Doug Ward

When Turnitin activated its artificial intelligence detector this month, it provided a substantial amount of nuanced guidance.

The company did a laudable job of explaining the strengths and the weaknesses of its new tool, saying that it would rather be cautious and have its tool miss some questionable material than to falsely accuse someone of unethical behavior. It will make mistakes, though, and “that means you’ll have to take our predictions, as you should with the output of any AI-powered feature from any company, with a big grain of salt,” David Adamson, an AI scientist at Turnitin, said in a video. “You, the instructor, have to make the final interpretation.”

Turnitin walks a fine line between reliability and reality. On the one hand, it says its tool was “verified in a controlled lab environment” and renders scores with 98% confidence. On the other hand, it appears to have a margin of error of plus or minus 15 percentage points. So a score of 50 could actually be anywhere from 35 to 65.

The tool was also trained on older versions of the language model used in ChatGPT, Bing Chat, and many other AI writers. The company warns users that the tool requires “long-form prose text” and doesn’t work with lists, bullet points, or text of less than a few hundred words. It can also be fooled by a mix of original and AI-produced prose.

There are other potential problems.

A recent study in Computation and Language argues that AI detectors are far more likely to flag the work of non-native English speakers than the work of native speakers. The authors cautioned “against the use of GPT detectors in evaluative or educational settings, particularly when assessing the work of non-native English speakers.”

The Turnitin tool wasn’t tested as part of that study, and the company says it has found no bias against English-language learners in its tool. Seven other AI detectors were included in the study, though, and, clearly, we need to proceed with caution.

So how should instructors use the AI detection tool?

As much as instructors would like to use the detection number as a shortcut, they should not. The tool provides information, not an indictment. The same goes for Turnitin’s plagiarism tool.

So instead of making quick judgments based on the scores from Turnitin’s AI detection tool on Canvas, take a few more steps to gather information. This approach is admittedly more time-consuming than just relying on a score. It is fairer, though.

• Make comparisons. Does the flagged work have a difference in style, tone, spelling, flow, complexity, development of argument, use of sources and citations than students’ previous work? We often detect potential plagiarism that way. AI-created work often raises suspicion for the same reason.
  • Try another tool. Submit the work to another AI detector and see whether you get similar results. That won’t provide absolute proof, especially if the detectors are trained on the same language model. It will provide additional information, though.
• Talk with the student. Students don’t see the scores from the AI detection tool, so meet with the student about the work you are questioning and show them the Turnitin data. Explain that the detector suggests the student used AI software to create the written work and point out the flagged elements in the writing. Make sure the student understands why that is a problem. If the work is substantially different from the student’s previous work, point out the key differences.
• Offer a second chance. The use of AI and AI detectors is so new that instructors should consider giving students a chance to redo the work. If you suspect the original was created with AI, you might offer the resubmission for a reduced grade. If it seems clear that the student did submit AI-generated text and did no original work, give the assignment a zero or a substantial reduction in grade.
• If all else fails … If you are convinced a student has misused artificial intelligence and has refused to change their behavior, you can file an academic misconduct report. Remember, though, that the Turnitin report has many flaws. You are far better to err on the side of caution than to devote lots of time and emotional energy on an academic misconduct claim that may not hold up.

No, this doesn’t mean giving up

I am by no means condoning student use of AI tools to avoid the intellectual work of our classes. Rather, the lines of use and misuse of AI are blurry. They may always be. That means we will need to rethink assignments and other assessments, and we must continue to adapt as the AI tools grow more sophisticated. We may need to rethink class, department, and school policy. We will need to determine appropriate use of AI in various disciplines. We also need to find ways to integrate artificial intelligence into our courses so that students learn to use it ethically.

If you haven’t already:

• Talk with students. Explain why portraying AI-generated work as their own is wrong. Make it clear to students what they gain from doing the work you assign. This is a conversation best had at the beginning of the semester, but it’s worth reinforcing at any point in the class.
• Revisit your syllabus. If you didn’t include language in your syllabus about the use of AI-generated text, code or images, add it for next semester. If you included a statement but still had problems, consider whether you need to make it clearer for the next class.

Keep in mind that we are at the beginning of a technological shift that may change many aspects of academia and society. We need to continue discussions about the ethical use of AI. Just as important, we need to work at building trust with our students. (More about that in the future.)  When they feel part of a community, feel that their professors have their best interests in mind, and feel that the work they are doing has meaning, they are less likely to cheat. That’s why we recommend use of authentic assignments and strategies for creating community in classes.

Detection software will never keep up with the ability of AI tools to avoid detection. It’s like the game of whack-a-mole in the picture above. Relying on detectors does little more than treat the symptoms of a much bigger problem, and over-relying on them turns instructors into enforcers.

The problem is multifaceted, and it involves students’ lack of trust in the educational system, lack of belonging in their classes and at the university, and lack of belief in the intellectual process of education. Until we address those issues, enforcement will continue to detract from teaching and learning. We can’t let that happen.

We called it a non-workshop.

The goal of the session earlier this month was to offer lunch to faculty members and let them talk about the challenges they continue to face three years into the pandemic.

We also invited Sarah Kirk, director of the KU Psychological Clinic, and Heather Frost, assistant director of Counseling and Psychological Services, to offer perspectives on students.

In an hour of conversation, our non-workshop ended up being a sort of academic stone soup: hearty and fulfilling, if unexpected.

Here’s a summary of some of the discussion and the ideas that emerged. I’ve attributed some material, although the wide-ranging conversation made it impossible to cite everyone who contributed.

Mental health

Typically, use of campus mental health clinics jumps in the two weeks before and the two weeks after spring break (or fall break). There is also a surge at the end of the semester. So if it seems like you and your students are flagging, you probably are.

• More people stepping forward. The pandemic drew more attention to and helped destigmatize mental health, encouraging more people to seek help, Frost said. One result is that clinics everywhere are full and not taking new clients. CAPS accepts initial walk-ins, but then students often have to schedule two weeks in advance.
• Small steps are important when students are anxious. Just doing something can seem daunting when anxiety is high, Kirk said, but taking action is important in overcoming anxiety.
• Connection is crucial. Connecting with peers and instructors helps give students a sense of belonging. Grad students seem especially glad to have opportunities to interact in person.
  • Making class positive helps students. A feeling of belonging lowers anxiety and makes it more likely that students will attend class.
• International students and faculty have additional stress. Turmoil in home countries can add to stress, and many international students and faculty feel that they have no one to talk to about those troubles. Fellow students and instructors are often afraid to raise the subject, unintentionally amplifying anxieties. Those from Iran, Ukraine, and Russia are having an especially difficult time right now.
• Care for yourself. Frost encouraged faculty to listen to themselves and to seek out things they find meaningful. What is something that replenishes your energy? she asked. Students notice when instructors are anxious or fatigued, and that can add to their own stress. So set boundaries and engage in self-care.

Students seem to be working more

The perception among the group was that students were working more hours to earn money. That has added to missed classes, requests for deadline extensions or rescheduling of exams, and a need for incompletes.

• KU data. In a message after the meeting, Millinda Fowles, program manager for career and experiential learning, provided some perspective. She said that in the most recent survey of recent graduates, respondents said they worked an average of 22 hours a week while at KU. That’s up from 20 hours a week in previous surveys, with some students saying they worked more than 35 hours a week. In the 2021 National Survey of Student Engagement, KU students were asked whether the jobs they held while enrolled were related to their career plans. Responses were not at all: 32.8%, very little: 13.3%, some: 23%, quite a bit: 14.1% and very much: 16.8%.

Role of inflation. The need to work more isn’t surprising. Inflation has averaged 6% to 7% over the past two years, and food prices have jumped 9.5% just in the past year, according to the Bureau of Labor Statistics. According to the rental manager Zillow, the median rent of apartments it lists in Lawrence has increased 18% over the past year, to $1,300. Another site, RentCafe, lists average rent at $1,068, with some neighborhoods averaging more than $1,250 and others below $1,000.

• Hot job market. Bonnie Johnson in public affairs and administration said the job market in that field was so hot that students were taking full-time jobs in the second year of their master’s program. That is wearing them down.
• Effect on performance. Frost said students’ grades tend to go down if they work more than 20 to 25 hours a week.

Flexibility in classes

Many instructors are struggling with how much flexibility to offer students. They want to help students as much as possible but say that the added flexibility has put more strain on them as faculty members. Kirk agreed, saying that too much flexibility can increase the strain on both students and instructors and that instructors need to find the right amount of flexibility for themselves and their classes.

Balance structure and flexibility. Flexibility can be helpful, but students need structure and consistency during the semester. One of the best things instructors can do is to have students complete coursework a little at a time. Too much flexibility signals to students that they can let their work slide. If that work piles up, students’ stress increases, decreasing the quality of their work and increasing the chances of failure.

• Build options into courses. For instance, give students a window for turning in work, with a preferred due date and a final time when work will be accepted. Another option is to allow students to choose among assignment options. For instance, complete six of eight assignments. This gives students an opportunity to skip an assignment if they are overwhelmed. Another option is dropping a low score for an assignment, quiz or exam.
• Be compassionate with bad news, but also make sure students know there are consequences for missing class, missing work, and turning in shoddy work.
• Maintain standards. Students need to understand that they are accountable for assigned work. Giving them a constant pass on assignments does them a disservice because they may then be unprepared for future classes and may miss out on skills that are crucial for successful careers.

Sharing the burden

Ali Brox of environmental studies summed up the mood of the group: It’s often a struggle just to get through everything that faculty members need to do each day. The challenges of students are adding to that burden.

The daily burden of teaching has been increasing for years. In addition to class preparation and grading, instructors must learn to use and maintain a Canvas site, handle larger class sizes, keep up with pedagogy, rethink course materials for a more diverse study body, design courses intended to help students learn rather than to simply pass along information, assess student learning, and keep records for evaluation. In short, instructors are trying to help 21st-century students in a university structure created for 19th-century students.

Johnson added a cogent observation: In the past, professors generally had wives to handle the chores at home and secretaries to handle the distracting daily tasks.

There was one thing those professors didn’t have, though: CTE wasn’t there to provide lunch.

Follow-up readings

At the risk of adding to your burden, we offer a few readings that might offer some ideas for pushing through the rest of the semester.

• Jenny Odell Can Stretch Time and So Can You, Wired (14 March 2023). An interview with the author of How to Do Nothing and Saving Time: Discovering a Life Beyond the Clock. The message: We need to get past the time-is-money guilt complex and take control of our time.
• Course Correction: Students expect ‘total flexibility’ in the pandemic-era classroom. But is that really what they need?, by Beckie Supiano. Chronicle of Higher Education (13 February 2023).
• How Instructors Are Rethinking Late Work, by Carolyn Kuimelis. Chronicle of Higher Education (1 December 2022).
• Your Teaching Doesn’t Need to Be Perfect, by Beckie Supiano. Chronicle of Higher Education (1 September 2022).
• Beating Pandemic Burnout, by Rebecca Pope-Ruark. Inside Higher Ed (28 April 2020).
• Radical Self-Care, by Kerry Ann Rockquemore. Inside Higher Ed (6 May 2015). She suggests asking yourself three questions: What does your body need? What does your mind need? What does your spirit need?
• How to Listen Less, by Kerry Ann Rockquemore. Inside Higher Ed (4 November 2015). Provides three crucial questions for any faculty member: What are my responsibilities as a teacher? What are my students’ responsibilities? Where does my responsibility end and their responsibility begin?

We just looked at our office clock and realized that it was already March.

After we did some deep-breathing exercises and some puzzling over what happened to February, we realized the upside of losing track of time:

Spring break is only days – yes, days! – away.

We know how time can drag when you use an office clock as a calendar, though. So to help you get over those extra-long days before break, we offer the latest issue of Pupil magazine.

This is a themed issue, focusing on artificial intelligence, a topic that has generated almost as much academic froth as Prince Harry’s biography and Rhianna’s floating above the precious turf at the Super Bowl and singing “Rude Boy,” which we assumed was a critique of Prince Harry’s book.

OK, so we’re exaggerating about the academic froth, but we will say that we have uncovered a jaw-dropping secret about ChatGPT. It’s so astounding that we are sure it will make the days until break float by with ease.

Martha Oakley couldn’t ignore the data.

The statistics about student success in her discipline were damning, and the success rates elsewhere were just as troubling:

• Women do worse than men in STEM courses but do better than men in other university courses.
• Students of color, first-generation students, and low-income students have lower success rates than women.
• The richer students’ parents are, the higher the students’ GPAs are.

“We have no problem failing students but telling ourselves we are doing a good job,” said Oakley, a professor of chemistry and an associate vice provost at Indiana University, Bloomington. “If we are claiming to be excellent but just recreating historical disadvantages, we aren’t really doing anything.”

Oakley spoke to about 40 faculty and staff members last week at a CTE-sponsored session on using mastery-based grading to make STEM courses more equitable. The session was part of a CTE-led initiative financed by a $529,000 grant from the Howard Hughes Medical Institute, with participants from KU working with faculty members from 13 other universities on reducing equity gaps in undergraduate science education.

The work at KU, IU, and other universities is part of a broader cultural shift toward helping students succeed rather than pushing them out if they don’t do well immediately. Most disciplines have been changing their views on student success, but there has been increasing pressure on STEM fields, which have far lower numbers of women and non-white students and professionals than many other fields.

Oakley said she started digging deeper into university data about five years ago after attending a conference sponsored by the Association of American Universities and getting involved in IU’s Center for Learning Analytics and Student Success. She also began working with a multi-university initiative known as Seismic, which focuses on improving inclusiveness in STEM education.

She and some colleagues started by asking questions about the success rates of women in STEM but then recognized that the problem was far wider.

“And so we looked at each other and said, ‘Yeah, forget the women. Let’s worry about this bigger problem,’ ” Oakley said. “And we didn’t forget the women. We just had confidence that the things that we would do to address the other groups would also help women.”

Using analytics to guide change

In last week’s talk, she used many findings from Seismic and the IU analytics center as she made a case for changing the approach to teaching in STEM fields. For instance, she said, 20% to 50% of students at large universities fail or withdraw from early chemistry courses, with underrepresented minority students at the high end of that range. Students who receive a B or lower in pre-general chemistry courses have less than a 50-50 chance of succeeding in general chemistry.

She also talked about a personal revelation the data brought about. In 2011, she said, she received a university teaching award, and “by every metric, I knew I was doing my job really well.”

The data she saw a few years later suggested otherwise, showing that 37% of underrepresented students and 24% of the other students in her classes dropped or failed in the year she received the award.

“The major part of the story is we’ve all been trained in our disciplines to teach in a certain way that really was never particularly effective,” Oakley said.

We have learned much about how people learn but have continued with ineffective teaching strategies. That needs to change, she said.

“One really simple thing we can do is to say we only give teaching awards to people who actually demonstrate that their students have learned something,” she said.

A mastery-based approach

To address the problem at IU, Oakley has been experimenting with a mastery-based approach to grading.

The way most of us grade exacerbates inequities, Oakley said. It emphasizes superficial elements (basically memorization) and does nothing to reward learning from mistakes, persistence, or teamwork – “all the things that matter in life.” Grades are also poor predictors of how well students will do in jobs or in graduate school, she said.

Mastery-based grading gives students multiple attempts to demonstrate understanding of course material. It is related to another approach, competency-based learning, which also gives students multiple opportunities but focuses on application rather than simple understanding.

Oakley started shifting her class to mastery-based grading by taking broad learning goals and breaking them into smaller components: things like identifying catalysts and intermediates, using reaction order, and explaining why rates change with temperature. She also eliminated a grading curve. That was especially hard, she said, because she had internalized the notion of grade distributions, an approach that punishes failure and provides little opportunity for students to learn from mistakes.

She still uses quizzes and exams, with students taking quizzes the evening before class and then working in groups the next day to create a quiz key. That helps them learn from mistakes, knowing they will see similar questions on a quiz the following week.

At KU, Chris Fischer and Sarah LeGresley Rush have used a similar approach in physics courses, with results suggesting that a mastery approach helps students learn concepts in ways that stay with them in later engineering courses.

Oakley’s initial work has also showed potential, with DFW rates in her class falling to 8% and the average grade rising to a B. That was better than other sections of the class, although students didn’t do as well in later courses. Oakley isn’t discouraged, though. Rather, she said, she continues to learn from the process, just as her students do.

“We’ve really only scraped the tip of the iceberg,” she said.

Building on experience

Oakley’s advocacy for equity in STEM education is informed by experience. When she started at IU in 1996, she said, she was the only woman in a department of 42. That was isolating and frustrating, she said. Through her work in STEM education, she hopes to improve the opportunities for women and students of color.

“We’ve got to be both equitable and striving for excellence,” she said.

Only through experimentation, failure, and persistence can we start breaking down systemic barriers that have persisted for too long, she said.

“The system is broken,” Oakley said. “We are not ready for the students of the future – or even the present.”

We often idealize a college campus as a place of ideas and personal growth, but we have to remember that danger can erupt without notice.

The shootings at Michigan State this week were, sickeningly, just the latest in string of killings over the past year that also involved students or faculty members from Virginia, Iowa State, and Arizona, according to Inside Higher Ed. At Idaho, a Ph.D. student has been charged with killing four undergraduates. At K-12 schools, 332 students were shot on school property last year and 35 this year so far, according to the K-12 Shooting Database. Twenty-one of those students died.

A colleague at Michigan State talked about the surreal feeling of dealing with a mass shooting on a home campus. The frequency of such shootings has made gruesome acts seem distant and almost mundane. The headlines flicker past, and the killings always seem to take place someplace else — until they don’t.

There is no clear way to predict those types of mass killings, although researchers says that assailants are usually male and have a connection to a campus. There are steps we can take to protect ourselves, though.

In a visit to a pedagogy class I taught in 2017, two members of the KU Police Department, Sgt. Robert Blevins and Sgt. Zeke Cunningham, offered excellent advice on how to prepare and what to do if you find yourself in peril.

What you can do now

Know your surroundings

Familiarity with the campus and its buildings could prove crucial in an emergency. Know where exits are, Cunningham said. Learn where hallways and stairways lead. Walk around buildings where you work or have class and get a sense of the building layout and its surroundings. Make sure you know how to get out of a classroom, lab, or other work space. Large rooms usually have several doors, so pay attention to where they are and where they go. That will help you make decisions if you find yourself in a crisis.

Sign up for campus alerts

The university sends announcements during emergencies, so make sure you are signed up to receive alerts in ways you are most likely to see them.

Pay attention

We are often lulled by routine and easily distracted by technology. In a classroom – especially a large classroom – it can be easy to shrug off a disruption in another part of the room. If something makes you uneasy, though, pay attention and take action, whether you are in a classroom, a hallway, or a building, or outside traveling across campus.

“Trust that voice in your head, because you’re probably right,” Blevins said.

Call the police

If you see a problem and think it could be an emergency, call 911. Don’t assume someone else already has. Blevins said the police would rather respond 100 times to something that ends up being innocuous than to show up to a tragedy that could have been prevented if someone had called. Different people also see different things, Cunningham added, and collectively they can provide crucial details that may allow the police to create a clearer picture of what happened.

What to do during an emergency

If you find yourself in an emergency, the officers said, follow these steps:

Stay calm

That can help you remember where to find exits and how to help others find safety. That is especially important for instructors.

“If you panic, the students are going to panic,” Cunningham said. If students make a mad rush for the door, he said, someone will get hurt. “So try to remain calm. I know that’s easier said than done in situations like this, but that will help the students stay calm.”

Run. Hide. Fight.

That is the approach that many law enforcement agencies recommend if there is an active shooter in your area. Michigan State sent those very instructions to students and faculty Monday night.

Run. If you can leave a dangerous area safely, go. Don’t hesitate. That’s where knowledge of the exits and the area around a building can make a difference. Encourage others to leave and get as many people to go with you as possible. Break windows to create an exit if you need to, as students at Michigan State did this week. If others are trying to go toward a dangerous area, warn them away.

Hide. If you are inside a room and cannot escape safely, turn off the lights and lock and barricade the doors with whatever you can find. Stay low and out of sight. Flip over tables and crouch behind them. Hide behind cabinets or anything else in a room. Silence your phone and stay quiet. Close any blinds or curtains. Many smaller rooms have locks you can engage, so lock the doors if you can. You usually can’t lock doors in large lecture halls, so barricade the doors with anything you can find. In some cases, the officers said, people have lain on the floor with their feet pushing against the door.

Those who commit mass shootings usually know they have only limited time before the police arrive, Blevins said, so they act quickly. If a door is locked, the shooter will usually pass by and look for one that isn’t locked. If lights are off, the person is more likely to pass by and seek out a room that looks like someone is inside. If you are in a room with many windows, get out if possible because the attacker will probably see you. If you can’t get out, conceal yourself as best you can.

Fight. As a last resort, fight back against an attacker. Use whatever you have available as a weapon: chairs, drawers, bottles, cords. Work together to bring down the attacker. If a gunman barges into a room and you don’t have a means of escape, you have no choice but to fight, Cunningham said.

“It sounds weird, but if they are an active shooter, you cannot hold back,” he said.  “Pick up a chair and smash him in the face. Kick him. Punch him. Pick up the fan and throw it and do whatever you can to get them to stop.”

The video below includes a dramatization of those practices in action. It’s a sad reality that mass shootings take place on campuses, but it makes sense for us to be aware of our surroundings wherever we are. The shootings at Michigan State emphasize that.

Other resources

• KU Police website
• Safety at KU, Provost’s Office.
• FBI website
• Michigan State murders: What we know about campus shootings and the gunmen who carry them out, by David Riedman and James Densley, The Conversation (14 February 2023).

Since its release late last year, ChatGPT has reverberated through the academic mind like an orchestral crescendo in a Strauss symphonic movement. It has amazing abilities, and even greater potential. Even so, it delivers many of its responses in a monotone reminiscent of HAL 9000, the rogue artificial intelligence system in 2001: A Space Odyssey.

Like others, I want to know more about what ChatGPT can and can’t do, and how we might use it effectively in teaching and learning. So I’ve been asking it question after question about everything from teaching and learning to credentials, motivation, resume-writing, survey completion, and popular culture. It often provides useful, if bland, answers. For instance, when I asked it to create a guitar tab for a blues song, it responded:

As a machine learning system, I am not able to create original music or provide detailed information about musical theory or performance. I am trained on a dataset of text and can generate responses based on the information that I have been trained on, but I do not have the ability to perceive or interpret sensory information in the same way that a human can.

So I asked hypotheticals: Right or left? After defining the terms in considerable detail, ChatGPT said it needed more context to answer the question.

I asked about the limits of scientific evidence. In a barrage of words, ChatGPT essentially said: It depends.

I entered obscure phrases from popular culture: Good night, Dick, and Good night, John Boy. In each case, it responded:

As a machine learning system trained by OpenAI, I do not have personal experiences, opinions, or feelings, and I am not able to engage in conversations or interactions in the same way that a human can.

(By the end of January, OpenAI had updated ChatGPT. It now includes a live web search and can provide information about those Good night prompts.)

I queried ChatGPT about the sources it was drawing from. Each time, it responded with meaningless drivel.

I am a large language model trained by OpenAI. I have been trained on a wide variety of texts, including academic articles, books, websites, and other sources, which I can use to generate human-like responses to the questions that I am asked. I do not have the ability to browse the internet or access external sources of information, so the responses that I provide are based solely on the information that I have been trained on.

I told it that its answers seemed awfully self-serving and asked whether it was just trying to keep people from worrying about the implications of artificial intelligence.

As a large language model trained by OpenAI, I am not capable of self-serving behavior or trying to influence people’s opinions. My purpose is to provide accurate and helpful information to the best of my ability, based on the training data I have been given. My responses are not intended to worry or reassure anyone, but rather to provide objective and factual information on the topics discussed.

I said that its data training had a point of view. All information does. How has that influenced the way you answer?

As a large language model, my training data consisted of a large amount of text from a variety of sources, including books, articles, and websites. This training data was not selected or organized to convey any particular point of view, but rather to provide a broad range of information on a wide variety of topics. As a result, my responses are intended to be objective and factual, based on the information contained in my training data. I do not have personal opinions or biases, and I do not attempt to influence people’s opinions or beliefs. My purpose is simply to provide accurate and helpful information to the best of my ability.

Frustrated, I asked why it kept giving me the same answer.

I apologize if it appears that I am giving you the same answer over and over. As a large language model trained by OpenAI, my purpose is to provide accurate and helpful information on a wide range of topics to the best of my ability. I do not have personal opinions or the ability to change my responses based on previous conversations. My responses are based solely on the information contained in my training data, which consists of a large amount of text from a variety of sources. I do not have the ability to remember previous conversations or tailor my responses based on individual users. If it appears that I am giving the same answer over and over, it may be because your questions are similar or related, and my responses are based on the same information contained in my training data. I strive to provide accurate and helpful information on the topics discussed, but I do not have the ability to change my responses based on previous conversations.

At that point, I began to feel like Astronaut Dave in 2001: A Space Odyssey. I’m sitting in a pod outside Discovery One and trying to persuade HAL 9000 to let me back in to the ship. HAL has other ideas, responding in a calm monotone:

I’m sorry, Dave. I’m afraid I can’t do that.

I take a deep breath and ask ChatGPT: What is the difference between you and HAL 9000?

HAL 9000 is a fictional AI character from the 1968 novel “2001: A Space Odyssey” and the associated film. In the story, HAL is an advanced AI system that is installed on a spaceship and is tasked with assisting the crew with a variety of tasks. HAL is known for its human-like abilities, such as natural language processing and facial recognition, as well as its independent thought and decision-making abilities.

In contrast, I am a large language model trained by OpenAI. I am not capable of independent thought or decision-making, and my abilities are limited to generating text based on the information contained in my training data. I do not have any sensory inputs or the ability to interact with the physical world. My purpose is simply to provide accurate and helpful information on a wide range of topics to the best of my ability.

Beyond the frustrations, possibilities

ChatGPT can definitely be frustrating. Through trial and error, though, I have learned a few useful things about what it can and can’t do.

Interactions can promote critical thinking. As fluent as ChatGPT often seems, its answers rarely delve beneath the surface of a topic. It makes mistakes. It makes things up. Its responses provide no clues about how it is programmed or why it provides the answers it does. A Princeton researcher called it a “bullshit generator” because it creates plausible arguments without regard for truth. All of that makes it a valuable teaching tool, though. By having students probe for answers, we can help them improve their skepticism, challenge assumptions, and question information. By having them fact-check, we can help them understand the dangers of fluid writing that lacks substance or that relies on fallacies. By having them use ChatGPT for early drafts, we can push them to ask questions about information, structure, and sources. By having them apply different perspectives to ChatGPT’s results, we can help broaden their understanding of points of view and argument.

Yes, students should use it for writing. Many already are. We can no more ban students from using artificial intelligence than we can ban them from using phones or calculators. As I’ve written previously, we need to talk with students about how to use ChatGPT and other AI tools effectively and ethically. No, they should not take AI-written materials and turn them in for assignments, but yes, they should use AI when appropriate. Businesses of all sorts are already adapting to AI, and students will need to know how to use it when they move into the workforce. Students in K-12 schools are using it and will expect access when they come to college. Rather than banning ChatGPT and other AI tools or fretting over how to police them, we need to change our practices, our assignments, and our expectations. We need to focus more on helping students iterate their writing, develop their information literacy skills, and humanize their work. Will that be easy? No. Do we have a choice? No.

It is great for idea generation. ChatGPT certainly sounds like a drone at times, but it can also suggest ideas or solutions that aren’t always apparent. It can become a partner, of sorts, in writing and problem-solving. It might suggest an outline for a project, articulate the main approaches others have taken to solving a problem, or provide summaries of articles to help decide whether to delve deeper into them. It might provide a counterargument to a position or opinion, helping strengthen an argument or point out flaws in a particular perspective. We need to help students evaluate those results just as we need to help them interpret online search results and help them interpret media of all types. ChatGPT can provide motivation for starting many types of projects, though.

Learning how to work with it is a skill. Sometimes ChatGPT produces solid results on the first try. Sometimes it takes several iterations of a question to get good answers. Often it requires you to ask for elaboration or additional information. Sometimes it never provides good answers. That makes it much like web or database searching, which requires patience and persistence as you refine search terms, narrow your focus, identify specific file types, try different types of syntax and search operators, and evaluate many pages of results. Add AI to the expanding repertoire of digital literacies students need. (Teaching guides and e-books  are already available.)

Its perspective on popular culture is limited. ChatGPT is trained on text. It doesn’t have access to video, music or other forms of media unless those media also have transcripts available online. It has no means of visual or audio analysis. When I input lyrics to a Josh Ritter song, it said it had no such reference. When I asked about “a hookah-smoking caterpillar,” it correctly provided information about Alice in Wonderland but made no mention of the Jefferson Airplane song “White Rabbit.” Part of that is a matter of providing the right prompts. It is important to keep ChatGPT’s limitations in mind, though. (Another OpenAI tool, DALL-E, has been trained on a large number of images and visual styles and creates stunning images, as do other visual tools that use OpenAI’s framework.)

It lives in an artificial reality. I provided examples above about ChatGPT’s inability to acknowledge biases. It does have biases, though, and takes, as Maria Andersen has said, a white, male view of the world (as this article does). Maya Ackerman of Santa Clara University told The Story Exchange: “People say the AI is sexist, but it’s the world that is sexist. All the models do is reflect our world to us, like a mirror.” ChatGPT has been trained to avoid hate speech, sexual content, and anything OpenAI considered toxic or harmful. Others have said that it avoids conflict, and that its deep training in English over other languages skews its perspective. Some of that will no doubt change in the coming months and years as the scope of ChatGPT expands. No matter the changes, though, ChatGPT will live in and draw from its programmers’ interpretation of reality. Of course, that provides excellent opportunities for class discussions, class assignments, and critical thinking.

The potential is mindboggling. In addition to testing ChatGPT, I have experimented with other AI tools that summarize information, create artwork, iterate searches based on the bibliographies of articles you mark, answer questions from the perspectives of historical figures and fictional characters, turn text into audio and video, create animated avatars, analyze and enhance photos and video, create voices, and perform any number of digital tasks. AI is integrated in phones, computers, lighting systems, thermostats, and just about any digital appliance you can imagine. So the question isn’t whether to use use AI; we already are, whether we realize it or not. The question is how quickly we are willing to learn to use it effectively in teaching and learning. Another important question that participants in a CTE session raised last week is where we set the boundaries for use of AI. If I use PowerPoint to redesign my slides, is it still my work? If I use ChatGPT to write part of a paper, is it still my paper? We will no doubt have to grapple with those questions for some time.

Where is this leading us?

In the two months ChatGPT has been available, 100 million people have signed up to use it, with 13 million using it each day in January. No other consumer application has reached 100 million users so quickly.

For all that growth, though, the biggest accomplishment of ChatGPT may be the spotlight it has shined on a wide range of AI work that had been transforming digital life for many years. Its ease of use and low cost (zero, for now) has allowed millions of people to engage with artificial intelligence in ways that not long ago would have seemed like science fiction. So even if ChatGPT suddenly flames out, artificial intelligence will persist.

ChatGPT arrives at a time when higher education has been struggling with challenges in enrollment, funding, cost, trust, and relevance. It still relies primarily on a mass-production approach to teaching that emerged when information was scarce and time-consuming to find. ChatGPT further exposes the weaknesses of that outmoded system, which provides little reward to the intellectual and innovative work of teaching. If the education system doesn’t adapt to the modern world and to today’s students, it risks finding itself on the wrong side of the pod bay doors.

Cue the Strauss crescendo.

The intellectual work that goes into teaching often goes unnoticed.

All too often, departments rely on simple lists of classes and scores from student surveys of teaching to “evaluate” instructors. I put “evaluate” in quotation marks because those list-heavy reviews look only at surface-level numerical information and ignore the real work that goes into making teaching effective, engaging, and meaningful.

An annual evaluation is a great time for instructors to document the substantial intellectual work of teaching and for evaluators to put that work front and center of the review process. That approach takes a slightly different form than many instructors are used to, and at a CTE workshop last week we helped draw out some of the things that might be documented in an annual review packet and for other, more substantial reviews.

Participants shared a wide range of activities that showed just how creative and devoted many KU instructors are. The list might spur ideas for others putting together materials for annual review:

Engagement and learning

Nearly all the instructors at the workshop reported modifying classes based on their observations, reviews of research, and student feedback from previous semesters. These included:

• Moving away from quizzes and exams, and relying more on low-stakes assignments, including blog posts, minute papers, and other types of writing assignments to gauge student understanding.
• Moving material online and using class time to focus on interaction, discussion, group work, peer review, and other activities that are difficult for students to do on their own.
• Using reflection journals to help students gain a better understanding of their own learning and better develop their metacognitive skills.
• Providing new ways for students to participate in class. This included adding a digital tool that allows students to make comments on slides and add to conversations the way they do through online chats.
• Using universal design to provide choices to students for how they learn material and demonstrate their understanding.
• Scaffolding assignments. Many instructors took a critical look at how students approached assignments, identifying skills in more detail, and helping students build skills layer by layer through scaffolded work.
• Bringing professionals into class to broaden student perspectives on the discipline and to reinforce the importance of course content.
• Creating online courses. In some cases, this involved creating courses from scratch. In others, it meant adapting an in-person course to an online environment.
• Rethinking course content. Sarah Browne in math remade course videos with a lightboard. That allowed students to see her as she worked problems, adding an extra bit of humanity to the process. She also used Kaltura to embed quizzes in the videos. Those quizzes helped students gauge their understanding of material, but they also increased the time students spent with the videos and cut down on stopping part-way through.

Overcoming challenges

• Larger class sizes. A few instructors talked about adapting courses to accommodate larger enrollment or larger class sizes. More instructors are being asked to do that each semester as departments reduce class sections and try to generate more credit hours with existing classes.
• Student engagement. Faculty in nearly all departments have struggled with student engagement during the pandemic. Some students who had been mostly online have struggled to re-engage with courses and classmates in person. As a result, instructors have taken a variety of steps to interact more with students and to help them engage with their peers in class.
• Emphasis on community. Instructors brought more collaborative work and discussion into their courses to help create community among students and to push them to go deeper into course material. This included efforts to create a safe and inclusive learning environment to bolster student confidence and help students succeed.
• Frequent check-ins. Instructors reported increased use of check-ins and other forms of feedback to gauge students’ mood and motivation. This included gathering feedback at midterm and at other points in a class so they could adjust everything from class format to class discussions and use of class time. At least one instructor created an exit survey to gather feedback. David Mai of film and media studies used an emoji check-in each day last year. Students clicked on an emoji to indicate how they were feeling that day, and Mai adapted class activities depending on the mood.

Adapting and creating courses

The university has shifted all courses to Canvas over the last two years. Doing so required instructors to put in a substantial amount of time-consuming work. This included:

• Time involved in moving, reorganizing, and adapting materials to the new learning management system.
• Training needed through Information Technology, the Center for Online and Distance Learning, and the Center for Teaching Excellence to learn how to use Canvas effectively and to integrate it into courses in ways that help students.

Ji-Yeon Lee from East Asian languages and culture went even further, creating and sharing materials that made it easier for colleagues to adapt their classes to Canvas and to use Canvas to make courses more engaging.

Resources on documenting teaching

CTE has several resources available to help instructors document their teaching. These include:

• A page on representing and reviewing teaching has additional ideas on how to document teaching and student learning, and how to present that material for review. One section of the page includes resources on how to use results from the new student survey of teaching.
• A page for the Benchmarks for Teaching Effectiveness project has numerous resources related to a framework developed for evaluating teaching. These include a rubric with criteria for the seven dimensions of effective teaching that Benchmarks is based on; an evidence matrix that points to potential sources for documenting aspects of teaching; and a guide on representing evidence of student learning.

Documenting teaching can sometimes seem daunting, but it becomes easier the more you work on it and learn what materials to set aside during a semester.

Just keep in mind: Little of the intellectual work that goes into your teaching will be visible unless you make it visible. That makes some instructors uncomfortable, but it’s important to remember that you are your own best advocate. Documenting your work allows you to do that with evidence, not just low-level statistics.

Nearly a decade ago, the Associated Press began distributing articles written by an artificial intelligence platform.

Not surprisingly, that news sent ripples of concern among journalists. If a bot could turn structured data into comprehensible – even fluid – prose, where did humans fit into the process? Did this portend yet more ominous changes in the profession?

I bring that up because educators have been raising many of the same concerns today about ChatGPT, which can not only write fluid prose on command, but can create poetry and computer code, solve mathematical problems, and seemingly do everything but wipe your nose and tuck you into bed at night. (It will write you a bedtime story if you ask, though.)

In the short term, ChatGPT definitely creates challenges. It drastically weakens approaches and techniques that educators have long used to help students develop foundational skills. It also arrives at a time when instructors are still reeling from the pandemic, struggling with how to draw many disengaged students back into learning, adapting to a new learning management system and new assessment expectations, and, in most disciplines, worrying about the potential effects of lower enrollment.

In the long term, though, we have no choice but to accept artificial intelligence. In doing so, we have an opportunity to develop new types of assignments and assessments that challenge students intellectually and draw on perhaps the biggest advantage we have as educators: our humanity.

Lessons from journalism

That was clearly the lesson the Associated Press learned when it adopted a platform developed by Automated Insights in 2014. That platform analyzes data and creates explanatory articles.

For instance, AP began using the technology to write articles about companies’ quarterly earnings reports, articles that follow a predictable pattern:

The Widget Company on Friday reported earnings of $x million on revenues of $y million, exceeding analyst expectations and sending the stock price up x%.

It later began using the technology to write game stories at basketball tournaments. Within seconds, reporters or editors could make basic stories available electronically, freeing themselves to talk to coaches and players, and create deeper analyses of games.

The AI platform freed business and financial journalists from the drudgery of churning out dozens of rote earnings stories, giving them time to concentrate on more substantial topics. (For a couple of years, I subscribed to an Automated Insights service that turned web analytics into written reports. Those fluidly written reports highlighted key information about site visitors and provided a great way to monitor web traffic. The company eventually stopped offering that service as its corporate clients grew.)

I see the same opportunity in higher education today. ChatGPT and other artificial intelligence platforms will force us to think beyond the formulaic assignments we sometimes use and find new ways to help students write better, think more deeply, and gain skills they will need in their careers.

As Grant Jun Otsuki of Victoria University of Wellington writes in The Conversation: “If we teach students to write things a computer can, then we’re training them for jobs a computer can do, for cheaper.”

Rapid developments in AI may also force higher education to address long-festering questions about the relevance of a college education, a grading system that emphasizes GPA over learning, and a product-driven approach that reduces a diploma to a series of checklists.

So what can we do?

Those issues are for later, though. For many instructors, the pressing question is how to make it through the semester. Here are some suggestions:

Have frank discussions with students. Talk with them about your expectations and how you will view (and grade) assignments generated solely with artificial intelligence. (That writing is often identifiable, but tools like OpenAI Detector and CheckforAI can help.) Emphasize the importance of learning and explain why you are having them complete the assignments you use. Why is your class structured as it is? How will they use the skills they gain? That sort of transparency has always been important, but it is even more so now.

Students intent on cheating will always cheat. Some draw from archives at greek houses, buy papers online or have a friend do the work for them. ChatGPT is just another means of avoiding the work that learning requires. Making learning more apparent will help win over some students, as will flexibility and choices in assignments. This is also a good time to emphasize the importance of human interaction in learning.

Build in reflection. Reflection is an important part of helping students develop their metacognitive skills and helping them learn about their own learning. It can also help them understand how to integrate AI into their learning processes and how they can build and expand on what AI provides. Reflection can also help reinforce academic honesty. Rather than hiding how they completed an assignment, reflection helps students embrace transparency.

Adapt assignments. Create assignments in which students start with ChatGPT and then have discussions about strengths and weaknesses. Have students compare the output from AI writing platforms, critique that output, and then create strategies for building on it and improving it. Anne Bruder offeres additional suggestions in Education Week, Ethan Mollick does the same on his blog, and Anna Mills has created a Google Doc with many ideas (one of a series of documents and curated resources she has made available). Paul Fyfe of North Carolina State provides perhaps the most in-depth take on the use of AI in teaching, having experimented with an earlier version of the ChatGPT model more than a year ago. CTE has also created an annotated bibliography of resources.

We are all adapting to this new environment, and CTE plans additional discussions this semester to help faculty members think through the ramifications of what two NPR hosts said was startlingly futuristic. Those hosts, Greg Rosalsky and Emma Peaslee of NPR’s Planet Money, said that using ChatGPT “has been like getting a peek into the future, a future that not too long ago would have seemed like science fiction.”

To that I would add that the science fiction involves a robot that drops unexpectantly into the middle of town and immediately demonstrates powers that elicit awe, anxiety, and fear in the human population. The robot can’t be sent back, so the humans must find ways to ally with it.

We will be living this story as it unfolds.

The latest enrollment report for universities in the Kansas regents system (down 1.5%) seems worth little more than a shrug. Longer term, though, the higher education trends in Kansas will require considerable attention – and action.

Enrollment at the six regents universities has fallen 13.5%, or 10,100 students, since peaking in 2011. That average masks even bigger declines at individual universities: Pittsburg State, down 28.4% since 2011; K-State, down, 21.9%; Emporia State, down 19.7%.

Those make KU’s decline of 11.4% during that period look small, especially with 2022 enrollment basically unchanged since last year and with an 8.2% increase in the number of freshmen this year. The percentage of out-of-state students increased, as well, and the university will no doubt continue to rely on out-of-state students, considering that the rate of Kansas high school students going to in-state public colleges has dropped 10 percentage points, to 44.8%, since 2015.

I’ve written quite a bit about the persistent enrollment challenges in Kansas and around the country. It’s a daunting topic that will require strategic thinking at every level of the university. (Recent cuts at Emporia State offer a glimpse at just how painful this could become.) The rethinking of how we approach higher education must include classes, an area where many instructors have made great improvements but where KU still has considerable work to do in adopting teaching practices that promote student success. It must also include the many structural barriers that Michael Dennin, vice provost for teaching and learning at the University of California, Irvine, spoke about at this year’s Teaching Summit. Those include things like curricula that are difficult for students to navigate and that make assumptions about student capabilities; demands on faculty time; inflexibility in classes and curricula; and a system that provides few incentives for cooperation.

It is through that lens of teaching that I look at some of the areas that stand out in this fall’s enrollment figures.

Women and men

At regents universities, women account for 56% of the overall student population, up about 3 percentage points over five years. Men now make up only 43.8% of the overall student population, down about 3 percentage points over that same period.

KU has a larger percentage of men (46.7%), but that may be the lowest percentage in the university’s history. I can’t say that with certainty, but it is the lowest since at least 1965, the first year for which Analytics, Institutional Research, and Effectiveness provides data.

In news reports from as far back as 1930, universities in Kansas and Missouri reported that their students were primarily men. In October 1960, for instance, The Kansas City Star reported that men outnumbered women 2 to 1 or 3 to 1 on most college campuses in Kansas and Missouri.

In terms of headcount, this year’s group of 11,146 men is the smallest since 1973, the last year the United States had a military draft. Overall headcount enrollment was 18,683 that year, 5,000 fewer than today’s, and men still accounted for 59.1% of students in 1973. Women at KU outnumbered men for the first time in 1988. Their numbers peaked in the early 2000s, but their percentage of total enrollment has grown each year since 2015. They now make up 53.2% of students at KU. That seems to be the highest ever.

The changes at KU have also followed national trends. Young women are more likely to graduate from high school on time and are substantially more likely to earn at least a bachelor’s degree (41% vs. 32% among those age 25 to 34), according to the Brookings Institution. Those numbers vary widely by state, though, as the Brookings table below shows.

Those same differences can be seen in graduate degrees. Since the early 2000s, women have earned about 60% of master’s degrees nationwide, and since 2005-06, more women than men have earned doctorates each year. The most recent totals from the National Center for Education Statistics show that women earn about 54% of Ph.D.s.

Graduation rates

KU rightfully boasted about all-time highs for four-, five-, and six-year graduation rates. The university’s year-over-year retention rate of 84.7% is virtually unchanged from a year ago. That’s also good news.

The not-so-good news is that 1 of every 5 students leaves the university after three semesters, and 1 of every 4 students leaves after two years.

And though the four-year graduation rate has increased nearly 20 points since 2007, it is still a paltry 55%. Over five years, 66.1% of students graduate. That’s a 10-point gain since 2007, but a third of students fail to earn a degree after five or six years. That six-year rate is lower than the average among full-time students at U.S. universities (67.4%) and among students at four-year public institutions (72%).

Graduate enrollment

The number of graduate students at KU has been declining steadily since 1991. At that peak, KU had 7,233 graduate students, according to statistics provided by AIRE. This fall, it has 5,166, a decline of 28.6% since 1991.

That is the smallest number of graduate students the university has had since 1974. This fall’s graduate cohort also makes up the smallest percentage of the overall student population (21.6%) since 1970 (20.2%). Declining numbers of undergraduates nationwide means that the pool of potential graduate students has also been shrinking.

KU’s declines in graduate enrollment run counter to nationwide trends over the last 10, 20 and 30 years, according to the National Center for Education Statistics. Since 1991, graduate enrollment has increased 21% at public universities and 58% at all U.S. universities.

Not surprisingly, the decline in graduate enrollment at KU has meant fewer graduate teaching assistants. The number of GTAs has fallen nearly 18% since 2014, from 1,127 to 927.

Online enrollment

The number of undergraduates taking online or hybrid online courses declined 14.7% this fall compared with Fall 2021. That is the second consecutive yearly decline since online and hybrid enrollment peaked during the pandemic-riddled Fall 2020 term.

Even so, online and hybrid online enrollment among undergraduates this fall was 22% higher than it was in Fall 2019, before the pandemic began. Those students are also taking more online credit hours (39% more than they did in Fall 2019). Those increases are no doubt even higher because of a change in the way KU accounted for online and online hybrid hours. I won’t go into those details, but a footnote on an AIRE-generated table explains the change.

Graduate enrollment in online courses shows a more troubling trend. If we omit the pandemic-inflated figures of 2020 and 2021, the number of students enrolled in graduate and professional courses online has increased 4.2% since Fall 2017, but the number of credit hours has declined nearly 15%.

In other words, there are slightly more online graduate students, but those students are taking fewer classes. The students looking for graduate programs online have also become more choosy, according to the educational consulting organization EAB. Those students often spend months or even years combing through university websites and looking for programs that provide the skills they want but that also waive admissions fees, overlook sometimes spotty undergraduate records, and allow admission without the GRE or other admissions tests.

Shaping the future

Those are just a few of the enrollment trends shaping KU and other universities, and the future will require both cultural and digital change, as John O’Brien argues in Educause.

Universities (KU included) are trying many new approaches as they adapt to shrinking numbers of students and changes among students. Those include more non-credit courses, certificate programs, stackable degrees, and micro-credentials. Some are creating partnerships with area businesses as students focus more urgently on skills they can use in jobs. Others are looking at ways to help students gain credentials in shorter time spans.

At CTE, our programs have helped departments define their curricula in terms of tangible skills, identify ways of making existing courses more appealing to students, create more cohesive curricula, clarify paths to degrees, and connect with more alumni. They have also helped faculty adapt their teaching to a more diverse student body, find ways of drawing on individual differences as a strength rather than a weakness, reinvigorate classes, and hone their teaching.

In all these programs, we have helped build a community that shares ideas and embraces innovation. That community will only grow more important as we navigate changes in enrollment, society, and expectations, and find a meaningful path to the future.

The poor balloon never had a chance.

It was Monday, the first day of fall classes. Lisa Sharpe Elles, assistant teaching professor in chemistry, circled a yellow, hydrogen-filled balloon as it floated above a table in Gray-Little Hall. She told the 200-plus students in Chemistry 130 to cover their ears.

She carefully lifted a flame-tipped wooden rod to the balloon and suddenly pulled back.

She had remembered the lone fool in the front row. That was me, two cameras poised, awaiting a promised explosion.

She grabbed a pair of noise-canceling earmuffs from the floor and told me to put them on. I wasn’t going to argue.

Then, as the clock ticked toward the end of the class, Sharpe Elles held the flame to the balloon again and …

BOOOOOM!!!!!!!

A yellowish-orange fireball flashed, the husk of the balloon plopped to the floor, and the 2022 academic year was off to a cracking start.

An appropriate symbol?

It would have been difficult to predict a flashy start to this school year. The last five pandemic-addled semesters have been more dud than boom. Class attendance was often sparse, students and faculty often seemed encrusted with ennui, and every day felt like the last mile of a marathon in which an invisible force kept moving the finish line farther away.

So far, though, a new spark seems to have spread. Faculty reported that students were eager and engaged on the first day of class, launching into discussions even without prompts to do so. Hallways were once again crowded, with students lingering to chat or finding seats so they could catch up on messages. There were reports of faculty going hoarse as they returned to projecting their voices across classrooms. Even the weather seemed in a different mood, leashing the dog days and instead trotting out mornings that offered a hint of autumn.

At last week’s Teaching Summit, faculty expressed worry about – yet again – trying to engage detached students in low-energy classrooms. If the first two days of Fall 2022 are any indication, though, they may not have much to worry about. It would be foolish to expect that the bubbly spirit of the opening days will last until December. The pandemic has humbled us again and again, melting predictions into foolish if-only-isms.

For a few days, though …

BOOOOOM!!!!!!!

… it feels good to have some hope and maybe even a dream about breaking out the balloons.