AI in Education and Software Engineering: Insights and Future Directions

Source: https://itbrief.com.au/story/exclusive-the-future-of-adobe-and-ai-the-experts-tell-all

I. Introduction

AI has undeniably revolutionized the world, proving to be a highly versatile and impactful tool across various industries. Its influence is particularly prominent in education and software engineering. As AI continues to improve in efficiency and effectiveness, its growing role within these fields could become increasingly dominant. While some view it as a convenient solution for debugging programming syntax, others utilize it to craft complete narrative essays. This raises important ethical considerations, yet AI remains a valuable resource capable of alleviating workloads for many.

II. Personal Experience with AI:

1. Experience WODs e.g. E18

I did not rely on ChatGPT or any AI tools for the experience WODs. I believe it’s important to take on the challenge of navigating uncertainty and finding the solution independently, as this is how I learn best. Additionally, if you’re unable to complete an experience WOD, most of them had a solution video, which makes using ChatGPT or AI unnecessary.

2. In-class Practice WODs

I did not use ChatGPT or AI for the in-class practice WODs as I felt that there wasn’t a need for me to. I wanted to make sure that I was using it as practice for the real in-class WODs and I wanted to ensure that I was understanding what I was doing during them. Furthermore, we also were able to work with a partner during them, so that made it easier to not use ChatGPT or AI.

3. In-class WODs

I did use ChatGPT for one of my in-class WODs, which was WOD: Typescript2. This is what I used it for: “I used ChatGPT to help resolve the error in my Score class where line, angle, style, and xfactor were giving the error of having no initializer and not being assigned in the constructor. To fix it, I took the answer ChatGPT gave which was to make them definite by adding a ‘!’ after the variable name.” In summary, I used it to fix an error that I was facing during the WOD, so I put it into ChatGPT and it gave me a solution that worked for it. Besides this WOD, I did not use ChatGPT in the in-class WODs.

4. Essays

For essays, I did use Grammarly to help correct simple mistakes such as punctuation and misspelling. Although, I did not use the grammar suggestions that it would give or suggestions that would change my wording because I feel that it takes away from my individuality.

5. Final project

For the final project, I used ChatGPT to help me learn how to write route.ts files (used for routing logics), as that is something that I have never done before. I did not ask specifically for the code to write the route.ts files, but to just guide me on how to write it so that I could understand how to write them on my own. Additionally, I would use this as a backup to help clarify parts I did not understand after watching a YouTube video or an online resource.

6. Learning a concept/tutorial

As mentioned in the final project section, I did use ChatGPT to help teach me how to write route.ts files. However, regarding the other aspects of the class, I did not use it as I felt the resources included in the modules were enough for me to learn everything. If there was something I felt I didn’t fully understand from the module, then I would look for a YouTube video to watch on that topic.

7. Answering a question in class or in Discord

I didn’t answer any questions in class as I felt there wasn’t really a need to and usually they would be answered or another classmate would have already asked the question. Additionally, I didn’t ask any questions in the Discord channel as I didn’t really feel that there was a need to. Therefore, I did not use ChatGPT or AI when answering a question in class or in Discord.

8. Asking or answering a smart-question

Since I did not really use the Discord except for mandatory announcements and assignments, I did not ask or answer smart-questions. However, I would take a look at the channel when I would have issues with an experience WOD or a homework assignment. If the issue was common and others were encountering it as well, I could resolve it quickly. But, if others did not ask about the issue I was having, I would assume that I did something wrong and try to resolve it on my own. I did not use ChatGPT or AI to ask or answer questions in the smart-questions channel.

9. Coding example

I did not use ChatGPT or AI to provide myself with coding examples. For me, all the resources provided in the modules were sufficient enough to understand usually, and if I still did not understand the topic, then I would depend on YouTube.

10. Explaining code

I did use ChatGPT to explain code for me when I was learning how to code something new, and I felt that the module resources and YouTube weren’t enough. For example, in the final project, I used it to help explain and guide me through how to write a route.ts file, since it was something new for me to do. Additionally, I also used it for WOD: Typescript2 so I could learn how to fix the error I was having, as stated above.

11. Writing code

I did use ChatGPT for WOD: Typescript2, but it was to fix an error that I was facing during it. Here’s what I used it for: “I used ChatGPT to help resolve the error in my Score class where line, angle, style, and xfactor were giving the error of having no initializer and not being assigned in the constructor. To fix it, I took the answer ChatGPT gave which was to make them definite by adding a ‘!’ after the variable name.” During this WOD, I was stuck with this error for a while so I found a solution through ChatGPT. Outside of this WOD, I did not use ChatGPT or AI to write code for me.

12. Documenting code

I did not use ChatGPT or AI to document code, as I would write the comments myself within the code. Even though ChatGPT or AI could write it, it often doesn’t provide comments that are in-depth and efficient. I also believe that the writer of the code should be the one who writes the comments for it so that whoever reads it knows what is happening from the writer’s perspective.

13. Quality assurance

I did not use ChatGPT or AI for quality assurance. I did feel though that some of the extensions we used like ESLint are the closest thing to it. It would always watch my code and was good about catching errors within it. Since ESLint did such a good job, I did not have a need to use AI for quality assurance.

14. Other uses in ICS 314 not listed

I did not use AI in ICS 314 outside of the prompts already listed.

III. Impact on Learning and Understanding:

AI is definitely a powerful tool that can enhance people’s learning experience. ChatGPT and AI did help me understand and learn more from this class, since I was not using it to help provide answers to code with it. Instead, I would use it to teach me how to do things and guide me through how to do things. Additionally, anywhere in the technology field where you may encounter problems that people are not readily available to help you solve, AI could assist in that struggle.

IV. Practical Applications:

In some of my other classes (not in ICS 314), I have used ChatGPT and AI to find sources that were relevant to topics I was looking for, since I found that it could find sources pretty efficiently. When writing an informative essay, ChatGPT can be used to find a new perspective. For example, when writing an informative essay on the psychology and benefits of incorporating regular breaks in your study sessions, it could be difficult finding sources on such a niche topic. Using ChatGPT to find sources that may indirectly relate to the topic strengthens the structure and points of the essay.

Besides using it for some of my other classes, I don’t really use ChatGPT or AI, since I don’t really have a use for it outside of that.

V. Challenges and Opportunities:

The most significant drawback of AI is its tendency to provide incorrect information. This is frustrating when the errors are very obvious, and can be especially problematic in technical domains like mathematics, where AI might provide elaborate solution steps while inadvertently introducing extremely difficult calculations. In addition to this, AI struggles to accurately reflect a user’s depth of understanding on a specific topic.

Despite these challenges, AI’s potential remains extraordinary. Its applications span numerous fields, and it continues to improve in accuracy and efficiency. Looking ahead, AI could potentially develop capabilities like creating comprehensive academic curricula based on authoritative sources. On a personal level, it might help individuals optimize their daily routines, while on a broader scale, it could assist policymakers in quickly accessing and comparing critical information, such as public health data across different communities.

VI. Comparative Analysis

In traditional educational approaches, students rely on resources provided by instructors, such as in-person lectures, prescribed textbooks, and study guides. However, these resources often have limitations: lectures can be excessively long, textbooks may contain unnecessary information, and study guides might not accurately reflect exam content.

Artificial Intelligence presents an alternative by offering more efficient information processing. AI can quickly analyze textbooks, extract key topics and main ideas, and generate targeted study guides. Learning materials could transform into flexible digital documents with multimedia resources like reference videos, accessible at the learner’s most productive times.

Many students already appreciate asynchronous learning, and AI could further enhance this approach by providing constant academic support. Unlike professors who may be challenging to contact, AI would be readily available to answer questions. While self-directed learning requires significant individual motivation, the educational experience could be personalized and more adaptive.

Nevertheless, human interaction remains crucial. Many students value synchronous classes and the social connections they provide, particularly in collaborative fields like software engineering. The most promising educational model might involve a balanced integration of AI tools with traditional instructor-led teaching, leveraging technology while maintaining essential human engagement.

VII. Future Considerations:

Beyond its current state, AI shows immense promise as a transformative force in education and software engineering. While challenges exist, such as occasional factual inaccuracies, addressing these issues will undoubtedly enhance AI’s capabilities. One potential solution might involve specialized AI platforms focused on specific academic domains, which could help mitigate the spread of misinformation. In the realm of educational technology, AI could potentially become a benchmark for coding practices, with future programming standards potentially emphasizing code that is AI-friendly—meaning it is clear, comprehensible, and easily manipulated by artificial intelligence systems.

VIII. Conclusion:

The current spotlight on artificial intelligence is huge, with promising developments in software engineering and education on the horizon. While AI technology continues to evolve, its present limitations are likely temporary. For scholars and researchers, the ability to quickly access curated information is invaluable, though the technology is still imperfect. Despite some concerns about the rapid pace of AI advancement, there’s still a genuine excitement about its potential to create meaningful global improvements.