Wednesday, August 26, 2026

AI 4: Experimenting with Potential Ways to Incorporate AI in My Teaching Practice


Rebecca A. Norton, Ph.D

Massachusetts Maritime Academy


This is the fourth in a series of four blog posts in response to the call: For many reasons, including AI, we had to adapt our teaching strategies and learn as we go this year. So let’s share what we found that was useful, promising, and/or positive in some way!  Our audience is NE-COMMIT and anyone else curious about improving teaching mathematics.


The posts are ordered from those describing practices more resistant to AI to those describing practices more embracing of AI.


Here are links to the remaining posts: AI 1 Thinking Video Notes to my future forgetful self by Christine von Renesse, AI 2 Changing My Writing Assignments by Debbie Borkovitz, and AI 3 Teaching Calculus III in the Age of AI by Ileana Vasu.


Using AI to help students prepare for class


Several years ago, I started asking students in my Applied Calculus course to prepare for their upcoming classes by “reading” a section in the eBook and answering a “Getting Ready for Class” question. I thought asking them to do some preparation (in addition to their problem sets), would accomplish a couple of things. First, I thought it might make things more equitable for students who had not previously taken Calculus. Second, I hoped that students would learn how to access and use their eBook.

In recent years, as you might suspect, students began to use AI to respond to the questions without ever opening their eBook. I gave students’ zeros and started requiring page and paragraph citations in their answers, but I quickly grew weary of “policing” their work. I still liked the idea of students preparing for class, though, and I was curious to know how to use AI to help students learn. So, I designed an assignment that asked students to paste the “Getting Ready for Class” question into an AI tool of their choice, and then answer some questions about the response that AI provided them. I implemented the new assignment via Blackboard in the Spring 2026 semester, and throughout the semester I made tweaks to the questions to try to get students to read and reflect on the information that AI provided them. Students completed the questions on Blackboard, so it is difficult to share the assignments with you, but below is a fairly typical exchange that a student had with AI when completing one of the assignments. The questions are numbered with the students’ response below each question. I kept the formatting the same as how it appeared in the student’s submission.


Directions: The following question comes from a "Getting Ready for Class" (GRC) assignment in your eBook. Read the GRC question and then complete the questions on the form below. NOTE: It is okay to copy and paste the question into an AI platform, but make sure to also include the designated prompt that is given in question 2.




1. Which AI tool(s) are you using?

chaptgpt


2. Prompt your AI tool to give you an answer to the GRC question without a lot of calculus  jargon. Copy and paste the response it gives you below (include the entire response): 


            \(f(x)=ln(g(x)) \)

            and 

            \(f(x)=e^{g(x)} \)

            are similar because both use the chain rule. In each function, there is an “inside

            function” \(g(x)\), so after differentiating the outside function, you multiply

            by the derivative of the inside function, \(g'(x)\).

            For \(f(x)=ln(g(x))\)

            \(f'(x)=g(x)g'(x)\). For \(f(x)=e^{g(x)}\):

            \(f'(x)=e^{g(x)} \cdot g'(x)\) In both cases, the derivative includes \(g′(x)\), which shows

            that both functions follow the same chain rule process.


3. After reading the AI tool's response, think of a good follow-up question that would help you clarify your understanding of the topic.  Do not use AI's suggested follow-up questions; think of your own follow-up question based on the answer AI provided.  The follow-up question must be directly related to AI's previous response.  Paste the prompt you give AI here:

how come for the ln problem, you have to divide compared to multiply?


4. Paste the AI tool's response to your follow-up question here:

            For logarithms:

            \(d/dx[ln(x)]=1/x\)

            So when the inside is \(g(x)\), the chain rule gives:

            \(\frac{1}{g(x)} \cdot g'(x)\) which is the same as:

            \(\frac{g'(x)}{g(x)}\). That is why you divide.



5. What is one thing that you learned in AI's initial and/or follow-up response(s)?  Be specific, and use your own words.  (Do not copy and paste from the AI tool's response(s).

I learned that the reason you divide is because it's actually 1 over g(x) times the

derivative of g(x) which is the same as dividing.


6. What is one thing that you think AI could have done better to help you understand the topic?

I feel like it could have answered the questions in a shorter, more simple way.

For my last questions when I asked why I divided, there was a long complex

explanation, but when I asked again it gave me it in a simple sentence.


7. OPTIONAL: Did you find any errors in any of the AI tool's responses that you pasted above?  If so, explain what the mistake was.  If Dr. Norton agrees with you, you'll earn an extra point on the next quiz.  If not, type "N/A".

NA




Overall, I think using AI made for a better assignment than I had been giving in

previous semesters. There were still some students who were “gaming” the

assignment and not putting much effort into learning anything by completing it. 

There are others who I think found it helpful.  As a first adventure into using AI

in my classroom, I think it worked fairly well. Here are a few positives I observed:


A) More students were completing the AI assignments than they had been in my

previous classes where I used the original prep assignments.  They seemed more

willing to read the output of an AI model than they were a section of an eBook.

B) AI’s responses do not include body language, tone of voice, or negative words

that may discourage students from asking questions.  Plus, it never tires of

questions or runs out of time.  In that way, AI can serve as a valuable and patient

tutor or study partner, and students in my class seemed to be comfortable

interacting with AI.

C) My students were exposed to different ways to prompt AI, witnessed the results

that followed based on different types of  prompts, and reflected whether AI’s

response was helpful.  “Prompt engineering” is something that I have personally

gotten much better at compared to when I first started using AI; I think my students

may have learned a little about that, too.

D) Finally, on a personal level, I learned more about which AI tools my students

were relying on, which was something I was curious about, and I also saw the

differences in how the different tools answered the same questions.  ChatGPT

was the most popular model among my students, but there were a variety of

different models that students used.  ChatGPT is the most verbose in its responses.


Here are a few negatives:

A) Though AI seems to be fairly reliable in explaining topics related to math, it still

gets things wrong, and sometimes hallucinates.  It seems to have difficulty creating

graphics.  I saw a lot of confusing and inaccurate graphs/diagrams in students’

submissions. Here’s an example:





B) Very few students took me up on the last question to earn extra credit if they

found something wrong with AI’s response.  That worried me because it means

that they were not recognizing when AI was telling them something inappropriate.

C) Certain models, especially ChatGPT, provided “tips” for students about what

they should write for credit.  For example, it would say something like, “If you want,

I can give you a super short one-sentence answer that you can write on a test.  It

was as if the model had been trained on providing students shortcuts instead of

helping them to learn the concepts.


Despite what my students may or may not have learned by completing these

assignments, I learned a great deal by reading the responses, and I grew much

more comfortable with knowing what to expect from AI.  I am debating on whether

I want to use this type of assignment again with my students.  On one hand, it

would be easy to do, because all of the assignments are set up in Blackboard

ready to be used again.  On the other hand, based on some additional experimentation

I did with AI over the summer, I think I have found a more useful way to use AI to

help students prepare.  I write about it in the section below titled “Creating a ‘Study

Buddy’ bot for students to interact with.”


Trying to get AI to evaluate students’ homework assignments


At the start of the Spring 2026 semester, I decided not to use the online homework

system that was associated with the eBook I was using in my Applied Calculus

course.  Based on my own observations and discussions with other professors in

my department, I realized that even though students were completing the

assignments, they were not getting the practice they needed.  It was too easy to

cut and paste homework problems into AI and get the answer for the problems on

the assignment.  I thought that if I asked students to turn in a written assignment on

Blackboard that even if they ended up using AI to complete the problems, they would

at least have to write the work down, and that would be more helpful than just cutting

and pasting answers online.

  

Fresh from the winter break, and not thinking carefully about my time commitments,

I thought that if I used a rubric to grade the homework assignments, I’d be able to

turn them around quickly enough to provide relevant feedback to my students.  As

the semester progressed, however, I got behind in grading them, and found myself

at the bottom of a grading hole.  Since grading is tedious, and it is difficult to motivate

myself to do it, I started experimenting with AI to see if it could help.


I began using an AI platform called BoodleBox because my school had bought a

license for the Spring semester for faculty to experiment with. The platform is

designed for educational settings.  It claims that it somehow provides access to

different AI agents without allowing those agents to collect information about the

interactions that you have with it.  I am skeptical about that part, but I took my

chances and experimented anyway.  I wanted to see if I could teach it how to apply

a rubric to my students’ submissions and provide an appropriate grade.

 

I provided the AI agent with my rubric and an answer key for the relevant problems,

and without any other input,  it did a decent grading job.  It applied the rubric a little

differently than I did, though, so I created a flowchart to guide the AI agent to apply

the rubric in a way that it would arrive at the same score as me.  That took some

effort.  I tweaked the flowchart by doing several grading runs where I compared

the scores I assigned using the rubric versus the scores that AI assigned.  I also

added in some steps based on the feedback that the AI agent gave me so it would provide me with more reliable results.  Here is a link to the flowchart I ended up with.


In general, I was happy with the way AI implemented the flowchart;  I was definitely pleased with how quickly it could apply it and format the output for me.  It turned out, however, that the whole process was not as efficient as I had hoped.  AI often had difficulty with students’ handwriting, or finding all of the problems within a student’s submission, or being unable to read the problems if the student submitted a photograph of poor quality.  In those cases, it would grade the assignments based on what it could read, and then flag it for me to review.  When I looked at those cases, it rarely provided the appropriate grade.  In its defense, it gave me some advice to help improve its ability to score the submissions, but its main suggestion was that I ask students to format their homework in a specific way.  Since the students had already turned in the assignments, I was not able to implement the advice it gave.  Additionally, based on specifications with the BoodleBox platform, I had to upload the students’ work in batches and that eally slowed the whole process down.

 

In the end, I don’t think I saved any time in grading my assignments for the Spring 2026 semester.  In fact, I may have spent more time trying to tweak things with my flowchart than I would have if I had just graded the assignments.  It wouldn’t have been as fun, though!  Plus, I’ll be able to use what I designed in the future.  Now that I know what the model needs in order to process the students’ submissions accurately, I can require that students complete their work in the required format.  I will also consider using a homework folder on BoodleBox, which is another suggestion the platform gave to me,because then it could check to see if a student’s submission was acceptable and require the student to resubmit their assignment if the model was unable to read it.  Plus, having the student upload it directly to BoodleBox would keep me from having to transfer the files between Blackboard and BoodleBox, which was the biggest time consumer in getting AI to grade the assignments.

 

Overall,, I learned a lot about how to interact with an AI agent in a productive way.  It felt a bit like having a teaching assistant.  As I noted in the previous section, AI never gets tired and it is not possible to hurt its feelings.  So it is perfectly “happy” to make adjustments until you are satisfied with the outcome.  It is important to be explicit in your instructions, though, because it will assume things that may or may not align with your own philosophies.  In coming semesters, I plan to implement the lessons I learned during the Spring 2026 semester and continue to experiment with asking AI to apply rubrics to help grade student assignments.



Creating a “Study Buddy” bot for students to interact with


At the last minute, I was asked to co-teach a summer course called Introduction to Python for Business Data Analysis.  I did not have much time to prepare.  It was not a course I had ever taught before, and it was not a course that my school had offered before, so I didn’t have anyone else’s materials to borrow from.  Plus, it had been a while since I’d really done any programming myself.  So, I knew I was going to have to leave myself lots of planning and thinking time to make sure I was prepared to teach the classes, especially since each summer class was the equivalent of a week during a regular semester.  

I wanted to make assignments that provided students with some feedback, but that I would not have to spend much time looking at or commenting on myself.  I had learned my lesson trying to collect and look over my students’ homework in my Applied Calculus class during the Spring 2026 semester, and I did not want to dig myself into any more grading holes!  So, I tried to design a bot within BoodleBox that specialized in the material that we were focusing on.  I named it “Python Study Buddy”.  You may have to sign up for a BoodleBox account, but if you do, you can try it out here:


https://box.boodle.ai/a/@PythonStudyBuddy


Last I checked, BoodleBox was giving two-month free trials.  If you do call up the bot, the first thing it will ask you is what chapter you want to work on.  Tell it a chapter number between 7-14; those are the chapters in Part II of a book by Lee Vaughn titled Python Tools for Scientists.  Students were required to buy a pdf version of the book.

In between class meetings, students were assigned to interact with the bot.  At the end of the session, students would ask the bot to print out a transcript, and then upload the transcript to Blackboard.  I then reviewed the transcript and assigned a grade based on a rubric.  The rubric included four categories: Topic, Productive Interaction, Demonstrated Learning, and Time-on-Task.  As an aside, I had AI create the initial draft of the rubric based on a description I gave it. 


I considered this use of AI to be a success.  The bot acted as an assistant that condensed the information that I needed to give students the proper grade and allowed me to apply my rubric quickly.  Additionally, at the end of the course, several of the students mentioned how helpful they had found Study Buddy and that they used it as their main study tool because it helped them decipher the information within each chapter in a conversational way.  I will definitely continue to experiment with similar tools in my upcoming classes this fall. 










AI 4: Experimenting with Potential Ways to Incorporate AI in My Teaching Practice

Rebecca A. Norton, Ph.D Massachusetts Maritime Academy This is the fourth in a series of four blog posts in response to the call: For many...