Modeling the evolution of Staphylococcus aureus through gameplay
By Jacqueline Griffith and Robert Marsteller
The theory of evolution is one of the most important concepts in all of biology, appearing in just about every subcategory of the subject. For high school students, it is also one of the most poorly understood ideas (Baumgartner and Duncan 2009). Oversimplified misconceptions found in evolutionary curriculum continue to be taught without considering how this misinformation affects students and their understanding of other biological concepts (Baumgartner and Duncan 2009). To avoid reaffirming these misconceptions, teachers can have students play a game of chance to simulate the random development of mutations in individuals within a population.
Computer-based and paper-based games have been useful tools when teaching students of all levels concepts that are often deemed too advanced (Liu and Chen 2013). Game-based learning mirrors problem-based learning; both strategies significantly improve student understanding of scientific topics (Pornpimon, Suwannattachote, and Kaemkate 2013). Game-based learning also helps students retain information learned in class (Gee 2008). The following activity helps correct misconceptions while integrating gameplay to improve student understanding of microevolution; the activity uses an example familiar to many high school students: methicillin-resistant Staphylococcus aureus (MRSA). Students compete against each other in small groups to evolve their own strain of MRSA. The largest bacterial population with the most adaptations wins, but at its core, this activity is a game of chance.
This activity was implemented in two different college-prep biology courses to introduce the evolution unit. These courses are classified as the lowest level biology courses at our school. Students played the game on the first day of our evolution unit, which lasted about four weeks. Our classes are taught within 90-minute blocks that meet every other weekday. The game was played by 145 students from six different classes taught by two different content-specific teachers and one special educator. Four of the classes are taught in a co-teacher setting; all these classes are taught by the same content-specific primary teacher and special education teacher. A different content-specific instructor taught the other two classes. The results of this experimental activity were compared to the results of two different co-taught classes, which were taught evolution using a discussion-based lesson that focused on antibiotic resistance. The discussion-based lesson participants received the same pretest and posttest given as the experimental group.
At the beginning of the activity, ask students, “What do you know about MRSA?” Students can record their responses in their science notebooks. Once students record their ideas in their notebooks, a whole-class discussion can take place. In our discussion, students were asked to share their thoughts and disclosed that they heard MRSA could be caught when playing sports and that it could be found on sports equipment. In all participating classes, students mentioned (without prompting from a teacher) that they heard a person could be infected with MRSA while playing sports or using sports equipment. Students knew that it was an infectious disease and that it could cause tissue degradation if left untreated.
The point of the introductory discussion is to gauge current student understanding and to help students build a personal connection to the content. We purposefully chose not to give too much information away before the activity. Understanding the specific characteristics of MRSA was not the goal of this activity. MRSA was merely used as a vehicle to teach evolution; we were more concerned with students understanding the mechanism of evolution and chose MRSA as an example to help them do so. Much of the information that students learn about MRSA comes from the discussion before the activity, and the Lives of Staph Actions List (Appendix C) needed to play the game. Following the discussion and before students were able to engage in the activity, they were given a pretest (Appendix A) to establish a baseline of student understanding of evolutionary concepts.
Students gathered in groups of three to five so that they could compete against one another and compare their progress throughout each round of the game. Ideally, you will have larger groups playing the game; groups of five have longer rounds and allow students to see a variety of outcomes. For students who require more personalized support, such as those with an individualized educational plan (IEP), smaller groups of three will work. This sort of grouping may limit distractions by having shorter rounds. During the activity, each group requires a Lives of Staph Game Rules (Appendix B), Lives of Staph Actions List (Appendix C), and two dice. Each player needs a paper clip, a pencil, and a Lives of Staph Player Sheet (Appendix D). Once all group and individual materials have been gathered, prompt students to begin setting up their games with the directions provided in the following section.
Tell students: “Place the Actions List and dice in the center of your table so all members of your group can use them.” Once they complete the previous task, tell students that they should clip their paper clip at population-level 1 on round 1 of their player sheet (physically model this action using your own worksheet and paper clip to clarify). Then, have students determine what order players in their group will take their turn. Students may establish who goes first by whoever rolls the largest number.
This activity was implemented in classes that contained a maximum of 30 students and a minimum of about 25 students. Students were allowed to pick their own groups but were encouraged to have closer to five group members in each group. When students chose their own groups, they seemed more engaged with the activity. If student behavior is a significant concern for your class, teacher-selected groups may work better. Each class would have about five to eight groups in total completing the activity at one time. Within the four classes taught in a co-teacher setting, 30% of the student population had an IEP.
After a player rolls the dice, two things may happen to the bacterium and its population in a round:
Rounds should last about 10–15 minutes. You can set a timer to regulate the amount of time students spend in a round. A game that runs from 30 to 45 minutes is a sufficient amount of time to understand the content being discussed. Limit gameplay to three 15-minute rounds. Students will record the results of their rounds on their player sheet. Remind your students that at the end of each round, they should cross out or circle the population size their bacterium ended with. Also, setting a timer for each round or for the length of the game helps keeps students focused during the limited time. Groups who complete rounds early may need additional player sheets to continue playing within the allotted time.
Actively circulate the room to gauge the pace of your students. Use the first round to allow students to learn the rules of the games. Also, remind students not to become too competitive; this is a game of chance, and no one can predict who will win. Toward the end of the second round, ask students if they notice any patterns within the game. Be sure to ask questions like, “What kind of populations are surviving until the end of the game?” “How would you describe the frequency of different genetic mutations?” or “Can you predict when a mutation will occur in an individual?” Keep up that line of questioning throughout round 3. Students who participated in the game in our classes responded by saying individuals had a higher chance of surviving when
Once students have played three rounds of the game, their Lives of Staph Player Sheet (Appendix D) will contain three very different looking bacteria and either Xs through or circles around the number on the population-level chart indicating the population-level that bacteria ended on. These results should display a pattern. The more adaptations a student’s bacterial population accumulates, the greater its fitness is in that environment. Also, a student can end a round on population-level 1 without any adaptations. Because this is a game of chance, many varying outcomes are possible. These worksheets, along with the other provided materials, serve as artifacts for students to use when responding to the Lives of Staph Analysis Questions worksheet (Appendix E).
Once a majority of the class has completed the game, provide students with the Lives of Staph Analysis Questions worksheet (Appendix E). Allow students to keep the game materials at their desks so they can refer to them as they answer questions. Students should look at other students’ Lives of Staph Player Sheets to get a sense of the different possible outcomes that may be experienced while playing the game. The questions on the analysis worksheet are student-centered and were written for students who played the game according to the rules. Students may reflect on their own experiences or the experiences of students in their group. Students may need between 15 and 30 minutes to complete the questions, depending on their academic level. Allow students to work through the analysis questions in their groups before facilitating a discussion around the results of the game as a class. Encourage students to work in their game groups to develop their answers; they will need to rely on the data collected by all players to answer the questions effectively. Discussing the results of the game as a class may assist with understanding the analysis questions. Facilitating a whole-class discussion on gameplay analysis using the Lives of Staph Analysis Questions worksheet (Appendix E) can be used as a summarizing activity if you have shorter class periods; additional supporting activities may not be necessary.
To assess formative student progress, these worksheets (Appendix E) can be collected and graded. Even though students will have different individual experiences while playing the game, they will develop similar answers to the questions. The events may be random, but after rolling the dice many times, certain events are more statistically likely to occur than others. Evolutionary patterns become more apparent the longer students play the game, and students can articulate those patterns by answering the questions outlined in Appendix A and Appendix E. Students can work on these questions independently; however, working within their game groups provides more data on which to base their conclusions and data unique to their game experience.
A few questions to emphasize and clarify are:
The questions concerning the growth and decline of a population can be explained by drawing parallels between the two; they are inversely related. If students can predict the events that cause an increase in a population, they can predict that the opposite event will cause a decrease in a population (i.e., more food vs. less food or more space vs. less space). Students predicting the outcome of continuing to play the game give specific examples, such as “a bacterial population will grow to be more evolutionarily fit or successful” or “populations with fewer adaptations will continue to fail.” However, their response to the question does not have to be specific; students can simply say that patterns will emerge as gameplay continues, and if they would like to make a specific prediction, they can. You can ask students how they defined evolution; as a whole group, analyze those definitions based on the commonalities they share and develop a definition the entire class can use throughout the evolution unit.
Questions regarding antibiotics and antibiotic resistance can be briefly discussed before being addressed using the TedEd video referred to in the following summarizing strategy section. A class discussion can also follow the analysis of the game, or the analysis of the game can act as a summarizing strategy on its own. Teachers can summarize the activity however they want, but a specific strategy is outlined below. As a segue into the summarizing activity, ask students, “What was the main takeaway of today’s activity?”
A possible summarizing activity following game completion could be a video discussion of the topics covered through the game. We used a TedEd video lesson (“What causes antibiotic resistance?”) that discussed the use and misuse of antibiotics. The goal of the video discussion was for students to connect the diminishing effectiveness of antibiotics to the microevolution of MRSA (Wu 2017). As the video plays, students could summarize the main idea of the video or develop a question that the video may lead them to ask. Following the video-based discussion, students share their main ideas as a whole group or in small groups. This activity is meant to emphasize the phenomenon that drove student learning during the game. The questions from the formative assessment can be reviewed or reiterated alongside this video.
Assessments and Student-Based Goals
After playing the game, students will know that
After playing the game, students will be able to describe the process of evolution by way of natural selection while using MRSA as an example and identify patterns in population changes with regard to explaining what caused them to occur.
The pretest and posttest assessments can be used to establish a baseline of student learning and determine how much progress students made to the learning goals. A posttest (Appendix A) can be administered to assess growth. Our classes were given a posttest that was identical to the previously provided pretest. Both the control group and the experimental group improved significantly; there was no significant difference between the two groups. The mean score for the control group’s posttests was 49.56%, while the mean for the experimental group’s posttests was 53.90%. The pretests and posttests were developed to assess both the discussion-based lesson and the game-based lesson.
Feedback was provided by the three participating teachers, as well as two veteran teachers who did not participate in the implementation of the game but they reviewed the activity’s paper-based materials. One of the veteran teachers remarked that “game-based learning makes learning evolutionary theory more accessible to student populations that perform at a lower academic level.” She thought the game was a good way of teaching evolution. One of the participating teachers noted that if “maybe a little preloading [important information] with literature or a formal discussion before the game would have [been clarifying].” The game was played without an in-depth discussion of the topics to see what information students learned from just the game; this additional information would be presented as a short excerpt or a video that could improve student understanding. This activity can be modified to meet the needs of students and the preferences of teachers.
This introductory activity serves as an anchor that students may hold onto when they are trying to make sense of the finer details of evolutionary theory. Our experimental group’s ability to define a mutation improved by 14% following the game, while their ability to define evolution improved by 21%. Student understanding of evolution occurring within populations and not in an individual organism improved by 29%. Understanding the fundamental processes that drive evolution will make it easier for students to deal with the more detailed aspects of it, as long as they have something tangible to hold onto. Using a game-based approach to teach evolutionary theory can be just as effective as delivering a traditional lecture-based lesson.
Jacqueline Griffith (firstname.lastname@example.org) is a secondary biology teacher at Dover High School and an adjunct assistant professor in biology at Delaware State University in Dover, DE, and Robert Marsteller is an assistant professor in education at Wesley College in Dover, DE.
Baumgartner, E., and K. Duncan. 2009. Evolution of students’ ideas about natural selection through a constructivist framework. The American Biology Teacher 71 (4): 218–27.
Gee, J.P. 2008. Learning and games. The ecology of games: Connecting youth, games, and learning, ed. K. Salen, 21–40. Cambridge, MA: The MIT Press.
Lui, E. Z.F., and P.-K Chen. 2013. The effect of game-based learning on students’ learning performance in science learning- A case of “Conveyance Go.” Procedia - Social and Behavioral Sciences 103: 1044–1051.
NGSS Lead States. Next Generation Science Standards: For States, by states. Washington, DC: National Academies Press.
Pornpimon, R., P. Suwannatthachote, and W. Kaemkate. 2013. Problem-Based Educational Game Becomes Student-Centered Learning Environment. IADIS International Conference on Cognition and Exploratory Learning in Digital Age: 336–40.
Wu, K. [Ted-Ed] (2017, August 7) “What causes antibiotic resistance?” https://www.youtube.com/watch?v=znnp-Ivj2ek
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