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This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media application design in cerebrating practices of lecturer education in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledgeable about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementation, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication and interaction in a multilingual setting that promotes both language and movement skills. This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media application design in cerebrating practices of lecturer education in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledgeable about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementation, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication and interaction in a multilingual setting that promotes both language and movement skills.

The aim of this study was to examine the effectiveness of the Sport Integrated Circuit (SIC) training model on the improvement of badminton skills by student-athletes in the age bracket of 12 and 15 years. Physical, technical, and cognitive training are combined in the SIC model, with the aim of improving performance. Qualitative descriptive with a sample of 30 students was the design adopted, where the data obtained through use of observations, semi-structured interviews and focus group discussions. The observations measured the level of participation, the skill acquisition and training intensity, while the interviews and focus group discussions gave feedback and experiences of the participants. The findings showed that key skills related to badminton were effectively improved through the SIC training model. Observations indicated that there were advancements in footwork, reaction time, and control of the shuttle, with 28 students making noticeable enhancement in the said areas. A good proportion of the participants claimed high engagement levels and satisfaction in the training, reporting improvement in performance and self-confidence. However, there were some challenges recorded: some students were unable to cope with the intensity of the training provided and more personalized instruction was required for various students. In addition, it was recommended by participants that more strategic game play scenarios could be included in the model for better preparation of athletes in competitive settings. In conclusion, the SIC training model has suitable results when oriented in enhancing badminton skills owing to its integrated nature. It is suggested that refinements that include altering the training load and reliance on one-on-one coaching as well as the use of more competitive situations be incorporated in order to improve the effectiveness of the model and match it more appropriately to the demands of younger sports participants.

This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media application design in cerebrating practices of lecturer education in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledgeable about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementation, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication and interaction in a multilingual setting that promotes both language and movement skills. This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media application design in cerebrating practices of lecturer education in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledgeable about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementation, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication and interaction in a multilingual setting that promotes both language and movement skills.

This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media applicationdesign in cerebrating practices of lecturereducation in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledge-able about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementa-tion, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication andinteraction in a multilingual setting that promotes both language and movement skills Esta investigación tiene como objetivo determinar el papel de la Inteligencia Artificial (IA) y el diseño de aplicaciones de medios de aprendizaje interactivos Thunkable en las prácticas cerebrales de la formación docente en el contexto de la formación integrada con métodos de educación física (EF). Surgen preguntas sobre cómo los profesores pueden reforzar las lecciones de educación física con tecnologías como la IA y Thunkable y qué desafíos enfrentan al hacerlo. Este estudio utilizó un diseño de investigación descriptivo y los datos se recopilaron mediante entrevistas semiestructuradas con profesores de educación física que conocían y habían utilizado IA o Thunkable en su práctica docente. El análisis de los datos cuantitativos también fue descriptivo, pero se centró en transcribir los datos cualitativos basados, entre otros, en la competencia tecnológica de los docentes, los beneficios y desafíos de la implementación, los resultados delos estudiantes y las respuestas cualitativas de los docentes. Los resultados revelaron que, a pesar de que el 70% de los profesores eran conscientes de la IA en las clases de educación física, sólo el 30% de ellos utilizaba las herramientas de IA disponibles para las clases. De los pocos profesores que intentaron utilizar la aplicación Thunkable, sólo el 25 % pudo generar aplicaciones, que es el objetivo de la aplicación. Los profesores sugirieron que los estudiantes se beneficiarían mucho de la IA, especialmente a través de la participación activa recompensada con retroalimentación instantánea sin la posibilidad de abordar adecuadamente las inquietudes debido a una capacitación e infraestructuras técnicas insuficientes. Las implicaciones de este estudio se centrarán en la lingüística educativa considerando los usos prácticos de las herramientas de IA en el lenguaje educativo en términos de educación física. El uso de sistemas de inteligencia artificial en las lecciones de educación física puede mejorar la comunicación y la interacción en un entorno multilingüe que promueve tanto el lenguaje como las habilidades de movimiento.

This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media application design in cerebrating practices of lecturer education in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledgeable about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementation, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication and interaction in a multilingual setting that promotes both language and movement skills. This research aims to determine the role of Artificial Intelligence (AI) and Thunkable interactive learning media application design in cerebrating practices of lecturer education in the context of physical education (PE) methods integrated training. Questions arise on how lecturers can reinforce PE lessons with technologies such as AI and Thunkable and what challenges they face in doing so. This study utilized descriptive research design and data was collected by means of semi-structured interviews with PE lecturers who were knowledgeable about and had utilized AI or Thunkable in their teaching practice. Analysis of quantitative data was also descriptive but focused on transcribing the qualitative data based on, among others, lecturers' technological competence, benefits and challenges of the implementation, student outcome, and qualitative, lecturers' responses. Results found out that despite 70% of lecturers’ awareness of AI in PE lessons, only 30% of them used the available AI tools for the lessons. Out of the few lecturers who attempted to use the Thunkable application, only 25% were able to generate apps which is the focus of the application. Lecturers suggested that students would benefit a lot from AI especially through active participation rewarded by instant feedback without possibilities of concerns being addressed properly due to insufficient training and technical infrastructures. The implications of this study will focus on educational linguistics considering practical uses of AI tools in the language of education in terms of physical education. The use of AI systems in PE lessons can enhance communication and interaction in a multilingual setting that promotes both language and movement skills.