Along the lines of my last post, I’ve tweaked another game that I have used previously — the marshmallow challenge. My goal was to illustrate how economic development can be considered a collective action problem in which trust plays a key role. Here are the rules of the game:
Each team has 18 minutes to build a tower topped by a marshmallow using the materials provided.
The members of the team that builds the tallest tower earn 25 points each.
A “Red” player secretly placed on your team gets 25 points if their real team wins.
If a team correctly identifies its Red player, each team member wins 25 points. Only one guess per team.
The debriefing discussion included my brief description of Rousseau’s stag hunt scenario, and these questions:
If one considers the height of a tower as an indicator of a society’s level of economic development, why did some societies (teams) develop more quickly than others?
Did cultural values promote trust among team members?
What was in each person’s best interest? Were these interests achieved?
How did having a Red on your team affect your team’s behavior?
Who do you think the Reds were? Why?
How does it feel to be accused of being a Red?
At the very end of the discussion, I revealed that there were no Red players.
The class had ten students that I divided into three teams. One team’s tower collapsed when time expired, but none of the teams exhibited a high degree of dysfunction due to suspicions about the identity of its Red player. As usual, I think the game would work better in a class with more students.
In an attempt to rectify the failure of my previous classroom game on ethnic heterogeneity, democracy and dictatorship, I created another game that included a loss aversion component. I intended the game to demonstrate the concepts found in Mancur Olson’s 1993 article, “Dictatorship, Democracy, and Development” (The American Political Science Review 87, 3). Here are the rules for game’s initial version:
Each person gets a playing card and 4 chips.
The class is divided into small groups.
The person with the highest card value in each group is a bandit.
The game has five rounds.
Each group’s bandit confiscates 1, 2, 3, or 4 chips each round from every other group member. This decision is made by the bandit. The bandit has to confiscate at least 1 chip from each group member each round, assuming the group member has a chip.
After round 1, 2, 3, and 4, each non-bandit gets 1 additional chip if they have ended the round with > 0 chips.
The person in each group with the most chips after round 5 earns points equivalent to the number of chips in their possession.
Version 2 of the game has the same rules as Version 1, plus:
A bandit can switch to a different group after each of rounds 1-4. The bandit with a higher value card turns another group’s bandit into an ordinary person.
The new bandit takes the eliminated bandit’s chips and can keep them or distribute some or all of them in any manner to members of their new group.
Version 3 has the same rules as Versions 1 and 2, plus:
Members of a group can eliminate a bandit if (a) they have card suits different from the bandit’s suit, and (b) the combined value of their cards exceeds the value of the bandit’s card. If a bandit is eliminated, the bandit’s chips are distributed equally among the challengers.
A bandit can retain control if (a) group members with cards of the same suit as the bandit’s decide to ally with the bandit and (b) the combined value of cards of this suit exceeds that of the bandit’s challengers.
Before play started, I stacked the deck with cards from only three suits because of the small class size — thirteen students are registered for the course, but only eleven showed up. I divided these eleven students into three groups.
For all versions of the game, all bandits confiscated the same number of chips from their group’s members in each round, even though the rules did not specify that they had to do this. In Version 1, one bandit confiscated all the chips from every group member in one round, which ended that group’s game play for the remaining rounds — demonstrating that it’s better for a stationary bandit to extract only a portion of wealth from the populace at any given time. During Version 2, no bandit changed groups, and in Version 3, no one tried to eliminate a bandit.
This game worked better than the last one, but it still needs a much larger number of participants for it to function as intended.
I recently ran a game in two classes that I had hoped would demonstrate the effects of ethnic heterogeneity in dictatorships and democracies. The basic mechanics of the game:
The class is split into groups. Each person gets a playing card. Card suit represents ethnicity, though I didn’t tell students this. A card’s numeric value equates to the power level of the person holding it. If someone in a group has a face card, then the group is a dictatorship. The person in the group with the highest value face card is the dictator, who makes all decisions. If no one in the group has a face card, then the group is a democracy, with decisions made by majority vote. The numeric values of the cards don’t matter.
The game is played in multiple rounds, with a greater number of points at stake in each round — I used five rounds, worth 3, 5, 7, 10, and 15 points, respectively. These points count toward the final course grade. In every round, each group allocates its points to its members according to the rules above. If anyone in a group is dissatisfied with how the points were distributed, the person can recruit a cluster of allies who have cards of the same suit to challenge the distribution. In a dictatorship, the challenge succeeds if the cluster’s combined power level exceeds that formed by the dictator’s allies. In a democracy, the challenge succeeds if the cluster’s total power level exceeds that of the rest of the group. When there is a successful challenge, the group has to distribute its points in a different way. Each round had a time limit of just a few minutes, and if a group failed to successfully allocate its points before a round ended, the group’s points for that round disappeared.
My youngest is currently getting stuck into her school’s debating society. Weekly topics range from getting rid of the monarchy to pushing vaccine mandates, with pupils getting dropped into a side at random, and at short notice.
You might well have done the same yourself when you were younger; I didn’t, mainly as I was too busy being awkward and gangly.
My daughter really likes the approach, both for the range of topics (which we often end up discussing over the dinner table) and for the reflection it promotes about how to make an effective case.
The other day as we sat at the orthodontist, waiting for a replacement retainer (hers, not mine), we were deep into whether a technocracy was better than a democracy when she raised a concern.
The format of debates requires you to defend a position, regardless of what you believe. So far, she’s not found herself pushing something she strongly disagrees with, but she felt uncomfortable about the thought of it.
Indeed, your beliefs – and any objective facts – count for nothing in formal debating. Yes, you can bring evidence, but it is in compelling presentation and investment in the logic of ‘your’ side that you can usually prevail. Put differently, debating seems to care more for what is convincing than for what is grounded in evidence.
At which point we wave from our PoliSci benches and give a big ‘hello’.
I noted that when I allocate students into my negotiations, I often like to put people in roles that don’t fit their own views, on the grounds that it’s a good exercise in learning to empathise. You might find it axiomatically true that X is right, but there are others out there who (strongly) disagree, so perhaps by trying to put yourself in their shoes for a bit you might better understand where they’re coming from.
But you see already the potential for a replication of the same dynamic as that debating society: maybe everyone focuses on ‘winning’ rather than the empathy.
In the debating society the format is very much focused on that competition, so it’s a real issue. For negotiations, I hope we have more latitude to limit the problem.
Most obviously, I never judge negotiation exercises on who ‘wins’, and often there is no clear ‘win’ available in basic structural terms. Secondly, the debrief that always follows is about process and substance, with consideration of the differing value judgments, how they arise and their impact. And finally there is often a degree of integration: progress towards agreements is usually about finding common ground rather than domination.
However, the orthodontist discussion did give serious pause for thought. In an age when politicians sometimes seem to be willing/able to say anything to gain support/profile, there is a danger that simply giving students rhetorical skills breeds a false impression that all truths are equal and find their value only in how well you speak of them.
Yes, the scientific method does point us towards the essential need for evidence, but maybe this isn’t enough. Empathy cannot be presented as a equivalent of sympathy or of equivalence, but as a tool for improving our understanding of contested spaces and topics, with which we can then work to find more inclusive ways forward, working together.
Maybe I’ll suggest that as a future topic for someone’s debating society.
Today we have a guest post from Michelle Goodridge, academic librarian at Wilfrid Laurier University. She can be contacted at mgoodridge [at] wlu [dot] ca.
After a casual conversation about classroom games with my colleague Professor Andrew Robinson, we created a foreign policy simulation for his course, HR 100 Human Rights and Human Diversity. We had two goals for the simulation: first, have students explore why state actors fail to advance human rights domestically and internationally, and second, measure the simulation’s effectiveness in helping students achieve desired learning outcomes.
Orienting the exercise around human rights instead of international trade.
Dividing students into three teams of high and middle-income pro-human rights. democracies, two teams of low-income democracies indifferent to human rights, one team of a high-income state that is anti-human rights, and one team representing an NGO.
Introducing the political objective of re-election.
Creating different winning conditions for each team.
To form teams, students picked one of several different colored t-shirts that we had laid out around the classroom. Each team received a corresponding packet of instructions and resources. I had the role of The Trader who accepted the geometric shapes produced by teams in exchange for political support units. Andrew injected human rights crises into the simulation via PowerPoint. The simulation ran an hour, with defined victory conditions that needed to be met to have a winner. Often none of the teams met its victory condition, which came as a shock to the students, but it helped illustrate the complexity of international relations.
After the game concluded, we took time to debrief the students, and this is when students made robust connections between the simulation and concepts they had been studying. I can only assume this is because verbalizing these responses right after the exercise is easier than writing them down a week afterward.
We attempted to measure the effectiveness of our Human Rights Foreign Policy Game with pre/post test evaluations. The evaluation results were anonymized, coded, and analyzed using SPSS. We found that the richest data came from students’ responses to the evaluation’s open-ended questions. So far, we have run this simulation in six semesters, and we will probably continue to use it in the future because of the high percentage of students reporting that it helped them learn. For more details, please see our article “Objective Assessment of Pedagogical Effectiveness and the Human Rights Foreign Policy Simulation Game,” Journal of Political Science Education 17, 2 (2021): 213-233, DOI: 10.1080/15512169.2019.1623048.
Today we have a guest post from Eric Cox, an associate professor at Texas Christian University. He can be contacted at e[dot]cox[at]tcu[dot]edu.
Does the online Statecraft simulation improve student learning when used as a key component of international relations classes? I explored this question in a Journal of Political Science Education article through a controlled comparison of two IR course sections taught during the same semester. One section was randomly chosen to participate in Statecraft, the other was assigned a research paper. The primary finding of the study was that students in both sections performed similarly on exams when controlling for other factors.
Statecraft is a turn-based simulation that divides students into “countries” that they govern. Each country must choose its form of government, economic system, and other attributes. Players also choose whether to focus on domestic spending priorities such as schools, hospitals and railroads, or on military capabilities. They must deal with terrorism, the melting of Ice Mountain, pirates, and rumors. The simulation is, to put it mildly, complex. I have been using it for just over a decade.
To try to put the students doing the research paper on an equal footing with those engaged with Statecraft, I dedicated several days of class to instruction in research writing skills and peer review. The students in this section spent roughly the same amount of time in class on their paper as the students in the Statecraft section did on the simulation. Both groups also wrote about the same amount.
At the end of the semester, I compared class performance on three exams and gave students a brief survey on their experiences. The initial findings were surprising: the research paper class did much better on exams but were less satisfied with the research assignment than the Statecraft students were with the simulation. I obtained access to students’ GPA when entering the course, and re-ran my analysis with GPA, whether students were taking the course for a grade, and whether students were political science majors as controls. Once these controls were introduced, the effect of Statecraft went away. The strongest predictor of course performance was their incoming GPA. Students with high prior GPAs made As, B students made Bs, and so on. Academic performance was independent of the research paper or Statecraft assignment. However, students in the Statecraft section showed a strong preference for the simulation over a traditional research paper, and students in the research paper section indicated they would have rather done Statecraft. Subsequent student evaluations have also demonstrated the relative popularity of Statecraft.
That said, my use of Statecraft has evolved, something I discuss in detail in my chapter of Teaching International Relations. Foremost, I dedicate class time to the simulation, and draw examples from the simulation when discussing IR theory, issue areas, and current events. Students have indicated that the simulation gives them a greater appreciation for the complexity of international relations and the challenges leaders face.
Editor’s note: previous posts on Statecraft can be found here.
Two weeks ago, students in my economic development and environmental politics course played my simulation on freshwater resource scarcity in Asia. If my memory is correct, it was the first time running the simulation in the physical classroom, and I was interesting in whether students behaved differently in the face-to-face environment compared to a prior iteration of the simulation that occurred online.
The underlying mechanics of the simulation were unchanged: six teams, each representing a different country with one or more transnational rivers crossing its territory. Turn by turn, the population expands, more food must be produced, and water demand increases, yet countries are building dams upriver and rainfall declines because of climate change. Eventually a country has a famine and millions of refugees spill into its neighbors.
This time around I added a victory condition: members of the team with the greatest percentage growth in GDP per capita when the simulation ended earned five points (out of a thousand) toward their final grades. I put a copy of the simulation’s spreadsheet, which shows how actions taken by teams affect water availability, food production, hydroelectricity generation, and GDP, on the LMS and encouraged students to experiment with it before the simulation started.
Student did seem more engaged with the simulation in the classroom than they had online, though it was far easier for me to observe their interactions. The real surprise was how baffled students were about the cause and effect relationships built into the spreadsheet. Growth in GDP requires growth in hydroelectric capacity, which only comes from building dams. Yet teams were hesitant to build dams. By the end of the simulation, China, for example, had stockpiled enough of a reserve to have constructed over one hundred dams, yet it had built only a handful. The largest change in GDP among the six teams? Only 1.1 percent over a twelve year period.
Students clearly had not tried to figure out the spreadsheet before the simulation started, and none of them seemed to understand the relationship between economic growth, food, and water. Consequently, many of them flailed about helplessly as their country’s water supply steadily dwindled. When asked during the debriefing why they chose inaction instead of action, I got mostly blank looks. As I’ve noted before, many students seem to have little understanding of cause and effect; instead, in their worlds, stuff just happens. While I would prefer not adding multiple assignments to the course to force students to work with the simulation’s causal relationships before the simulation actually begins, it might be necessary.
As I’ve mentioned before, part of my new role involves designing a negotiation exercise of an online, asynchronous programme.
This presents a number of rather basic problems, so consider this a bit of my attempt to try and work them out.
First up is the asynchronicity.
A fundamental part of negotiating is interaction, so if you can’t do that there-and-then, you have to deal with a major challenge. In this case, our usual cycle for students is a week, within which we set work for them to fit around their other commitments. Since most of our students are working, or have other major life obligations, that means it’s really hard to ask for anything speedier.
Even if most could turn things around in a matter of days, we can’t be certain that everyone can, so those not able to would suffer in the exercise.
Secondly, there a debrief issue.
The materials we produce are intended to be used for several years: our role is relatively separate from delivery, as our system of associate lecturers handle most of the pedagogic queries and support. If we accept that negotiation must have debriefing (and I certainly do), then how do we fit that into this system? Is it my work, or associates’, or do we have some generic points to reflect upon, and how would any of these models operate?
Finally, we have the tiny question of scale.
I don’t know how many students will be using this exercise in any given presentation (as we call our delivery), so I need a negotiation that can cope with both a large number of participants and a varying number of participants. Our plans say 80, but that’s neither here nor there, except in the most general of terms.
Oh, and I have to assume none of the students will have any prior experience in negotiating.
So what to do?
I’ve been working around some different abstracted options for a while to handle all of this, and it might be useful to consider these for a while. They vary by how much of a ‘negotiation’ they involve, since that interaction issue strikes me as the most fundamental one.
Obviously, the starting model is a set-up where there is direct student-to-student negotiation: it’s prototypical and best allows them to develop practical skills. But it needs much time, much support and debrief. Plus you have to work out roles.
So maybe you could have instead a ‘negotiation’ with an automated interlocutor: a ‘chose-your-own-adventure’ approach, effectively, but with a computer programme rather than a paper-based text. It can be played individually, paths/outcomes are fixed so feedback is easy, but it’s not so very much like actual negotiating.
A different direction would be to ask students to do the prep work for a negotiation: drawing up negotiating briefs, setting out positions and the like. This is crucial part of negotiating, so it’s prototypical, but without the pointy end of testing out ideas. It’s more manageable for support and debrief, but probably isn’t as engaging.
And most distantly of all, you could ask students to study a real-world negotiation, through the lens of some theory. That’s also a good skill to learn, but it’s not so hands-on as any of the others.
In short, it’s a world of compromises.
For our purposes, we really want to build practical skills, so we’re currently closest to the first option: the ‘proper’ negotiation. As we often discuss here, the purpose of the exercise needs to be clear to you and to the student, otherwise it’s pointless making choices. In that sense, having the discussion with the rest of the team was an essential step in moving this on.
My tentative model right now looks like the following, working within the constraints I have.
In my 4 week block for this, and alongside other work they need to do, I’m planning to give students a crash course in how to negotiate (week 1); two (and maybe three) rounds of negotiating (weeks 2-4); and some debriefing (week 4).
The block topic is international challenges to political stability, so I’ll be using a climate change topic as the substantive focus, which also allows me to use a UNFCC-style format, with a couple of hundred roles that I can allocate to individuals. Those roles will have an order, so we start by populating key representative states (in terms of the different preferences) and then work through to everyone else, so we can accommodate the varying numbers. Probably that means making a generic position pack, plus some headlines for each role, with some requirement to expand on that through their own research.
The training would be some materials on practical negotiating, plus an option to download a small crisis game, to play offline with friends/family or even just to muse upon.
The main section would then require students to post positions/text on a forum each week, ideally to build a single text for final approval. This will require relatively simple technology, but does rely on students to be able to build coalitions and engage in discussion, which will be an issue for some.
To keep debrief viable, we’d probably need to start with a draft text – to keep things within relatively clear bounds – then provide cues to students to aid their own reflection, with some debrief points that could track key issues within the draft. This should make it more possible to keep associates on top of what’s gone on.
And that’s about as far as I’ve got on this.
There are lots of practicalities to work through, at all steps, but we think the basic design is viable. As I work through those, I’ll write more, but I’d love to hear thoughts.
Today we have a guest post from Elia Elisa Cia Alves, Federal University of Paraíba (UFPB), and Ana Paula Maielo Silva and Gabriela Gonçalves Barbosa, State University of Paraíba (UEPB), of Brazil. Elia Elisa Cia Alves can be contacted at eliacia [at] gmail [dot] com.
The Challenge Game was developed by a group of professors at the State University of Paraiba and the Mettrica Lab in Brazil. It is suitable for teaching concepts in international relations theory, such as state survival within an anarchic system, the security dilemma, alliances and the balance of power, and hegemony.
To play this game in the classroom, you will need 1) approximately 8 to 50 students who can play either individually or in teams, depending on the purpose to which the game is put, 2) candy, points, or some other reward that can be distributed, and 3) a method of determining the winner of a challenge between two parties, such as dice (high roll wins), rock-paper-scissors, or an online random number generator. Also, the rules of the game should be visible to students during the game.
The game is played in four rounds of approximately ten minutes each. A challenge is a one-candy bet (a loss results in one piece of candy being taken away) with a 50% probability of winning. Any individual or team that is challenged must participate in the challenge. Only one challenge should occur at a time so that the instructor can note what happens. A student or team that ends up with zero candy can no longer issue challenges; they are “dead” for the remainder of the round.
Round 1: Each student starts with one piece of candy. The winner of a challenge takes one piece of candy from the loser and can then challenge someone else. Any student who loses all of his or her candy is out of the game for the round. Depending on class size, the instructor may want to limit each student to a maximum number of challenges.
Round 2: Candy is distributed unequally among students. Most students should have 1-2 candies, a few students should have 3, and only a couple of students should have 4. The instructor may want to allow students to form alliances, in which case students can borrow candies from each other if needed. However, the loan is optional.
Round 3: Group students into teams. Distribute candy unequally among teams as in Round 2. Each team represents a nation-state. Students within a team decide, using any decision making method they choose, whether the team challenges any other team. As in Round 2, the instructor might allow teams to form alliances.
Round 4: Group students into teams and distribute candy as in Round 3. The professor grants special rules to only teams that have the greatest number of candies, such as altering their odds of winning a challenge. After the game, the professor should debrief the class to link theoretical international relations concepts to students’ experiences of the game. In our JPSE article, we suggest several questions that can be used as part of the debriefing.