Abstract
Neuroeducation is a discipline that is based on knowledge of the brain, how it learns and how this knowledge allows to improve learning teaching processes, where teaching is approached from other possibilities, especially at a time when education requires substantial changes leading to quality education, as proposed in the fourth Sustainable Development Goal. This article is the result of a research process that aims to develop a pedagogical proposal aimed at improving the motivation of students of the bachelor's in physical education, starting from strategies focused on the model Brain-Targeted Teaching (BTT) based on the principles of Neuroeducation. The control group sample (GrCtr) is defined as the Movement Analysis module (n = 38) and the experimental group (GrEx) as the Physiology of Physical Activity module (n = 24). A study of mixed methods was carried out using a quasi-experimental pretest posttest design. Data collection was carried out through the application of the self-regulatory learning questionnaire. For the data analysis, normality tests were applied finding that the data have no normal distribution; for what, we try to normalize the distribution to meet the assumptions of parametric tests through logarithmic transformation and square root, even so, no significant changes are presented, therefore, the non-parametric U-test of Mann–Whitney is used, finding statistical significance in five items of the questionnaire. The results obtained suggest an association between the implementation of the proposal and favorable changes in specific components of academic motivation in university students.
1 Introduction
The concepts of teaching - learning share a direct and relevant relationship since they are the pillar of the training process and involve the teacher - student relationship. It is therefore not possible to talk about one without the other. According to (Oviedo, 2015) this relationship is not only theoretical, but also practical, and it is there, in this relationship, that the disposition for guidance, engagement, and problematization lies. National tests administered by (ICFES, 2024) that measure the quality of higher education for students who are nearing graduation, show that in 2021, 2022, and 2023, students in the Bachelor of Physical Education program obtained averages below the mean. This demonstrates low levels of performance. The need arises to investigate the possible reasons that answer the reason for this low performance as it constitutes a warning sign on the need to innovate in teacher training. After a questioning process (diagnostic questionnaire) with students from the fifth to tenth semester of the bachelor's degree in Physical education, Recreation and Sports, it is reported that the motivation, prior knowledge and strategies of the teacher are factors that hinder the learning process in the theoretical subjects of the biological medical component; especially in Physiology of physical activity, Morphophysiology and Analysis of movement. Therefore, the objective of this study is to determine the impact of a pedagogical proposal based on the BTT model on academic motivation of students given its involvement in learning. Motivation affects the way of thinking of individuals, in their decision to choose the degree of interest used in the activities to be carried out, greater curiosity about the challenges they must face “a positive assessment of tasks could lead the student to become more involved in their own learning and to use cognitive strategies more frequently” (Lamas, 2008).
The relationship between the teacher and levels of motivation of students are relevant and critical aspects of the teaching-learning process (Soares et al., 2021). consider that university students must hold a significant level of motivation, as they face academic challenges demanding greater persistence and depth to achieve better learning outcomes. This establishes the importance of motivation within the learning process. A search is made for information on topics in line with current educational trends, which make it possible to innovate the processes of vocational training development on a theoretical basis; finding a discipline based on how the brain learns and how this knowledge improves learning teaching processes. This is how information about education based on the science of the brain, known as Neuroeducation or educational neuroscience, defined by its interdisciplinary field that connects cognition and psychology, and educational theory, where it seeks to “transform educational practices by applying ideas from the dynamic neural sphere and brain plasticity in the classroom” (Pradeep et al., 2024). This integration improves and powers student learning processes and memory (Mora, 2021). Neuroeducation has great potential in transforming the paradigm of the teaching process and is presented as a new model for early childhood and adult learning (Tokuhama-Espinosa, 2008).
Interest in developing pedagogical strategies that improve the motivation of university students through Neuroeducation, is based on the Brain Targeted Teaching model (BTT) proposed by Hardiman (2012) who believes that the BTT model allows to improve and optimize learning and teaching practice through components that focus on aspects such as emotional and physical climate, skills, the application of what has been learned in the real world, and a continuous evaluation of the learning of students. In addition, the evidence on its application in higher education and, particularly, in university students in teacher training, remains limited, so this gap represents an opportunity to intervene in the training of future educators by setting a precedent by presenting favorable changes in motivation that not only improves their own learning, rather opens up an option for future generations of teachers to use the neurobiological tools needed to transform the classroom from the base.
2 Theoretical framework
2.1 Motivation
The motivation is defined as the interest of students in successful learning. For (Lens et al., 2008), it is a psychological process involving the interaction of personality characteristics and perception that individuals have of their surroundings. The motivation of university students, combined with the methodological strategies employed by the instructor, should generate autonomy and depth in learning. Research on motivation references theories that attempt to explain or understand motivation in the academic field (Iraola-Real et al., 2022; Lens et al., 2008; Soares et al., 2021; Valenzuela et al., 2022).
2.1.1 Self-determination theory
Motivation possesses a multidimensional nature, ranging from extrinsic to intrinsic types. Intrinsic motivations generate a greater positive effect on the activation and maintenance of learning due to high concentration on activities, better time management, and improved information processing. In contrast, extrinsic motivation types have a lower impact as they are externally regulated; a practice exemplified by this regulation is the use of rewards and punishments (Ryan and Deci, 2020). This distinction between motivations is the central focus of the present study, since the NeuroMotiva proposal seeks to shift the student's focus from controlled motivation (notes and external pressures) towards an autonomous motivation, specifically assessed using the dimensions of the instrument (Matos, 2009).
2.1.2 Self-efficacy theory
Sustains that motivation is based on the level of competence perceived by the student in successfully completing a task, as self-efficacy promotes greater engagement and better academic adjustment (Hattie et al., 2020). In the intervention, self-efficacy is operationalized through graphic and body representation strategies that allow the physical education student to be perceived as competent in handling complex Physiological content.
2.1.3 Expectancy-value theory
Considers that motivation is determined by the expectation and the value assigned to the task. That is, learning depends on the expectation of successfully completing the task and the value attributed to that task (Wigfield and Eccles, 2020). The value of the task is enhanced in this research by connecting theoretical content with real problems from the professional field of the physical educator, thus increasing the intrinsic interest in learning.
2.1.4 Achievement goal theory
Intends to explain and understand why students engage in academic settings (McGregor and Elliot, 2002). Student orientation towards learning is evaluated as a personal challenge, a key indicator of success in transforming academic mindsets.
2.2 Neuroeducation
Brain-based education, known as Neuroeducation/Mind, Brain, and Education Science (MBE), integrates neuroscience, cognitive neuroscience, psychology and education; this interdisciplinary articulation allows for the optimization of educational outcomes by relating teaching experience to scientific knowledge about cognitive processes such as attention, motivation, executive functions and memory related to learning (Luzzatto et al., 2024). In this sense, academic motivation takes on special relevance, since it constitutes a fundamental component of the involvement of students in their educational process and the quality of learning. From this perspective, neuroeducation is not limited to transferring neuroscientific findings to the classroom but seeks to critically articulate them with pedagogical knowledge to enrich educational practice. Tokuhama-Espinosa (2008) recognizes in neuroeducation an important potential to transform the paradigm of the teaching learning process, by presenting it as an approach capable of enriching the formative processes both in early childhood and in adulthood. In the case of teachers in training, this approach could promote a more solid appropriation, both theoretical and practical, of the knowledge specific to their specialty. In addition (Mora, 2021), affirms, neuroeducation allows us to take advantage of findings from the neurosciences regarding how the brain learns. When integrated with psychology, sociology, and medicine, this knowledge enhances the learning and memory processes of students. He conceives five objectives for neuroeducation: 1) to understand the tools neuroscience provides to educators for more efficient teaching in educational settings; 2) to provide tools that detect neurological and psychological problems impeding or interfering with learning; 3) to provide tools that help form critical citizens who balance emotion and cognition; 4) to help bridge the gap between knowing and knowing how to teach. For Mora, “teaching without knowing how the brain works is like trying to design a glove without ever having seen a hand”.
2.3 Brain targeted teaching model
Neuroeducation emerges as a multidisciplinary field that bridges neuroscience and educational practices. While it has been received with great expectation by educators, research such as that by Torrijos-Muelas et al. (2021) suggests that many teachers still hold misconceptions due to a lack of access to high-quality scientific literature. This results in the prevalence of neuromyths como la incorrect interpretations of scientific facts used to justify educational interventions (OECD, 2002). Furthermore, Leal Ramírez (2025) argues that these myths are often reproduced within teacher training programs that lack a solid epistemological foundation. To avoid these pitfalls, this study adopted a model grounded in rigorous theoretical and scientific evidence, moving away from pseudoscientific concepts. Specifically, the research is based on the Brain-Targeted Teaching (BTT) Model proposed by (Hardiman, 2012, p. 6), which focuses on implementing effective instruction informed by neuro and cognitive sciences. Notably, explicitly debunks common neuromyths, such as hemispheric dominance, the Mozart effect and the fallacy that humans only use 10% of their brain.
The design and implementation of strategies are aimed at optimizing determinants in the teaching-learning process such as motivation, in order to contribute to the strengthening of a quality education, since the model serves as a pedagogical framework that provides teachers with knowledge of neurocognitive sciences so that it is understood and applied when introducing into their educational practices, activities based on the notions of brain functioning.
The BTT model favors the union of research and practice, in order to provide teachers with a model that is consistent and effective in instruction, as argued by Parr (2016) seeks to optimize learning environments and methodologies used by teachers considering how the brain handles information, i.e., its processing and retention. Also, the model recognizes that optimal learning arises when educational practices align with natural cognitive processes in the brain. “Its main objective is to improve learning by applying techniques that stimulate various regions of the brain, including the visual, auditory and kinesthetic systems, among others” (Kumar and Amin, 2023).
The Brain Targets developed by
Hardiman (2012)are described below and focus on aspects such as emotional and physical climate, skill mastery, real world application of what is learned, and continuous assessment of student learning.
Establishing the Emotional Climate for Learning. Establish an emotional and welcoming climate in the classroom for learning that provides students with emotional connections to content so that the topic is relevant and meaningful. Positive language and “emotional temperature checks” are some strategies proposed by the model. This is because the neurocognitive sciences have demonstrated that cognition and emotions are connected in terms of brain structure and function. Mindfulness is also proposed as a practice that reduces negative reactions at both psychological and cognitive levels, as it increases brain density in regions associated with memory and emotion regulation (Hölzel et al., 2011).
Creating the Physical Learning Environment. The physical environment of an educational institution is a tacit messenger. Elements such as a well-lit space, attention to novelty, order, and movement facilitate access to learning. The brain focuses its attention on that which is novel and significant, ignoring or losing interest in stimuli presented for extended periods. Good lighting has effects on health and academic performance given its influence on the pineal gland and melatonin regulation (Heschong-Mahone-Group, 1999).
Designing the Learning Experience. Activities and assessments are the content and curriculum based elements used to determine learning goals and objectives. These elements can be presented to students visually, as a “big picture”, using graphic organizers or concept maps. The goal is to create associations between content, thereby promoting more effective recall and deeper understanding (Chiou, 2008).
Teaching for Mastery of Content, Skills, and Concepts. Teachers must help students apply knowledge creatively in the real world, building a background knowledge base where they retain and use information meaningfully. The use of arts, graphic representation, role-playing, and repeated rehearsal are strategies that require staging of the information. These are mental processes that demand interpretation rather than just reading or listening; engaging in representations promotes conceptual thinking, reflective questioning, and diverse perspective in students (Kandel, 2007).
Teaching for the Extension and Application of Knowledge. Promote the application of that knowledge in solving real-world problems through creative and innovative thinking. Developing the divergent thinking of students through various solutions that give an answer to a problem allows them to enhance their creativity; divergent thinking involves the prefrontal region of the cortex, associated with executive functions. which make use of working memory to plan and organize activities in problem solving and abstract thinking, such as the hippocampus, a structure associated with memory, may increase in size due to the daily repetition of activities that have a certain degree of demand as people playing musical instruments (Plucker and Renzulli, 1998).
Evaluating Learning. Assessment is not only given at the end of the unit but should be given at each stage of the teaching and learning process in order to provide teachers and students with indicators to help them determine progress and continuously improve instruction. Strategies such as feedback, spacing (to consolidate information in memory), active information retrieval, portfolios, and research serve not only to assess the progress of learning but also to enhance learning itself through timely and correct feedback (Marzano and Pickering, 2001).
3 Methodology
3.1 Design
The study is conducted using a mixed-methods research approach, guiding the research through the three phases of Educational Action Research proposed by (Restrepo, 2004) as the qualitative method, and utilizing data systematization and statistical analysis as the quantitative method.
The study follows a pretest-posttest design using the Learning Self-Regulation Questionnaire, validated by Matos (2009) for university students. This instrument is widely recognized in research aimed at assessing motivational profiles within higher education contexts. This instrument has a Cronbach's alpha internal consistency index of 0.79 for the autonomy scale and 0.78 for the control scale. For data analysis, the Statistical Package for the Social Sciences (IBM SPSS) version 30.0 was used. Training of four sessions is carried out with the teacher leader of GrEx Physiology of physical activity on the BTT model.
3.2 Participants
The participants included sixty-two students from the Bachelor of Physical Education, Recreation, and Sports program at Universidad Libre, Bogotá campus. Students who attended the Physiology of Physical Activity module were established as the Experimental Group (GrEx) (n = 24), and who attend in the Movement Analysis module as the Control Group (GrCtr) (n = 38) without loss of samples. Although the sample is small to reach a generalization of results, it is representative and sufficient for a pilot study or educational action research in a specific classroom context such as a bachelor's program in higher education (Table 1).
Table 1
| Gender | Experimental group GrEx | Control group GrCtr | Total |
|---|---|---|---|
| Female | 10 | 17 | 27 |
| Male | 14 | 21 | 35 |
| Total | 24 | 38 | 62 |
| % | 38.7% | 61.3% | 100% |
Distribution of participants by group and sex.
The average age of participants is 23.5 years.
3.3 Instrument
Study participants completed the Learning Self-Regulation Questionnaire, which was used as an instrument to evaluate student motivation in the pretest and posttest. It consists of 14 items or statements rated on a 1–7 Likert type scale: 1 = Totally Disagree, 4 = Neutral, and 7 = Totally Agree. The questionnaire assesses two forms of learning self-regulation: autonomy, with six items (1,3,6,9,11,12) related to the importance the student places on their learning, and control, with eight items (2,4,5,7,8,10,13,14), where the regulation of learning is assumed to stem from external factors not inherent to the self. It is important to mention that, for the validation of Matos, item 5 has factorial load for both dimensions.
3.4 Procedure
The study was conducted under five stages that are described below: stage 1, is defined as shown by the students of the subjects Physiology of physical activity and Analysis of movement; subsequently, the randomization process is carried out in a closed envelope with both groups, resulting as GrCtr Analysis of Movement and GrEx Physiology of Physical Activity; stage 2, training for the leading teacher of the Physiology of Physical Activity group, the sample is characterized and the pretest is applied; stage 3, the thematic contents to be addressed in the semester are reviewed in order to develop the ten strategies based on the BTT model, time planning is carried out, resources; step 4, the implementation of strategies is developed and step 5, where the posttest is applied and data analysis for the socialization of results is carried out.
The “NeuroMotiva” pedagogical proposal had a duration of ten weeks, during which ten strategies based on the BTT model were applied. The design of these activities sought to integrate the six components of the model in an organic way, adapting to the contents and objectives of the Physiology of Physical Activity module. The procedure began with the establishment of a positive emotional climate and the adequacy of the physical environment, using strategies such as “Down with stress” for reducing cortisol levels and “Setting the mood” to generate states of novelty and curiosity in the classroom. For the mastery of content and skills, interactive tools such as Nearpod and methodologies based on art and body expression were used, such as “Acting to not forget” and “Paint a companion”, in order to facilitate the understanding of complex concepts by designing creative learning experiences. Finally, the evaluation and application of knowledge was consolidated through the development of a learning portfolio, which allowed students to record their individual progress and develop profound reflections on their future teaching. This process of implementation was framed within the phases of Research-Educational Action proposed by Restrepo (2004) in the reconstruction phase of pedagogical practice, while the use of the portfolio and the application of the posttest constituted the evaluation phase of the effectiveness of the reconstructed practice.
Throughout the implementation of the proposal, different motivational theories were integrated, an approach similar to that developed by Valenzuela et al. (2022) in their research “…We have chosen not to limit ourselves to a single motivational theory. Looking across multiple motivational theories allows for a deeper understanding of those elements that promote or hinder the motivation to learn in university”. The application of the six components of the BTT model was conducted in accordance with proposal of Hardiman, in that it is an organic system that guides and informs instruction and should not be viewed as a linear application (Table 2).
Table 2
| Estrategia | Componentes BTT – Motivación | Objetivo |
|---|---|---|
| Creating connections | 3. Design of learning experience *Self-determination theory | Stimulating the cognitive structure of students (outline). Work on the intrinsic motivation from teamwork, so that they integrate and apply the knowledge each has to achieve the goal. |
| Nearpod | 1. Setting the emotional climate for learning 4. Teaching to master content, skills and concepts 6. Assessing learning * Theory of achievement goals. | Focus attention of students through the use of interactive platforms. |
| Down with the stress | 1. Establish the emotional climate for learning. 4. Teaching to master content, skills and concepts. 6. Assessing learning *Self-determination theory | Reducing cortisol levels through an activity that decreases the degree of anxiety. Allow students to identify and express their emotions. Reflect on the responsibilities they have within their academic process. |
| Acting to not forget | 3. Design of learning experience *Self-efficacy theory | Reinforce the concepts addressed about muscle contraction, so that it is a more meaningful learning through creative activities. Integrating art into the learning process as another form of classroom teaching. |
| Let's paint a companion | 4. Teaching to master content, skills and concepts. 5. Teaching for the Extension and Application of Knowledge. 6. Assessing learning *Self-efficacy theory | Provide space for students to develop activities where they make use of art and generate interest and curiosity in them. Expose the domain on the topics viewed. |
| Setting the space | 2. Creation of the physical learning environment. *Self-determination theory | Make use of different spaces, to create more exciting environments for learning, especially in a practical session. |
| assessing learning | 1. Establish the emotional climate for learning. 6. Evaluate learning. *Expectation/value theory | Propose alternative ways of conducting the valuations. Conduct more engaging assessments for students so that their anxiety levels for the partials decrease and they can have greater clarity when responding. |
| Match | 2. Creation of the physical learning environment. 3. Designing the learning experience *Self-determination theory | Reinforce the concepts seen. Mobilize students around the room to activate their muscles. Change the order of the classroom to generate novelty in them, thus a greater retention of information by associating what has been learned with that class. |
| All in one | 1. Establish the emotional climate for learning. 2. Creation of the physical learning environment. 4. Teaching to master content, skills and concepts 5. Teaching for the Extension and Application of Knowledge. 6. Evaluate learning *Self-efficacy theory | Empower them to be autonomous. Provide spaces for them to demonstrate their skills and how they associate them with the information worked on during the semester. |
| Portfolio | 1. Establish the emotional climate for learning. 5. Teaching for the Extension and Application of Knowledge. 6. Evaluate learning. *Expectation/value theory | Record the progress of the module towards learning objectives. Motivate students to develop this tool as a reference material in the near or medium term. Increase students’ motivation by seeing their progress and effort recorded in the elaboration and completion of the portfolio. Encourage the creativity and commitment of students in the elaboration of the portfolio to which they were assigned ratings for cover elaboration, documentation worked in class, additional searches of information, learning reflections and a self-assessment covering the whole semester. Conduct a qualitative and quantitative assessment of the portfolio, with the intention of recognizing the effort made by each student. |
Strategies applied during the implementation of the neuroMotiva proposal based on the BTT model.
The numbers correspond to the component of the BTT model. The asterisk corresponds to motivational theories.
4 Results
4.1 Analysis of quantitative data
For data analysis, the Statistical Package for the Social Sciences (IBM SPSS) version 30.0 and the non-parametric Mann–Whitney U-test were used. The internal consistency analysis of the Learning Self-Regulation Questionnaire (Matos, 2009) demonstrated appropriate reliability in the participant sample. For the autonomy dimension an alpha coefficient of Cronbach 0.84 was obtained, while the value for the control dimension was 0.81, indicating high internal consistency in both cases. In its original validation, the questionnaire showed alpha of Cronbach values of 0.79 for autonomy and 0.78 for control, Thus confirming the reliability of the instrument in this university context.
The general descriptive statistics of the evaluated dimensions Autonomy and Control in the two study groups are presented, reporting a total sample of 76 observations at the pre- and post-test times for GrCtr and 48 for GrEx. In the Autonomy dimension, both groups exhibit identical behavior in their ranges, with a minimum score of 4 and a maximum score of 7, which suggests a trend toward medium-high levels of autonomous motivation. As for the dimension of Control, differences are identified in the upper limits; while the GrCtr reached a maximum score of 6, the GrEx reported a maximum value of 5. This difference in the upper range indicates that the students of the GrEx showed lower dispersion towards higher levels of external regulation compared to the GrCtr (Table 3).
Table 3
| Group | Dimension | N | Min. | Max. |
|---|---|---|---|---|
| Control | Autonomy | 76 | 4 | 7 |
| Control | 76 | 1 | 6 | |
| Experimental | Autonomy | 48 | 4 | 7 |
| Control | 48 | 1 | 5 |
General descriptive statistics of the dimensions by group.
Source: Authors.
The results show divergence in the motivational trajectory of both groups. While GrCtr experienced a slight decrease in its Autonomy (Δ = −0.08), the GrEx showed an increase (Δ = + 0.63), reaching an average of 6.17 in the posttest. Despite starting from a lower level of autonomy in the pretest (5.54 vs. 5.87), the GrEx surpassed the GrCtr after the application of the BTT model; also, the reduction in the standard deviation of the GrEx (from 1.14 to 0.91) suggests that the intervention favored a more consistent and homogeneous motivational response among students, compared to GrCtr (from 0.87 to 0.99). In the control dimension, both groups showed an increase between pretest and posttest. The GrCtr increased from 3.53 to 3.71 (Δ = + 0.18), while the GrEx increased from 2.83 to 3.04 (Δ = + 0.21). Although the trend was upward in both cases, the GrEx maintained scores below the GrCtr at both times of measurement. Additionally, the decrease in standard deviation in GrEx (from 1.00 to 0.90) suggests a lower dispersion of responses at the end of the intervention, while in GrCtr an increase in variability was observed (from 1.17 to 1.41) (Table 4).
Table 4
| Group | N | Moment | Autonomy (M ± SD) | Control (M ± SD) |
|---|---|---|---|---|
| Control | 38 | Pretest | 5.87 ± 0.87 | 3.53 ± 1.17 |
| Posttest | 5.79 ± 0.99 | 3.71 ± 1.41 | ||
| Experimental | 24 | Pretest | 5.54 ± 1.14 | 2.83 ± 1.00 |
| Posttest | 6.17 ± 0.91 | 3.04 ± 0.90 |
Means and standard deviations in pretest-posttest by group and dimension.
M, mean; SD, standard deviation.
Below are presented the medians, interquartile ranges and significances for all 14 items of the questionnaire, including sizes of the r-effect (Table 5).
Table 5
| Item questionnaire | Control Median (RIC) | Experimental Mediana (RIC) | p | |||
|---|---|---|---|---|---|---|
| Pretest | Posttest | Pretest | Posttest | Pretest | Posttest | |
| 1 | 5 (2) | 5 (3) | 4 (3) | 5 (3) | 0.060 | 0.618 |
| 2 | 1 (2) | 2 (3) | 1 (1) | 2 (3) | 0.109 | 0.104 |
| 3 | 6 (2) | 6 (2) | 4 (4) | 5.5 (3) | 0.121 | 0.858 |
| 4 | 4 (2) | 4 (3) | 3 (4) | 4 (3) | 0.100 | 0.347 |
| 5 | 5 (2) | 4.5 (2) | 5 (2) | 5 (1) | 0.384 | 0.023* |
| 6 | 6 (1) | 6 (2) | 6 (1) | 6 (2) | 0.482 | 0.278 |
| 7 | 2 (3) | 3 (4) | 1 (1) | 1 (2) | 0.172 | 0.002* |
| 8 | 3 (3) | 4 (3) | 2 (3) | 2.5 (3) | 0.007* | 0.011* |
| 9 | 6 (1) | 6 (2) | 7 (2) | 7 (2) | 0.766 | 0.275 |
| 10 | 3 (4) | 4 (3) | 2.5 (3) | 2 (3) | 0.290 | 0.019* |
| 11 | 6 (1) | 6 (1) | 6.5 (1) | 7 (1) | 0.944 | 0.151 |
| 12 | 6 (1) | 6 (1) | 6 (2) | 7 (1) | 0.046* | 0.008* |
| 13 | 4 (3) | 4 (2) | 4 (3) | 4 (3) | 0.731 | 0.100 |
| 14 | 2 (3) | 3 (4) | 1.5 (2) | 1.5 (2) | 0.145 | 0.098 |
Medians and interquartile ranges (RIC) of the self-regulatory learning questionnaire in the control and experimental groups (pretest and posttest).
The values correspond to the medians and interquartile ranges (IQR) of the items in the questionnaire. The p-values are from the Mann–Whitney U-test.
Show statistically significant differences (p < .05).
The data presented after the application of the pretest show an equivalent state between the groups with a consistency of more than 80% of the items, so there is an initial basis for making comparisons in the posttest. However, item 8 related to the control scale component has a p-value of 0.007 due to the tendency of GrEx to reject passive participation, different from GrCtr. Similarly, item 12, component of the autonomy scale, presents statistical significance with a p-value of 0.046, therefore there is a trend in the GrCtr towards greater orientation to learning as a challenge.
In the comparison between GrCtr and GrEx during posttest, significant differences (p < 0.05) were observed in five items, where GrEx achieved a statistically significant reduction in 50% of control dimension items (4 out of 8 items: 5, 7, 8, and 10), rejecting follow-up of suggestions by notes (p = 0.023), follow-up by opinion of others (p = 0.002), follow-up by ease (p = 0.011), follow-up by culpability (p = 0.019). Regarding the autonomy dimension, there is an increase in item 12 related to learning as a challenge (p = 0.008), evidenced by the increase of “Totally true” in active participation (41.7% vs. 26.3% of control), deep understanding (41.7% vs. 26.3%) and especially in the perception of learning as a challenge (62.5% vs. 31.6%). At the same time, a significant reduction in extrinsic motivators was observed in GrEx, with higher percentages in “Nothing true” for items related to external opinion (62.5% vs. 28.9%) and follow-up by ease (41.7% vs. 13.2%).
Although some items did not reach statistical significance, positive trends were observed in the experimental group towards greater intrinsic motivation, as evidenced by the increase in interest in learning (62.5% vs. 39.5%) and the decline in reliance on notes and external recognition. These results suggest that the intervention was effective in promoting a more autonomous learning orientation in the experimental group, reducing the influence of extrinsic motivators and strengthening intrinsic motivation compared to the control group. In relation to the size of the effect, its ranges were between small and moderate (−0.11 and −0.39). While these magnitudes should be interpreted with caution, they may be considered pedagogically significant in the university context, where motivational dispositions often show relative stability and their transformation becomes complex in short intervention periods.
4.2 Qualitative data analysis
After the intervention, there are positive effects on the motivation of students that transcend statistical analysis, finding a significant convergence in the learning reflections given by the students at the end of the semester. The integration of these two dimensions is presented below.
4.2.1 Strengthening intrinsic motivation
Although statistical improvement was concentrated in 16% of the intrinsic indicators (specifically in item 12 related to learning as a challenge), this finding resonates with testimonials that describe a class “different from the others in this subject line” where it was possible “better understand the issues”. This perception of cognitive challenge resulted in increased retention effectiveness, with students stating the following: The methodologies used were very effective in facilitating information retention, allowing me to understand and assimilate content in a meaningful way; “They provided me with knowledge through different methodologies and activities”; “It was a dynamic class and that helped us to understand more the themes”; “The concepts learned in class are reflected in daily practice”.
4.2.2 Mitigation of extrinsic motivation
The 50% reduction in extrinsic motivation indicators (items 5, 7, 8 and 10) is directly linked to greater autonomy and a rejection of academic passivity. The students' reflections validate this transition from external pressure to self-regulation “In the first cut I experienced inconveniences, although in the second in company of the portfolio I sought new study methods”. This search for own solutions shows that the BTT model encouraged personal responsibility for compliance. The students valued the content as “paramount for future teacher training”, recognizing that the proposal provided them with “necessary tools to design safe and effective exercise programs”. Taken together, these testimonies suggest that the scope of the NeuroMotiva proposal lies not only in the improvement of isolated indicators, but in the beginning of a change of identity towards deeper learning, self-regulated and with a clear professional sense for their future teaching performance.
4.2.3 Emotional climate and pedagogical connection
The creation of a positive emotional climate, fundamental pillar of neuroeducation, is evident in the explicit mention of having learned “with warmth from teaching processes and methodologies”. This emotional connection allowed the students not only to assimilate information, but to do so in an environment that fostered their well-being and scientific curiosity (Table 6).
Table 6
| Self-regulated learning | ||
|---|---|---|
| Item | Pretest | Posttest |
| U de Mann -Whitney | U de Mann -Whitney | |
| 5. I follow the suggestions of my teachers because by following them, I will get a good grade. | (Z = −0.87; p = 0.384) (r = −0.11) Small effect | (Z = −2.28; p = 0.023) (r = −0.29) Small effect |
| 7. I follow the suggestions of my teachers because I want others think I am good. | (Z = −1.36; p = 0.172) (r = −0.17) Small effect | (Z = −3.07; p = 0.002) (r = −0.39) Moderate effect |
| 8. I follow the suggestions of my teachers because it is easier to do what they tell me than to think about it | (Z = −2.69; p = 0.007) (r = −0.34) moderate effect | (Z = −2.55; p = 0.011) (r = −0.32) Moderate effect |
| 10. I follow the suggestions of my teachers because probably I would feel guilty if I did not. | (Z = −1.06; p = 0.290) (r = −0.13) Small effect | (Z = −2.35; p = 0.019) (r = −0.30) Moderate effect |
| 12. The reason I will continue to expand my knowledge is because it is a challenge to really understand what we do in the courses. | (Z = −1.99; p = 0.046) (r = −0.25) Small effect | (Z = −2.66; p = 0.008) (r = −0.34) Moderate effect |
Results of the items with statistical significance in the questionnaire learning self-regulation pretest - posttest.
Source: Authors.
5 Discussion
The results obtained from the analysis of data and information provided by the students allowed for the identification of positive effects generated by the intervention based on the BTT model and implemented with the GrEx. It can be affirmed that developing activities applying principles of Neuroeducation, such as the model proposed by (Hardiman, 2012) fosters a conducive environment for enhancing student motivation. This improvement is not limited to an isolated statistical interpretation but correlates with the learning reflections given by the students at the end of the semester, who highlighted: “They provided me with knowledge through different methodologies and activities” and that was a “dynamic class and that helped us to understand more about the themes”. The results obtained align with those presented by (Ventura et al., 2024), who affirm that the application of strategies based on neurodidactics contributes to an increase in positive psychological capital. Additionally, they assert that implementing neurodidactic programs in educational institutions generates benefits for future teachers, as it increases their efficacy in the educational tasks they perform and enhances their resilience to adverse situations in the educational field. Meanwhile (Valerio et al., 2016), present the relationship between neuroscience proposed teaching practices and increased attention, motivation, and academic performance in university students. This aligns with the findings of the present research, as the teacher student relationship affects the teaching-learning process a relationship that is conditioned by the motivation of students toward their academic development.
6 Conclusions
The effects presented after the implementation of the NeuroMotiva proposal demonstrate a favorable reconfiguration of the motivational profile of students. Quantitative results reveal that the intervention was particularly effective in mitigating extrinsic motivation, achieving a statistically significant reduction (p < 0.05) in 50% of its indicators (items 5, 7, 8 and 10), reducing reliance on notes and pressure for external approval. Likewise, intrinsic motivation was strengthened, highlighting that 16% of their items show a statistical improvement; in this indicator, the perception of learning as a personal challenge rose from 20.8% to 62.5% at the GrEx Totally true level. These findings suggest that intervention promotes a more autonomous orientation, reducing dependence on external factors and reinforcing participation by deep understanding.
The model is considered to help strengthen motivation of students through the relationships and interactions that occur between the actors of the educational process, as well as the variety of options offered to students to demonstrate the acquired knowledge in a realistic and meaningful way, which promotes their interest, creativity and autonomy. In addition, a greater willingness and acceptance of the group towards innovative methodologies and alternative assessments was observed, factors that allowed strengthening the components of the BTT model.
6.1 Pedagogical implications
The way future teachers learn directly influences their teaching practice. Consequently, prioritizing new and diverse ways of learning during their academic training is essential. Based on this, it is important that during their professional training process they experience diverse didactics, methodologies, and resources that enrich their pedagogical knowledge and promote the development of their educational processes from a neuroeducational perspective, as was implemented in the “NeuroMotiva” proposal. This proposal included activities that permit more active student participation, both in reflection on how the academic process is being conducted and in suggestions or decisions regarding the presentation of their works.
The use of educational platforms for creating interactive material was also employed, as was the inclusion of art as a means to foster creativity, autonomy, and critical thinking. In the same way (Ballesta-Claver et al., 2024), affirm that a neuroactive proposal generates improvements in the didactic scientific learning of teachers in training. It also allows them to implement the model developed in their research within their future professional practice, as it fosters curiosity, active inquiry, and utilizes virtual or multimedia resources, permitting greater reasoning and comprehension.
6.2 Limitations
Although space was available to accomplish the activities proposed for the intervention, along with the full cooperation of instructor and the students, the implementation was limited by the schedule and times and spaces of the subject of the leading teacher; However, it is important to emphasize that given the previous training on the BTT model for the teacher and the strict accompaniment during class sessions, it was possible to comply with the application and full immersion of the components proposed in the model. It is recommended that for future research using the BTT model, the researcher should be the leading lecturer; this would allow for a smoother integration of content, topics, and methodologies, which would potentially lead to stronger consolidation of the observed effects through more direct adherence to neuroscientific evidence in the classroom. This approach aligns with the principles of educational action research, where educators investigate and refine their own teaching practices. In addition, future studies should aim for a larger sample size to improve generalization of findings and increase statistical power by providing more robust data.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Ethics statement
The studies involving humans were approved by Ethics Committee Libre University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
AF-P: Methodology, Formal analysis, Writing – review & editing, Conceptualization, Investigation, Writing – original draft. JA-M: Methodology, Supervision, Conceptualization, Writing – original draft, Investigation, Writing – review & editing. MB-R: Writing – review & editing, Writing – original draft, Supervision, Conceptualization, Resources, Methodology. MR: Methodology, Resources, Conceptualization, Writing – review & editing, Supervision, Writing – original draft. EA: Data curation, Resources, Supervision, Writing – review & editing, Writing – original draft, Methodology, Conceptualization.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This project was carried out with the financial support of the Fundación Universitaria los Libertadores, Bogotá.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was used in the creation of this manuscript. The authors acknowledge the use of AI-assisted language models to review the translation of the document from Spanish to English. The authors retain full responsibility for the final content and accuracy of the manuscript.
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Summary
Keywords
brain targeted teaching model, motivation, neuroeducation, physical education, university students
Citation
Figueroa-Palacios A, Alvarado-Melo J, Buitrago-Ropero ME, Riveros-Medina M and Ávila Gil EH (2026) Neuroeducation and motivation: application of the brain-targeted teaching model in university students. Front. Educ. 11:1746539. doi: 10.3389/feduc.2026.1746539
Received
05 December 2025
Revised
11 March 2026
Accepted
17 March 2026
Published
08 April 2026
Volume
11 - 2026
Edited by
Cristina Dumitru, Polytechnic University of Bucharest, Romania
Reviewed by
Gabriel Estuardo Cevallos, Tsa'chila Higher Technological Institute, Ecuador
Trimurtini Trimurtini, State University of Semarang, Indonesia
Updates
Copyright
© 2026 Figueroa-Palacios, Alvarado-Melo, Buitrago-Ropero, Riveros-Medina and Ávila Gil.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Angela Figueroa-Palacios angelam-figueroap@unilibre.edu.co
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.