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INTRODUCTION
In the rapidly evolving landscape of education, much attention has been paid to innovative approaches to improving learning outcomes (Oliveira et al., 2021; Reyes et al., 2020, 2023, 2024). Among these, gamification has become a powerful tool to engage students and potentially foster critical thinking skills (Ruíz-Chávez & Terrones-Marreros, 2023).
Gamification has been conceived as the application of game design elements and game principles in non-playful contexts (Deterding et al., 2011; Yang et al., 2020; Ruíz-Chávez & Terrones-Marreros, 2023), and has been increasingly adopted in educational settings. Its potential to motivate learners, increase engagement, and improve learning outcomes has been widely recognized (Xi & Hamari, J2019). At the same time, the development of critical thinking skills remains a crucial goal in education, as these skills are essential for success in the twenty-first century workplace and for an informed citizenry (Salazar Aguirre & Cabrera, 2020).
In the literature, it has been reported that the concepts of gamification and critical thinking have been addressed. When examining the influence of gamification on critical thinking, it has been found that studies tend to be undertaken based on correlations between gamified learning experiences and critical thinking outcomes, with those that have also employed pre-test/post-test comparisons to measure the impact of gamification interventions on critical thinking skills (Dichev and Dicheva, 2017; Sailer & Homner, 2020). Gamification in education refers to the integration of game elements and mechanics into learning environments to improve motivation, engagement, and learning outcomes (Deterding et al., 2011; Yang et al., 2020; Ruíz-Chávez & Terrones-Marreros, 2023). These elements can include points, badges, leaderboards, challenges, rewards, and narratives, among others (Cózar-Gutiérrez & Sáez-López, 2016). The underlying principle is to harness the motivational power of games to make learning more enjoyable and effective (Jagušt et al., 2018; Gómez-Carrasco et al., 2020).
Research has shown that gamification can have positive effects on several aspects of learning (Dwyer et al., 2014). For example, a meta-analysis by Sailer & Homner (2020) found that gamification in education had small but significant positive effects on cognitive, motivational, and behavioral learning outcomes. The authors noted that the effectiveness of gamification depends on several factors, including context, specific game elements used, and learning domain.
Sailer & Homner (2020) conducted a systematic review of gamification research and reported that gamification was most commonly applied in computer science and information technology courses, although it is also possible to find them in experimental sciences and language learning courses. Toda et al. (2019) highlight that gamification generates positive results in terms of student participation, motivation, and academic performance. However, it is important to note that the effectiveness of gamification is not fully accepted. Some studies have reported neutral or variable results, emphasizing the need for careful design and implementation of gamified learning experiences (Dichev & Dicheva, 2017).
Critical thinking is a complex cognitive skill that involves the ability to analyze, evaluate, and synthesize information to form reasoned judgments and solve problems (Liu et al., 2014; Ruíz-Chávez & Terrones-Marreros, 2023). It encompasses a series of subskills, such as interpretation, analysis, evaluation, inference, explanation, and self-regulation (Ruíz-Chávez & Terrones-Marreros, 2023).
The importance of critical thinking in education and beyond cannot be overstated. In an era characterized by information overload and rapid technological change, it has been reported that the ability to think critically is essential to achieving academic success (Liu et al., 2014). Critical thinking skills are crucial for academic performance across disciplines, as they allow students to engage deeply with course material and develop sophisticated understanding (Liu et al., 2014), not forgetting that it is a topic that involves school ethics (Kim & Werbach, 2016). It has also been pointed out that it serves for job preparation, being a desirable skill for employers and critical thinking is also valued in terms of having an informed and civic citizenry (Aguilar Vargas et al., 2020).
And it has become a relevant factor for lifelong learning, because it favors the ability to think critically and continuous adaptation in a rapidly changing world (Dwyer et al., 2014). Given its importance in promoting critical thinking skills, it has been present in the intentions of education at all levels. However, developing these skills can be challenging, and educators are continually looking for effective methods to promote critical thinking in their students. This paper shows the results of the application of a gamification strategy to develop critical thinking in tenth grade students of Basic General Education in Ecuador. It was assumed that an appropriate strategy could increase the levels of this skill in young schoolchildren.
METHODOLOGY
The research is quantitative and comparative, proposed under a pre-experimental design (pre-test / post-test). A total of 74 students in the tenth year of Basic General Education from an Educational Unit in Quito, who were studying mathematics, were consulted. A survey was used, and the instrument was the Critical Thinking Evaluation Questionnaire by Palma et al. (2021) (23 items; α: 0.76), and whose pilot test (30 subjects) yielded a α: 0.81. It contemplated the dimensions of interpretation, analysis, evaluation, inference, the ability to explain and self-regulation.
The gamification strategy included 10 face-to-face sessions, with durations ranging from 2 to 3 academic hours. This initiative had a playful and collaborative approach. First, a pre-test was carried out that served as a baseline and diagnosis, followed by the implementation of the strategy over 4 weeks, to then proceed to its assessment by means of a Posttest, using the same questionnaire. The levels of both tests were calculated as proposed by Palma et al. (2021). The descriptive analysis included measures of frequencies and percentages by levels. For comparison, the non-parametric Wilcoxon Test (Wilcoxon-T) comparison test was used (H1: pretest < posttest; e.g. value < 0.05).
RESULTS
Strategy Description
The gamification strategy implemented in this research was developed with the purpose of investigating and stimulating the development of students' critical thinking in the subject of mathematics. The strategy involved pedagogical activities that incorporated playful aspects, considering challenges, rewards and competitive activities, with the intention of making the teaching of curricular content more attractive and promoting a participatory and active learning environment.
In the implementation process, it covered 10 sessions, where different games and activities were applied, designed to be able to approach mathematics concepts in a creative way, allowing students to participate individually and collaboratively in solving problems.
The activities were adapted to the cognitive level of the students and a progressive degree of difficulty was assumed, in order to promote analytical thinking and logical reasoning.
Pedagogical techniques were used that encouraged students to question and reflect on the information, as well as the transfer of the knowledge acquired to different contexts. Gamification aspects, such as challenges and rewards, and the use of scores, were incorporated in a way that stimulated student participation and engagement in the learning process, contributing to the development of skills such as decision-making and critical and interpretive analysis, respecting their own pace (self-regulation). A pre-test and a post-test were carried out to evaluate the effects of gamification on the development of students' critical thinking.
Comparison between the Pretest and the Posttest
Table 1 presents the data concerning the interpretation dimension. It was observed that, during the pre-test, 15% of the young people showed a high level, while the intermediate level contemplated 31%; the prevailing level being low, with 54%. In the post-test, the metrics varied, registering a change in the percentage structure.
There was evidence of a change in the high level, going from 15% to 51%, and in the low level, which went from 54% to 15%. The W-T showed that there was a significant difference (e.g. value 0.032 < 0.05); and that therefore the application of the strategy generated a change in the levels.
Table 1 Comparison: interpretation dimension.
| Dimension | Levels | Pre-test | % Acum. | Postest | % Acum. | Wilcoxon-T (W-T) | ||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | |||||
| Interpretation | High | 11 | 15 | 15 | 40 | 51 | 51 | 0.032* |
| Middle | 23 | 31 | 46 | 18 | 34 | 85 | ||
| Low | 40 | 54 | 100 | 16 | 15 | 100 | ||
| Total | 74 | 100 | 74 | 100 | ||||
Nota: * p ≤ 0.05; ** p ≤ 0.01.
Table 2 shows the data from the analysis dimension. It could be seen that, in the pre-test, 14% of the students exhibited a high level, while the medium level contemplated 32%; the low-level prevailing, with 54%. Post-test metrics varied, with a percentage improvement recorded.
The high level went from 14% to 52%, and at the low level, it went from 54% to 20%. The W-T showed a significant difference (p.value 0.025 < 0.05); and that therefore the strategy and its application generated the expected effect.
Table 2 Comparison: analysis dimension.
| Dimension | Levels | Pretest | % Now. | Postest | % Now. | Wilcoxon-T (W-T) | ||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | |||||
| Analysis | High | 10 | 14 | 14 | 39 | 42 | 42 | 0.025* |
| Middle | 24 | 32 | 46 | 19 | 38 | 80 | ||
| Low | 40 | 54 | 100 | 16 | 20 | 100 | ||
| Total | 74 | 100 | 74 | 100 | ||||
Nota: * p ≤ 0.05; ** p ≤ 0.01.
Table 3 shows the metrics of the evaluation dimension. The pre-test showed that only 18% of the students exhibited a high level of evaluation, in contrast to the low level (44%). It can be seen that 83% had a medium or low level. These metrics changed after the strategy was implemented. In the post-test results, the high level rose to 44% and the medium level went from 34% to 49%. The low level only reflected 7%. The W-T again showed that the strategy and its application generated the desired effect (e.g. value 0.035 < 0.05).
Table 3 Comparison: evaluation dimension.
| Dimension | Levels | Pretest | % Now. | Postest | % Now. | Wilcoxon-T (W-T) | ||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | |||||
| Evaluation | High | 13 | 18 | 18 | 34 | 44 | 44 | 0.035* |
| Middle | 25 | 34 | 51 | 21 | 49 | 93 | ||
| Low | 36 | 49 | 100 | 19 | 7 | 100 | ||
| Total | 74 | 100 | 74 | 100 | ||||
Nota: * p ≤ 0.05; ** p ≤ 0.01.
Table 4 shows the metrics for the inference dimension. The pre-test showed that the high level (18%) went to 38%, after the application. The low level ranged from 50% to 20% on Posttest. This is reflected in the W-T (e.g. value 0.041 < 0.05), demonstrating the effect of the application.
Table 4 Comparison: inference dimension.
| Dimension | Levels | Pretest | % Now. | Postest | % Now. | Wilcoxon-T (W-T) | ||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | |||||
| Inference | High | 15 | 20 | 20 | 33 | 38 | 38 | 0.041* |
| Middle | 22 | 30 | 50 | 24 | 42 | 80 | ||
| Low | 37 | 50 | 100 | 17 | 20 | 100 | ||
| Total | 74 | 100 | 74 | 100 | ||||
Nota: * p ≤ 0.05; ** p ≤ 0.01.
Table 5 shows the results of the explanation dimension. Percentage-wise, positive variations were observed between the pre-test and the post-test. The most relevant variation focuses on the high level (18% vs 51%).
The low level ranged from the initial 45% to 7% on Posttest. This is also reflected in the W-T (p.value 0.01 < 0.05), exhibiting a significant relationship.
Table 5 Comparison: explanation dimension.
| Dimension | Levels | Pretest | % Now. | Postest | % Now. | Wilcoxon-T (W-T) | ||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | |||||
| Explanation | High | 15 | 20 | 20 | 41 | 51 | 51 | 0.01** |
| Middle | 26 | 35 | 55 | 22 | 42 | 93 | ||
| Low | 33 | 45 | 100 | 11 | 7 | 100 | ||
| Total | 74 | 100 | 74 | 100 | ||||
Nota: * p ≤ 0.05; ** p ≤ 0.01.
The results of Table 6 summarize what was observed for the self-regulation dimension. Percentage-wise, positive changes were also observed between the pre-test and the post-test. The variation that stands out the most is focused on the high level (14% vs 33%). The low level varied from the initial 46% to 16% in the Postest, with the favorable change being evident. The W-T (e.g. value 0.039 < 0.05), exhibits a significant relationship that validates the application of the gamification strategy.
Table 6 Comparison: self-regulation dimension.
| Dimension | Levels | Pretest | % Now. | Postest | % Now. | Wilcoxon-T (W-T) | ||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | |||||
| Self-regulation | High | 10 | 14 | 14 | 31 | 33 | 33 | 0.039** |
| Middle | 30 | 41 | 54 | 21 | 51 | 84 | ||
| Low | 34 | 46 | 100 | 22 | 16 | 100 | ||
| Total | 74 | 100 | 74 | 100 | ||||
Nota: * p ≤ 0.05; ** p ≤ 0.01.
Table 7 summarizes what is reflected in the dimensions. It can be seen that critical thinking was increased from the gamification strategy. The high level reflects the favorable effect (16% vs 46%), and a reverse change was seen at the low level (46% vs 19%). This was demonstrated with the W-T (p.value 0.014 < 0.05). In this sense, the usefulness of the strategy is demonstrated at the level of dimensions and variables.
Discussion of results
The discussion of the results reveals that gamification, as a pedagogical strategy, had a significant impact on strengthening critical thinking in students. The findings demonstrate a considerable increase in critical thinking skills. Holguín et al. (2020) point out that many teachers do not use gamification effectively due to a lack of training and resources. However, after the implementation of gamification, there was a significant increase in students' ability to analyze and organize information, so its use is recommended, in agreement with Cotes et al. (2023).
Another relevant aspect is the improvement in the students' ability to evaluate information on the topics addressed, as demonstrated in the post-test. This reflects the importance of gamification in the development of evaluation and analysis skills, as proposed by López et al. (2022), who consider that critical thinking is essential to discern the validity of information.
The results also showed that students improved their ability to apply the information received and analyze mathematical concepts through gamification, which confirms the one pointed out by Encalada (2021), that gamification facilitates the understanding and retention of concepts. This strategy provided students with opportunities to apply their knowledge in a practical and real way.
The findings are consistent with what has been reported in pre-test/post-test studies, such as that of Cózar-Gutiérrez and Sáez-López (2016), whose results showed a significant improvement in critical thinking scores in the experimental group (p < 0.001), while the control group showed no significant changes. This is also in line with what was pointed out by Gündüz et al. (2020), who found a significant increase in critical thinking scores in the experimental group (p < 0.001), compared to no significant change in the control group.
The findings are similar to those highlighted by Jagušt et al. (2018) with primary school students in Croatia, where their results have significant effects on problem-solving skills for students who used the gamified application (p < 0.001), especially for students who had lower performance.
A study by Yang et al. (2020) in China also reports concurrent results with significant improvements in the level of critical thinking (p < 0.001) after the gamified pedagogical intervention.
It also coincides with the findings of Holguín García et al. (2020), who also reported that gamification generated favorable effects in the teaching of mathematics. Such pre-test/post-test studies endorse the results obtained here and validate the thesis of the positive effects of gamification on critical thinking skills explored in various thematic areas and educational contexts.
CONCLUSIONS
From this evaluation, it was possible to identify a significant increase in the use of skills such as interpretation, analysis, evaluation, mathematical and cognitive inference, the ability to explain and self-regulation, which confirms the effectiveness of gamification as a pedagogical tool to strengthen critical thinking.
Evidence suggests that gamification, when carefully designed and implemented, has the potential to have a positive impact on the development of critical thinking skills across various educational levels and subject areas. Comparisons between the pre-test and the post-test have shown significant improvements in critical thinking skills after gamification interventions in various educational settings, something that is confirmed by this work.
However, the field of study also faces several challenges, including context dependence, measurement issues, and the need for careful design to avoid potential pitfalls such as distraction or overemphasis on extrinsic motivation. These challenges point to important directions for future research, including the need for longitudinal studies, research of diverse contexts and populations, the development of design principles, and consideration of ethical implications.
