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Last month on the blog, I floated the idea of thinking about generative AI tools like ChatGPT, Bing, and Bard as technologies for learning. I drew an analogy to the digital camera I used as I learned photography. As I was developing a conceptual understanding of photography, I was also learning how to use the tool in my hands, with all its knobs and buttons, and these two kinds of learning informed and supported each other. Could we use generative AI tools in a similar fashion, teaching students to use the tools well as part of learning other skills, like writing and researching? If so, it might help to know what kind of tools we’re dealing with when we talk about ChatGPT and other AI text generation tools.
For instance, I saw this post by Simon Harris go around Mastodon a couple of weeks ago:
15yo: I use ChatGPT quite a bit.
Me: Oh?
15yo: Today, I asked it to give me the last digit of Pi.
Me:but there is no…
15yo: …exactly
Me:
15yo: Apparently, it’s 4
This is funny because ChatGPT is so, so wrong about pi. As an irrational number, pi has a nonterminating decimal representation; there’s no last digit of pi. The joke, however, relies on an assumption that ChatGPT is supposed to be some kind of answer machine, a tool for answering questions correctly. However, ChatGPT is famously not that. It’s well known for “hallucinating” facts and inventing citations. There are, in fact, a lot of educators who are worried that students will rely too much on ChatGPT and similar tools because these tools produce text that is factually incorrect. For example, check out this YouTube video of a chemistry instructor evaluating the accuracy of ChatGPT’s answers to various organic chemistry questions. Spoiler: It didn’t do that great.
So if these tools aren’t answer machines, what are they? I would argue that ChatGPT and similar tools are actually wordsmiths. They are powered by large language models that mix words together to create fluent prose. Ask it to draft an essay for you on a given topic, and it will put words together to do just that. Ask it to revise that draft based on your feedback, and it will do that, too. See, for instance, how Ethan Mollick used Bing to help him craft the final paragraph of his April 26th newsletter. Ask it to summarize a long text, and, because it’s good with words, you’ll get a pretty decent summary. It’s a wordsmith that actually doesn’t know what it’s writing but still produces intelligible texts.
This is, in fact, the other reason that educators are worried about AI text generators, because they can quickly produce acceptable responses to pretty standard essay question prompts, and educators are worried that students will use these tools to cheat, whether the essay question is of the “writing as assessment,” “writing to learn,” or “learn to write” variety. Because ChatGPT and its peers are good with words.
I’m struck by how the initial reporting and framing of these tools affect the ways we think about them. While AI text generators were seen as answer machines (albeit flawed ones), AI image generators have been seen as “smiths” of a different kind, working with pixels to create images. While a tool like ChatGPT making stuff up is seen as a problem, if I ask Midjourney or DALL-E (a couple of popular image generators) to give me a scene of robots playing basketball, no one worries about the result not being real-world realistic.
If AI text generators are tools for learning, as I argued on the blog last month, then I think it’s helpful to think of them as wordsmithing tools. Does a student struggle to come up with counter arguments for their thesis? Ask an AI tool to generate a few. Does a student freeze up when confronted with a blank page? Ask an AI tool to write a first draft. Does a student find it hard to adopt the right voice for their writing? Ask an AI tool to rewrite a draft essay in different voices. These are all wordsmithing tasks that ChatGPT and its ilk can handle pretty well.
Please note that I’m not suggesting we shouldn’t help students learn to develop counter arguments or to get past writer’s block or to figure out their writing voice. I am suggesting, however, that AI tools might be used to help students learn these skills, just as my digital camera helped me learn photography. Cynthia Alby uses the metaphor of learning to ride a bicycle with training wheels to talk about how AI tools might provide a kind of scaffolding for students learning writing skills. When I heard that metaphor, I was reminded of a 2012 blog post by Mark Sample, in which he talks about balance bikes as a different way to teach kids to ride bicycles. Learning with training wheels means getting help with balancing while learning to pedal, while learning with a balance bike means not worrying about pedaling while learning to balance, which is apparently easier for most kids. We might need to think carefully about where our students need the kind of support that AI tools can provide, and the answer might vary by student.
I’ve been using the training wheels and balance bike metaphors in my recent talks on teaching with AI, and I was all ready to bust out the “AI as wordsmith” argument above at a talk I gave earlier this week. But then I signed up for ChatGPT Pro to see what ChatGPT’s plugins are all about. Back in March, OpenAI, the company behind ChatGPT, announced that the tool would have plugins that allowed it to communicate (in a fashion) with other web tools and websites. It’s taken me three months, but I finally started playing around with these plugins. I quickly realized that some of the advice I had given faculty earlier in the year about designing “ChatGPT-proof” assignments hadn’t been accurate for a while!
For instance, if I ask the free version of ChatGPT, which uses GPT-3.5, to tell me about the May 2023 Supreme Court decision that dealt with Andy Warhol’s art, here’s the response I get:
I apologize for the confusion, but as of my knowledge cutoff in September 2021, I’m not aware of any specific Supreme Court decision in May 2023 related to Andy Warhol’s art. It’s possible that such a decision may have occurred after my knowledge cutoff or it may be a hypothetical scenario that hasn’t actually taken place. I recommend checking reliable news sources or legal references to get the most accurate and up-to-date information on any recent Supreme Court decisions regarding Andy Warhol’s art.
If I think about ChatGPT as an answer machine, I’m not getting the answer I want, but at least the tool is telling me what it doesn’t know. That’s an improvement over how the chatbot presented information at the start of 2023. But watch what happens when I use the same prompt in ChatGPT Pro with the VoxScript plugin enabled:
In May 2023, the U.S. Supreme Court ruled against the Andy Warhol Foundation in a copyright infringement case. The case was centered around a series of silk screen images that Warhol created based on a photograph of the late musician Prince, taken by photographer Lynn Goldsmith in 1981.
The court ruled in a 7-2 vote that Warhol infringed on Goldsmith’s copyright. The case hinged on whether Warhol’s images of Prince transformed Goldsmith’s photograph to a great enough degree to stave off claims of copyright infringement and therefore be considered as fair use under copyright law.
Goldsmith had sued the Andy Warhol Foundation for the Visual Arts (AWF) for copyright infringement after the foundation licensed an image of Warhol’s titled “Orange Prince” based on Goldsmith’s image of the pop artist to Condé Nast in 2016 for use in its publication Vanity Fair…
It goes on for another couple of paragraphs, and it gives me the news source it used to generate this summary of the case, a May 18th NPR report. This version of ChatGPT is indeed acting like an answering machine!
Quick sidebar: It is also now possible to share one’s ChatGPT correspondences with others. A few months ago, you needed some third-party tool to do so, but now ChatGPT has a share button for every chat. Thus the argument that there’s no “paper trail” for how one uses ChatGPT is no longer true.
I used ChatGPT for the above examples, but please remember that ChatGPT isn’t the only game in town. I asked Bing about the Andy Warhol case, and I got a similar summary, this time with three different news sources cited. Google Bard gave me a similar summary and added some text about how fair use works in the United States. Its sources, however, were meeting notes from a 2004 Congressional subcommittee hearing and a Quizlet created for maybe a law course? Your mileage may vary with these tools.
So are these tools now, in fact, answer machines? I’m going to argue that while they can be used in that way, a better way to think of them is as interfaces to other systems. Just as Siri or Alexa act as a voice-based interface to the apps on your digital devices, ChatGPT and Bing and such are text-based interfaces to, for instance, all the transcripts attached to all the YouTube videos. These tools are still wordsmiths, but wordsmiths used as interfaces.
To use a left field example, the fast food chain Wendy’s recently announced that it was working on an AI chatbot to take drive-thru orders. That’s AI-as-interface, with the chatbot, which is good with words, taking spoken orders for a cheeseburger and a Frosty and turning that into an order in the restaurant’s food production system. For a more academic example, consider Elicit, an AI research assistant that can help you find research in its corpus of 115 million academic papers that might address your research question. Ask it a question like “How should I form groups of students when using group work in the college classroom?” and (because it’s good with words) it will return a table of potentially relevant papers, summarized and tagged by intervention, sample size, and outcomes.
AI as answer machine, AI as wordsmith, AI as interface… I’m not sure where we’ll land with how we think about these tools, but I believe these framings are helpful in assessing what the tools can and cannot do and what roles they might play as learning technologies.
One more caveat: Most of what I’ve presented here is focused squarely on AI text generation tools powered by large language models. There are lots of other kinds of AI tools, like Cornell University’s Merlin app, which can identify birds by their songs, or that AI-powered agent that excelled at the strategic negotiation game Diplomacy, that don’t fall into any of the categories I’ve described here.
In our newest "how can we help you?" thread,
My employer uses turnitin and asks us to investigate every single case where turnitin shows any percentage of assignments being generated by AI. I think this has gotten a bit out of hand despite constantly warning my students about the policy. (Student who have something detected also tend to conclude their assignments with “some experts say X some experts say Y and this is an important issue so we need to investigate further and have more discussions.”)
I think this has substantially increased my workload and that of the casual staff who works with me. Is this getting more common? How have others dealt with the increased workload and potential unpaid work of casual staff?
Good questions. I haven't had a major surge in investigations or made any major changes to how I teach yet yet, but I spoke to friend recently who has who told me that they are now simply having students do all of their work by hand in class.
What about the rest of you? Have you experienced a big surge in academic misconduct cases because of AI? If so, how are you dealing with it? And either way, if you have experienced a surge or not, have you adopted any teaching strategies to prevent AI-based misconduct?
I have the pleasure of teaching my PhD class in higher education finance again at Tennessee this summer. Our students take classes year-round, and I am offering the class in a condensed five-week format this summer to best meet the needs of our students. That means a lot of reading for all of us in a short period of time, but I’m excited as always for this class.
The last three times that I taught the course (spring 2022, spring 2020, and fall 2017), I shared my reading list for the class on this blog. I do not use a textbook for the course because the field is moving so quickly and there are more topics to cover than a textbook could ever include. Instead, I use articles, working papers, and other online resources to provide a current look at the state of higher education finance. As a result, the reading list for my class changes considerably each time.
Here is the reading list I am assigning my students for the course. I link to the final versions of the articles whenever possible, but those without access to an academic library should note that earlier versions of many of these articles are available online via a quick Google search.
The higher education finance landscape and data sources
Chetty, R., Friedman, J. N., Saez, E., Turner, N., & Yagan, D. (2017). Mobility report cards: The role of colleges in intergenerational mobility. Working paper. (link)
Schanzenbach, D. W., Bauer, L., & Breitwieser, A. (2017). Eight economic facts on higher education. The Hamilton Project. (link)
Webber, D. A. (2021). A growing divide: The promise and pitfalls of higher education for the working class. The ANNALS of the American Academy of Political and Social Science, 695, 94-106. (link)
Recommended data sources:
College Scorecard: https://collegescorecard.ed.gov/ (underlying data at https://collegescorecard.ed.gov/data/)
Equality of Opportunity Project: http://www.equality-of-opportunity.org/college
IPEDS: https://nces.ed.gov/ipeds/use-the-data
NCES Data Lab: https://nces.ed.gov/datalab/index.aspx
Postsecondary Value Commission’s Equitable Value Explorer: https://www.postsecondaryvalue.org/equitable-value-explorer/
ProPublica’s Nonprofit Explorer: https://projects.propublica.org/nonprofits/
Urban Institute’s Data Explorer: https://educationdata.urban.org/data-explorer/colleges/
Institutional budgeting
Barr, M.J., & McClellan, G.S. (2010). Understanding budgets. In Budgets and financial management in higher education (pp. 55-85). Jossey-Bass. (link)
Jaquette, O., Kramer II, D. A., & Curs, B. R. (2018). Growing the pie? The effect of responsibility center management on tuition revenue. The Journal of Higher Education, 89(5), 637-676. (link)
Rutherford, A., & Rabovsky, T. (2018). Does the motivation for market-based reform matter? The case of responsibility-centered management. Public Administration Review, 78(4), 626-639. (link)
University of Tennessee System’s FY2023 budget: https://finance.tennessee.edu/budget/documents/
University of Tennessee System’s FY2022 annual financial report: https://treasurer.tennessee.edu/reports/
UTK’s Budget Allocation Model website: https://budget.utk.edu/budget-allocation-model/
Higher education expenditures
Archibald, R. B., & Feldman, D. H. (2018). Drivers of the rising price of a college education. Midwestern Higher Education Compact. (link)
Cheslock, J. J., & Knight, D. B. (2015). Diverging revenues, cascading expenditures, and ensuing subsidies: The unbalanced and growing financial strain of intercollegiate athletics on universities and their students. The Journal of Higher Education, 86(3), 417-447. (link)
Commonfund Institute (2021). 2021 higher education price index. (link)
Griffith, A. L., & Rask, K. N. (2016). The effect of institutional expenditures on employment outcomes and earnings. Economic Inquiry, 54(4), 1931-1945. (link)
Hemelt, S. W., Stange, K. M., Furquim, F., Simon, A., & Sawyer, J. E. (2021). Why is math cheaper than English? Understanding cost differences in higher education. Journal of Labor Economics, 39(2), 397-435. (link)
State sources of revenue
Chakrabarti, R., Gorton, N., & Lovenheim, M. F. (2020). State investment in higher education: Effects on human capital formation, student debt, and long-term financial outcomes of students. National Bureau of Economic Research Working Paper 27885. (link)
Gándara, D. (2020). How the sausage is made: An examination of a state funding model design process. The Journal of Higher Education, 91(2), 192-221. (link)
Kelchen, R., Lingo, M., Baker, D., Rosinger, K. O., Ortagus, J. C., & Wu, J. (2023). A typology and landscape of state funding formulas for public colleges and universities from 2004 to 2020. InformEd States. (link)
Kunkle, K., & Laderman, S. (2023). State higher education finance: FY 2022. State Higher Education Executive Officers Association. (link)
Ortagus, J. C., Kelchen, R., Rosinger, K. O., & Voorhees, N. (2020). Performance-based funding in American higher education: A systematic synthesis of the intended and unintended consequences. Educational Evaluation and Policy Analysis, 42(4), 520-550. (link)
Shaw, K., Asher, L., & Murphy, S. (2023). Mapping community college finance systems to develop equitable and effective finance policy. HCM Strategists. (link)
Tennessee’s outcomes-based funding formula: https://www.tn.gov/thec/bureaus/ppr/fiscal-policy/outcomes-based-funding-formula-resources/2020-25-obf.html
Federal sources of revenue
Bergman, P., Denning, J. T., & Manoli, D. (2019). Is information enough? The effect of information about education tax benefits on student outcomes. Journal of Policy Analysis and Management, 38(3), 706-731. (link)
Black, S. E., Turner, L. J., & Denning, J. T. (2023). PLUS or minus? The effect of graduate school loans on access, attainment, and prices. National Bureau of Economic Research Working Paper 31291. (link)
Graddy-Reed, A., Feldman, M., Bercovitz, J., & Langford, W. S. (2021). The distribution of indirect cost recovery in academic research. Science and Public Policy, 48(3), 364-386. (link)
Kelchen, R., & Liu, Z. (2022). Did gainful employment regulations result in college and program closures? Education Finance and Policy, 17(3), 454-478. (link)
Ward, J. D. (2019). Intended and unintended consequences of for-profit college regulation: Examining the 90/10 rule. Journal of Student Financial Aid, 48(3), Article 4. (link)
The financial viability of higher education
Ducoff, N. (2019, December 9). Students pay the price if a college fails. So why are we protecting failing institutions? The Hechinger Report. (link)
EY-Parthenon (2018). Transitions in higher education: Safeguarding the interests of students. (link)
Kelchen, R. (2020). Examining the feasibility of empirically predicting college closures. Brookings Institution. (link)
Massachusetts Board of Higher Education (2019). Final report & recommendations. Transitions in higher education: Safeguarding the interest of students (THESIS). (link)
Sullivan, G. W., & Stergios, J. (2019). A risky proposal for private colleges: Ten reasons why the Board of Higher Education must rethink its plan. Pioneer Institute. (link)
Tarrant, M., Bray, N., & Katsinas, S. (2018). The invisible colleges revisited: An empirical review. The Journal of Higher Education, 89(3), 341-367. (link)
College pricing, tuition revenue, and endowments
Baker, D. J. (2020). “Name and shame”: An effective strategy for college tuition accountability? Educational Evaluation and Policy Analysis, 42(3), 1-24. (link)
Baum, S., & Lee, V. (2018). Understanding endowments. Urban Institute. (link)
Cheslock, J. J., & Riggs, S. O. (2023). Ever-increasing listed tuition and institutional aid: The role of net price differentials by year of study. Educational Evaluation and Policy Analysis. (link)
Hatch, B., Myskow, W., & Trivedi, I. (2022, August 15). Stopping the enrollment slide. The Chronicle of Higher Education. https://www.chronicle.com/article/stopping-the-slide.
Kramer II, D. A., Ortagus, J. C., & Lacy, T. A. (2018). Tuition-setting authority and broad-based merit aid: The effect of policy intersection on pricing strategies. Research in Higher Education, 59(4), 489-518. (link)
Ma, J., & Pender, M. (2022). Trends in college pricing and student aid 2021. The College Board. (link)
Webber, D. A. (2017). State divestment and tuition at public institutions. Economics of Education Review, 60, 1-4. (link)
Financial aid policies, practices, and impacts
Anderson, D. M., Broton, K. M., Goldrick-Rab, S., & Kelchen, R. (2020). Experimental evidence on the impacts of need-based financial aid: Longitudinal assessment of the Wisconsin Scholars Grant. Journal of Policy Analysis and Management, 39(3), 720-739. (link)
Bird, K., & Castleman, B. L. (2016). Here today, gone tomorrow? Investigating rates and patterns of financial aid renewal among college freshmen. Research in Higher Education, 57(4), 395-422. (link)
Dynarski, S., Page, L. C., & Scott-Clayton, J. (2022). College costs, financial aid, and student decisions. National Bureau of Economic Research Working Paper 30275. (link)
Guzman-Alvarez, A., & Page, L. C. (2021). Disproportionate burden: Estimating the cost of FAFSA verification for public colleges and universities. Educational Evaluation and Policy Analysis, 43(3), 545-551. (link)
Kelchen, R., Goldrick-Rab, S., & Hosch, B. (2017). The costs of college attendance: Examining variation and consistency in institutional living cost allowances. The Journal of Higher Education, 88(6), 947-971. (link)
Student debt and financing college
Baker, D. J. (2019). When average is not enough: A case study examining the variation in the influences on undergraduate debt burden. AERA Open, 5(2), 1-26. (link)
Black, S. E., Denning, J. T., Dettling, L. J., Goodman, S., & Turner, L. (2020). Taking it to the limit: Effects of increased student loan availability on attainment, earnings, and financial well-being. National Bureau of Economic Research Working Paper 27658. (link)
Boatman, A., Evans, B. J., & Soliz, A. (2017). Understanding loan aversion in education: Evidence from high school seniors, community college students, and adults. AERA Open, 3(1), 1-16. (link)
Ritter, D., & Webber, D. (2019). Modern income-share agreements in postsecondary education: Features, theory, applications. Federal Reserve Bank of Philadelphia Discussion Paper 19-06. (link)
Scott-Clayton, J. (2018). What accounts for gaps in student loan default, and what happens after. Brookings Institution Evidence Speaks Report #57. (link)
Returns to education
Darity, Jr., W. A., & Underwood, M. (2021). Reconsidering the relationship between higher education, earnings, and productivity. Postsecondary Value Commission. (link)
Deterding, N. M., & Pedulla, D. S. (2016). Educational authority in the “open door” marketplace: Labor market consequences of for-profit, nonprofit, and fictional educational credentials. Sociology of Education, 89(3), 155-170. (link)
Doyle, W. R., & Skinner, B. T. (2017). Does postsecondary education result in civic benefits? The Journal of Higher Education, 88(6), 863-893. (link)
Ma, J., & Pender, M. (2023). Education pays 2023: The benefits of higher education for individuals and society. The College Board. (link)
Webber, D. A. (2016). Are college costs worth it? How ability, major, and debt affect the returns to schooling. Economics of Education Review, 53, 296-310. (link)
rkelchen
Faculty and students can—and must—govern their own institutions, so that universities maintain their vital power.
The post As Society Evolves, So Too Does the University appeared first on Public Books.
In our newest "how can we help you?" thread, a reader writes:
I am teaching Critical Thinking in the Fall. I took Critical Thinking as an undergraduate and it was one of the most dreadfully dull courses I ever took in my degree. The main thing I remember from it is that we spent most of the semester memorizing the forms of fallacies. So, I was wondering if anyone has suggestions for how to approach Critical Thinking in a way that would make for a more exciting/beneficial class. I'd appreciate any recommendations for good textbooks or sample syllabi that I could model my own off of. I'm particularly interested in opportunities to integrate more global voices and/or philosophy into my eventual syllabus.
Two readers submitted replies
I recommend this book for CT. I use it and students have responded well. https://www.amazon.com/Critical-Thinking-Effective-Successful-Independent/dp/152971852X/ref=sr_1_1?keywords=critical+thinking+tom+chatfield&qid=1686512965&sprefix=critical+thinking+tom%2Caps%2C164&sr=8-1 I also recommend supplementing it with Daniel Kahneman's 'Thinking Fast and Slow' - by anon
another: https://www.amazon.com/Epistemology-Psychology-Judgment-Michael-Bishop/dp/0195162307 - by critical thinking
Do any other readers have any helpful tips or resources to share?
My friend Jenny Warner, who has died aged 87, was a speech therapist and one of the three founding members, in the mid-1970s, of the faculty in speech pathology and therapy at the University of Manchester. There she combined clinical practice with lecturing and writing academic papers and practical works.
Born in Kuala Lumpur in Malaya (now Malaysia), Jenny escaped the Japanese occupation of the country with her mother, Winifred (nee Herbertson), a secretary, at the age of six. After making their way to Singapore, they secured passage to Britain on the last evacuation ship to leave, in January 1942. Her father, Stanley Warner, who served in the RAF, rejoined the family in August of that year but was killed a few months later during a German bombing raid while he was a patient at the RAF officers’ hospital based at the Palace hotel in Torquay, Devon, in 1942.
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This workshop on Developing a Reflective Practice was offered in May 2023 for the MSU COLA Fellows. It was converted to this asynchronous format for those who weren’t able to attend.
This workshop consists of four main parts, with a reflection point separating each part. You may use the reflection prompt individually, or if you have a colleague, partner (or group of them) doing these activities together you may find it helpful to discuss and reflect together. To get the full benefit of working through these materials plan to spend about 45 minutes to watch through the videos, take the time for reflection, and to make any final notes.
Reflective Practice as defined by Donald Schon is “Thinking about one’s actions so as to engage in a process of continuous learning.” By engaging in an intentional reflective practice we are able to learn about ourselves and to make meaning from our experiences in ways that help us learn to do things differently, better, or otherwise in ways that are informed by our reflection. In this part of the workshop take some time to watch this short video and then consider the reflection/discussion prompt that follows
Watch video “What is Reflective Practice?” – 3 min 42 sec
This reflection/discussion topic is around your individual approaches to reflection and reflective practice. Take 5-7 minutes to think/write/discuss your thinking on the following:
Outcome from this activity: Find common methods of reflection/tools you use, and learn about other options from your discussion partners.
Watch video “Starting Your Reflective Practice” – 3 min 32 sec
This reflection/discussion topic is about the approaches your discipline uses for reflection. Take 5-7 minutes to think/write/discuss your thinking on the following:
Outcome from this activity: Identify ways your discipline conducts reflective activities. Learn from other disciplines and identify other possible frameworks, approaches, or tools for reflecting.
Watch video “Enacting Your Reflective Practice” – 7 min 14 sec
This last reflection/discussion topic is about critically engaging in the activities of reflection and reflective practice. Take 5-7 minutes to think/write/discuss your thinking on the following:
Outcome from this activity: Consider the affordances and limitations of different ways of reflecting and where/how you might want to share your reflection or not.
Take a few minutes to gather your notes and thoughts from the previous activities and then set your timer for another 5 minutes of self-reflection to set a plan up for developing/refining your reflective practice over the coming months.
If you are in the COLA Program you have to reflect at the end of the summer on all the work and thinking you are doing with the program, how might you develop and use an intentional reflective practice to document your work this summer? If you are not in the program think about how developing and implementing an intentional reflective practice might help you over the next couple of months.
How might you use the habits you form through reflective practice in these coming months to influence your teaching going forward? How might it help you in your next annual review or other reporting points, or how it might generally help you to become a better teacher, researcher, etc?
Remember that changing and developing habits is HARD WORK. You likely won’t develop a lasting practice overnight or in a short amount of time, a slow and steady pace is a great way to develop these habits that will last a long time.
Reflective practice is personal—the challenge is to figure out what works for you and supports your learning. Take some time to try out different things, see what works/doesn’t and what you connect with. Ask colleagues who are doing this work and learn from them.
Some ideas to get started and/or support your practice:
This workshop was recorded on May 25, 2023 as part of the MSU COLA Fellows workshop series.
“All I did was go to a website that is designed to facilitate cheating and set up a kind of camera to see who visited it.”
That’s Garret Merriam, associate professor of philosophy at Sacramento State University, who recently caught 40 of the 96 students in his online Introduction to Ethics course cheating on a take-home final exam.
[“Girl with a Pearl Earring” by Johannes Vermeer, 1665, (left) with “The Smiling Girl” by an unknown artist, 1925, (right)]
I decided to ‘poison the well’ by uploading [to Quizlet] a copy of my final with wrong answers. (The final is 70-80 questions, all multiple choice, 5 options each.) Most of these answers were not just wrong, but obviously wrong to anyone who had paid attention in class. My thinking was that anyone who gave a sufficient number of those same answers would be exposing themselves, not only as someone who cheated by looking up the final online, but who didn’t even pay enough attention in class to notice how wrong the answers were.
When the students turned in their finals, and he noticed that many of the students had selected the “obviously wrong” answers from the planted version of the final, he had to decide how to distinguish the cheaters from those who merely made mistakes. He ended up using the following standard: if there was no more than a 1 in 100 chance that the number of matching wrong answers a student gave was a coincidence, he counted them as having cheated, as he explains:
When my students turned in their finals this semester, I compared their answers with the wrong answers from the planted test. A total of 45 questions on this semester’s final were on the planted final. (The exact questions change every semester, depending on a number of factors.) As expected, nearly all students had at least a few wrong answers that matched; statistically speaking this is likely given the number of questions. I ran a binomial analysis and found the likelihood that someone whose answers matched on 19 out of the 45 planted questions had about a 1:100 chance of doing so by coincidence. That was my (admittedly somewhat arbitrary) threshold, and anyone who matched at least that many, I suspected of cheating. (The highest match was 40 out of 45, which has a 1:10-Quintillion chance of being a coincidence.)
To my amazement, that threshold implies that 40 out of 96 students looked at and used the planted final for at least a critical mass of questions.
When he confronted those students about this, most of them admitted they had cheated; the consequences for their grades are still being determined:
I emailed these students telling them what I had done and what I found. About 2/3rds of them confessed right away or denied it at first and quickly changed their tune. The remaining third either haven’t gotten back to me yet or have insisted on their innocence. (I am considering that possibility for one student who is right ‘on the bubble’, but the rest are upwards of 1:1 billion chance, or more.)
I am in discussion with my Chair about exactly what response is appropriate for these students, but a zero on the final is the bare minimum, and an F in the class is likely for some, if not all of those who cheated.
He adds:
As you can probably imagine, this has been exceptionally stressful for me (I’m neither a forensic mathematician, nor a cop, so this work took a lot of time that I would have preferred to have spent grading final essays.)
Professor Merriam wanted to share what happened on Daily Nous to see what other people in philosophy made of the situation and the actions he took. He had discussed it a little on Twitter, and while some people were, he says, “sympathetic and supportive,” others (for example) expressed the view that what he did was itself unethical. He disagrees:
As far as I can tell, their argument seems to boil down to the claim that my actions were deceptive or dishonest. I was accused of ‘entrapment’ and ‘honey-potting.’ More than a few seemed to think that my transgression was as bad or even worse than my students’. They suggested I should have just taken the copy of my test down and left it at that. As far as I can tell most of these people are not teachers of any kind, and none of them seemed to teach philosophy, ethics, or humanities.
These charges don’t make sense to me. I did not encourage or nudge my students to cheat, I did not do anything to make such cheating more likely or easier. Quite the opposite: I tell all my students what will happen if I catch them cheating, and I gave them a comprehensive study guide for the final.
As far as Quizlet goes, all I did was go to the website that is designed to facilitate cheating and set up a kind of camera to see who visited it. I honestly do not see what is objectionable about that. My University has an academic honesty policy that explicitly says that looking at other tests without the instructor’s permission counts as cheating (Although had I know it would be this much of an issue I would have been explicit about that in my syllabus as well, rather than just linking to the policy, an oversight I plan to correct going forward.)
Though he disagrees with his critics, he “open to the possibility that I might be wrong”
Maybe (as the saying goes) I am the asshole here. But I would take that possibility a lot more seriously if that were the judgment of my immediate peers (philosophers at least, if not specifically ethicists), and even more so still if those peers could articulate an argument beyond simplistic accusations of dishonesty or ‘entrapment.’
So, I thought I would reach out to you and see if you could share this with Daily Nous readers and ask them: Am I the unethical one here?
That’s one question. But it might be more useful to consider more generally: (a) feasible cheat-deterring strategies for professors teaching large classes, (b) what professors should do when they catch their students cheating (when this is not settled by university policy), and (c) the extent to which professors should concern themselves with whether their students are cheating.
The post “Am I the unethical one?” A Philosophy Professor & His Cheating Students first appeared on Daily Nous.
On Monday I submitted grades, and this afternoon I reviewed my teaching evaluations. That closes the books on my 14th year as a college professor. I am currently 42 years old, so by my math, I have been doing this for roughly one-third of my life. That is strange to think about! I’ve been a higher ed teacher for longer than I myself was in higher ed, and longer than I was in public schools. Over the next couple years, I will be going through a major evaluation, so I’m in a reflective mood. Obviously the way I’ve chosen to live my life indicates that learning is very important to me. What have I learned?
Other than a two-year period as visiting faculty at Kalamazoo College, my entire teaching career has been spent as part of the Shimer Great Books program, first at the independent school in Chicago and subsequently at North Central College. As I’ve written many times before, that program has a very distinctive ethos. All of our courses are discussion-based seminars based on important primary sources — no textbooks, no lectures, no high-stakes in-class exams. Since joining North Central I have been called upon to teach outside the Shimer program and have needed to fold lecture-based pedagogy back into some courses, but the discussion model remains my center of gravity. My goal is always, somehow, to get as close as I can to the day where my students can sit in a circle and talk open-endedly about what they’ve read.
This consistent pedagogical training has had a huge impact on me as a person. First of all, it has mellowed me out. I am still in many ways the irritable and impatient person that this blog made infamous when I was in my 20s, but that part of myself comes out much more rarely, and essentially never with students or colleagues. I’ve always been interested in some kind of intellectual community, but engaging with my students in extended dialogue day after day, year after year, brought home to me how much culvitating that community is an act of service and care. I was and still am attracted to the “sage on stage” model (which I am able to indulge periodically in invited lectures), but the kind of teaching I’ve been called upon to do has forced me to to stay more in the background, facilitating the process of other people working through ideas rather than showing off what I have figured out. This has led me to claim that I’m one of the only male academics out there who knows how to shut up and listen to others.
But it’s not just about listening. I decided early on that I would always be honest and straightforward about my own viewpoint and interpretation, whenever it seems appropriate to share. I find it off-putting and arrogant when professors proudly announce that, for instance, they want students to be able to get to the end of the semester not knowing whether they’re an atheist or a believer, or a Democrat or Republican. When I put forward a particular interpretation of the text — supported by textual evidence, of course! — my students set to work assessing it for themselves using those same means. Often I learn that my reading is half-baked and I need to go back to the drawing board. I’ve never had a student adopt my viewpoint because it was my viewpoint. This experience makes it hard for me to take seriously the idea that students are or could be indoctrinated in college.
That being said, I don’t think it’s boastful to say that I know a lot about a surprising range of topics. That’s the other side of the Great Books curriculum — since the center of authority is the class materials rather than the professor, scholarly expertise is not only unnecessary but can be a positive obstacle. I’ve spent most of my career at Shimer teaching outside my areas of expertise, and I’ve always found it pedagogically helpful for me to be learning alongside the students.
In fact, a big part of our training was to literally be learning alongside the students, by auditing courses. My first semester at Shimer College also marked my return to the classroom as a student, where I sat in on Humanities 1: Art and Music. Fine arts topics have since become a staple of my teaching, as I try to incorporate some art and music into every course where it’s halfway plausible. It’s been incredibly rewarding to reconnect with classical music and to gain a deeper appreciation for painting and sculpture. As a direct result of these teaching experiences, I am now a regular at the Chicago Symphony Orchestra and I have the holdings of the Art Institute of Chicago virtually memorized.
The Shimer program pushed me to develop a whole new teaching competence in Islam, which is now becoming a scholarly interest for me as well. It gave me the unique opportunity to teach courses in the history of science, including actual labs — how many theology PhDs can say they have taught lab science courses? It has broadened and deepend my knowledge of the classics of the Western tradition and pushed me to engage with the classics of other traditions as well. I left grad school as a committed generalist, but my teaching has transformed me into what I consider a truly educated person — not just someone who happens to know a lot, but someone who has learned how to learn in a wide and expanding number of areas. As My Esteemed Partner characterizes my approach to teaching, my motto is, “I haven’t taught that — yet!”
That experience of broad and deep learning and the genuine satisfaction and joys it brings has in turn looped back to my teaching. I may have a special knack for this kind of thing, but I believe everyone can become an open-ended sincere learner and that they deserve the chance to do so. At the old Shimer College, we had students of all ability levels, and everyone who took the process seriously grew as a thinker and as a person — “it works if you work it.”
We had the advantage back then of working with a self-selecting group of students who had opted into a particular kind of intellectual culture. Now we have to work harder to reach students who might be simply checking off a box, who might even resent more traditionally academic classes as an unnecessary waste of time when all they want to do is get a job. I haven’t found the secret formula by any means, but I do manage to reach some — to connect them with a part of themselves that is curious and interested and therefore interesting as well. Sometimes I feel like I’m putting out so much energy that I’m shaving days or weeks off my life expectancy, but enough students seem to find my performance of intellectual curiosity compelling that my classes can basically work as sites of some kind of inquiry — even that oddball gen-ed senior seminar that half of them were told was going to be about sprucing up your resume and practicing mock interviews but turns out to be a study of utopian and dystopian futures.
I don’t want to paint an unrealistically rosy picture. There are bad days in class and just plain bad classes. There is drudgery and conflict and stress and precarity and status anxiety and all manner of disappointments and frustrations that I have not yet learned to handle with as much grace and dignity as I’d like. But I’m still collecting regular paychecks, against all odds, and still living the life I’ve always wanted to live.
great books
akotsko
AutomatED, a guide for professors about AI and related technology run by philosophy PhD Graham Clay (mentioned in the Heap of Links last month), is running a challenge to professors to submit assignments that they believe are immune to effective cheating by use of large language models.
Clay, who has explored the the AI-cheating problem in some articles at AutomatED, believes that most professors don’t grasp its severity. He recounts some feedback he received from a professor who had read about the problem:
They told me that their solution is to create assignments where students work on successive/iterative drafts, improving each one on the basis of novel instructor feedback.
Iterative drafts seem like a nice solution, at least for those fields where the core assignments are written work like papers. After all, working one-on-one with students in a tutorial setting to build relationships and give them personalized feedback is a proven way to spark strong growth.
The problem, though, is that if the student writes the first draft at home — or, more generally, unsupervised on their computer — then they could use AI tools to plagiarize it. And they could use AI tools to plagiarize the later drafts, too.
When I asserted to my internet interlocutor that they would have to make the drafting process AI-immune, they responded as follows…: Using AI to create iterative drafts would be “a lot of extra work for the students, so I don’t think it’s very likely. And even if they do that, at least they would need to learn to input the suggested changes and concepts like genre, style, organisation, and levels of revision.”…
In my view, this is a perfect example of a professor not grasping the depth of the AI plagiarism problem.
The student just needs to tell the AI tool that their first draft — which they provide to the AI tool, whether the tool created the draft or not — was met with response X from the professor.
In other words, they can give the AI tool all of the information an honest student would have, were they to be working on their second draft. The AI tool can take their description of X, along with their first draft, and create a new draft based on the first that is sensitive to X.
Not much work is required of the student, and they certainly do not need to learn how to input the suggested changes or about the relevant concepts. After all, the AI tools have been trained on countless resources concerning these very concepts and how to create text responsive to them.
This exchange indicates to me that the professor simply has not engaged with recent iterations of generative AI tools with any seriousness.
The challenge asks professors to submit assignments, from which AutomatED will select five to be completed both by LLMs like ChatGPT and by humans. The assignments will be anonymized and then graded by the professor. Check out the details here.
In our newest "how can we help you?" thread, a reader asks:
I'm new to teaching and I'm struggling with making the transition from lecture preparation to delivery. I have no problem doing the readings/research, making detailed notes, making up a plan for the lecture, etc. What I'm not sure how to do is take all this and deliver a lecture where I'm not just reading my notes/slides or where I'm not just memorizing what I want to say. Does anyone have any tips?
Excellent question, and several other readers submitted responses:
https://www.youtube.com/watch?v=Unzc731iCUY - Submitted by Patrick Winston
First, remember that teaching, unless you are blessed with innate talents, should be hard and exhausting at first. I have been teaching for several years, and still find that I spend a lot more time than I want to preparing for teaching. Second, plan places for students to participate. It can be a vote on "do you agree with X;" "let's explore why you dis/agree;" pause whenever introducing key and difficult to understand ideas, and try to get students spell out their frustration (if any). The participation time can also be used as a short break for you. Third, find connections to things students might care about. It's easier for me as I'm moral, social, legal, and political, so I basically read the news and try to understand local politics. But my guess is that other fields have their ways of getting students to care about the content of the course. Fourth, talk about what constitutes excellent writing. This, if done well, will make life significantly easier when we have to do the marking. - Submitted by 'my two cents'
I say this only with a bit of irony, but you should approach the delivery of lecture more like Freddie Mercury singer Fat Bottomed Girls - see the video on You Tube. That is, you need to engage the audience, and care less about the specifics of the article, etc. that you are teaching. - Submitted by Freddie Jr.
Any other readers have any helpful tips for a new teacher?
Lesley Matthews and Margaret Squires respond to a piece by Adrian Chiles in which he compares the workload at English and French universities
Adrian Chiles (English students spend a fortune to go to university. Shouldn’t that buy them more teaching and less partying?, 29 March) extols the virtues of the French university regime, comparing it with the UK, where students can do what they like. At the start of my sixth form (60 years ago), our history teacher told us that he would not be chasing us to get our essays in on time as he knew that we wanted to go to university. We had to be self‑motivated. Result? I did nothing for a year and a half. I failed my mock A-level history exam. I then worked prodigiously hard and got a B in my A-level. I went to university. He had not just taught me history – he had taught me to be responsible for my own learning.
Lesley Matthews
Shipley, West Yorkshire
• Adrian Chiles is right to blame the culture in some universities in this country for scrappy degrees. Maybe the universities should make it compulsory for each student to join a work group. When my daughter studied in Belgium, a group of Germans asked her if she had one, and seeing that she did not understand the concept, invited her to join theirs. She has never worked so hard in her life.
Margaret Squires
St Andrews, Fife
FreshRSS 
