In the analysis of scale 1, “Game-based Learning in Initial Training”, we can see that most students bring positive assessments regarding the consideration of this approach as essential in training future teachers, and regarding the importance in initial university training to work with immersive environments, with positive values (agree or strongly agree) higher than 95 %. The benefits of 3D interactive gaming environments in initial teacher training also get positive values from over 90 % of the sample. As for initial training and skills in this field, just under a quarter of the sample had worked with video games and gamification in college applications; similar values are seen related to how to design video game activities in educational settings.
With regard to scale 2 “Gamification in Educational Contexts”, we would point out that 100 % of the students assess creativity with positive values (agree or strongly agree). Over 97 % of students also emphasize the collaborative advantages, skills development and educational innovation. And finally, more than 94 % indicate that communication, interaction and motivation in learning processes are positive aspects.
Regarding “Active Learning”, scale 3 highlights that 100 % of the students provide positive values regarding the view that the gamification approach allows the subject to be more interesting. Over 96 % of the sample believes that game-based learning permits active participation and that students ultimately learn. And more than 80 % consider that engaging with the content is better using this approach.
Finally, on scale 4 “Fun”, over 90 % of the participants say that they were happy, motivated and enjoyed the activity, and more than 80 % felt relaxed and comfortable in the process.
Therefore, the values shown on the scales are quite positive, close to 90 % on most items except those referring to the experience of students in working with gamification and game-based learning and applications in college (item 1.4) and the ability to design video game activities in educational settings (1.5). These obtained values close to only 25 % of the sample.
Statistical Inference: Wilcoxon test and sign test
With regard to statistical inference, non-parametric tests were applied to test samples to evaluate related data from the pre-test post-test quasi-experimental design (as in the above description of the present study). Significant improvements were considered made only if the value was less than 0.05 in both the Wilcoxon test and the sign test (Table 1).
Significant improvements are obtained with regard to the evaluation of work based on video games and gamification in college applications. Students value work with higher positive results after the activity. Therefore, it is important to work games and gamification into initial training at university to enhance their future professional performance. Although the descriptive analysis highlighted that about 80 % of the students do not know how to design video game activities in educational settings, involvement in the activity has resulted in a significant improvement in this regard. Moreover, the experience has allowed the students to study various technologies to design approaches to gamification and game-based learning (items 1.4, 1.5 and 1.6).
With regard to scale 2 “Gamification in Educational Contexts”, the Wilcoxon test and the sign test found significant improvements with regard to educational improvement as students believe that game-based learning through MinecraftEdu encourages educational innovation processes (item 2.5). In addition, the motivation of students is also enhanced, i.e., working with MinecraftEdu increases motivation in learning processes (item 2.6).
Note that with respect to other items significant improvements are not seen since the pre-test values related to attitudes on gamification were already quite high and so the post-test results were very similar at close to 90 %, as detailed in the descriptive analysis. However, the intervention has led to improvements in the work, knowledge and creation of tools for designing gamification and game-based learning approaches, assessing the possibilities of motivation and its importance in educational innovation processes.
Exploratory factor analysis
We proceeded to carry out an exploratory factor analysis in the studied dimensions. It was verified to be appropriate to conduct factor analysis of the data provided by the Kaiser-Meyer-Olkin analysis (close to 0.8 in the four scales) and the Bartlett test of sphericity (all significant, 0.000). The extraction method is the principal component analysis and the rotation method was Varimax with Kaiser normalization. Therefore, we checked the underlying structure of the data matrix by analyzing the interrelationships of variables and using the information collected to explain the interrelationships. The factors were interpreted from estimated correlations with the same variables of the study. These refer to various approaches described in the study and are structured in a coherent way.
On scales 3, “Active Learning”, and 4, “Fun”, only a rotated factor was obtained, so it was not necessary to proceed to data reduction. On scale 1 in Table 2 based on initial teacher training game learning, two factors explain 59.418 % of the total variance obtained.
Factor 1 is “attitudes to game-based learning” and refers to the ability and management presented by the participants with regard to the gamification approach as present today in emerging technologies. Factor 2 is “training benefits”, and bears a relation to the advantages of the approach of game-based learning in teaching and learning processes in university contexts for the initial training of future teachers.
Moreover, for scale 2 “Gamification in Educational Contexts”, three factors explain 73.526 % of total variance obtained (Table 3).
Factor 1 refers to motivation and innovation in respect of the aforementioned practices. The second factor points to collaborative and creative possibilities and the third factor refers to developed skills, with special emphasis on communicative elements.
Qualitative analysis: open questions
Implementing the survey technique using a mixed questionnaire as the tool, there are open-ended questions to which allow students can respond freely. Frequencies are numbered and recorded in each subject of the questions, which provide elements and factors relevant to the study. They function to strengthen and reaffirm values obtained in the quasi-experimental design and the descriptive analysis.
Answers to the question “In your view, what programs or applications offer a game-based learning approach?” highlight that, after the intervention, several subjects greatly valued the Minecraft application for educational purposes in the context of game-based learning (Fig. 1).
Answers to the question “In your view, what are the strengths of using gamification in the classroom?” (Fig. 2) essentially highlight motivation, to the extent that it is the value with the highest frequency across the qualitative part of the study. Other listed strengths are interest, meaningful learning and participation. To a lesser extent, other elements such as creativity, attention, cooperation, fun and active approach are mentioned.
Answers to the last question “In your view, what are the weaknesses of using gamification in the classroom?” mainly highlight the need for teacher training in design, implementation and development of these practices in their teaching profession. Teacher training and distraction are the factors with the highest frequency. The distraction factor can disrupt or hinder the students’ learning processes, so an evaluation of this issue is proposed for future study. The availability of resources and lack of time in class are also considered difficulties that may arise when implementing this game-based learning approach (Fig. 3).