Minimizing Competition Increases Academic Performance in High School Students
Updated: Jun 11
Komathi Sivakumar, Meghana Kotta, Shivani Gotur
Seven Lakes High School Science and Engineering Fair of Houston
This project seeks to assess the competitiveness of many modern education systems while establishing adequate limits to prevent stress from excessive competition. As a result, the possibility of an optimal degree of competitiveness in the education of secondary school students that would be most efficient for most, if not all, students was researched. Competitiveness, despite its drawbacks, can improve student efficiency when utilized wisely, thus encouraging productivity while minimizing undue stress.
Three levels of competitiveness were used for the experimentation: least, moderate, and most competitive. As the competitive level increased, the individuality of the setting increased along with greater stakes. In each level, students were given a similar verbal lecture. Afterwards, they participated in an activity corresponding to a level of competitiveness and were tested on their comprehension of the topic lectured. Through manipulating levels of competition, student efficiency was measured. In addition to score, two categories were used to calculate student efficiency: comfort level and perceived effectiveness. Comfort level is the reported level of student ease in learning while perceived effectiveness is a rating on how much information students thought they retained of the information provided. The conclusion is that students are most effective in the least competitive setting and least effective in the most competitive setting. The results from the moderately competitive level indicate that moderating competitiveness does not provide a significant benefit or drawback from maintaining either a high or low competitive level. This study was initiated in the hopes of driving schools to take action by monitoring competitive practices, reforming unhealthy levels of competitiveness, and thereby augmenting academic performance as well as student satisfaction and mental health.
The focus of “Assessing the Optimal Degree of Competitiveness in the Education of Secondary Students” is to evaluate the role that competition in schools plays on learning in order to employ the optimal level of academic competition, maintaining a healthy amount of stress and promoting learning. Vicki Zakrzewski, Education Director of the Greater Good Science Center of the University of California, Berkeley, explains that, although competition inevitably causes students to face loss, it is beneficial as it teaches students to cope and develop a firm self-confidence. However, high competitive levels are shown to induce stress which result in health problems such as “high blood pressure, heart disease, obesity and diabetes,” evident in research conducted by the Mayo Clinic. Moreover, “overwhelming stress related to school not only demotivates [students] to do the work [but also reduces their] overall academic achievement and can lead to increased dropout rates,” as observed by the JED Foundation, a nonprofit organization that promotes emotional wellbeing for teens. In fact, according to John Shindler, a Professor in the Department of Curriculum and Instruction, it is the role of schools to “guide [student’s] choices…during a competitive experience” so that they are able to benefit from a regulated competitive environment. Similarly, “Cooperative Learning in a Competitive Environment: Classroom Applications,” a research paper by Dr. Simon Attle and Dr. Bob Baker, states that “A properly balanced approach combining cooperation and competition in fostering student learning” is crucial in achieving effective education as students are in “concert with others on their team.” With consideration to both competition’s benefits and drawbacks, it hypothesized that students in a moderately competitive environment are more likely to perform better compared to students in high or low competitive environments.
This study researches levels of competition and their effect on high school students. Competition was defined as “a social process that occurs when rewards are given to people on the basis of how their performances compare with the performances of others” by Jay Coakley, a renowned sociologist. Competition is induced through individualistic systems that “urge people to pursue personal achievement” according to Dr. Yuji Ogihara and Dr. Yukiko Uchida, researchers from Kyoto University. Collin Bertram, in a 2012 study, from Eastern Michigan University emphasizes that in the U.S., individualism paved a way to standardized high stakes testing which became the “shaping force in education” by fostering competition. Furthermore, Patrice Apodaca from LA Times reports that extreme competition “infects” the education system in various ways such as the case of Mariner's Elementary School in Newport Beach where the principal manipulated the application for a highly desired California Ribbon Award. This portrays the lengths of leap that schools may take which may push students to above and beyond limit for a “shiny trophy.” As this study hopes to assess the optimal degree of competitiveness in the secondary school system, high school students were used for experimentation. In order to construct the appropriate level of competition, the seating of students during the experimentation was planned so as to encourage or discourage individuality.
The independent variable is the competitive level. Due to the rise in debates regarding educational reform, the competitive environment of American high schools, accused of inflicting stress upon young students, has been widely contested. A key factor in the rise in competitiveness is college admissions, which are becoming increasingly selective each year. Last year, Harvard’s admission rate was 4.6%, a jarring contrast to its 11.1% admission rate only two decades prior. Another factor is the United States’ lamented performance on the PISA test, a global test that ranks the educational level of countries around the world, where the USA ranked 25 in 2018–outpaced by most developed countries. Both these and many other factors lead advocates to call for greater competition in public schools to ready students for their place in colleges as well as among their global counterparts. For the purpose of determining the validity of both sides of the debate on educational reform, three levels of competitiveness were established, ranging from low to high. Moreover, a moderately competitive level was also included to assess if competitiveness could be beneficial in smaller degrees. As competitiveness was operationally defined in this study as the individuality of learning in an environment characterized by high stakes, each level featured an ascending degree of individuality and incentive (meant to serve as stakes).
The dependent variable in this study was student effectiveness. This variable was measured through three categories: comfort level, score, and perceived effectiveness. Comfort level and perceived effectiveness were observed through a student survey, with a rating from 1-10. The scores were measured by how many questions out of 5 each student answered correctly–with each question being worth 20 points out of 100. Rather than simply measuring score, which would certainly reveal a student’s comprehension of a subject matter, comfort level and perceived effectiveness were also observed. According to a study conducted by Dr. Hasan Yusefzadeh, test anxiety, a phenomenon caused by stress prior to an exam, demonstrates that academic performance diminishes when students experience low comfort levels. Moreover, due to variations in learning strategies, student opinion on a particular educational environment shapes their focus and productivity. According to Louis Deslauriers, a Director of Science Teaching and Learning in the Faculty of Arts and Sciences, “The question of whether students’ perceptions of their learning matches with how well they’re actually learning is particularly important.” Therefore, it is necessary to discover which competitive level not only ensured effective comprehension but also the ease with which a student was able to learn and how well they believed they were able to effectively retain the information in the environment of a particular competitive level.
While deliberating the appropriate procedure for this experiment, two methods were discussed. The first was to conduct a naturalistic study: researchers would observe how students behaved and performed in competitive classes and compare them with classes with limited competition. The second method was to conduct an experiment, allowing the researchers to determine a causal relationship and personally manipulate environmental conditions. While the first method would be more convenient, the second method was chosen for this study as it was concluded to be more insightful for the overall purpose of assessing the optimal degree of academic competitiveness. Additionally, the data used is discrete, with each student rating from 1-10 and scoring from 0-100.
Materials and Methods
This study aims to find an optimal level of competitiveness in secondary school students. Furthermore, students in a moderately competitive environment are more likely to perform better compared to students in high or low competitive environments.
Due to the nature of this experiment, the only materials used were the incentives. The first level was minimally competitive. Researcher A read aloud a sheet of information (simulating a conventional lecture). The other two levels also had a lecture, however there was a different topic for each in order to prevent students participating in a later experiment from having an unfair advantage. The three lectures were worded as similarly as possible and the information provided was kept consistent. The students were seated closely across five tables, ensuring that all students could discuss with one another (both within and across tables) in order to eliminate individuality. Students then played a Kahoot game in classic mode, in which the students were tested on retention with 10 questions. There was no leaderboard, time limit (4 minutes max) and no points so as to ensure minimal competition. There was a low participatory incentive for everyone at the end, regardless of their performance.
The second level was moderately competitive. Researcher A again read aloud a sheet of information. Afterward, students were organized randomly into 4 teams of 4 students. They were tested on retention through a Kahoot game in the team mode with a time limit of 60 seconds. The team that placed 1st received a moderate incentive.
The third level was the most competitive. Researcher A again read aloud a sheet of information. They were then tested on retention through a Kahoot game in individual mode, and there was a time limit of 20 seconds. The top three performing students received a high incentive at the end.
Each level was performed on a different day. Regardless of the level, all participants finished by completing a Google form, in which they were briefly tested on their individual recall (with 5 questions that were 20 points each to measure scores). The questions asked on the Google form were the same across the three topics. The google form was also used to collect data on comfortableness and perceived effectiveness (on a scale of 1-10).
After completing the experimentation process, the results of the Google form were compiled to assess student comfort levels, average scores, and perceived effectiveness. In measuring student opinions, a scale from 1-10 was provided for students to rate their comfortableness and perceived effectiveness of the learning model. Finally, the data was analyzed by measuring the mean and standard deviation, while outliers were noted and recorded. Statistical significance was measured using analysis of variance (ANOVA) and confidence intervals.
Student Comfort Levels
Comfortableness can be defined as the reported level of student ease and stressless learning for each particular level of competition. Students’ comfort level averaged to 6.71, 6.8, and 7.9 in order from the least to most competitive level. As comfortableness increases, the competitive level also increases. On average, the data for all competitive levels varies by about 2 points. However, by conducting analysis of variance, it is unlikely that the results for comfort level are statistically significant. In order to assess this, the values depicted in Figure 2 were calculated. The sum of squares for groups (SS Groups) and the sum of squares for errors (SS Errors) were used to calculate the mean-squared variation due to groups (MSG) and the mean-squared errors (MSE). By calculating MSG/MSE, the F-value was found, which in this case is 1.33.
The academic performance was measured through a google form assessing the number of questions students correctly answered out of 5 (meaning each question was worth 20 points which added up to 100 points). The mean score for the least competitive level was 92 points, moderately competitive was 86 points, and finally, the most competitive was 70 points. A general trend can be observed, where the average scores decrease as the competitiveness increases. On average, the data varies from the mean the most by 34.318 points in the most competitive stage. The other two competitive levels demonstrate significantly lower standard deviations of 19.5 and 13.5 for least and moderately competitive levels, respectively. There are no outliers for the scores in moderate and most competitive levels; however, the least competitive level has 3 outliers at 20, 60, 80. By conducting analysis of variance, it is likely that the results for scores that are statistically significant between the least competitive and most competitive levels. This idea was supported with statistical evidence provided by the ANOVA, the values of which are depicted in Figure 4. The sum of squares for groups (SS Groups) and the sum of squares for errors (SS Errors) were used to calculate the mean-squared variation due to groups (MSG) and the mean-squared errors (MSE). By calculating MSG divided by MSE, the F-value was found, which in this case is 3.52.
Afterward, the confidence intervals were calculated by taking the mean difference between two competitive levels and adding and subtracting it from the margin of error. To calculate the margin of error, the critical value of z for confidence intervals was first calculated using a 95% confidence level, resulting in the value 1.96. Then, the sample sizes for the two competitive levels being subtracted (e.g. the least competitive level minus the most competitive level) were reciprocated and added. The square root of the resulting value was then multiplied with the square root of MSE. Finally, the difference between the means of the two competitive levels was taken, and this difference was both added and subtracted from the aforementioned margin of error to create the two-proportion confidence interval. This process was conducted for the least minus the moderately competitive level, the moderately minus the most competitive level, and the least minus the most competitive level. Respectively, these intervals are [-10.82, 23.58], [-4.02, 36.02], and [5.18, 39.58]
At the conclusion of all three stages of the experiment, the least competitive setting was reported to have the greatest average rating of perceived effectiveness. Students were asked to rate how effective they believed their setting was in teaching them about their topic on a scale from 1-10, with 1 being the least effective and 10 being the most effective. Using the same ANOVA procedure, Hence, it is unlikely that the results obtained in this experiment occurred due to random chance. In order to assess this, the values depicted in Figure 6 were calculated using ANOVA, generating an F-value of 1.89.
This study began in the hopes of determining how competitive the secondary school system should be in order to ensure optimal student efficiency. The hypothesis of this study was that the moderately competitive level would display the greatest overall effectiveness. It was believed that, if this hypothesis was proved through experimentation, then a veneer of validity could be offered to both sides of the argument regarding the role of competition in education–that students could thrive when the competition was presented in healthy doses. However, the results weakly support this hypothesis as the moderately competitive level did not peak in any of the three categories: comfort level, score, and perceived effectiveness. In fact, the moderately competitive level had the lowest student rating in perceived effectiveness. In the other two categories, it had median results–having neither the greatest nor the least value. Overall, the least competitive level had the greatest success while the most competitive level had the least success.
The variables used to assess the optimal degree of competitiveness were student comfortableness, scores, and effectiveness. To begin, comfortableness during the Kahoot activity was measured using a student-reported survey on a 10-point scale. The students rated comfortableness based on how at ease they felt in their environment as a way to assess the level of stress experienced in the arrangement. In the data collected, it was observed that although the means of comfort levels appear to increase along with the level of competition, this is in fact unlikely as the analysis of variance (ANOVA) calculated an F-value of 1.33. As the F value is considerably small, it can be determined that comfort level is not significant to competitive level. As a result, comfort level will be excluded from further analysis as it is likely irrelevant to competition.
Secondly, perceived effectiveness was also measured on a scale from 1-10. Participants were instructed to give a rating on how much information they thought they retained of the information provided based on the competitive setting. This was given to account for decreased or increased learning that would have occurred as a result of the environment. As learning takes a different form for each student, individual preference for the style of education was assessed through perceived effectiveness. A lower rating would indicate that the style of education for the student in question was not successful in teaching them about the topic as they were not able to effectively retain the information presented. The vice versa would be true for a higher rating of perceived effectiveness. The ANOVA procedure for perceived effectiveness generated an F-value of 1.89. As the F value is considerably small, it can be determined that perceived effectiveness is not significant to competitive level. As a result, perceived effectiveness will also be excluded from further analysis as it is likely irrelevant to competition.
Finally, average scores were measured using five questions on the google form out of 100 points. These questions, which were identical across all three competitive settings, measured retention of the information presented in the lecture. The score was based on the number of questions the participants answered correctly out of five (each question was worth 20 points). Rather than perceived effectiveness, these questions more accurately measured how well students remembered the topic lectured. In terms of outliers, the least competitive setting yielded three outliers for scores. However, according to the ANOVA procedure, the scores are significant to the competitive levels. As a result, the focus of the analysis was on scores, and it was used as the sole meter to measure student efficiency as both comfort level and perceived effectiveness are not affected by competitive level.
In order to analyze scores, the two-proportion confidence intervals were calculated. As both the confidence intervals that included the moderately competitive level included zero and negative values, it is likely that moderating competition yields no significant result as opposed to simply using either a high or low competitive level. However, the least competitive setting and the most competitive setting yielded a positive, non-zero difference in their two-proportion confidence interval. Hence, it can be concluded that low competition in the education of secondary students is more effective than high competition. No significant conclusion can be drawn about the efficiency of moderate competition.
Research regarding competitiveness finds that moderately competitive methods of learning yielded greater benefits to the students. In Competition and Cooperation: An Assessment and integration of seemingly paradoxical actions, Kyle Turner concluded that “competition and cooperation independently of one another, an interdependent conceptualization of these two phenomena may be more appropriate” than mere competition alone whereas the research supports least competitive method. To maintain consistency among participants, the procedure did not allow the participants to take notes during the lecture. This may or may not be their norm in a typical lecture which could have affected their performance on the assessment.
The findings of this study are subject to limitations that should be addressed in further research. Although all levels were presented with the appropriate level of incentive (a greater incentive for a higher competitive level, as to ensure the gradual increase in stakes for competition), it is possible that the incentives did not match student preference and hence caused a misappropriation of motivation for certain students. Another confounding variable is that some students may have experienced a variation in the difficulty of the three subjects chosen for the lecture, although they were designed to be equally difficult. The findings of this study may not be applicable to the broader population of secondary students as the sample was produced from only one high school. Furthermore, the teaching method employed was a verbal lecture, so student scores may not be representative of their retention due to variations in learning strategies, such as reading the lecture or a visual display of the content. The scope of the results is limited as learning is operatively defined as retention of subject matter in this study and therefore cannot be applicable to other aspects of learning such as practical skill learning or thorough comprehension of contextual ideas.
The moderately competitive level was hypothesized to be the most effective of the three levels, but this is incorrect as per the findings of this study. It is suggested, in hopes of furthering this study, that the sample size be enlarged and replicated across multiple secondary schools to broaden the application of its findings. While it cannot be proved that competition is a helpful tool in increasing student efficiency, it is possible to indicate that higher levels of competition are debilitating to students. On the contrary, the results of this study bring to question whether competition decreases academic effectiveness and if the best path forward for secondary schools is to drive all elements of competition out of their system.
Dean, Kyle. Competition and Cooperation: An Assessment and Integration of Competition and Cooperation: An Assessment and Integration of Seemingly Paradoxical Actions Seemingly Paradoxical Actions. 2015.
Shindler, John. “Chapter 18: Competition in the Classroom.” Web.calstatela.edu, 2009, web.calstatela.edu/faculty/jshindl/cm/Chapter18competition-final.htm.
Butera, Fabrizio, et al. “Competition in Education.” University of Lausanne, 5 Dec. 2020, www.researchgate.net/publication/346923549_Competition_in_Education.
Attle, Simon, and Bob Baker. “Cooperative Learning in a Competitive Environment: Classroom Applications.” International Journal of Teaching and Learning in Higher Education, vol. 19, no. 1, 2007, pp. 77–83, www.isetl.org/ijtlhe/pdf/IJTLHE121.pdf.
Cantador, Iván, and José Conde. EFFECTS of COMPETITION in EDUCATION: A CASE STUDY in an E-LEARNING ENVIRONMENT. 2010.
Yusefzadeh H, Amirzadeh Iranagh J, Nabilou B. The effect of study preparation on test anxiety and performance: a quasi-experimental study. Adv Med Educ Pract. 2019;10:245-251. doi.org/10.2147/AMEP.S192053