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Essays on Computer Science

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The Ethics of Social Media: The Exploitation of User Data by Facebook

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My Motivation to Pursue Higher Education in Computer Science in Germany

Motivation letter for computer science scholarship, what motivates me to do my masters in computer science at florida state university, the eniac project: its significance in computer science and society, my goal to pursue a career in computer science and engineering, how the movie hackers got me interested in computer science, personal experience in the computer science education, computer science - a stepping stone to your career, why i have decided to apply for the master of computer science program at colorado state university, how mathematics curiosity has brought me to computer science, the role of experimentation in computer science, computer systems and architecture, my fascination for science and technology, my desire to continue learning computer engineering, my goals of becoming a computer scientist for nasa, the role of computers in financial accounting, a research of contemporary issues, opportunities, trends, challenges and innovations within ict industry connected with google company, computing exponentially faster: implementing a non-deterministic universal turing machine using dna, the types of programming languages and the language of a game engine, the possibility of machines to be able to think and feel.

Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to practical disciplines (including the design and implementation of hardware and software).

The four areas of computer science are: theory of computation, algorithms and data structures, programming methodology and languages, and computer elements and architecture. CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, human-computer interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.

Alan Turing (the “father of modern computing”), Tim Berners-Lee (inventor of the World Wide Web), John McCarthy, Grace Hopper, Julian Assange, Steve Wozniak, etc.

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• Artificial Intelligence

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How to Write the “Why Computer Science?” Essay

What’s covered:, what is the purpose of the “why computer science” essay, elements of a good computer science essay, computer science essay example, where to get your essay edited.

You will encounter many essay prompts as you start applying to schools, but if you are intent on majoring in computer science or a related field, you will come across the “ Why Computer Science? ” essay archetype. It’s important that you know the importance behind this prompt and what constitutes a good response in order to make your essay stand out.

For more information on writing essays, check out CollegeVine’s extensive essay guides that include everything from general tips, to essay examples, to essay breakdowns that will help you write the essays for over 100 schools.

Colleges ask you to write a “ Why Computer Science? ” essay so you may communicate your passion for computer science, and demonstrate how it aligns with your personal and professional goals. Admissions committees want to see that you have a deep interest and commitment to the field, and that you have a vision for how a degree in computer science will propel your future aspirations.

The essay provides an opportunity to distinguish yourself from other applicants. It’s your chance to showcase your understanding of the discipline, your experiences that sparked or deepened your interest in the field, and your ambitions for future study and career. You can detail how a computer science degree will equip you with the skills and knowledge you need to make a meaningful contribution in this rapidly evolving field.

A well-crafted “ Why Computer Science? ” essay not only convinces the admissions committee of your enthusiasm and commitment to computer science, but also provides a glimpse of your ability to think critically, solve problems, and communicate effectively—essential skills for a  computer scientist.

The essay also gives you an opportunity to demonstrate your understanding of the specific computer science program at the college or university you are applying to. You can discuss how the program’s resources, faculty, curriculum, and culture align with your academic interests and career goals. A strong “ Why Computer Science? ” essay shows that you have done your research, and that you are applying to the program not just because you want to study computer science, but because you believe that this particular program is the best fit for you.

Writing an effective “ Why Computer Science ?” essay often requires a blend of two popular college essay archetypes: “ Why This Major? ” and “ Why This College? “.

Explain “Why This Major?”

The “ Why This Major? ” essay is an opportunity for you to dig deep into your motivations and passions for studying Computer Science. It’s about sharing your ‘origin story’ of how your interest in Computer Science took root and blossomed. This part of your essay could recount an early experience with coding, a compelling Computer Science class you took, or a personal project that sparked your fascination.

What was the journey that led you to this major? Was it a particular incident, or did your interest evolve over time? Did you participate in related activities, like coding clubs, online courses, hackathons, or internships?

Importantly, this essay should also shed light on your future aspirations. How does your interest in Computer Science connect to your career goals? What kind of problems do you hope to solve with your degree?

The key for a strong “ Why This Major? ” essay is to make the reader understand your connection to the subject. This is done through explaining your fascination and love for computer science. What emotions do you feel when you are coding? How does it make you feel when you figure out the solution after hours of trying? What aspects of your personality shine when you are coding? 

By addressing these questions, you can effectively demonstrate a deep, personal, and genuine connection with the major.

Emphasize “Why This College?”

The “ Why This College? ” component of the essay demonstrates your understanding of the specific university and its Computer Science program. This is where you show that you’ve done your homework about the college, and you know what resources it has to support your academic journey.

What unique opportunities does the university offer for Computer Science students? Are there particular courses, professors, research opportunities, or clubs that align with your interests? Perhaps there’s a study abroad program or an industry partnership that could give you a unique learning experience. Maybe the university has a particular teaching methodology that resonates with you.

Also, think about the larger university community. What aspects of the campus culture, community, location, or extracurricular opportunities enhance your interest in this college? Remember, this is not about general praises but about specific features that align with your goals. How will these resources and opportunities help you explore your interests further and achieve your career goals? How does the university’s vision and mission resonate with your own values and career aspirations?

It’s important when discussing the school’s resources that you always draw a connection between the opportunity and yourself. For example, don’t tell us you want to work with X professor because of their work pioneering regenerative AI. Go a step further and say because of your goal to develop AI surgeons for remote communities, learning how to strengthen AI feedback loops from X professor would bring you one step closer to achieving your dream.

By articulating your thoughts on these aspects, you demonstrate a strong alignment between the college and your academic goals, enhancing your appeal as a prospective student.

Demonstrate a Deep Understanding of Computer Science

As with a traditional “ Why This Major? ” essay, you must exhibit a deep and clear understanding of computer science. Discuss specific areas within the field that pique your interest and why. This could range from artificial intelligence to software development, or from data science to cybersecurity. 

What’s important is to not just boast and say “ I have a strong grasp on cybersecurity ”, but instead use your knowledge to show your readers your passion: “ After being bombarded with cyber attack after cyber attack, I explained to my grandparents the concept of end-to-end encryption and how phishing was not the same as a peaceful afternoon on a lake. ”

Make it Fun!

Students make the mistake of thinking their college essays have to be serious and hyper-professional. While you don’t want to be throwing around slang and want to present yourself in a positive light, you shouldn’t feel like you’re not allowed to have fun with your essay. Let your personality shine and crack a few jokes.

You can, and should, also get creative with your essay. A great way to do this in a computer science essay is to incorporate lines of code or write the essay like you are writing out code. 

Now we will go over a real “ Why Computer Science? ” essay a student submitted and explore what the essay did well, and where there is room for improvement.

Please note: Looking at examples of real essays students have submitted to colleges can be very beneficial to get inspiration for your essays. You should never copy or plagiarize from these examples when writing your own essays. Colleges can tell when an essay isn’t genuine and will not view students favorably if they plagiarized.

I held my breath and hit RUN. Yes! A plump white cat jumped out and began to catch the falling pizzas. Although my Fat Cat project seems simple now, it was the beginning of an enthusiastic passion for computer science. Four years and thousands of hours of programming later, that passion has grown into an intense desire to explore how computer science can serve society. Every day, surrounded by technology that can recognize my face and recommend scarily-specific ads, I’m reminded of Uncle Ben’s advice to a young Spiderman: “with great power comes great responsibility”. Likewise, the need to ensure digital equality has skyrocketed with AI’s far-reaching presence in society; and I believe that digital fairness starts with equality in education.

The unique use of threads at the College of Computing perfectly matches my interests in AI and its potential use in education; the path of combined threads on Intelligence and People gives me the rare opportunity to delve deep into both areas. I’m particularly intrigued by the rich sets of both knowledge-based and data-driven intelligence courses, as I believe AI should not only show correlation of events, but also provide insight for why they occur.

In my four years as an enthusiastic online English tutor, I’ve worked hard to help students overcome both financial and technological obstacles in hopes of bringing quality education to people from diverse backgrounds. For this reason, I’m extremely excited by the many courses in the People thread that focus on education and human-centered technology. I’d love to explore how to integrate AI technology into the teaching process to make education more available, affordable, and effective for people everywhere. And with the innumerable opportunities that Georgia Tech has to offer, I know that I will be able to go further here than anywhere else.

What the Essay Did Well 

This essay perfectly accomplishes the two key parts of a “ Why Computer Science? ” essay: answering “ Why This Major? ” and “ Why This College? ”. Not to mention, we get a lot of insight into this student and what they care about beyond computer science, and a fun hook at the beginning.

Starting with the “ Why This Major? ” aspect of the response, this essay demonstrates what got the student into computer science, why they are passionate about the subject, and what their goals are. They show us their introduction to the world of CS with an engaging hook: “I held my breath and hit RUN. Yes! A plump white cat jumped out and began to catch the falling pizzas. ” We then see this is a core passion because they spent “ Four years and thousands of hours ,” coding.

The student shows us why they care about AI with the sentence, “ Every day, surrounded by technology that can recognize my face and recommend scarily-specific ads ,” which makes the topic personal by demonstrating their fear at AI’s capabilities. But, rather than let panic overwhelm them, the student calls upon Spiderman and tells us their goal of establishing digital equality through education. This provides a great basis for the rest of the essay, as it thoroughly explains the students motivations and goals, and demonstrates their appreciation for interdisciplinary topics.

Then, the essay shifts into answering “ Why This College? ”, which it does very well by honing in on a unique facet of Georgia Tech’s College of Computing: threads. This is a great example of how to provide depth to the school resources you mention. The student describes the two threads and not only why the combination is important to them, but how their previous experiences (i.e. online English tutor) correlate to the values of the thread: “ For this reason, I’m extremely excited by the many courses in the People thread that focus on education and human-centered technology. ”

What Could Be Improved

This essay does a good job covering the basics of the prompt, but it could be elevated with more nuance and detail. The biggest thing missing from this essay is a strong core to tie everything together. What do we mean by that? We want to see a common theme, anecdote, or motivation that is weaved throughout the entire essay to connect everything. Take the Spiderman quote for example. If this was expanded, it could have been the perfect core for this essay.

Underlying this student’s interest in AI is a passion for social justice, so they could have used the quote about power and responsibility to talk about existing injustices with AI and how once they have the power to create AI they will act responsibly and help affected communities. They are clearly passionate about equality of education, but there is a disconnect between education and AI that comes from a lack of detail. To strengthen the core of the essay, this student needs to include real-world examples of how AI is fostering inequities in education. This takes their essay from theoretical to practical.

Whether you’re a seasoned writer or a novice trying your hand at college application essays, the review and editing process is crucial. A fresh set of eyes can provide valuable insights into the clarity, coherence, and impact of your writing. Our free Peer Essay Review tool offers a unique platform to get your essay reviewed by another student. Peer reviews can often uncover gaps, provide new insights or enhance the clarity of your essay, making your arguments more compelling. The best part? You can return the favor by reviewing other students’ essays, which is a great way to hone your own writing and critical thinking skills.

For a more professional touch, consider getting your essay reviewed by a college admissions expert . CollegeVine advisors have years of experience helping students refine their writing and successfully apply to top-tier schools. They can provide specific advice on how to showcase your strengths, address any weaknesses, and generally present yourself in the best possible light.

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Essays in computing science

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Academic Writing for Computer Science Richard Zanibbi Rochester Institute of Technology (NY, USA) Oct. 2005, Revised: Sept. 2007, Aug. 2008, May 2014, June 2023

The purpose of this document is to summarize my views on academic writing for Computer Science. Comments are welcome ([email protected]). For those interested in more detailed advice, including how to structure a paper and how to use math, pseudo code and figures effectively, I recommend consulting Zobel's excellent book on this topic . As an aside, for examples of excellent essay writing on Computer Science topics, see the (particularly early) work of Paul Graham . Writing Clearly A reader's attention is a scarce resource that written documents need to make the best possible use of. Writing clearly allows you to increase the amount of information that the reader can take in within a fixed (let's face it: usually short) amount of time. Some of the main issues to address are the following: Have someone else read your document , even if only quickly. We're often surprised by what is unclear in our writing when we show it to others, and this is a very efficient way to identify possible weaknesses in the document. Know who your reader, the audience, is. For a course paper, this is the instructor/markers. For research, this is researchers in a research area (e.g. AI, Expert Systems, or Software Engineering), etc. Tell the reader what the topic of the document is, in as specific terms as possible ; this lets them make use of what they already know. Organize the document clearly into sub-topics, issues, or problems , with section headings (titles for sections) to reflect this, but within reason. Too many headings can actually slow a reader down. Tell the reader about the organization of topics in the document , and order the sub-topics in a way that makes sense (providing a good "flow" of ideas). A good academic paper is not a mystery novel; its main function is to explain clearly, not to entertain, inspire, or awe. Insure that your text is as technically correct and complete as possible. This means that explanations and examples are correct and consistent with one another, data such as experimental results are presented in their entirety, accurately and without bias, and that important relationships between concepts are made explicit. Any additional information required for a complete understanding is indicated through citations of appropriate references. What references are needed depends upon who we are writing for (for example: citing documents explaining basic automata or complexity theory is usually a waste of time for Computer Science students). Use the clearest and simplest language possible. Academic writing should be formal and use appropriate terminology, but a clear explanation is more important than always using the formal term for a concept. For example, if a children's game is a good analogy for a concept you are presenting, it is probably better to talk about "the children in the game" rather than "the set of players employing mixed strategies in CG-A" to introduce the analogy. Use grammatically correct and stylistically consistent prose. I strongly recommend the famous book "The Elements of Style" by Strunk and White , which discusses writing clearly and correctly, and is quite short and cheap. Here is a (silly) example of stylistically inconsistent prose: "The negative correlation of increased ice cream prices with child happiness has been well documented by Vitiello and Natarajan [3,6,10,17]. I really wish they would keep prices down, because I really love chocolate ice cream (yummy!) and graduate school doesn't pay that much (you've read Ph.D. comics, right?)."

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Essays In Computing Science

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Ilias Bergstrom

How diverse are the ways that programming is done? While a variety of accounts exist, each appears in isolation, neither framed in terms of a distinct practice, nor as one of many such practices. In this work we explore accounts spanning software engineering, bricolage/tinkering, sketching, live coding, code-bending, and hacking. These practices of programming are analyzed in relation to ongoing research, and in particular HCI’s ‘practice turn’, offering connections to accounts of practice in other contexts than programming. The conceptualization of practice helps to interpret recent interest in program code as craft material, and also offers potential to inform programming education, tools and work as well as future research.

This dissertation is an ethnographic study, accomplished through semi-structured interviews and participant observation, of the cultural world of third party Apple software developers who use Apple’s Cocoa libraries to create apps. It answers the questions: what motivates Apple developers’ devotion to Cocoa technology, and why do they believe it is a superior programming environment? What does it mean to be a “good” Cocoa programmer, technically and morally, in the Cocoa community of practice, and how do people become one? I argue that in this culture, ideologies, normative values, identities, affects, and practices interact with each other and with Cocoa technology in a seamless web, which I call a “techno-cultural frame.” This frame includes the construction of a developer’s identity as a vocational craftsman, and a utopian vision of software being developed by millions of small-scale freelance developers, or “indies,” rather than corporations. This artisanal production is made possible by the productivity gains of Cocoa technology, which ironically makes indies dependent on Apple for tools. This contradiction is reconciled through quasi-religious narratives about Apple and Steve Jobs, which enrolls developers into seeing themselves as partners in a shared mission with Apple to empower users with technology. Although Cocoa helps make software production easier, it is not a deskilling technology but requires extensive learning, because its design heavily incorporates patterns unfamiliar to many programmers. These concepts can only be understood holistically after learning has been achieved, which means that learners must undergo a process of conversion in their mindset. This involves learning to trust that Cocoa will benefit developers before they fully understand it. Such technical and normative lessons occur at sites where Cocoa is taught, such as the training company Big Nerd Ranch. Sharing of technical knowledge and normative practices also occurs in the Cocoa community, online through blog posts, at local club meetings, and at conferences such as Apple’s WWDC, which help to enroll developers into the Cocoa techno-cultural frame. Apple’s relationship with developers is symbiotic, but asymmetrical, yet despite Apple’s coercive power, members of the Cocoa community can influence Apple’s policies.

Dariusz Jemielniak

The paper discusses the issue of time slips in software development. Increasing time sacrifices toward work constitutes an important part of modern organizational environment. In fact, the reign over time is a crucial element in controlling the labor process. Yet a lack of cultural studies covering different approaches to this issue remains—particularly those focusing on high-skilled salaried workers. This article is a small attempt to fill this gap, based on an analysis of unstructured qualitative interviews with high-tech professionals from a B2B software company. It focuses on the issue of timing in IT projects, as perceived by software engineers. The findings indicate that managerial interruptions in work play an important part in the social construction of delays. However, interruptions from peer software engineers are not perceived as disruptive. This leads to the conclusion that time is used in a symbolic way, both for organizational domination and solidarity rituals. The use of time as a symbolic currency in knowledge-work rites is presented as often influencing the very process of labor and schedules. It is revealed to be the dominant evaluation factor, replacing the officially used measures, such as efficiency, or quality.

Bedir Tekinerdogan

Abstract: To grasp the essence of software engineering and understand its inherent problems, this paper provides a thorough and critical analysis of software engineering from a broad perspective. To this aim, a problem solving perspective is adopted and software engineering is analyzed and compared with the mature problem solving disciplines of philosophy and the traditional engineering disciplines such as electrical engineering, mechanical engineering, civil engineering and chemical engineering.

AI & Society

Xin Wei Sha

About 20 years ago, the ecology of media art practices proliferated in two domains: those that attached themselves to high technology labs or companies likeXerox PARC, and those that took advantage of personal computing to form collectives only loosely coupled to academic institutions or disciplines. In this essay, I closely examine the diverse epistemic cultures and diverse technical, political, and generational interests in such ‘‘cyber-anarchist’’ networks. I sketch the economy of knowledge in recent media arts and technology communities of practice in the wake of Open Source. I use as my lens the experience of creating a responsive media space called theTGarden, with a collective that gathered more than 26artists and engineers from 11 institutions and 7 nations.

Helen Grady

This paper explores how assigning software developers the identity of “engineers” metes out specific assumptions about IT projects. To this end, the paper describes an alternative metaphor of programming as art, which is commonly used by the programmers interviewed. In addition, the discussion draws conclusions from the discrepancies between the two views as well as from the proposed metaphor, explaining organizational reluctance to aesthetical vocabulary. This paper discusses occupational identity—emphasizing the identity of programmers—using qualitative research methods. As such, it enriches the literature currently available on this profession.

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College of Arts & Sciences

Integrated Writing in Computer Science

In developing the integrated-writing requirement in computer science, the faculty identified five guiding principles.  First, we wanted the requirement to focus on the form of writing most useful for computing professionals with four-year degrees.  Second, we wanted the integrated-writing requirement to support the department’s undergraduate learning goals.  Third, to comply with the university’s requirements for integrated writing, we had to ensure that all majors would complete the requirement in the same manner.  Fourth, we wanted the learning and practice of integrated writing to span multiple courses and years.  Fifth, we wanted to reinforce and expand a student’s exposure to writing over multiple courses.

The integrated-writing requirement primarily supports three of the department’s high-level learning goals .  Students should understand “how theoretical underpinnings of the discipline influence practice.”  They should deploy “appropriate theory, practices, and tools for the specification, design, implementation, and maintenance as well as the evaluation of computer-based systems.”  Finally, students should communicate “scientific understanding in oral and written forms.”  In the following paragraphs, we connect the elements of the integrated-writing requirement to these learning goals.

In computer science, the three most important forms of writing are technical writing, academic writing, and professional writing.  While all of these forms are important for computing professionals, technical writing is the form that all majors must learn and practice, as technical writing is the form of writing that computing professionals with a four-year degree will use most.  Note that there are opportunities for students to learn and practice the other two forms of writing.  For example, all majors have the option of writing a senior thesis, which gives them instruction on academic writing.

To implement the integrated writing requirement, the faculty identified five required classes that are common to all students pursuing the Bachelor of Science (BS) and Bachelor of Arts (AB) degrees and that are most appropriate for technical writing assignments:

• Computer Science II (COSC-052)
• Mathematical Methods for Computer Science (COSC-030)
• Advanced Programming (COSC-150)
• Data Structures (COSC-160)
• Introduction to Algorithms (COSC-240)

These courses span three of the four years that students pursue their degree.  Students normally take Computer Science I and Mathematical Methods for Computer Science in the spring semester of their first year.  They take Advanced Programming and Data Structures in their sophomore year.  They take Introduction to Algorithms in their third or fourth year.

Additionally, we can group these five courses into two categories: courses in which students learn to write formal algorithms and proofs and courses in which students learn to write software requirements, designs, and documentation.  Mathematical Methods for Computer Science and Introduction to Algorithms form the first category, with Computer Science II and Advanced Programming forming the second.  Data Structures falls into both categories.

Our implementation supports three important learning goals.  Students learn two main forms of technical writing.  They learn how to write formal proofs and formal algorithms.  They also learn how to write documentation for software as well as designs for software systems.  Learning about these forms of technical writing is most appropriate for students pursuing a four-year degree in computer science, most of whom will join companies in technical roles as software developers, product managers, and software engineers.

Computer Science Essay Topics

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Published on: May 5, 2023

Last updated on: Jan 30, 2024

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One of the biggest challenges students face when it comes to writing an essay is choosing the right topic. 

This is especially true for computer science students, who often struggle to find a topic that is relevant to the subject.

That's where our blog comes in!

We have crafted a list of over 160 computer science essay topics to help students find inspiration. Whether you're looking to write an impressive essay or simply looking for topic suggestions, we have got you covered.

So, let's get started!

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Computer Science Essay - Overview

A computer science essay is a written piece that explores various topics related to computer science. These include technical and complex topics, like software development and artificial intelligence. They can also explore more general topics, like the history and future of technology.

In most cases, computer science essays are written by students as part of their coursework or academic assignments.

Computer science essays can take many forms, such as research papers, argumentative essays, or even creative writing pieces. 

Regardless of the format, a well-written computer science essay should be informative, engaging, and well-supported by evidence and research.

Now that we understand the purpose of it, let's explore some of the most popular and interesting topics within this field. 

In the following sections, we will dive into over 160 computer science essay topics to inspire your next writing project.

Computer Science Essay Topics For High School Students

• How Artificial Intelligence is Revolutionizing the Gaming Industry
• The Ethics of Autonomous Vehicles: Who is Responsible for Accidents?
• The Role of Computer Science in Modern Healthcare
• The Benefits and Drawbacks of Artificial Intelligence
• The Future of Cybersecurity: Challenges and Opportunities
• How Virtual Reality is Changing the Way We Learn
• The Ethics of Autonomous Vehicles
• The Role of Big Data in Modern Business
• The Pros and Cons of Cloud Computing
• The Implications of Blockchain Technology

Computer Science Essay Topics For Middle School Students

• How Computers Work: An Introduction to Hardware and Software
• The Evolution of Video Games: From Pong to Virtual Reality
• Internet Safety: Tips for Staying Safe Online
• How Search Engines Work: Understanding Google and Bing
• Coding Basics: An Introduction to HTML and CSS
• The Future of Technology: What Will We See in the Next 10 Years?
• The Power of Social Media: How it Impacts Our Lives
• The Ethics of Technology: The Pros and Cons of Social Media
• The Science of Cryptography: How Messages are Secured
• Robots and Artificial Intelligence: What Are They and How Do They Work?

Computer Science Essay Topics For College Students

• The Role of Machine Learning in Business
• Cybersecurity and Data Privacy in the Digital Age
• The Impact of Social Media on Political Campaigns
• The Ethics of Artificial Intelligence and Autonomous Systems
• The Future of Cloud Computing and Cloud Storage
• The Use of Blockchain Technology in Financial Services
• The Integration of IoT in Smart Homes and Smart Cities
• The Advancements and Challenges of Quantum Computing
• The Pros and Cons of Open Source Software
• The Impact of Technology on the Job Market: Opportunities and Threats

Computer Science Essay Topics For University Students

• The Application of Machine Learning and Deep Learning in Natural Language Processing
• The Future of Quantum Computing: Challenges and Prospects
• The Impact of Artificial Intelligence on the Labor Market: An Empirical Study
• The Ethical Implications of Autonomous Systems and Robotics
• The Role of Data Science in Financial Risk Management
• Blockchain and Smart Contracts: Applications and Limitations
• The Security Challenges of Cloud Computing: A Comparative Analysis
• The Prospects of Cognitive Computing and its Implications for Business Intelligence
• The Integration of IoT and Edge Computing in Smart City Development
• The Relationship between Cybersecurity and National Security: A Theoretical and Empirical Study.

 Research Paper Topics in Computer Science

• Artificial Intelligence in Cybersecurity: Advancements and Limitations
• Social Media and Mental Health: Implications for Research and Practice
• Blockchain Implementation in Supply Chain Management: A Comparative Study
• Natural Language Processing: Trends, Challenges, and Future Directions
• Edge Computing in IoT: Opportunities and Challenges
• Data Analytics in Healthcare Decision Making: An Empirical Study
• Virtual Reality in Education and Training: Opportunities and Challenges
• Cloud Computing in Developing Countries: Opportunities and Challenges
• Security Risks of Smart Homes and IoT Devices: A Comparative Analysis
• Artificial Intelligence and the Legal Profession: Challenges and Opportunities

Computer Science Essay Topics On Emerging Technologies

• 5G Networks: Trends, Applications, and Challenges
• Augmented Reality in Marketing and Advertising: Opportunities and Challenges
• Quantum Computing in Drug Discovery: A Review of Current Research
• Autonomous Vehicles: Advancements and Challenges in Implementation
• Synthetic Biology: Current Developments and Future Prospects
• Brain-Computer Interfaces: Opportunities and Challenges in Implementation
• Robotics in Healthcare: Trends, Challenges, and Future Directions
• Wearable Technology: Applications and Limitations in Healthcare
• Virtual Assistants: Opportunities and Limitations in Daily Life
• Biometric Authentication: Advancements and Challenges in Implementation

Computer Science Essay Topics On Solving Problems

• Using Artificial Intelligence to solve traffic congestion problems
• Implementing Machine Learning to predict and prevent cyber-attacks
• Developing a Computer Vision system to detect early-stage skin cancer
• Using Data Analytics to improve energy efficiency in buildings
• Implementing an IoT-based solution for monitoring and reducing air pollution
• Developing a software system for optimizing supply chain management
• Using Blockchain to secure and manage digital identities
• Implementing a Smart Grid system for energy distribution and management
• Developing a mobile application for emergency response and disaster management
• Using Robotics to automate and optimize warehouse operations.

Computer Science Argumentative Essay Topics

• Should the development of autonomous weapons be banned?
• Is social media addiction a mental health disorder?
• Should governments regulate the use of artificial intelligence in decision-making?
• Is online privacy a fundamental human right?
• Should companies be held liable for data breaches?
• Is net neutrality necessary for a free and open internet?
• Should software piracy be treated as a criminal offense?
• Should online hate speech be regulated by law?
• Is open-source software better than proprietary software?
• Should governments use surveillance technology to prevent crime?

Computer Science Persuasive Essay Topics

• Should coding be a mandatory subject in schools?
• Is artificial intelligence a threat to human jobs?
• Should the use of drones for commercial purposes be regulated?
• Is encryption important for online security?
• Should governments provide free Wi-Fi in public spaces?
• Is cyberbullying a serious problem in schools?
• Should social media platforms regulate hate speech?
• Is online voting a viable option for elections?
• Should algorithms be used in decision-making processes in the criminal justice system?
• Should governments invest in space exploration and colonization?

 Current Hot Topics in Computer Science

• The ethical implications of facial recognition technology
• The role of blockchain in data security and privacy
• The future of quantum computing and its potential applications
• The challenges and opportunities of implementing machine learning in healthcare
• The impact of big data on business operations and decision-making
• The potential of augmented and virtual reality in education and training
• The role of computer science in addressing climate change and sustainability
• The social and cultural implications of social media algorithms
• The intersection of computer science and neuroscience in developing artificial intelligence

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Controversial Topics in Computer Science

• The ethics of Artificial Intelligence
• The dark side of the Internet
• The impact of social media on mental health
• The role of technology in political campaigns
• The ethics of autonomous vehicles
• The responsibility of tech companies in preventing cyberbullying
• The use of facial recognition technology by law enforcement
• The impact of automation on employment
• The future of privacy in a digital world
• The dangers of deep face technology

Good Essay Topics on Computer Science and Systems

• The history of computers and computing
• The impact of computers on society
• The evolution of computer hardware and software
• The role of computers in education
• The future of quantum computing
• The impact of computers on the music industry
• The use of computers in medicine and healthcare
• The role of computers in space exploration
• The impact of video games on cognitive development
• The benefits and drawbacks of cloud computing

Simple & Easy Computers Essay Topics

• How to choose the right computer for your needs
• The basics of computer hardware and software
• The importance of computer maintenance and upkeep
• How to troubleshoot common computer problems
• The role of computers in modern business
• The impact of computers on communication
• How to protect your computer from viruses and malware
• The basics of computer programming
• How to improve your computer skills
• The benefits of using a computer for personal finance management.

Computer Science Extended Essay Topics

• The impact of Artificial Intelligence on the job market
• The development of a smart home system using IoT
• The use of Blockchain in supply chain management
• The future of quantum computing in cryptography
• Developing an AI-based chatbot for customer service
• The use of Machine Learning for credit scoring
• The development of an autonomous drone delivery system
• The role of Big Data in predicting and preventing natural disasters
• The potential of Robotics in agriculture
• The impact of 5G on the Internet of Things

Long Essay Topics In Computer Science

• The ethical implications of artificial intelligence and machine learning.
• Exploring the potential of quantum computing and its impact on cryptography.
• The use of big data in healthcare: Opportunities and challenges.
• The future of autonomous vehicles and their impact on transportation and society.
• The role of blockchain technology in securing digital transactions and information.
• The impact of social media and algorithms on the spread of misinformation.
• The ethics of cybersecurity and the role of governments in protecting citizens online.
• The potential of virtual reality and augmented reality in education and training.
• The impact of cloud computing on business and IT infrastructure.
• The challenges and opportunities of developing sustainable computing technologies

Most Interesting Computers Topics

• The rise of artificial intelligence in information technology: opportunities and challenges.
• The evolution of programming languages and their impact on software development.
• The future of pursuing computer science education: online learning vs traditional classroom.
• The impact of virtualization on computer systems and their scalability.
• Cybersecurity threats in information technology: prevention and mitigation strategies.
• An analysis of the most popular programming languages and their advantages and disadvantages.
• The role of cloud computing in the digital transformation of businesses.
• Emerging trends in pursuing computer science education: personalized learning and adaptive assessments.
• Developing secure computer systems for critical infrastructure: challenges and solutions.
• The potential of quantum computing in revolutionizing information technology and programming languages.

How To Choose The Right Computer Science Essay Topic

Choosing the right computer science essay topic can be a challenging task. Here are some tips to help you select the best topic for your essay:

• Consider your Interests

Choose a topic that you are genuinely interested in. This will help you to stay motivated and engaged throughout the writing process.

• Do your Research

Spend some time researching different computer science topics to identify areas that interest you and have plenty of research material available.

• Narrow Down Your Focus

Once you have a list of potential topics, narrow down your focus to a specific aspect or issue within that topic.

• Consider the Audience

Think about who your audience is and choose a topic that is relevant to their interests or needs.

• Evaluate The Scope Of The Topic

Make sure that the topic you choose is not too broad or too narrow. You want to have enough material to write a comprehensive essay, but not so much that it becomes overwhelming.

Take some time to brainstorm different ideas and write them down. This can help you to identify patterns or themes that you can use to develop your topic.

• Consult With Your Instructor

If you're struggling to come up with a topic, consider consulting with your instructor or a tutor. They can provide you with guidance and feedback to help you choose the right topic.

Tips To Write An Effective Computer Science Essay

Writing an effective computer science essay requires careful planning and execution. Here are some tips to help you write a great essay:

• Start with a clear thesis statement: Your thesis statement should be concise and clearly state the purpose of your essay.
• Use evidence to support your arguments: Use credible sources to back up your arguments. Also, make sure to properly cite your sources.
• Write in a clear and concise manner: Use simple and straightforward language to convey your ideas. Avoid using technical jargon that your audience may not understand.
• Use diagrams and visual aids: If appropriate, use diagrams and visual aids to help illustrate your ideas. This will make your essay look more engaging.
• Organize your essay effectively: Use clear and logical headings and subheadings to organize your essay and make it easy to follow.
• Proofread and edit: Before submitting, make sure to carefully proofread your essay to ensure that it is free of errors.
• Seek feedback: Get feedback from others, to help you identify areas where you can improve your writing.

By following these tips, you can write an effective computer science essay that engages your audience and effectively communicates your ideas.

In conclusion, computer science is a vast and exciting field that offers a wide range of essay topics for students. 

Whether you're writing about emerging technologies, or hot topics in computer science, there are plenty of options to choose from.

To choose the right topic for your essay, consider your interests, the assignment requirements, and the audience you are writing for. Once you have a topic in mind, follow the tips we've outlined to write an effective essay that engages your audience.

If you're struggling to write your computer science essay, consider hiring our professional essay writing - CollegeEssay.org. 

We offer a range of services, including essay writing, editing, and proofreading, to help students achieve their academic goals.

With our essay writer AI , you can take your writing to the next level and succeed in your studies. 

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Donna C (Law, Literature)

Donna has garnered the best reviews and ratings for her work. She enjoys writing about a variety of topics but is particularly interested in social issues, current events, and human interest stories. She is a sought-after voice in the industry, known for her engaging, professional writing style.

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Essays in Computing Science (Prentice-hall International Series in Computer Science)

• ISBN-10 0132840278
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• Publisher ‏ : ‎ Prentice Hall (January 1, 1989)
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Chapter 6: 21st-century media and issues

6.14.2 Literacy in computer science (research essay)

John Parker

English 102, April 2021

Introduction.

Computer Science is one of the fastest growing fields as the world transitions to increased automation. Schools of all levels are putting a greater emphasis on educating the younger generation on programming. This suggests that schools are growing their STEM departments, which house the fields of science, technology, engineering, and mathematics. In order to understand why many educators are approaching the field of Computer Science in this way, it must be understood what Computer Science is. It is most commonly defined as the study of computer software and computing systems. More specifically, it deals with creating, reading, and error-checking programming or code. While it is true that STEM is very important within the field of programming, there are other important aspects of coding that are not frequently considered by many educators. Coding includes being able to read, write, and communicate in a unique way, which implies that literacy involved in the field. Any form of literacy that is not directly learning how to read, write, or communicate in standard English is often not considered to be literacy, which is a major reason that its importance within programming is not recognized. The fact that many educators within the field of Computer Science do not realize the importance of literacy alludes to the idea that the teaching of programming may be flawed in its methods and implementation.

Computer Science is very important in my life, as I am currently pursuing a degree in the field. I have been programming for just over a year now and have experience in Python and Java programming languages. I have taken three courses on programming/computer science in college, in which I have learned so much about programming and Computer Science in general. In addition to coursework, I frequently work on coding projects for my own entertainment and read/watch articles and videos on programming. Any knowledge that I gain on the most effective ways to learn programming is very important to my future. Even more important than gaining this knowledge for myself, being able to spread this knowledge to grow the field is paramount.  Although I am not an expert in programming, I have had many learning experiences with programming that qualify me to discuss my personal experiences with learning how to program. Since the focus of this essay deals with the teaching methods and learning experiences of programming, the relative freshness of my learning experiences with programming provides me with an advantage over industry professionals in this discussion.

Writing in Computer Science

   Although it may be somewhat difficult to discover the parallels between computer programming and literacy, the literacy aspect of writing can be understood very easily. When thinking of what a programmer does, one of the simplest and high-level descriptions could be “someone who writes code.” The main similarity between the two practices is the exist in the process of creating a finalized piece of work, whether it be a novel for an application. In Felienne Hermans and Marlies Aldewereld’s article, “Programming is Writing is Programming,” the authors describe the beginning of the writing process and programming workflow to include a high-level plan (1). The next step in both processes is to convert these high-level designs into low-level, workable steps. For writers, these low-level steps include sentences and words; for programmers, they include methods, functions, and lines of code. For both practices, intermediate steps are needed manage the organization of the work, such as chapters in writing and classes and objects in programming (Hermans and Marlies 2). In the programming course that I am currently enrolled in, every coding assignment that is submitted must be accompanied by pseudocode, which is essentially a plan for how the final code will look. This pseudocode, which is written in a mix of English and Java syntax, begins with high-level plans that are broken down into smaller, more manageable steps. The process of writing pseudocode was not all that difficult to me when I realized that it was just like the outlines that I have been writing for English courses for years. These outlines broke up the goal of the essay into manageable portions and consisted of some wording that would be directly added to the essay and some rough ideas that would need to be converted into cohesive writing.

In Ziva R. Hassenfeld’s et al article, “If you can Program you can Write,” explores the constructs shared by computer programming and writing in great detail. The authors discuss the similar constructs between the two practices as, “planning and prewriting, creating and drafting, testing and evaluating, and debugging and editing and revising” (Hassenfeld et al. 68). The study described in this article, which focuses on the correlation between elementary student’s ability to write and ability to learn programming, showed that these similarities between the two practices produce a correlation between students’ ability to write and their ability to program (Hassenfeld et al. 75). In the section titled “Programming as Literacy” of Annette Vee’s novel, “Coding Literacy: How Computer Programming is Changing Writing,” she discusses an extremely interesting way to observe the similarities between writing and programming. Vee dives into exploring the ways in which programming is treated like writing within United States law. The United States Congress amended the 1976 Copywrite Act in 1980 to categorize computer code as a “literary work” and a “form of writing” (Vee 450). Since a law protecting writing and forms of creative expression, it can be alluded that the United States law views computer programming as a form of writing.

Reading in Computer Science

Reading is also extremely prevalent within the world of programming and Computer Science in general. Peg Grafwallner’s article, “Encoding Literacy in Computer Science,” examines an instructional coach and computer science teacher’s attempt to implement literacy lessons into a computer science class. The article states that reading within Computer Science requires students to focus on one specific area at a time, thinking in a linear and conceptual manner (Grafwallner). The computer science class discussed in this article was taught with an emphasis on literacy through directions, ultimately proving to boost the success of the students’ ability to program. The ability to read instructions was determined to be the most vital skill in programming (Grafwallner).

In Marthie Schoeman’s article, “Reading Skills Can Predict the Programming Performance of Novices,” the relationship between reading and ability to code is discussed extensively. In the study described in the article, the reading level of students were determined using eye-tracking technology. The students then took an introductory course in computer programming that would be followed by a final examination (Schoeman 44). The results of the study show that students with low reading skills failed the programming component, while those with higher reading skills did better overall. These results depict the fact that reading skills do play a role in one’s ability to learn programming (Schoeman 48). This relation can be attributed to the fact that programming is a form high-level written language in its own sense. In my own experiences, reading programming has proved to be one of the most vital skills that a computer programmer can possess. One of the main points of emphasis within Computer Science classes is being able to read and debug others’ code. Since there are so many different ways that a program can be created, I initially struggled with reading others’ code. The skill of reading code is very similar to reading literary works, as some authors are naturally easier to follow along with than others. Reading code is a vital aspect of computer programming and is a skill that I am still working on improving.

Communication in Computer Science

Although communication is not necessarily involved in the creation of all computer programs, communication in vital within the professional setting of Computer Science, in addition to engaging in programming within a team environment. In Gilles Dubochet’s article, “Computer Code as a Medium for Human Communication,” it is stated that communication between a human and a computer is the main objective of computer programming. The article goes on to state that computer programming itself has become a channel for human communication (Dubochet 1). The article explores the increase in team usage in the field of computer science, suggesting that the ability to understand the code that other’s write is extremely important (2). Understanding the code that others write is not only dependent on one’s ability to read and understand coding syntax and standards, but also the ability of the person reading the code and the person who wrote the code to communicate effectively with one another. The article suggests that communication is not only prevalent through oral dialect, but that programming languages are becoming a channel for communication between programmers (Dubochet 13). In other words, programmers are able to convey their thoughts through a programming language.

At the start of my college career, I did not expect for communication to be as prevalent as it was within my Computer Science courses. Throughout the entire Fall Semester of my introduction to programming course, a team of students that we were assigned to were required to code a robot. Due to the business of the group members’ schedules, we often had to do portions of the project on our own. This meant that I would often log in to add a portion to the code and would be confused by the code that was just written above. Through a simple phone call or text, all of the team members were able to understand the others’ work. The communication between our team was extremely important for this reason, as the project would have fallen apart without it. Throughout the semester, our team began to “comment” our code, which is simply inserting explanation within the code that do not affect how the code runs. If “//” is used before a line, the programming software environment understands that this is just for programmers to read. This simple addition to our code meant that we were actually able to communicate directly through the code, without having to text, call, or talk at all.

Marc Riemer breaks down the importance of communication and language skills in a broader field of engineering in the article titled, “Communication Skills for the 21st Century Engineer.” Riemer discusses the importance of communication skills in engineering, primarily focusing on the English language. He states that English is the most widespread language in the world and that effective communication in English is a skill that develops more successful engineers (91). Riemer examines the importance of communication between engineers and stakeholders (95). After engineers’ years of education in upper-level concepts, it can be difficult to decipher what stakeholders are familiar and not familiar with. Being able to effectively break down the concepts into more common terminology plays a major role in one’s success within the field of Computer Science as well as all other engineering disciplines. The findings of this article suggest that an increase in communication and language courses in college curriculums will produce more successful engineers (Riemer 98). Although this article focuses more broadly on engineering, Computer Science is a major branch of engineering that shares in the same challenges of communication as all other major fields of engineering.

Computer Programming as a Language in Itself

Computer Programming is much more than a computational practice, as learning programming languages comes with many of the same challenges as learning human languages, uncovering the fact that computer programming is its own unique form of literacy or language. When I was applying for colleges and deciding on a major, I honestly did not know what I wanted to do. I knew that I loved math and problem solving and would want to pursue a career in math-based field. The reason that I chose to pursue a career in Computer Science was purely for this reason, as I have never taken a coding course or had any prior experience. Once I began coding in my collegiate level courses, I fell in love with the problem-solving aspect. I was grasping the various coding techniques and problem-solving methods, but found that the portion I was struggling with the most was syntax and coding conventions. I thought that learning to program would be like learning Calculus, but, in reality, it was actually like learning a new language.

The world of programming is extremely complex, with syntax and grammar of its own, comparable to the grammar and structure used in human languages. The article, “Classifying Programming languages,” is an excellent source for understanding how programming languages are classified and the many similarities and differences between. The authors state that there are eight major categories of programming languages, categorized by “linguistic structure, expressive features, possibility of efficient implementation, direct support for certain programming models, and similar concerns” (“Classifying Programming Languages”). This practice of categorizing languages based on various features is used extensively in human languages also. For example, the Romance Languages are all rooted in Latin and have similar sounds, sentence structure, etc. The article goes on to explain there are many styles of programming that can be used within one language (“Classifying Programming Languages”). This is also a construct that is common throughout human languages, as there are many styles of writing within the English language. Programming languages also have their own grammar and syntax. The grammar portion of coding could be described through common code standards, such as camel case being used for variable names or uppercase being used for constant names. The syntax portion of coding is slightly different than in English, as errors in syntax within programming will cause the program to crash, losing functionality.

In Ana Harris’ article, “Human Languages vs. Programming Languages,” she breaks down the criteria for something to be considered a language. Harris states that the main function of language is communication. She goes on to explain that the function of programming languages is to communicate a series of an instructions to a computer or machine, alluding to the idea that programming languages are indeed unique forms of literacy/language. Harris zooms in on another major similarity between human languages and programming languages, being structure. She discusses the concepts of semantics (meaning connected to a certain concept) and syntax (rules for aligning words and phrases) from the perspective of a linguist. She states that programming uses semantics, as every program has a specific intention, and syntax, which includes following rules for the use of variables, functions, parenthesis, colons, etc. (Harris). These many similarities allow for programming to be considered its own unique form of literacy or language.

Connection between Literacy Skills and Programming Ability

Due to the many parallels between computer programming and literacy, it can be gathered that programming ability and literacy skills benefit one another. Although I enjoy and excel in mathematics and problem solving more-so, I have always loved reading and writing. Throughout my journey of learning programming, this love and ability has helped to excel in the field. Although many of my peers are more advanced than myself in mathematics, this ability has proved to give me a slight upper hand in some aspects of coding. Many of my peers who lack in this ability often have trouble with their code simply because they missed a portion of the instruction when reading, misunderstood what was being asked of them, or they had trouble recalling the semantics and syntax required for the program.

In Sharin Jacob and Mark Warschauer’s article, “Computational Thinking and Literacy,” the authors discuss how literary skills can lead to stronger computational skills. The authors describe in detail how computational thinking (computer programming) is a form of literacy, which was discussed earlier extensively (Jacob and Warschauer 3). The authors then switch gears to focus on how literacy skills can improve programming ability. The article describes the importance of verbal analysis of game architecture to their implementation of game design. The example that the authors use to back up this statement is as follows: The statement “the hunter killed the monkey” is implemented into the coding as “the monkey disappears when it touches the hunter” (Jacob and Warschauer 8). This example shows the importance of one literary element, transitive verb structures, to the success of a game developer. Jacob and Warschauer state, “students cannot master programming syntax without understanding the semantic meaning of commands if they cannot produce correct linguistic forms without considering their corresponding meanings” (10). The authors are saying that students are required to use the same skills within literacy courses that they are required to use within programming, just manifest in different ways. Therefore, skills that are taught in literacy primarily can assist in improving programming ability.

Marthie Schoeman’s article discussed above, “Reading Skills Can Predict the Programming Performance of Novices,” further displays how literacy skill can affect programming performance. This article discusses a study of the relationship between reading skills and the ability to code. The method of the study involved performing an initial eye tracking test on participants as they were reading to determine their reading proficiency. The participants were then given a short introductory course in programming, which would be followed by a knowledge exam (Schoeman 42). The results of the study displayed that those students with low reading skills failed the programming component, while students with higher reading skills did better overall (Shoeman 48). These results suggest that the literary skill of reading does indeed play a role in one’s ability to learn programming.

All of the findings discussed throughout the entirety of this essay display the fact that teaching programming to young people more similarly to the ways in which that literacy is taught may be more effective than just the typical STEM approach. Marina Bers’ article, “Coding as Another Language,” discusses a new method of teaching computer science to young children starting in kindergarten called “Coding as Another Language” (499). The method of teaching coding described in this article deviates from the typical STEM approach, offering the proposition that computer science teaching can be enhanced by incorporating the design of literacy instruction, due to the parallels that exists between natural languages and programming languages (Bers 504). According to Bers, research shows that teaching children how to read and write artificial languages in the same way as natural languages leads to a greater cognitive understanding of programming (503).

In Ziva R. Hassenfeld’s et al. article, “If you can Program you can Write,” the authors examine a study of elementary students learning through the “Coding as Another Language” curriculum. The article discusses results from a test on literacy and an assessment of students’ understanding of an introductory program language, drawing conclusions based upon their correlation (Hassenfeld et al. 73). The results of this study show that there is a connection between students’ literacy levels and their height of achievement in grasping an introductory programming language (Hassenfeld et al. 75). This indicates that there are fundamental understandings and constructs that are shared by literacy and computer programming, which are described in detail earlier. All of these articles suggest that the instruction of programming in early years is more effective when taught more similarly to literacy instruction than just being taught in the typical STEM approach.

The future of Computer Science is limitless, due to the increase in automation throughout societies. As the field continues to grow, programming education will become more and more prevalent within elementary and high schools across the country. The ways in which programming is taught needs to transition to a more literacy-based approach for younger children to improve the effectiveness of the education. If the instruction of programming evolves according to the findings displayed in this essay, so will the growth of the field of Computer Science. Just as most people hold the belief that literacy is not involved in the field of Computer Science, many people are unaware of its presence within all STEM fields, whether it be biology, nursing, or engineering. If the style of teaching programming is holding back the future of programming so drastically by ignoring literacy approaches, imagine how much the world is being held back by this issue.

Although approaching the instruction of computer programming from a literacy point of view is more effective than just the STEM approach overall, there are still many individuals that have disadvantages in learning programming no matter what teaching method that is used. According to Antonio Byrd’s article, “Between Learning and Opportunity: A Study of African American Coders’ Networks of Support,” racially marginalized individuals are not as likely to develop coding literacy skills for problem-solving applications (Byrd 31). A core issue for these marginalized communities gaining access to programming knowledge and experience is financial stability. Computer Programming boot camps and college education are both very expensive investments, which is often not an option for individuals from marginalized communities. Byrd expands on this by stating that even those that do not need to pay tuition for coding bootcamps are required to give of their emotional and physical labor (34). Since coding bootcamps require many hours of work a week, many individuals often have to take time away from their jobs and/or their families. This is something that many marginalized people can simply not afford. The study described in this article takes place at Clearwater Academy, where marginalized students do not pay tuition, which taught courses on programming languages such as JavaScript, HTML, and CSS (Byrd 35). The results of this confirm that African American adult’s access to coding literacy is limited by the social, emotional, and economic repercussions of white supremacy (Byrd 49). Unfortunately, there is no one easy solution that completely resolves this issue, as it stems from years of oppression and discrimination. In order to best combat this issue, universities, training centers, and employers need to take steps to accommodate the needs of marginalized groups. Taking steps in this direction will cultivate the field of Computer Science to grow exponentially and move towards equality.

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Five Hundred Most-Cited Papers in the Computer Sciences: Trends, Relationships and Common Factors

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This study reveals common factors among highly cited papers in the computer sciences. The 500 most cited papers in the computer sciences published between January 2013 and December 2017 were downloaded from the Web of Science (WoS). Data on the number of citations, number of authors, article length and subject sub-discipline were extracted and analyzed in order to identify trends, relationships and common features. Correlations between common factors were analyzed. The 500 papers were cited a total of 10,926 times: the average number of citations per paper was 21.82 citations. A correlation was found between author credibility (defined in terms of the QS University Ranking of the first named author’s affiliation) and the number of citations. Authors from universities ranked 350 or higher were more cited than those from lower ranked universities. Relationships were also found between journal ranking and both the number of authors and the article length. Higher ranked journals tend to have a greater number of authors, but were of shorter length. The article length was also found to be correlated with the number of authors and the QS Subject Ranking of the first author’s affiliation. The proportion of articles in higher ranked journals (journal quartile), the length of articles and the number of citations per page were all found to correlate to the sub-discipline area (Information Systems; Software Engineering; Artificial Intelligence; Interdisciplinary Applications; and Theory and Methods).

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Teh, P.L., Heard, P. (2021). Five Hundred Most-Cited Papers in the Computer Sciences: Trends, Relationships and Common Factors. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1366. Springer, Cham. https://doi.org/10.1007/978-3-030-72651-5_2

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• 10 April 2024

Randomness in computation wins computer-science ‘Nobel’

• Davide Castelvecchi

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Avi Wigderson received the Turing Award for his foundational contributions to the theory of computation. Credit: Dan Komoda

A leader in the field of computational theory is the latest winner of the A. M. Turing Award, sometimes described as the ‘Nobel Prize’ of computer science.

Avi Wigderson at the Institute for Advanced Study (IAS) in Princeton, New Jersey, is known for work straddling several disciplines, and had already won a share of the Abel Prize , a top mathematics award, three years ago.

He receives the Turing Award “for foundational contributions to the theory of computation, including reshaping our understanding of the role of randomness in computation, and for his decades of intellectual leadership in theoretical computer science”, the Association for Computing Machinery (ACM) in New York City announced on 10 April.

“I was extremely happy, and I didn’t expect this at all,” Wigderson tells Nature . “I’m getting so much love and appreciation from my community that I don’t need prizes.”

‘A towering intellectual force’

Wigderson was born in Haifa, Israel, in 1956. He studied at Technion — Israel Institute of Technology in Haifa and later at Princeton University; he has been at the IAS since 1999. He is known for his work on computational complexity — which studies how certain problems are inherently slow to solve, even in principle — and on randomness in computation. Many practical algorithms make random choices to achieve their objectives more efficiently; in a series of groundbreaking studies in the 1990s, Wigderson and his collaborators showed that conventional, deterministic algorithms can, in principle, be roughly as efficient as ‘randomized’ ones 1 . The results helped to confirm that random algorithms can be as accurate as deterministic ones are.

“Wigderson is a towering intellectual force in theoretical computer science,” said ACM president Yannis Ioannidis in a statement. In addition to Wigderson’s academic achievements, the ACS cited his “friendliness, enthusiasm, and generosity”, which have led him to be a mentor to or collaborate with hundreds of researchers worldwide. Wigderson admits that he is a “big proselytizer” of the intellectual pleasures of his discipline — he wrote a popular book about it and made it freely available on his website . “I think this field is great, and I am happy to explain it to anybody.”

The Turing Award is named after the celebrated British mathematician and code-breaker Alan Turing (1912–54), who in the 1930s laid the conceptual foundations of modern computing. “I feel completely at home with mathematics,” says Wigderson, adding that as an intellectual endeavour, theoretical computer science is indistinguishable from maths. “We prove theorems, like mathematicians.”

doi: https://doi.org/10.1038/d41586-024-01055-y

Impagliazzo, R. & Wigderson, A. in Proc. 29th ACM Symposium on Theory of Computing 220–229 (ACM, 1997).

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Mathematics

Mathematician wins turing award for harnessing randomness.

Avi Wigderson has won the 2023 Turing award for his work on understanding how randomness can shape and improve computer algorithms

By Alex Wilkins

10 April 2024

Avi Wigderson, winner of the 2023 Turing award

Peter Badge

The mathematician Avi Wigderson has won the 2023 Turing award, often referred to as the Nobel prize for computing, for his work on understanding how randomness can shape and improve computer algorithms.

Wigderson, who also won the prestigious Abel prize in 2021 for his mathematical contributions to computer science, was taken aback by the award. “The [Turing] committee fooled me into believing that we were going to have some conversation about collaborating,” he says. “When I zoomed in, the whole committee was there and they told me. I was excited, surprised and happy.”

Is everything predetermined? Why physicists are reviving a taboo idea

Computers work in a predictable way at the hardware level, but this can make it difficult for them to model real-world problems, which often have elements of randomness and unpredictability. Wigderson, at the Institute for Advanced Study in Princeton, New Jersey, has shown over a decades-long career that computers can also harness randomness in the algorithms that they run.

In the 1980s, Wigderson and his colleagues discovered that by inserting randomness into some algorithms, they could make them easier and faster to solve, but it was unclear how general this technique was. “We were wondering whether this randomness is essential, or maybe you can always get rid of it somehow if you’re clever enough,” he says.

One of Wigderson’s most important discoveries was making clear the relationship between types of problems, in terms of their difficulty to solve, and randomness. He also showed that certain algorithms that contained randomness and were hard to run could be made deterministic, or non-random, and easier to run.

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These findings helped computer scientists better understand one of the most famous unproven conjectures in computer science, called “ P ≠ NP ”, which proposes that easy and hard problems for a computer to solve are fundamentally different. Using randomness, Wigderson discovered special cases where the two classes of problem were the same.

Wigderson first started exploring the relationship between randomness and computers in the 1980s, before the internet existed, and was attracted to the ideas he worked on by intellectual curiosity, rather than how they might be used. “I’m a very impractical person,” he says. “I’m not really motivated by applications.”

However, his ideas have become important for a wide swath of modern computing applications, from cryptography to cloud computing. “Avi’s impact on the theory of computation in the last 40 years is second to none,” says Oded Goldreich at the Weizmann Institute of Science in Israel. “The diversity of the areas to which he has contributed is stunning.”

Quantum computers are revealing an unexpected new theory of reality

A powerful new idea about how the laws of physics work could bring breakthroughs on everything from quantum gravity to consciousness, says researcher Chiara Marletto

One of the unexpected ways in which Wigderson’s ideas are now widely used was his work, with Goldreich and others, on zero-knowledge proofs, which detail ways of verifying information without revealing the information itself. These methods are fundamental for cryptocurrencies and blockchains today as a way to establish trust between different users.

Although great strides in the theory of computation have been made over Wigderson’s career, he says that the field is still full of interesting and unsolved problems. “You can’t imagine how happy I am that I am where I am, in the field that I’m in,” he says. “It’s bursting with intellectual questions.”

Wigderson will receive a $1 million prize as part of the Turing award.

Article amended on 10 April 2024

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