Using AI to Get Feedback on Your Progress

One of the challenges of self-learning is figuring out how well you’re actually doing. When you’re in a class, a teacher or coach will evaluate your work and give you pointers. But if you’re learning on your own, you might miss that outside perspective. This is where AI (Artificial Intelligence) can step in as a sort of always-available assistant to provide feedback on your progress. In recent years, AI tools have become remarkably good at assessing certain kinds of tasks - from writing and coding to speaking a foreign language - and giving constructive feedback. Using AI to get feedback is like having a tutor or coach who is available anytime, anywhere.

Why feedback matters: First, it’s worth emphasizing why feedback is so crucial. When learning a new skill or subject, we improve by making adjustments. If you practice something but have no idea what you’re doing wrong (or right), you might reinforce bad habits or lose motivation because you’re unsure of progress. Traditional feedback comes from tests, instructors, or peers. Now, AI can provide another source of feedback, often instantaneously. This means you can iterate faster - make a mistake, get feedback, correct it on the spot, and try again. It turns practice into a more interactive and guided experience.

So, how can you use AI to get feedback? Let’s break it down by a few domains and examples:

Writing and essays: Suppose you’re learning a language or trying to improve your writing skills. There are AI-powered writing assistants (like Grammarly and others) that can highlight grammar errors, awkward phrasing, or suggest better word choices. If you write an essay or a report, you can feed it into such tools to get a critique on spelling, grammar, and even style. Beyond dedicated tools, you can use general AI chatbots for feedback too. For example, you could paste a paragraph of your writing into ChatGPT and ask, “Can you give me feedback on the clarity and tone of this paragraph? Is there a better way to phrase it?” The AI might respond with suggestions, pointing out sentences that were unclear or offering alternatives for variety. This is not very different from what a human editor might do, though a human might catch nuances better. Some advanced AI models can even evaluate the structure of an argument or the coherence of an essay. They might say, “Your introduction is strong, but the second paragraph seems off-topic, which might confuse readers.” Getting such feedback within seconds after writing a draft is incredibly useful - you can revise and improve while the material is fresh in your mind.

Coding and technical projects: If you’re learning programming, you might be familiar with the scenario of writing code and not being sure if it’s optimal or why it isn’t working. AI tools like code analyzers or GitHub’s Copilot (which is an AI assistant for coding) can help. While Copilot primarily helps by suggesting code as you write, there are also ways to get feedback on existing code. For instance, you could use an AI to review a function you wrote and ask, “Is there a bug or a better way to write this code?” and the AI might point out logical errors or inefficiencies. Some online coding platforms have built-in AI that can evaluate your solution to a problem, not just for correctness but also for style and complexity (like telling you if your solution is slower than it could be). Another example: if you write a piece of code and it’s not working, you can paste the code into a chatbot and say, “This code is supposed to do X, but it’s not working correctly. Can you help me find the issue?” The AI might identify a mistake or suggest debugging steps. Essentially, it’s like having a code reviewer or pair-programming partner available whenever you need one.

Language learning and pronunciation: Practicing a new language on your own can be tough because you might not realize when you mispronounce words or use awkward phrasing. Here, AI can act as a language partner. Apps like Duolingo, for example, use AI to listen to your speech and give feedback if you pronounced something correctly. Even without specialized apps, you can use general AI for feedback. For instance, you can speak to your phone’s virtual assistant or use speech-to-text features to see if it accurately transcribes what you said - which indirectly tells you if your pronunciation was clear. Some AI chatbots can role-play conversations and then highlight mistakes. You might type (or speak) in French or Spanish to an AI and then ask, “Did I use the correct tense in that sentence?” or “Can you correct any mistakes in what I just said?” The AI can then provide corrections or the more natural way to say it. This is immensely helpful for improving fluency, because you get immediate correction rather than repeating something wrong for weeks.

Public speaking and communication: Believe it or not, there are AI tools that analyze aspects of speech, like your pacing, filler words (“um”, “uh”), and even tone. If you’re preparing for a presentation and want feedback, you can record yourself and use an AI speech coach tool (some are available online) to get analysis. For example, the AI might tell you, “You spoke at an average of 150 words per minute, which is good, but you used the filler word ‘um’ 8 times. Also, your volume dropped at the end of sentences making it hard to hear.” Armed with that information, you know exactly what to work on - maybe practice slowing down a bit and consciously reducing those filler words. In the past, you’d have to rely on either self-awareness (which is hard while speaking) or a friend to count those for you. Now an AI can do it objectively.

Studying and quizzes: Let’s say you’re learning history or biology on your own. You’ve read a chapter or watched a video lecture. How do you know if you truly grasped it? You can prompt an AI to quiz you. For example, you could tell ChatGPT, “I just studied the causes of World War I. Can you ask me 5 quiz questions to test my understanding?” The AI can generate questions, which you then attempt to answer, and you can even have it check your answers. Alternatively, you can try to explain a concept in your own words to the AI (essentially teach the AI the concept), and then ask, “Did I explain that correctly? Is there anything important I missed?” The process of summarizing to an AI and getting its feedback can reveal gaps in your knowledge. If you missed something, the AI might say, “That’s a good explanation, but you didn’t mention X, which is also a key factor.” This way, AI doesn’t just test you like flashcards; it actively fills in the gaps.

Creative skills (design, music, etc.): AI is even starting to give feedback in creative domains. If you’re practicing graphic design, there are AI tools that can check things like color contrast (ensuring your designs are accessible) or alignment and balance in a layout. They might not “feel” creativity the way a human does, but they can catch technical issues. In photography, AI can analyze an image and comment on technical aspects like lighting or composition basics (some photo editing apps do this). For music, there are AI tools that can listen to a recording of you practicing an instrument and point out if you were off-beat or out of tune on certain notes. It’s not quite like a masterclass critique from a professional, but it’s better than practicing in a void with no idea how you sound. For example, if you’re learning guitar, an AI might highlight that you’re not holding a chord properly because a string sounds muted. Or if you’re composing music, some AI tools can analyze your chord progressions and suggest variations.

How to effectively use AI for feedback:

Be specific in what you ask for: AI will do its best to answer whatever prompt you give it. If you just say, “Is this good?” you might get a very generic answer. Instead, ask specific questions like, “What are some improvements I could make to this essay?” or “Can you find any errors in my solution?” or “Am I using the correct technique here?” The more precise your question or what you want feedback on, the more helpful the answer is likely to be.

Provide context if needed: Sometimes you have to tell the AI what the goal is. For example, if you want feedback on a piece of writing, mention who the intended audience is or what style you aim for, so the AI can judge appropriately (“I wrote this email to propose a project to my boss, can you review the tone and clarity?” might get more relevant feedback than just pasting the email without context).

Use the right tools: While general AI chatbots are versatile, sometimes a domain-specific tool is better. For instance, for programming, using an AI that’s integrated in a coding environment might yield better insights about code. For pronunciation, an app designed for language learners will be more accurate in feedback than a general AI. So explore what’s out there - many learning apps now have AI features.

Be aware of limitations: AI can provide feedback, but it’s not infallible. It might sometimes overlook an issue or give advice that’s not perfect. Use your own judgment too. If an AI suggests changing something that you feel strongly about, double-check through another source or consider if it’s a matter of style. Also, AI might not fully understand very complex or highly nuanced creative work - for example, it can grade a simple essay, but a deeply poetic piece of writing might confuse it in terms of “feedback.” So treat AI feedback as extremely useful data points, but not the absolute final verdict.

Iterate with the feedback: Once you get feedback and make changes, you can use AI again to see if your changes solved the issues. This iterative loop can accelerate improvement. It’s a bit like having multiple drafts reviewed in rapid succession. For example, you could ask, “I changed the introduction of my speech to try to make it more engaging, can you compare it to the earlier version and tell me if it’s better?” Yes, you can actually do that - feed the AI the two versions and it can highlight differences or which one might be more effective. This helps you learn from revisions.

A quick example scenario: Imagine you’re learning how to write Python code and you’ve just written your first small program that analyzes some data. You think it works, but you’re not completely sure if you followed best practices. You can go to an AI coding assistant and ask, “Can you review this code for any mistakes or suggest improvements?” The AI might point out that while your code runs, it could be made more efficient by using a certain library function instead of a long manual method you wrote. It might also catch a bug for a corner case you didn’t consider. You then take that feedback, modify your code, and perhaps ask the AI again, “Does this version address those issues?” When it says yes and perhaps points out something new or says it looks good, you now have more confidence that you’re learning the right habits. Over time, this kind of feedback loop teaches you general principles (like “oh, using built-in functions is better” or “I should always consider what happens if input is empty,” etc.).

To take another scenario, say you’re practicing for English proficiency exam essays. You write a practice essay and use an AI to score it or give feedback. It might tell you, “Your essay is logically structured and covers the topic, but you have some repetitive vocabulary. Try to use more varied expressions for ‘important’ (critical, significant, etc.). Also, your conclusion introduces a new idea, which might not be ideal; conclusions should summarize instead.” This is incredibly actionable feedback. You learn that: (a) You need to vary vocabulary - so you might study synonyms and practice them; (b) Don’t add new points in conclusion - a structural insight. Next time you write an essay, you’ll remember these tips.

Staying motivated and balanced: Getting AI feedback can sometimes be a double-edged sword emotionally. On one hand, it’s great to have clear pointers on what to improve. On the other hand, seeing a lot of suggestions could feel like criticism. Remember that the AI isn’t judging you personally; it’s just analyzing the work. Use it as a tool to improve, not as a measure of your worth or potential. In fact, try to view each suggestion as a mini lesson - something new you know now that you didn’t before. That’s progress.

Lastly, combine AI feedback with other forms of feedback when you can. If possible, still seek human feedback occasionally - humans can provide encouragement, share personal experiences, and catch nuances that AI might miss. But when human help isn’t available or you just want quick input, AI is a fantastic resource for the self-driven learner.

In conclusion, using AI to get feedback on your progress can significantly accelerate your learning process. It provides timely, often very detailed insights into your work, allowing you to correct course and refine your skills in real-time. It’s like having a personal tutor who can switch hats - one moment a writing coach, the next a code reviewer, then a language partner - all at your service whenever you need. As these tools continue to improve, they’ll become even more adept at guiding learners. So, don’t hesitate to make AI your study buddy. Try it out for your next project or practice session, and you might be pleasantly surprised at how much faster and smarter you can improve with an extra pair of (artificial) eyes on your work.