Lindenwood University



Prospective Students


Thank you for considering studying Computer Science at Lindenwood University. If you are here, you may find yourself asking questions; some of the more common ones include (click any question to see a brief answer):
Answering this question is often best done by first giving examples of things that are not Computer Science:
    • Designing (or playing) computer games.
    • Using Microsoft Office, PowerPoint, Excel, ..., or any other pre-packaged software
    • Using Microsoft Windows, Mac OS/X, or any other operating system
    • Searching and successful browsing of the Internet
    • Mastering basic HTML to build simple web pages
Note that all of the above represent applications of using computers, while Computer Science is about the design and building of computers and software. Items that are (respectively) related to the above bullet list and are representative of topics found in Computer Science include:
    • Writing the software for a computer game, or even designing the internal workings of a gaming system.
    • Actually building applications like Microsoft Office, PowerPoint, Excel, etc.
    • Understanding exactly how an operating system works, and being able to write components of an operating system yourself.
    • Understanding how data is transferred across the Internet and how a search engine actually works.
    • Building dynamic web pages with efficient scripting algorithms to fully utilize the power of the underlying computing systems.

If you have always found yourself looking at gadgets and fighting the urge to open them up to see how they work, you probably have the motivation to become a computer scientist. Furthermore, if you actually did take the gadget apart, got an idea of how it worked, actually managed to put it back together successfully, and then said to yourself "wow, that was fun, and I learned something" ... you are very likely to enjoy Computer Science.

However, in the modern world, personal enjoyment of a subject area may not be enough to justify the cost of a college education. Fortunately, graduates with a Computer Science degree usually find degree related work fairly quickly after graduation. Perhaps more importantly, Computer Science related careers have been consistently rated among both the best compensated and most satisfying over the past several decades. In other words, a Computer Science degree is likely to pay dividends to our graduates for essentially their entire career.

At LU, we offer three different degrees:
    • Bachelor of Science Computer Science This degree is best suited for individuals who are looking to earn a degree that will prepare them to enter the job market with a strong technical and scientific background. The degree requires significant coursework in Mathematics and Physics. Students considering graduate studies in Computer Science should choose this degree.
    • Bachelor of Arts Computer Science This degree is best suited for individuals who are interested in Computer Science and at least one other discipline. Most BA students also earn a minor (or even a second major) in another discipline. To help accommodate this, the degree requires slightly less Mathematics, Physics, and Computer Science elective coursework.
    • Bachelor of Science Computer Information Systems This degree is best suited for the student who wishes to enter the job market with a significant background in Business. Students earning this degree take a significant number of Business related courses (such as Accounting) in lieu of the Mathematics and Physics requirements of the other Computer Science degrees.
For more information on any of these degrees, click here.

This is a question that is asked by almost every freshmen Computer Science major, but hardly given a second thought by any students graduating in Computer Science. Essentially, the answer boils down to the fact that computers are tools of logic, and mathematics is, in a sense, the core language of logic. Since we communicate with computers in a language of logic, it only makes sense to study mathematics as well.

In terms of computer programming, mathematical models underpin essentially every program that has ever been coded. For example, there is a very complex mathematical model behind Google's search engine; without knowing linear algebra and statistics, the algorithms underlying that search engine would never have been built. Furthermore, a mathematical analysis of programs can often succinctly express the correctness of a program or even the efficiency of a program. As an example, consider looking up a word in a dictionary; you could either start reading the dictionary from page one (even if you were trying to look up "xylophone") and reading every word on every page until you found your word, or you could do something "smarter". Mathematical analysis can actually prove that the first method is (hopefully) worse than the "smarter" method.

So, one can quickly see that mathematics is the underpinnings of Computer Science. Without a mathematical background, communicating with computers would be immensely confusing and we would have little understanding of what "good" communication would be.

Computer Science is viewed as one of the more challenging majors available on any campus across the United States, and Lindenwood is not an exception. There is literally an entire body of contemporary research dedicated into determining why this is the case, and generally two conclusions have been reached:
  1. Students who are weak in mathematics tend to be weak in programming and therefore weak in Computer Science (see the above question regarding mathematics to see why this is an important point).
  2. Students tend to be unprepared for the constructive nature of the Computer Science discipline. In terms of coursework, this means that literally every topic discussed in any one class requires complete mastery of all previous work in the class. In other words, once you fall behind in a Computer Science class, your workload to catch up will double on an almost daily basis, and many students do not realize this until it is too late to recover. In most other disciplines this is not the case; for example, in mathematics, failure to master a particular topic might not mean you will not be able to understand the next one presented ... but in Computer Science, failure to master a topic is guaranteed to cause tremendous trouble with the next topic covered.
It is often said of Computer Science that "if it was easy, everyone would do it!", meaning that the job market would be saturated with computer scientists if the discipline was actually easy by nature. In fact, about a decade ago, you may recall a trend in outsourcing technology jobs to other countries with cheaper labor costs (and employees with correspondingly weaker skills). These outsourced positions have since come back to the United States, as the resulting quality of product was so low that it had to be (in some cases completely) rebuilt here in the United States by properly skilled computer scientists. This (among other reasons) is why there are so many available jobs in the technology field; but why are there so few people available to fill them? Simply put, the underlying Computer Science knowledge is challenging enough to learn that many students opt for a different path through college (that might well lead to interesting jobs in other disciplines), despite the almost guaranteed payoff upon graduation with a Computer Science degree.
The answer to this question could literally go on almost interminably. With that in mind, here is a list of example programs that have been used in classes recently, broken down by type:
    • Databases: Airline Reservation System, Textbook Ordering System
    • Games: Breakout, Canyon Bomber, Hangman, Criminal Justice System Explorer
    • Multimedia: Image Manipulations, Sound Manipulations
    • Network Applications: Web Browser, Web Server, Chatroom
    • Systems: Microcode Simulator, Job Scheduler
A wide range of programming/scripting languages/libraries has been used in developing such programs, including (but certainly not limited to):
    • C
    • C++
    • HTML
    • Java
    • JavaScript
    • Jython
    • PHP
    • Python
    • SQL
    • Visual Basic

You may find answers to other questions pertaining to Computer Science at Lindenwood by browsing through our website. Should you still have any unanswered questions regarding Computer Science at Lindenwood University, please fee to email us.




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