Castillo Salazar, David Ricardo
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Castillo Salazar, David Ricardo
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Ambato
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davidcastillo@uti.edu.ec
Scopus Author ID
57210800584

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Scaffolding quantum entanglement in secondary school: from tangible analogy to computational simulation

2026 , Castillo Salazar, David Ricardo , Saravana Prakash Thirumuruganandham , William Daniel Lituma González , Hugo Chancay Ortega

Background and purpose of the study: The rise of quantum technologies necessitates integrating foundational quantum mechanics (QM) concepts into secondary education. However, inherently abstract phenomena like quantum entanglement pose significant pedagogical challenges, as traditional formalism-based approaches are often inaccessible. This study introduces and delineates an innovative, scaffolded pedagogical model designed to foster robust conceptual understanding of entanglement in secondary STEM education, moving beyond reliance on mathematical formalism. The proposed pedagogical model: The presented contribution is a detailed pedagogical sequence following a deliberate learning trajectory. It begins with a tangible analogy (magnetic interactions) as a conceptual anchor for correlation, then transitions to computational tools (Bloch sphere visualization, Qiskit simulations). These tools facilitate exploration of quantum concepts weakly addressed by the analogy (e.g., superposition) and allow more authentic engagement with quantum behavior. Underpinned by constructivism, cognitive load theory, and QM education research, the model strategically repurposes the analogy’s limitations as pedagogical opportunities to introduce and contrast key quantum features like non-locality and superposition with classical intuition. The sequence integrates exploration, guided use of representations, and critical comparative discussion. Conclusions and potential implications: This paper provides a theoretically grounded pedagogical model for introducing quantum entanglement in secondary STEM education, combining tangible and computational tools in a scaffolded manner. The approach offers potential advantages over traditional methods by providing concrete starting points and explicitly using classical limitations to illuminate quantum principles. While promising, rigorous empirical validation is the essential next step. Future research should investigate the model’s effectiveness in authentic classroom settings, informing curriculum design and teacher development for incorporating QM into secondary STEM. Copyright © 2026 Castillo-Salazar, Thirumuruganandham, Lituma González and Ortega.

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Detection of Student Behavior Profiles Applying Neural Networks and Decision Trees

2020 , Guevara Maldonado, César Byron , Sanchez-Gordon S. , Arias Flores, Hugo Patricio , Varela Aldas, José , Castillo Salazar, David Ricardo , Borja M. , Fierro-Saltos W. , Rivera R. , Hidalgo-Guijarro J. , Yandún-Velasteguí M.

Education worldwide is a significant aspect for the development of the peoples and much more in developing countries such as those in Latin America, where less than 22% of its inhabitants have higher education. Research in this field is a matter of interest for each of the governments to improve education policies. Therefore, the analysis of data on the behavior of a student in an educational institution is of utmost importance, because multiple aspects of progress or student dropout rates during their professional training period can be identified. The most important variables to identify the student’s behavior are the socio-economic ones, since the psychological state and the economic deficiencies that the student faces while is studying can be detected. This data provides grades, scholarships, attendance and information on student progress. During the first phase of the study, all the information is analyzed and it is determined which provides relevant data to develop a profile of a student behavior, as well as the pre-processing of the data obtained. In this phase, voracious algorithms are applied for the selection of attributes, such as greedy stepwise, Chi-squared test, Anova, RefiefF, Gain Radio, among others. In this work, we apply the artificial intelligence techniques, the results obtained are compared to generate a normal and unusual behavior of each student according to their professional career. In addition, the most optimal model that has had a higher accuracy percentage, false positive rate, false negative rate and mean squared error in the tests results are determined. © Springer Nature Switzerland AG 2020.

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Editorial Design Based on User Experience Design

2020 , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Castillo Salazar, David Ricardo , Arias Flores, Hugo Patricio , Fierro-Saltos, W. , Rivera, R. , Yandún-Velasteguí, M. , Varela Aldas, José , Hidalgo-Guijarro J.

This research deals with editorial design based on user experience design. The traditional editorial design has had to adapt to the new digital media composition, where multimedia audiovisual elements unthinkable a few years ago need to be integrated. The participation of the reader, as an external observer who only receives information through texts and images, now has new scenarios in which he can actively participate and decide what will come to his hands. In this study, a work methodology based on UxD User Experience Design is presented, in which will generate the editorial design of an educational book on environmental issues, which includes augmented reality for children from 6 to 8 years of age. The aim of this study is to know if an editorial product with augmented reality and developed from the user experience design can improve meaningful learning in a playful and active way. For its development, a composition model based on the Fibonacci sequence and the golden ratio will be used. Additionally, its graphic composition will be guided by the Massimo Vignelli canon and will be complemented by the reticular model of Beth Tondreau. The augmented reality markers position will also be based on the composition model previously mentioned, which will allow keeping the attention of the reader in the printed document and in the augmented reality animations. The user experience design will be applied with teachers, parents and students from 4 schools in Quito and Ambato. Once the production is completed, the impact on teaching-learning process will be evaluated with a control and a test group, and the methodology with which they will work in the classroom with the educational material developed will be defined. At the end of the study, copies of the book will be delivered to the participating schools of this research for its implementation. © Springer Nature Switzerland AG 2020.

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Application of Machine Learning for the Development of Logical-Mathematical Thinking in Basic Education Students

2025 , Diana, Peñuela , Castillo Salazar, David Ricardo , Cabrera López, Julio Rafael , Dario Castillo Salazar

The research involves upper basic education students in arguments related to Scratch software, focusing on teaching mathematics from the perspective of the theory that suggests learners construct their own knowledge through experience and reflection. Using Scratch and artificial intelligence processes to generate projects promotes active and meaningful learning. From this perspective, the goal is for students to develop logical-mathematical thinking, which is essential for analyzing, evaluating, and effectively applying information, thereby strengthening creativity and problem-solving skills centered on knowledge assessment. This approach allows for the application of theoretical and practical AI in educational software applications. The results indicate that mathematical competencies improve with the use of Scratch software. Additionally, the research identifies students’ skills and interest in the potential of AI technologies to enhance the understanding of computational mathematical concepts. The research concludes that the integration of the AI module in Scratch strengthens mathematical competencies in the field of education

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Control of an Arm-Hand Prosthesis by Mental Commands and Blinking

2020 , Varela Aldas, José , Castillo Salazar, David Ricardo , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Arias Flores, Hugo Patricio , Fierro-Saltos, W. , Rivera, R. , Hidalgo-Guijarro, J. , Yandún-Velasteguí, M.

Patients who lack upper and lower extremities have difficulties in carrying out their daily activities. The new technological advances have allowed the development of robotic applications to support people with disabilities, also, portable electroencephalographic (EEG) sensors are increasingly accessible and allow the development of new proposals which involve the mental control of electronic systems. This work presents the control by mental orders of an arm-hand prosthesis using low-cost devices, the objective is to command the arm using the user’s attention and blinking, where the components are a brain signal sensor, a prosthesis, an Arduino board, six servomotors, and a computer. The developed program in Matlab allows controlling the arm by means of an attention level y blinking. The results show the functioning of the system through experimental tests and a usability test is applied, finally, the conclusions establish adequate coordination in the movements of the prosthesis and the patient indicate satisfaction with the proposal. © Springer Nature Switzerland AG 2020.

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Impact of Machine Learning on the Development of Mathematical Operations Using Scratch

2025 , Cabrera López, Julio Rafael , Castillo Salazar, David Ricardo , Diana, Peñuela , Darío Castillo Salazar

This research focused on analyzing the impact of Machine Learning (ML) applied through the Scratch platform on the development of mathematical operations in secondary school students. The quantitative, descriptive, and field-based study was conducted with a sample of 30 students from public schools in educational zone three. A survey technique was used with a questionnaire validated by education experts, and the instrument’s reliability was measured with a Cronbach’s Alpha of 0.89. The results obtained from pretest and posttest, as well as the application of the t-student test and ANOVA analysis, demonstrated that the experimental group, which used Scratch with ML, showed significant improvements in their mathematical performance compared to the control group. Additionally, the impact analysis based on Cohen’s D revealed a considerable effect on academic performance, reinforcing the effectiveness of the proposal. These findings not only highlight the importance of incorporating emerging technologies in education but also suggest that the use of interactive and adaptive approaches can optimize the learning of mathematics. The research concludes that integrating ML and Scratch in mathematics education is an effective tool for enhancing students’ understanding and developing critical skills

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Preprocessing Information from a Data Network for the Detection of User Behavior Patterns

2020 , Hidalgo-Guijarro J. , Yandún-Velasteguí M. , Bolaños-Tobar D. , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Varela Aldas, José , Castillo Salazar, David Ricardo , Arias Flores, Hugo Patricio , Fierro-Saltos W. , Rivera R.

This study focuses on the preprocessing of information for the selection of the most significant characteristics of a network traffic database, recovered from an Ecuadorian institution, using a method of classifying optimal entities and attributes, with the In order to achieve a complete understanding of its real composition to be able to generate patterns and identification of trends of behavior in the network, both of patterns that deviate from normal traffic behavior (intrusive), as well as normal, to detect with high precision possible attacks. Network management tools were used as a multifunctional security server software, as well as pre-processing of data tools for the selection of attributes, as well as the elimination of noise from the instances of the database, It allowed to identify which ins- tances and attributes are correct and contribute with effective information in the study. Among them we have: Greedy Stepwise Algorithm (Algoritmo Voráz), K-Means Algorithm, Discrete Chi-square Attributes and the use of computational models as Evolutionary Neural Networks and Gene Algorithms. © Springer Nature Switzerland AG 2020.

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Active Methodologies: An Approach to Virtual Teaching in Natural Sciences

2023 , Becerra-García E. , Castillo Salazar, David Ricardo , Viera Muñoz F.

During the training process on Natural Science subject in elementary school, it is important for the student to know, understand, respect, conserve, care for and value nature, the benefits it receives, interact with the environment, recognize the characteristics of each element of nature, its cycles, risks and care. The main objective of this work was to implement active methodologies in the science teaching-learning process. The methodology is based on quantitative methods, non-experimental designs, cross-sectional studies, theoretical, empirical and statistical methods. The technique used was a survey as an instrument and a questionnaire for data collection. A survey was applied to 40 people (students, teachers) of eighth grade, to obtain information on the interventions implemented by teachers. As a result of the survey analysis, the need to renew the essential methodological strategies to improve the teaching-learning process was identified, for which three active methodological strategies were developed for Natural Sciences’ teaching associated with the environment (physical, chemical and environmental). The strategies were designed with creativity, the use of environmental and recycling materials together with technology, each with the following elements: title, materials to be used, procedure, graphic representations and application examples. These active methodological strategies allow students to learn through the development of processes and skills that can be used in a variety of emerging situations and also allow teachers to provide a comprehensive and quality education. Based on the experience of the application of strategies in the area of Natural Sciences as future work in the educational context, it is intended to identify a set of abilities and skills in students in various subjects in order to strengthen teaching methodologies in teachers with the application of new technologies and digital resources that generate a new vision in the field of research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

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A Small Robotic Step for the Therapeutic Treatment of Mental Illnesses: First Round

2020 , Martinez C. , Castillo Salazar, David Ricardo , Rivera R.M. , Gomez A H.F.

The advances in psychological therapies to treat mental illnesses have been of vital importance in recent times, especially by the combination with technology. Appealing to new mechanisms gives some hope of improvement in treatments and patients. In this work we show the ease in the development of routines that can help the quality of life of people suffering from Alzheimer’s and autism, diseases that lend themselves to the programming of routines related to the daily life of patients. The routines developed by students of psycho-pedagogy and documented by our work team are waiting for being applied in case studies in future works. The general conclusion of the assignment is the concentration that arose having to use a robot as part of therapy routines and the quest for information to combine new technologies with psychology. The assignment can be considered as impressive because working with a robot awakens positive emotions in those who are developing robotic therapies. © 2020, Springer Nature Switzerland AG.

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Twitter Mining for Multiclass Classification Events of Traffic and Pollution

2020 , Chamorro V. , Rivera R. , Varela Aldas, José , Castillo Salazar, David Ricardo , Borja Galeas, Carlos , Guevara Maldonado, César Byron , Arias Flores, Hugo Patricio , Fierro-Saltos W. , Hidalgo-Guijarro J. , Yandún-Velasteguí M.

During the last decade social media have generated tons of data, that is the primal information resource for multiple applications. Analyzing this information let us to discover almost immediately unusual situations, such as traffic jumps, traffic accidents, state of the roads, etc. This research proposes an approach for classifying pollution and traffic tweets automatically. Taking advantage of the information in tweets, it evaluates several machine learning supervised algorithms for text classification, where it determines that the support vector machine (SVM) algorithm achieves the highest accuracy value of 85,8% classifying events of traffic and not traffic. Furthermore, to determine the events that correspond to traffic or pollution we perform a multiclass classification. Where we obtain an accuracy of 78.9%. © Springer Nature Switzerland AG 2020.

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