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The effect of gamification on learning performance of students in a STEM program

(2020)
Author
Promoter
(UGent) and Katherine Chiluiza Garcia
Organization
Abstract
Worldwide, there is a growing demand for Science, Technology, Engineering, and Mathematics (STEM) professionals to reshape the world of work (Fayer, Lacey, & Watson, 2017; Shapiro, Østergård, & Hougard, 2015). This demand has put STEM education at the center of educational reforms, such as motivate school-age students to pursue STEM-related careers (European Commission, 2015). Despite these efforts, STEM education currently faces different challenges: low enrolment and high attrition rates in higher education programs (Sithole et al., 2017), as well as low academic performance (OECD, 2018) and gender disparity (UNESCO, 2017). It is, therefore, not surprising that higher education institutions want to overcome the above issues by motivating more students to enroll in STEM fields. In this context, gamification is presented as an alternative active learning methodology by motivating and engaging students in their learning activities (Langendahl, Per-Anders Cook & Mark-Herbert, 2016; Ribeiro, Leal da Silva, & Quadrado Mussi, 2018). Gamification refers to the use of game elements in non-game contexts (Deterding, Dixon, Khaled, & Nacke, 2011). Given that worldwide, 57% of gamers range from 10 to 35 years old (Statista, 2017), it seems fit for STEM education to include gamification as part of the students’ active learning process. Thus, the current dissertation formulated its first research objective: analyze the current research gaps of gamification in STEM Higher Education. Two systematic reviews of research were conducted to address the objective. The first review focused on gamification in STEM Higher Education to have a general overview of the state-of-the-art in the topic (chapter 2). The second review focused explicitly on gamification and learning performance (chapter 3), the critical study variable. The reviews examined 30 and 23 studies, respectively. The findings in both studies helped to identify the following gaps. First, there was a lack of studies in certain STEM areas, which showed to be more inclined only to study Computer Science –related subjects. Second, most studies focused on a combination of game elements, causing a lack of understanding of the game element that has a positive impact on student performance. Third, there was a lack of validated psychometric measurements in the studies that could be questioned due to their weak reliability. Most studies used only the logs provided by the Learning Management System to assess student’s gamified actions. Fourth, there was a lack of focus on student’s mediating or moderating variables that could have an impact on student’s learning performance. Fifth, more studies were needed to underpin the direct or indirect linkage of gamification on learning performance. Sixth, there was a need to consider a suitable sample that could provide sufficient power, and effect sizes, and set up longer experimental interventions to avoid novelty effects and a lack of generalization. The identified gaps helped formulated the second research hypothesis. Evaluate the impact of specific gamified elements on learning performance. This objective was subdivided into three objectives, each aligned to a study. The gaps also helped us with design guidelines. An in-depth analysis of the literature on gamification (Chapter 1) also helped us identified the theoretical framework from which this dissertation was built on. For learning performance, we used the Theory of Gamified Learning (Landers, 2014) that indicates how gamification affects learning performance via mediation or moderation. Regarding motivation, The Self-Determination Theory (Ryan & Deci, 2000) with its corresponding sub-theories (e.g., Cognitive Evaluation Theory) helps us understand how intrinsic motivation and autonomous motivation can be achieved by fulfilling the need of autonomy, competence, and relatedness. Furthermore, it helped us understand under what conditions intrinsic motivation can be undermined or facilitated. In terms of self-efficacy, we chose Bandura's definition (1994), explaining people’s beliefs about their abilities to perform tasks focusing on four primary sources of influence. These are mastery experiences, vicarious experiences, performance feedback, and physiological or emotional states. As for student engagement, we built on Gunuc & Kuzu (2015), Fredricks, Blumenfeld, & Paris (2004), as well as Trowler (2010), explaining its different dimensions: behavioral, emotional, and cognitive. Finally, for the gamified design, we used the theory of Situated Motivational Affordances (Deterding, 2011), which explains that motivational needs are satisfied depending on how an artifact or, in this case, game elements are used, and not necessarily how they have been used. The 6Dimensions framework (Werbach & Hunter, 2012) also guided us in the design of the gamified environment. Study 1 (chapter 4) examined the effect of gamification – building on leaderboards - on learning performance. Furthermore, mediating variables such as intrinsic motivation, self-efficacy, engagement, and demographic variables such as gender, previous gaming experience, among others, were considered. A pretest-posttest quasi-experimental design (N=89) with an experimental (N=55) and a control condition (N=34) was set up in an Introductory Computer Programming course, lasting six weeks. Results indicated a significant improvement in the learning performance of students in the gamified condition. However, no interaction effect was detected due to mediating and demographic variables. Study 2 (chapter 5) also analyzed the impact of gamification on learning performance, intrinsic motivation, self-efficacy, and engagement in engineering students taking a basic programming course. The difference was the game element: badges. One hundred sophomore undergraduates participated in a quasi-experiment, lasting six weeks. A pretest-posttest design with control (N=50) and experimental group (N=50) was set up. Results showed a statistically significant improvement in engagement in gamification students, compared to the control group. However, no significant impact on learning performance, intrinsic motivation, self-efficacy, and any of the student demographic variables was observed. Study 3 (chapter 6) addressed the game element that showed a more favorable result: leaderboards. The limitations from studies 1 and 2 also helped improve the design of study 3, namely the need to include qualitative data to complement the quantitative data analysis, and to widen the motivation spectrum to analyze more than just intrinsic motivation. Thus, the study, once again, assessed the effect of gamification on learning performance. However, it now included the autonomous motivation as a mediating variable, apart from self-efficacy. Engagement was no longer studied. Furthermore, three demographic variables were not studied anymore: personality, age, and high school major. Participants were 175 undergraduate students enrolled in a Calculus class. The study was based on a pretest-posttest quasi-experimental design, involving students in an experimental (N=34) and control condition (N=141). The study lasted nine weeks. Results pointed at a significant improvement in learning performance in the gamified condition. Nevertheless, no effects are observed due to mediating variables. Overall, in this dissertation, we showed that students increased their learning performance more in the gamified environment compared to a control group using leaderboards. However, as much as we tried to present the gamified design differently, we did not find a significant change in motivation and self-efficacy. We did find a change in engagement only in the badge oriented course. When trying to understand the lack of significant results, different answers showed up (chapter 7). They could have been related to the nature of the subject, the gamified design, the methodological design, among others. Students could have still perceived the game elements as they were initially designed: leaderboards to foster competition, diminishing intrinsic motivation, and badges as external motivators only. Nevertheless, we reiterate that gamification has shown the potential to push STEM programs towards an increase in learning performance.
Keywords
Gamification, learning performance, self-efficacy, motivation, STEM, engagement

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Please use this url to cite or link to this publication:

MLA
Ortiz Rojas, Margarita Elizabeth. The Effect of Gamification on Learning Performance of Students in a STEM Program. Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen, 2020.
APA
Ortiz Rojas, M. E. (2020). The effect of gamification on learning performance of students in a STEM program. Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen.
Chicago author-date
Ortiz Rojas, Margarita Elizabeth. 2020. “The Effect of Gamification on Learning Performance of Students in a STEM Program.” Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen.
Chicago author-date (all authors)
Ortiz Rojas, Margarita Elizabeth. 2020. “The Effect of Gamification on Learning Performance of Students in a STEM Program.” Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen.
Vancouver
1.
Ortiz Rojas ME. The effect of gamification on learning performance of students in a STEM program. Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen; 2020.
IEEE
[1]
M. E. Ortiz Rojas, “The effect of gamification on learning performance of students in a STEM program,” Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen, 2020.
@phdthesis{8669113,
  abstract     = {Worldwide, there is a growing demand for Science, Technology, Engineering, and Mathematics (STEM) professionals to reshape the world of work (Fayer, Lacey, & Watson, 2017; Shapiro, Østergård, & Hougard, 2015). This demand has put STEM education at the center of educational reforms, such as motivate school-age students to pursue STEM-related careers (European Commission, 2015). Despite these efforts, STEM education currently faces different challenges: low enrolment and high attrition rates in higher education programs (Sithole et al., 2017), as well as low academic performance (OECD, 2018) and gender disparity (UNESCO, 2017). It is, therefore, not surprising that higher education institutions want to overcome the above issues by motivating more students to enroll in STEM fields.
In this context, gamification is presented as an alternative active learning methodology by motivating and engaging students in their learning activities (Langendahl, Per-Anders Cook & Mark-Herbert, 2016; Ribeiro, Leal da Silva, & Quadrado Mussi, 2018). Gamification refers to the use of game elements in non-game contexts (Deterding, Dixon, Khaled, & Nacke, 2011). Given that worldwide, 57% of gamers range from 10 to 35 years old (Statista, 2017), it seems fit for STEM education to include gamification as part of the students’ active learning process.
Thus, the current dissertation formulated its first research objective: analyze the current research gaps of gamification in STEM Higher Education. Two systematic reviews of research were conducted to address the objective. The first review focused on gamification in STEM Higher Education to have a general overview of the state-of-the-art in the topic (chapter 2). The second review focused explicitly on gamification and learning performance (chapter 3), the critical study variable. The reviews examined 30 and 23 studies, respectively. The findings in both studies helped to identify the following gaps. First, there was a lack of studies in certain STEM areas, which showed to be more inclined only to study Computer Science –related subjects. Second, most studies focused on a combination of game elements, causing a lack of understanding of the game element that has a positive impact on student performance. Third, there was a lack of validated psychometric measurements in the studies that could be questioned due to their weak reliability. Most studies used only the logs provided by the Learning Management System to assess student’s gamified actions. Fourth, there was a lack of focus on student’s mediating or moderating variables that could have an impact on student’s learning performance. Fifth, more studies were needed to underpin the direct or indirect linkage of gamification on learning performance. Sixth, there was a need to consider a suitable sample that could provide sufficient power, and effect sizes, and set up longer experimental interventions to avoid novelty effects and a lack of generalization. The identified gaps helped formulated the second research hypothesis. Evaluate the impact of specific gamified elements on learning performance. This objective was subdivided into three objectives, each aligned to a study. The gaps also helped us with design guidelines. An in-depth analysis of the literature on gamification (Chapter 1) also helped us identified the theoretical framework from which this dissertation was built on. For learning performance, we used the Theory of Gamified Learning (Landers, 2014) that indicates how gamification affects learning performance via mediation or moderation. Regarding motivation, The Self-Determination Theory (Ryan & Deci, 2000) with its corresponding sub-theories (e.g., Cognitive Evaluation Theory) helps us understand how intrinsic motivation and autonomous motivation can be achieved by fulfilling the need of autonomy, competence, and relatedness. Furthermore, it helped us understand under what conditions intrinsic motivation can be undermined or facilitated. In terms of self-efficacy, we chose Bandura's definition (1994), explaining people’s beliefs about their abilities to perform tasks focusing on four primary sources of influence. These are mastery experiences, vicarious experiences, performance feedback, and physiological or emotional states. As for student engagement, we built on Gunuc & Kuzu (2015), Fredricks, Blumenfeld, & Paris (2004), as well as Trowler (2010), explaining its different dimensions: behavioral, emotional, and cognitive. Finally, for the gamified design, we used the theory of Situated Motivational Affordances (Deterding, 2011), which explains that motivational needs are satisfied depending on how an artifact or, in this case, game elements are used, and not necessarily how they have been used. The 6Dimensions framework (Werbach & Hunter, 2012) also guided us in the design of the gamified environment.
Study 1 (chapter 4) examined the effect of gamification – building on leaderboards - on learning performance. Furthermore, mediating variables such as intrinsic motivation, self-efficacy, engagement, and demographic variables such as gender, previous gaming experience, among others, were considered. A pretest-posttest quasi-experimental design (N=89) with an experimental (N=55) and a control condition (N=34) was set up in an Introductory Computer Programming course, lasting six weeks. Results indicated a significant improvement in the learning performance of students in the gamified condition. However, no interaction effect was detected due to mediating and demographic variables.
Study 2 (chapter 5) also analyzed the impact of gamification on learning performance, intrinsic motivation, self-efficacy, and engagement in engineering students taking a basic programming course. The difference was the game element: badges. One hundred sophomore undergraduates participated in a quasi-experiment, lasting six weeks. A pretest-posttest design with control (N=50) and experimental group (N=50) was set up. Results showed a statistically significant improvement in engagement in gamification students, compared to the control group. However, no significant impact on learning performance, intrinsic motivation, self-efficacy, and any of the student demographic variables was observed.
Study 3 (chapter 6) addressed the game element that showed a more favorable result: leaderboards. The limitations from studies 1 and 2 also helped improve the design of study 3, namely the need to include qualitative data to complement the quantitative data analysis, and to widen the motivation spectrum to analyze more than just intrinsic motivation. Thus, the study, once again, assessed the effect of gamification on learning performance. However, it now included the autonomous motivation as a mediating variable, apart from self-efficacy. Engagement was no longer studied. Furthermore, three demographic variables were not studied anymore: personality, age, and high school major. Participants were 175 undergraduate students enrolled in a Calculus class. The study was based on a pretest-posttest quasi-experimental design, involving students in an experimental (N=34) and control condition (N=141). The study lasted nine weeks. Results pointed at a significant improvement in learning performance in the gamified condition. Nevertheless, no effects are observed due to mediating variables.
Overall, in this dissertation, we showed that students increased their learning performance more in the gamified environment compared to a control group using leaderboards. However, as much as we tried to present the gamified design differently, we did not find a significant change in motivation and self-efficacy. We did find a change in engagement only in the badge oriented course. When trying to understand the lack of significant results, different answers showed up (chapter 7). They could have been related to the nature of the subject, the gamified design, the methodological design, among others. Students could have still perceived the game elements as they were initially designed: leaderboards to foster competition, diminishing intrinsic motivation, and badges as external motivators only. Nevertheless, we reiterate that gamification has shown the potential to push STEM programs towards an increase in learning performance.},
  author       = {Ortiz Rojas, Margarita Elizabeth},
  keywords     = {Gamification,learning performance,self-efficacy,motivation,STEM,engagement},
  language     = {eng},
  pages        = {279},
  publisher    = {Universiteit Gent. Faculteit Psychologie en Pedagogische wetenschappen},
  school       = {Ghent University},
  title        = {The effect of gamification on learning performance of students in a STEM program},
  year         = {2020},
}