2 Is the College Essay Dead?

First, let’s get something out of the way: In 2024, as I am writing this book, many generative AI tools can “write” a pretty decent (C to B level) academic essay. Don’t believe me? Here’s a research paper on solar eclipses that I wrote with Copilot in about 30 minutes.

Now don’t get too excited. The fact that a chatbot can write an entry level college essay is not necessarily good news. For more than a hundred years, colleges have used the essay to teach and practice some important cognitive skills like critical thinking, problem solving, communication, ethics, and organization. If generative AI can write an essay for us, are these skills still important? And if we don’t write essays, how will we learn and practice these skills?

I argue that these skills are more important than ever. And to show you what I mean and how AI can be a partner in developing the communication and critical thinking skills you need for college and the workplace, I’m going to apply Ethan Mollick’s first three principles from Co-Intelligence and engage in a conversation with ChatGPT 4o about what the college essay teaches–and what we can do to learn and practice these skills in the age of generative AI

Here’s our conversation:

Me: I need your help in thinking through some assessment strategies. I would like you to be a writing program curriculum designer for a first-year writing program. What are the five most important skills that students learn from writing a traditional college essay such as a research paper that answers a research question?

ChatGPT: Certainly! Here are five important skills that students learn from writing a traditional college essay, such as a research paper that answers a research question:

1. Critical Thinking and Analysis:
   • Skill Development: Students learn to evaluate and synthesize various sources of information, identify biases, and construct logical arguments.
   • Importance: This skill helps students to approach problems systematically and make well-reasoned decisions in both academic and real-world contexts.
2. Research Skills:
   • Skill Development: Students learn how to locate, evaluate, and use primary and secondary sources effectively.
   • Importance: Mastery of research skills is essential for academic success and lifelong learning, enabling students to gather information, understand different perspectives, and build evidence-based arguments.
3. Writing and Communication:
   • Skill Development: Students improve their ability to organize their thoughts, articulate ideas clearly, and present information in a coherent and structured manner.
   • Importance: Effective communication is crucial in almost every field, helping students convey their ideas and arguments persuasively and professionally.
4. Time Management and Organization:
   • Skill Development: Writing a research paper involves planning, outlining, drafting, revising, and editing, which teaches students how to manage their time and organize their work efficiently.
   • Importance: These skills are essential for academic success and are highly valued in the workplace, helping individuals meet deadlines and manage multiple tasks effectively.
5. Academic Integrity and Ethical Use of Information:
   • Skill Development: Students learn the importance of citing sources properly, avoiding plagiarism, and respecting intellectual property.
   • Importance: Understanding and practicing academic integrity fosters a culture of honesty and respect for others’ work, which is critical in both academic and professional settings.

These skills not only contribute to the successful completion of a research paper but also prepare students for various challenges they will encounter in their academic and professional lives.

Me: Many students now have access to generative AI tools that can write college essays for them. What kinds of writing assessments can instructors use instead of a traditional college essay to teach these five skills and ensure that students have opportunities to learn and practice them? 

ChatGPT: In light of the accessibility of generative AI tools, instructors can design alternative writing assessments to ensure students learn and practice critical skills. Here are some suggestions:

1. Critical Thinking and Analysis

• Assessment: Annotated Bibliography
  • Description: Students compile a list of sources related to a research topic and write annotations summarizing and critically evaluating each source.
  • Skills Developed: Evaluating sources, identifying biases, and synthesizing information.
• Assessment: In-Class Debates
  • Description: Students participate in structured debates on relevant topics, requiring them to construct arguments, present evidence, and respond to counterarguments.
  • Skills Developed: Analytical thinking, oral communication, and argumentation.

2. Research Skills

• Assessment: Research Proposal
  • Description: Students write a proposal for a research project, including a research question, literature review, and methodology.
  • Skills Developed: Formulating research questions, conducting preliminary research, and planning research strategies.
• Assessment: Source Evaluation Exercises
  • Description: Students are given a set of sources to evaluate for credibility, relevance, and bias, and must justify their evaluations.
  • Skills Developed: Source evaluation and critical thinking.

3. Writing and Communication

• Assessment: Reflective Journals
  • Description: Students maintain journals where they reflect on their learning process, analyze readings, and connect course content to their experiences.
  • Skills Developed: Reflective writing, self-assessment, and personal expression.
• Assessment: Multimedia Presentations
  • Description: Students create presentations using various media (slides, videos, infographics) to communicate their research findings or arguments.
  • Skills Developed: Oral communication, visual literacy, and technical skills.

4. Time Management and Organization

• Assessment: Project-Based Learning
  • Description: Students work on long-term projects that require planning, research, and collaboration, with regular checkpoints and progress reports.
  • Skills Developed: Time management, organization, and teamwork.
• Assessment: Portfolio Compilation
  • Description: Students compile a portfolio of their work throughout the course, reflecting on their progress and growth.
  • Skills Developed: Organization, reflection, and self-assessment.

5. Academic Integrity and Ethical Use of Information

• Assessment: Ethics Case Studies
  • Description: Students analyze case studies related to academic integrity, plagiarism, and ethical use of information, and write responses or engage in discussions.
  • Skills Developed: Understanding and applying ethical principles.
• Assessment: Collaborative Research Projects
  • Description: Students work in groups to conduct research, with a focus on proper citation practices and collaborative writing, followed by a reflection on the process.
  • Skills Developed: Collaboration, ethical research practices, and accountability.

By incorporating these alternative assessments, instructors can provide diverse opportunities for students to develop and demonstrate their skills in critical thinking, research, writing, time management, and academic integrity.

Me: As a writing curriculum designer, what concerns you most about generative AI as you plan your writing classes for the upcoming year? What excites you the most about generative AI?

ChatGPT: 

1. Academic Integrity and Plagiarism:

• Concern: The ease with which students can use generative AI to produce essays and other assignments raises concerns about academic honesty. It may become challenging to ensure that the work submitted is genuinely the student’s own.
• Impact: This could undermine the value of the educational process and the credibility of academic qualifications.

2. Skill Development:

• Concern: Over-reliance on AI tools may impede students’ development of essential writing and critical thinking skills. If students use AI to generate content without engaging in the writing process, they miss out on key learning opportunities.
• Impact: This could result in graduates who are less prepared for professional and academic challenges that require independent thinking and writing skills.

3. Equity and Access:

• Concern: Not all students may have equal access to advanced AI tools, leading to disparities in the quality of work and learning experiences.
• Impact: This could exacerbate existing inequalities and create an uneven playing field in the classroom.

4. Assessment Validity:

• Concern: Traditional assessment methods may become less effective in evaluating student learning and performance if AI-generated content is not easily distinguishable from student-created work.
• Impact: This could challenge the validity and reliability of assessments, making it harder to gauge student progress accurately.

5. Ethical and Pedagogical Implications:

• Concern: The integration of AI in education raises ethical questions about authorship, creativity, and the role of technology in learning. There is also the challenge of developing pedagogical strategies that incorporate AI without compromising educational values.
• Impact: These issues require thoughtful consideration and innovative approaches to curriculum design.

Excitement about Generative AI in Writing Classes

1. Enhanced Learning Support:
   • Excitement: Generative AI can provide personalized writing assistance, offering real-time feedback, grammar correction, and suggestions for improvement. This can enhance the learning experience and help students improve their writing skills.
   • Impact: Students can receive individualized support, enabling them to progress at their own pace and address specific areas of weakness.
2. Creativity and Innovation:
   • Excitement: AI tools can inspire creativity by generating ideas, prompts, and even drafts that students can build upon. This can encourage students to explore new perspectives and experiment with their writing.
   • Impact: The use of AI can lead to more innovative and diverse writing assignments, fostering a creative and engaging learning environment.
3. Efficiency and Productivity:
   • Excitement: AI can streamline administrative tasks such as grading and providing feedback, allowing instructors to focus more on personalized instruction and mentoring.
   • Impact: This can increase efficiency in the classroom and enable instructors to dedicate more time to meaningful interactions with students.
4. Resource Availability:
   • Excitement: AI can generate a wealth of educational resources, such as example essays, writing prompts, and instructional materials, that can be used to supplement teaching.
   • Impact: Access to high-quality resources can enhance curriculum design and provide students with a rich array of learning materials.
5. Collaborative Learning:
   • Excitement: AI can facilitate collaborative learning experiences by enabling students to work together on writing projects, share feedback, and co-create content.
   • Impact: This can foster a sense of community in the classroom and encourage peer-to-peer learning.

Balancing these concerns and excitements will be crucial in designing a writing curriculum that leverages the benefits of generative AI while mitigating its potential drawbacks. (Open AI, 2024).

https://chatgpt.com/share/e/f406fa7b-1fad-4b1d-9fb0-c4f151d91d91

Why Writing Still Matters–And How AI Can Help

Does writing still matter? AI researcher Kartik Chandra (2023) certainly thinks it does, and I agree with her. In a 2023 essay for Inside Higher Ed, Chandra wrote:

[T]he question to ask about writing is not Will AI make it worthless? but rather What could possibly be more important? In a world flooded with the monotonous slurry AI excels at producing, power lies with those who can—and do—speak for themselves. Never have the skills of independent, critical thought and expression been more vital than in the AI era (para. 8).

Chandrik’s point gets at something essential about writing–your writing is a reflection of you. It’s how you communicate your self to the world. And no matter how well ChatGPT can churn out an essay on any given topic, what you think about that topic will always be important.

As you may have guessed by now, I’m pretty excited about the opportunities that writing assistants can provide. I personally use AI in a variety of ways. These are sometimes called “use cases.” I track things I’m trying on my blog, Artisanal Intelligence.

Two things I want you to know about me as a writer: First, I’m pretty confident about my own writing abilities. I have published an award-winning book with Penguin. I completed a doctoral dissertation with more than 200 sources and original quantitative research. I’ve written thousands of articles and more web content for doctors’ offices than I can imagine.

Second, so-called AI “plagiarism” checkers often falsely flag my writing as content written by generative AI. So if I ever ask you about whether you’ve used AI tools, don’t take it personally! I’m mostly just curious.  Also, you should know that no matter what anyone else tells you, these checkers do not work, and they never will. Worse, they disproportionately flag work by English language learners.

Let’s switch gears and consider where AI might be useful. I use generative AI tools in the following ways:

1. “Boring” Writing Tasks. Summary of a meeting? Recommendation letter template that I can personalize? Language for a new assignment prompt? I always invite AI to the table for these kinds of tasks–and I usually let AI write the first draft! As an instructor, I’m trying to make the writing tasks I assign to you less “boring” because I kind of assume you’ll use AI if you’re not that into it.
2. Administrative or Boilerplate Language. If I’m drafting a proposal or creating information about an academic program, generative AI is a great place to start (and sometimes, it nails this type of content on the first try, which probably says something about academic language). It’s also great with mission statements.
3. Summarizing Content. I really like to use AI in this way, not only for other people’s work, but also for my own. On my blog, I use generative AI tools to create a “Key Takeaways” header for each post. I recommend that you do something similar for your own essays and writing assignments. It’s a quick way to make sure that you are saying what you think you are saying.
4. Brainstorming or talking through ideas and concepts. This is one of my favorite ways to use generative AI, which is why I demonstrated it for you above. You can also use AI to prepare for debates, job interviews, or to identify gaps in your knowledge or arguments and address them. AI is great at helping you to narrow and focus a research question, define an audience’s needs, or create a working outline for a topic.
5. Developmental editing. I used AI as a developmental editor for both creative writing and academic writing, and I have found that it can be very helpful.

As you think about where you will use AI in your own writing process, you need to think about the kinds of cognitive activities that you enjoy. Do you like solving problems? Do you like learning about new ideas? Do you like testing concepts against your own values? Writing can be an excellent way to practice these skills.

Here are some places generative AI has been less useful for me:

1. Reflective writing. As the sample essay I shared shows, AI can actually “do” reflective writing. But what is the point? I like thinking about new ideas and reflecting on them. AI doesn’t think, but I do. Don’t deny yourself the opportunity to shape your own thoughts, ideas, and reactions in writing.
2. Writing for learning. When I am trying to learn something new, writing about it, whether it’s taking notes or writing up what I have learned, is an incredibly important way for me to create long-term robust memories. If you’re in any kind of major that requires content knowledge and subject matter expertise, don’t shortchange yourself. Sure, you can record lectures and have AI transcribe them (and you should!). But keep taking your own notes as well, then review your notes alongside the transcript. AI is not now and will never be a shortcut to learning things for yourself.
3. Research*. I’m putting an asterisk next to this one because I think it’s a rapidly evolving space. We’ll learn more about how AI works in the next chapter, but the important thing to know here is that right now, AI makes stuff up. It can make up highly convincing APA style references to sources that do not exist. There are tools like Perplexity, and generative AI tools with web access capabilities do a better job with research, but for me, at least right now, Google Scholar or the college library (or both) are better ways to locate high-quality sources.  I’m also putting an asterisk next to this one because it’s clear that researchers are using AI to produce scientific papers, and I honestly have no idea what the implications of that will be. For myself, I think I will continue to treat this area like I treat writing for learning. I like to do research. I like to critically evaluate whether a source will meet my needs, and I like to see the broad range of scholarship on a topic that interests me. I do use generative AI to help me narrow and focus my research questions and identify good key search terms though.
4. Creative Writing. I’ve used generative AI to write collaborative poems, and I also tried to get it to generate some dialogue for a short story I was writing, “Mirror, Mirror,” about a woman who falls in love with an AI-generated version of herself. The screenshot below shows how it wrote the break-up scene. Let’s just say screenwriters shouldn’t be too worried yet.

When shouldn’t you invite AI to the table? Different people will have different ideas about this but for me, any time you might violate another person’s privacy, you should not use generative AI. For example, if you copy and paste a peer’s paper or discussion post into a chatbot and ask the chatbot to write your peer review or response for you, you are violating your peer’s right to privacy unless you have informed consent from your peer that allows you to use their work in this way. Similarly, think about your own privacy rights before you put any content into a free chatbot that can use your data for its training model.

In future chapters, we’ll explore some basic concepts and terms associated with generative artificial intelligence tools.