In this blog series Drs. Michael Toomey, Andrew Judge, and Jenny Morrison (all University of Glasgow) explore how board games can be used as effective pedagogical tools to bring abstract concepts to life in the classroom. Each entry focuses on a specific game, outlining its mechanics, practical classroom applications, and any possible adaptions or limitations to its use within a standard seminar set up. In examining individual games, they aim to provide a support resource for educators seeking to experiment with games as part of their classroom activities, as well as engage critically with when and why we might use games within teaching. This month the series continues with Jenny Morrison’s review of Billionaires and Guillotines.
In this new blog series Drs. Michael Toomey, Andrew Judge, and Jenny Morrison (all University of Glasgow) explore how board games can be used as effective pedagogical tools to bring abstract concepts to life in the classroom. Each entry focuses on a specific game, outlining its mechanics, practical classroom applications, and any possible adaptions or limitations to its use within a standard seminar set up. In examining individual games, they aim to provide a support resource for educators seeking to experiment with games as part of their classroom activities, as well as engage critically with when and why we might use games within teaching. This month we continue with guest contributor Patrick Shea’sPeople Power, a game about political economy and conflict.
When I ask my students in the first class session in my Political Economy of Conflict course why conflicts happen, the answers tend to centre on power and territory. These answers are understandable, but they limit our ability to assess the motivations, strategies, and consequences for those involved in conflict. People Power: Insurgency in the Philippines, 1981-1986 is a board game that helps highlight the different political economy elements of conflict.
How does it work?
Designed by Ken Tee, People Power is part of GMT Games’ COIN (Counterinsurgency) series — a family of wargames that share gameplay mechanics across a range of historical conflicts. In this game, each player controls one of three factions: the Marcos Government, the insurgent New People’s Army (NPA), and the nonviolent Reformers. Each faction pursues asymmetric goals — the Government seeks territorial control and patronage, the NPA builds resistance through guerrilla operations, and the Reformers shift popular opinion through activism. Each turn, a card is drawn from an event deck that determines both the order in which factions may act and a historical event that players can choose to trigger. Factions that act on one card must pass on the next, forcing difficult decisions about when to act and when to wait. The game is organised into two Campaigns that culminate in Election Rounds, where victory is checked, resources are redistributed, and popular support can shift.
This guest post is by Dr. Sara van Goozen, lecturer at the University of York’s Department of Politics and International Relations. As well as teaching and researching political theory, Sara has pursued research on inclusive assessment and feedback practices, and is one of the founding members of the Teaching Political Theory Network.
If you use Turnitin to provide feedback on student work, the image on the right may be sadly familiar to you: it shows which students have viewed the feedback they received. In this case, it’s a random sample of essays submitted by first-year students in January 2025. The screenshot was taken around 6 months after the release of the mark and shows that in the given sample, only about 50% of students viewed their feedback.
Although it’s fairly widely accepted that good quality feedback is important for student learning, writing good feedback is only part of the work: students also need to engage with the feedback they receive (not just give it a cursory glance!). And ideally, they need to engage with it over a period of time. However, there’s a good amount of research on the various factors which affect a student’s ability to benefit from feedback: on the teacher’s side, feedback may be vague, unhelpful, alienating, too detailed or not detailed enough. On the student’s side, they may not fully appreciate the importance of engaging with feedback, they may not recognize the information they receive as feedback, or they may find it difficult to extract lessons (and act on them) from the feedback they receive.
This guest post is by Dr. Ray Mikell, an assistant professor of political science at Jackson State University, a historically black institution and urban research university in Jackson, Mississippi. He has taught courses and written test bank questions in American and comparative politics in connection with several widely used, introductory-level textbooks, and has worked with W.W. Norton & Co. and Pearson.
Editor’s Note (Pigeon, that is): This series adds to the sober discussion we’ve been posting about using AI in the classroom. In my assessment, this series highlights the importance of subject matter expertise. Ray has many years of experience in deploying relevant and accurate classroom exercise scenarios and thus has appropriate judgment in reviewing, evaluating, and editing LLM scenario outputs. Over to you, Ray!
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Could having individual students think through scenarios from the worlds of politics and government—about everything from international conflict to voter choices, and a whole introductory political science text laundry list of subjects—in an open-ended fashion help ease educator anxiety about cheating via artificial intelligence systems? Being at least a near-optimist, I wondered if such questions could help increase student skills in analytical and critical thinking as well.
A win-win? Maybe I’m naïve?
This is a conversation I started having with myself—and then a large language model (LLM)-powered online chatbot —in recent times for a couple of reasons: The first spark was faculty anxiety about LLMs and artificial intelligence, which many critics saw as plagiarism systems. (I came to share the unease over the past two years, despite some initial ambivalence.) Then, for freelance American Government test bank work I was doing in 2024, an editor asked me to write more scenario or vignette-oriented multiple-choice questions than usual. The rationale? In an era when LLMs can easily produce basic recall questions, coming as higher-order thinking was becoming more valued, it made sense to experiment.
Any political science instructor who has used publisher test banks over the past decade or two has come across these types of questions, in this case, what education researchers call context-dependent items. These typically introduce a brief story or scene before posing a course-relevant query. Some may be augmented by a data graphic, a photo, or video. Others are formatted as an item set, otherwise known as a testlet. In these (common in medical or health care-related education), a vignette is followed by two or more questions, often linked in step-by-step fashion. In effect, these are puzzle questions aimed at getting students to think critically about political situations and issues as they present themselves in our world.
Maddeningly, however, no research has ever shown whether these sorts of questions are demonstrably effective in increasing critical or higher-order thinking. I should know. In the late 2010s, I undertook context-dependent query experiments with a few introductory-level political science classes at Jackson State. Ultimately, I found only modest effects, at best, as far as knowledge retention and increasing critical thinking went (as judged via essays). Immediate online feedback had a somewhat stronger effect, but not a notably strong one.
Although the results suggested that these types of questions only slowly push students toward more analytical reasoning, I kept slipping scenario questions into student introductory-level classes and tinkering with question design. The rise of ChatGPT, however, led me to doubt how I would go about testing student knowledge and comprehension of course materials through such means.
More recently, amid a presidential administration where the federal government was not working in a textbook fashion, I had a change of heart. Maybe context-dependent questions had more worth than I thought? The major difference, it seemed, was that I could no longer see using essays to judge student recall and comprehension of course concepts and facts.
One way to adapt, I thought, would be to lean into pushing for more analytical thinking through open-ended scenario questions or prompts that students could address via essays, out-of-class research, presentations, and audio-visual content. It would not, I thought, be nearly as easy for students to try to skate by with LLM-provided responses to scenario prompts, given that the latter often can involve thinking through complex situations. Such assignments could require students to apply abstract concepts to real-world problems.
It was possible, of course, that LLMs could provide respectable responses to my prompts in the usual AI way, with clear and shiny, if bloodless, prose, thus proving my naivete. But to judge that, I had to jump right into AI-land. More specifically, I had a chat with Claude AI about the worth of using scenario questions to get around or above cheating and plagiarism. Although it, like all LLMs, aims to please users—which can seem seductively refreshing after reading peer reviews—the LLMs answers were nonetheless intriguing.
Next in this series: How Claude AI answered the prompts (preview #1: too many bullet points, long-winded, but would have kept students from having to worry about more basic concepts or facts about American government), what it had to say in conversation about (preview #2: it suggested incorporating data searches), and the questions about boosting critical thinking that its answers and information pose.
I am writing this post more so as a brief reflection about how I approached speaking to my classes today (11/6) after the results of the US presidential (any many other) elections. This post may be rough and brief, but I think for those of you who are teaching Political Science (broadly) or engaging with your students in some capacity today or in the next few days about the US election, this might be interesting to consider. This post might not be relevant anymore next week – or it could help in general facilitate a conversation about any “touchy” current issues that we feel necessary to clue our students into.
This semester I am once against tasked by my institution to introduce a new crop of students to the magical world of international relations theories. Yet, as many of us, who do that regularly, know, teaching theories in international relations can be a difficult feat, as many of our students (most of the time freshmen and sophomores) engage with abstract ideas/frameworks for the first time. In particular, keeping together the purpose of theories, why we have different ones, and what their core assumptions are in how they approach the world can be daunting – for both the student and the teacher tasked with that role. As a visual learner myself, I have adopted two measures in my classes to convey visually the meaning of theories and why we have them. Below, I briefly discuss them.
I’m excited to announce the publication of my book, Teaching Political Science, now available from Springer (Palgrave). This has been a project more than 3 years in the making, ever since Jamie Frueh asked me if I’d ever thought about writing a book. With his and the encouragement of many others, I’m thrilled to share this with you. My hope in writing this book was to provide a practical resource for the grad student, early career instructor, or polsci professor at any stage who hasn’t had the chance to systematically study the literature on teaching and learning in our field. While there are many incredible articles, chapters, handbooks, and edited books out there, I saw the need for a single-authored volume focused on the nuts and bolts of teaching from philosophy, to course design, to execution and assessment. Most of us learn as practitioners, I’m hoping with this book to provide a scholarly path toward learning how to teach, and to inspire others to share their approaches.
I just attended the Teaching and Learning with AI Conference in Orlando, and my brain is brimming with ideas on how to use AI in support of students and faculty. I think most of us remain stuck in the Chat GPT mindset, concerned about academic integrity and students using that platform to write their papers and discussion posts. I’m not downplaying either that, or the privacy and ethical concerns about AI. But that’s just one part of the conversation. In the last two years there has been an explosion of other tools that could have positive impacts in the teaching and learning environment, and as Jeremy noted, we should be talking about those, too.
If you’ve ever had the urge to say, ‘its in the syllabus!’ to a questioning student, I’ve got some good news: there’s an AI for that.
Facilitating discussion is one of those teaching tasks that is sneakily quite challenging: you need to have goals (beyond creating noise); keep the discussion on track to achieve those goals in the allotted time; manage the speaking order; address incorrect information or offensive remarks; enforce norms and rules; actively listen to students and capture themes; and encourage students to listen and respond to each other. Increasing inclusion is its own challenge–ensuring that every student has the access, opportunity, and encouragement to actively engage in the discussion and learn by being part of it.
A particular challenge can be the Dominant Derailer: the student(s) who speak up far more than their peers, sometimes on a pet topic that isn’t aligned with the learning goals, and has the result of shutting out other voices. When Dominant Derailers run the discussion, they turn their peers into Silent Spectators, who are no longer actively listening but instead just waiting for the ‘discussion’ to end.
