all your course work will be done by you. You will not need to use artificial intelligence (AI) tools such as ChatGPT for any of the assignments. In general, for this class, you should not have an AI instrument do the writing of any portion of any assignment, just as you would not have another person do your writing for you. My aim is to keep the focus on your originality and creativity, your learning and reflection. If you do use AI for any part of any assignment, you will need to cite it fully and properly, using MLA’s AI citation guidelines. Using an AI tool to generate assignment content without proper attribution would be a violation of the K-State Honor Pledge. (from Prof. Gregory Eiselein, Coffman University Distinguished Teaching Scholar)

Standard Syllabus Statements

Students with Disabilities

At K-State it is important that every student has access to course content and the means to demonstrate course mastery. Students with disabilities may benefit from services including accommodations provided by the Student Access Center. Disabilities can include physical, learning, executive functions, and mental health. You may register at the Student Access Center or to learn more contact:

• Manhattan/Olathe/Global Campus – Student Access Center
  • accesscenter@k-state.edu
  • 785-532-6441
• K-State Salina Campus – Julie Rowe; Student Success Coordinator
  • jarowe@k-state.edu
  • 785-820-7908

Students already registered with the Student Access Center please request your Letters of Accommodation early in the semester to provide adequate time to arrange your approved academic accommodations. Once SAC approves your Letter of Accommodation it will be e-mailed to you, and your instructor(s) for this course. Please follow up with your instructor to discuss how best to implement the approved accommodations.

Expectations for Conduct

All student activities in the University, including this course, are governed by the Student Judicial Conduct Code as outlined in the Student Governing Association By Laws , Article V, Section 3, number 2. Students who engage in behavior that disrupts the learning environment may be asked to leave the class.

Mutual Respect and Inclusion in K-State Teaching & Learning Spaces

At K-State, faculty and staff are committed to creating and maintaining an inclusive and supportive learning environment for students from diverse backgrounds and perspectives. K-State courses, labs, and other virtual and physical learning spaces promote equitable opportunity to learn, participate, contribute, and succeed, regardless of age, race, color, ethnicity, nationality, genetic information, ancestry, disability, socioeconomic status, military or veteran status, immigration status, Indigenous identity, gender identity, gender expression, sexuality, religion, culture, as well as other social identities.

Faculty and staff are committed to promoting equity and believe the success of an inclusive learning environment relies on the participation, support, and understanding of all students. Students are encouraged to share their views and lived experiences as they relate to the course or their course experience, while recognizing they are doing so in a learning environment in which all are expected to engage with respect to honor the rights, safety, and dignity of others in keeping with the K-State Principles of Community .

If you feel uncomfortable because of comments or behavior encountered in this class, you may bring it to the attention of your instructor, advisors, and/or mentors. If you have questions about how to proceed with a confidential process to resolve concerns, please contact the Student Ombudsperson Office . Violations of the student code of conduct can be reported using the Code of Conduct Reporting Form . You can also report discrimination, harassment or sexual harassment , if needed.

Netiquette

Online communication is inherently different than in-person communication. When speaking in person, many times we can take advantage of the context and body language of the person speaking to better understand what the speaker means, not just what is said. This information is not present when communicating online, so we must be much more careful about what we say and how we say it in order to get our meaning across.

Here are a few general rules to help us all communicate online in this course, especially while using tools such as Canvas or Discord:

• Use a clear and meaningful subject line to announce your topic. Subject lines such as “Question” or “Problem” are not helpful. Subjects such as “Logic Question in Project 5, Part 1 in Java” or “Unexpected Exception when Opening Text File in Python” give plenty of information about your topic.
• Use only one topic per message. If you have multiple topics, post multiple messages so each one can be discussed independently.
• Be thorough, concise, and to the point. Ideally, each message should be a page or less.
• Include exact error messages, code snippets, or screenshots, as well as any previous steps taken to fix the problem. It is much easier to solve a problem when the exact error message or screenshot is provided. If we know what you’ve tried so far, we can get to the root cause of the issue more quickly.
• Consider carefully what you write before you post it. Once a message is posted, it becomes part of the permanent record of the course and can easily be found by others.
• If you are lost, don’t know an answer, or don’t understand something, speak up! Email and Canvas both allow you to send a message privately to the instructors, so other students won’t see that you asked a question. Don’t be afraid to ask questions anytime, as you can choose to do so without any fear of being identified by your fellow students.
• Class discussions are confidential. Do not share information from the course with anyone outside of the course without explicit permission.
• Do not quote entire message chains; only include the relevant parts. When replying to a previous message, only quote the relevant lines in your response.
• Do not use all caps. It makes it look like you are shouting. Use appropriate text markup (bold, italics, etc.) to highlight a point if needed.
• No feigning surprise. If someone asks a question, saying things like “I can’t believe you don’t know that!” are not helpful, and only serve to make that person feel bad.
• No “well-actually’s.” If someone makes a statement that is not entirely correct, resist the urge to offer a “well, actually…” correction, especially if it is not relevant to the discussion. If you can help solve their problem, feel free to provide correct information, but don’t post a correction just for the sake of being correct.
• Do not correct someone’s grammar or spelling. Again, it is not helpful, and only serves to make that person feel bad. If there is a genuine mistake that may affect the meaning of the post, please contact the person privately or let the instructors know privately so it can be resolved.
• Avoid subtle -isms and microaggressions. Avoid comments that could make others feel uncomfortable based on their personal identity. See the syllabus section on Diversity and Inclusion above for more information on this topic. If a comment makes you uncomfortable, please contact the instructor.
• Avoid sarcasm, flaming, advertisements, lingo, trolling, doxxing, and other bad online habits. They have no place in an academic environment. Tasteful humor is fine, but sarcasm can be misunderstood.

As a participant in course discussions, you should also strive to honor the diversity of your classmates by adhering to the K-State Principles of Community .

Discrimination, Harassment, and Sexual Harassment

Kansas State University is committed to maintaining academic, housing, and work environments that are free of discrimination, harassment, and sexual harassment. Instructors support the University’s commitment by creating a safe learning environment during this course, free of conduct that would interfere with your academic opportunities. Instructors also have a duty to report any behavior they become aware of that potentially violates the University’s policy prohibiting discrimination, harassment, and sexual harassment, as outlined by PPM 3010 .

If a student is subjected to discrimination, harassment, or sexual harassment, they are encouraged to make a non-confidential report to the University’s Office for Institutional Equity (OIE) using the online reporting form . Incident disclosure is not required to receive resources at K-State. Reports that include domestic and dating violence, sexual assault, or stalking, should be considered for reporting by the complainant to the Kansas State University Police Department or the Riley County Police Department . Reports made to law enforcement are separate from reports made to OIE. A complainant can choose to report to one or both entities. Confidential support and advocacy can be found with the K-State Center for Advocacy, Response, and Education (CARE) . Confidential mental health services can be found with Lafene Counseling and Psychological Services (CAPS) . Academic support can be found with the Office of Student Life (OSL) . OSL is a non-confidential resource. OIE also provides a comprehensive list of resources on their website. If you have questions about non-confidential and confidential resources, please contact OIE at equity@ksu.edu or (785) 532–6220.

Academic Freedom Statement

Kansas State University is a community of students, faculty, and staff who work together to discover new knowledge, create new ideas, and share the results of their scholarly inquiry with the wider public. Although new ideas or research results may be controversial or challenge established views, the health and growth of any society requires frank intellectual exchange. Academic freedom protects this type of free exchange and is thus essential to any university’s mission.

Moreover, academic freedom supports collaborative work in the pursuit of truth and the dissemination of knowledge in an environment of inquiry, respectful debate, and professionalism. Academic freedom is not limited to the classroom or to scientific and scholarly research, but extends to the life of the university as well as to larger social and political questions. It is the right and responsibility of the university community to engage with such issues.

Campus Safety

Kansas State University is committed to providing a safe teaching and learning environment for student and faculty members. In order to enhance your safety in the unlikely case of a campus emergency make sure that you know where and how to quickly exit your classroom and how to follow any emergency directives. Current Campus Emergency Information is available at the University’s Advisory webpage.

Student Resources

K-State has many resources to help contribute to student success. These resources include accommodations for academics, paying for college, student life, health and safety, and others. Check out the Student Guide to Help and Resources: One Stop Shop for more information.

Student Academic Creations

Student academic creations are subject to Kansas State University and Kansas Board of Regents Intellectual Property Policies. For courses in which students will be creating intellectual property, the K-State policy can be found at University Handbook, Appendix R: Intellectual Property Policy and Institutional Procedures (part I.E.) . These policies address ownership and use of student academic creations.

Mental Health

Your mental health and good relationships are vital to your overall well-being. Symptoms of mental health issues may include excessive sadness or worry, thoughts of death or self-harm, inability to concentrate, lack of motivation, or substance abuse. Although problems can occur anytime for anyone, you should pay extra attention to your mental health if you are feeling academic or financial stress, discrimination, or have experienced a traumatic event, such as loss of a friend or family member, sexual assault or other physical or emotional abuse.

If you are struggling with these issues, do not wait to seek assistance.

• Kansas State University Counseling and Psychological Services offers free and confidential services to assist you to meet these challenges.
• Lafene Health Center has specialized nurse practitioners to assist with mental health.
• The Office of Student Life can direct you to additional resources.
• K-State Family Center offers individual, couple, and family counseling services on a sliding fee scale.
• Center for Advocacy, Response, and Education (CARE) provides free and confidential assistance for those in our K-State community who have been victimized by violence.

For Kansas State Salina Campus:

• Kansas State Salina Counseling Services offers free and confidential services to assist you to meet these challenges.
• The Kansas State Salina Office of Student Life can direct you to additional resources.
• The Kansas State Salina Campus offers several services for students, including health services, counseling, and academic assistance.

For Global Campus/K-State Online:

• K-State Online students have free access to mental health counseling with My SSP - 24/7 support via chat and phone.
• The Office of Student Life can direct you to additional resources.

University Excused Absences

K-State has a University Excused Absence policy (Section F62) . Class absence(s) will be handled between the instructor and the student unless there are other university offices involved. For university excused absences, instructors shall provide the student the opportunity to make up missed assignments, activities, and/or attendance specific points that contribute to the course grade, unless they decide to excuse those missed assignments from the student’s course grade. Please see the policy for a complete list of university excused absences and how to obtain one. Students are encouraged to contact their instructor regarding their absences.

Copyright Notice

© The materials in this online course fall under the protection of all intellectual property, copyright and trademark laws of the U.S. The digital materials included here come with the legal permissions and releases of the copyright holders. These course materials should be used for educational purposes only; the contents should not be distributed electronically or otherwise beyond the confines of this online course. The URLs listed here do not suggest endorsement of either the site owners or the contents found at the sites. Likewise, mentioned brands (products and services) do not suggest endorsement. Students own copyright to what they create.

Plagiarism Policy

Resources

• K-State Honor & Integrity System

Video Script

“On my honor, as a student, I have neither given nor received unauthorized aid on this academic work.” - K-State Honor Pledge

Plagiarism is a very serious concern in this course, and something that we do not take lightly. Computer programs and code are especially easy targets for plagiarism due to how easy it is to copy and manipulate code in such a way that it is unrecognizable as the original source but still performs correctly.

At its core, plagiarism is taking someone else’s work and passing it off as your own without giving appropriate credit to the original source. As a student at K-State, you are bound by the K-State Honor Code not to accept any unauthorized aid, and this includes plagiarized code.

When it comes to plagiarism in computer code, there is a fine line between using resources appropriately and copying code. In this program, you should strive to avoid plagiarism issues by doing the following:

1. Do not search for or use any complete solutions to projects in this course found online or from fellow students.
2. Small portions of code may be used or adapted from an online source with proper citation. To cite a piece of code, include a code comment section above it that contains the original source URL and a description of why it was used.

In general, copying or adapting small pieces of code to perform auxiliary functions in the assignment is permitted. Copying or adapting code that is the general goal of the assignment should be avoided. For example, if the assignment is to create a bubble sort algorithm, you should write the algorithm from scratch yourself since that is the goal of the assignment. If the assignment is to create a program for displaying data that you feel should be sorted, you may choose to adapt an existing sorting algorithm for your needs (or use one from a library).

If you aren’t sure about whether it is OK to use an online resource or piece of code in this course, please contact the instructors using the course discussion forums or help email address. You will not get in trouble for asking, and it will help you determine what the best course of action is. Plagiarism can really only occur when you submit the assignment for grading, so you are welcome to ask for clarification or a judgement on whether a particular usage is acceptable at any time before you submit the assignment.

Codio has features that will compare your submissions against those of your fellow students. Any submissions with a high degree of similarity may be subjected to additional scrutiny by the instructors to determine if plagiarism has occurred.

In this course, any violation of the K-State Honor Code will result in a 0 on that assignment and a report made to the K-State Honor Council. A second violation will result in an XF in this course, as well as any additional sanctions imposed by the K-State Honor Council.

For more information on the K-State Honor & Integrity system, please visit their website , which is linked in the resources section below this video.