Gamifying review sessions: helping students integrate their learning in a supportive, enjoyable environment

Student engagement is a hot topic in education at the moment, and gamification is one way we can create effective and engaging learning environments for our students. Gamification can also be an excellent way to consolidate learning and enable multiple topics to be tested in a synoptic way. We’ve done this by creating a Murder Mystery based on the well-known games ‘Among Us’ and ‘Mafia’ which have in turn inspired the popular TV programme ‘Traitors’.¹ We timetabled the game as a session at the end of our second-year biochemistry module with the aim to integrate learning for our students, having observed that many of them compartmentalised their study and were missing the wider context.

Meta analyses have shown that gamification benefits from a game fiction, students working together in teams, and splitting the games into smaller ‘quests’.^2,3 Murder mysteries are popular in fiction, TV, and games but we needed to ensure that students would not be ‘murdered’ and drop out of the game, as we wanted our students engaged for the whole of the session. Consequently, we created an original fiction featuring abstract characters called ‘Sprites’, one of whom is the murderer (“the Impostor”).

In each quest/mystery, students work in small teams, interpreting pieces of bioanalytical data from four techniques. Students receive data in cycles, with the facilitator inviting the students to suggest the identity of the Impostor after each cycle. The next cycle starts with another murder and a further data set to be interpreted. Students must use all the provided data to identify suspects knowing that there are errors embedded within the data to distract them from correctly identifying the Impostor. We did this deliberately to help prepare them for their capstone projects where they will collect their own data – which may be contradictory or confusing. After two of three cycles, the students are asked to identify the Impostor, which most of them were able to do successfully.

We considered a range of features when building the narrative for the game:

1. Game Flow: Each piece of data was released 90 seconds apart using a cuckoo clock sound to signal when the time is up and students reported the mild time pressure enhanced the experience.
2. Team Work: Students worked in groups of two or three, which provided an element of competition with each team having a name. We built into the game a consolidation period at the end of each cycle for students to discuss all the data before identifying their suspect.
3. Characters: We created an original narrative featuring abstract creatures called Sprites and named our characters using non-traditional colours as this is preferred by most people across different cultures;^4-6 this increases inclusivity as it reduces the risk of participants (e.g., from specific cultures) having negative associations with certain traditional colour names.^7-8
4. Generation of data: We provided four pieces of data for each cycle, with the game being comprised of 2-3 cycles. Building on our Unique Data Sets work,⁹ new data sets are created every time the game is played and we provide additional games for the students to play outside of class. It is essential that information is presented in a way that does not cognitively overload the students, for example, mass spectrometry data was provided as a summary table rather than as raw data.
5. Platform for game: We chose Mural to run the game which enables students to interact with the data independently on their own devices, remaining anonymous, while the facilitator can continue to release data to the whole class.
6. Student briefing: We provided our students with a document and video walk-through before the session so that students knew the game narrative, the experiments which were conducted to generate the data, and an introduction to how to play the game.

We collected student feedback on the game anonymously using Mentimeter and it was overwhelmingly positive with students finding the session fun and educational, and liking working in teams. We have run this session twice now, and student feedback from the first year (2021/22) allowed us to improve the session for the next cohort (2022/23): we were told the session was too easy in the first year and that the correct answer could be arrived at through pattern matching rather than actual understanding of the techniques. Consequently, we introduced some changes in how we presented the data and students reported they needed a little more time – we have a two-hour session booked for this year’s Murder Mystery. One student commented that the game integrated material from three different staff members, making it more immersive.

We have found that gamification is an effective way to engage students and enhance their learning experience. In particular, using this approach synoptically is of benefit at the end of a module and aids in their ability to make connections between different topics.

 

References:

1. Hill, A. M., and Harmer, N. J. ‘A Murder Mystery Gamification Session to Consolidate Analytical Biochemical Techniques Learning’, 2023, Chem. Educ., DOI: 10.1021/acs.jchemed.3c00279.
2. Sailer, M., Homner, L. ‘The Gamification of Learning: a Meta-analysis’., 2020, Psychol. Rev., 32(1), 77-112.
3. Huang, R., Ritzhaupt, A. D., Sommer, M., Zhu, J. W., Stephen, A., Valle, N., Hampton, J., Li, J. W. ‘The Impact of Gamification in Educational Settings on Student Learning Outcomes: a meta analysis’, 2020, Technol. Res. Dev., 68(4), 1875-1901.
4. Pratchett, T. The Thief of Time: a Novel of Discworld; Harper Collins: New York, 2021.
5. Tarantino, Q., Keitel, H., Madsen, M., Penn, C. Miramax Films; Copyright Collection (library of Congress). Reservoir Dogs; Miramax Films: Los Angelos, CA 1992; p 12 reels of 12 on 16 (ca. 8910 ft).
6. Pratt, M. K. How to Analyze the Films of Quentin Tarantino; ABDO Pub Co; North Mankato, MN, 2011.
7. Chou, H.-Y., Chu, X.-Y., Chiang, Y.-H. ‘What Should We Call This Color? The Influence of Color-naming on Consumer’s Attitude Toward the Product’, 2020, Psychology & Marketing, 37(7), 942-960.
8. Ku, H.-H., Chen, Y. ‘Naming Product Colors with an Individual’s Identity and Product Evaluation: Self-referencing as a Mediator’, 2023, Journal of Product & Brand Management, 32(6), 958-971.
9. Harmer, N. J., and Hill, A. M. ‘Unique Data Sets and Bespoke Laboratory Videos: Teaching and Assessing of Experimental Methods and Data Analysis in a Pandemic’, 2021, Chem. Educ., 98(12), 4094-4100.

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