scholarly journals Analysis and Design of the Web Game on Descriptive Statistics through the ADDIE Model, Data Science and Machine Learning

2020 ◽  
Vol 8 (3) ◽  
pp. 245 ◽  
Author(s):  
Ricardo-Adán Salas-Rueda ◽  
Érika-Patricia Salas-Rueda ◽  
Rodrigo-David Salas-Rueda
Keyword(s):  
Machine Learning ◽  
Data Science ◽  
Qualitative Data ◽  
Positive Influence ◽  
Educational Process ◽  
Descriptive Statistics ◽  
Model Data ◽  
Analysis And Design ◽  
Addie Model ◽  
The Web

This mixed research aims to analysis and design the Web Game On Descriptive Statistics (WGODS) through the ADDIE model, data science and machine learning. The sample consists of 61 students from a university in Mexico. WGODS is a technological tool (quiz game) that presents various questions and answers about statistics (quantitative and qualitative data). The results of the linear regression (machine learning) indicate that the content and aesthetics of WGODS have a positive influence on the educational process. The ADDIE model allows the organization of WGODS considering the needs of the students. Also, data science identifies 4 predictive models on the use of WGODS in the field of statistics through the decision tree technique. Finally, teachers can transform the organization and development of school activities through the ADDIE model and technology. In particular, WGODS improves the educational process on the quantitative and qualitative data through a pleasant, attractive, simple, easy and useful web interface.

scholarly journals Diseño y uso de una aplicación web para el campo de la estadística considerando el modelo ASSURE y la ciencia de datos

2019 ◽  
Vol 12 (1) ◽  
pp. 48-71
Author(s):  
Ricardo-Adán Salas-Rueda ◽  
Érika-Patricia Salas-Rueda ◽  
Rodrigo-David Salas-Rueda
Keyword(s):  
Machine Learning ◽  
Web Application ◽  
Data Science ◽  
Hypothesis Test ◽  
Web Design ◽  
Positive Influence ◽  
Educational Process ◽  
Data Simulation ◽  
Teaching Learning ◽  
The Impact

RESUMEN: Esta investigación mixta tiene como objetivo analizar el impacto de laAplicación web para el Proceso Educativo sobre la Prueba de Hipótesis (APEPH)en la asignatura Instrumentación estadística para los negocios durante el ciclo escolar 2018. El modelo instruccional ASSURE permite la organización, construcción e implementación de la aplicación APEPH. Los resultados del aprendizaje automático (regresión lineal) con 60%, 70% y 80% de entrenamiento indican que el contenido, el diseño web y la simulación de datos en la aplicación APEPH influyen positivamente en el aprendizaje y la motivación del estudiante. Asimismo, la ciencia de datos permite la construcción de 6 modelos predictivos sobre el uso de la aplicación APEPH en el proceso educativo por medio de la técnica árbol de decisión. Por último, la aplicación APEPH facilita el proceso de enseñanza-aprendizaje sobre la estadística por medio del contenido, el diseño web y la simulación de datos. PALABRAS CLAVE: tecnología educativa; modelo ASSURE; enseñanza superior; ciencia de datos; aprendizaje automático.   ABSTRACT: This mixed research aims at analyzing the impact of the Web Application for the Educational Process on the Hypothesis Test (APEPH) in the Statistical Instrumentation for Business subject during the 2018 school year. ASSURE model allows the organization, construction and implementation of the APEPH application. The results of machine learning (linear regression) with 60%, 70% and 80% of training indicate that the content, web design and simulation of data in the APEPH application have a positive influence on the student's learning and motivation. Likewise, data science allows the construction of 6 predictive models on the use of the APEPH application in the educational process by means of the decision tree technique. Finally, the APEPH application facilitates the teaching-learning process on statistics through the content, web design and data simulation. KEYWORDS: educational technology; ASSURE model; higher education; data science; machine learning.

scholarly journals Students' perceptions about the use of flipped classroom in the field of electronic electrical engineering

2021 ◽  
Vol 14 (1) ◽  
pp. 158
Author(s):  
Ricardo-Adán Salas-Rueda ◽  
Jesús Ramírez-Ortega
Keyword(s):  
Machine Learning ◽  
Flipped Classroom ◽  
Data Science ◽  
Electrical Engineering ◽  
Educational Process ◽  
Digital Design ◽  
Combinational Circuits ◽  
Design Data ◽  
School Year ◽  
The Impact

The objective of this mixed research is to analyze the impact of flipped classroom in the educational process on the Combinational Circuits through data science and machine learning. Flipped classroom facilitates the organization of active activities before, during and after the class. The participants are 17 students of Electronic Electrical Engineering who took the Digital Design course in the National Autonomous University of Mexico during the 2019 school year. The results of machine learning indicate that the consultation of the videos before the class, resolution of the exercises during the class through the Quartus software and realization of the laboratory practices after the class positively influence the development of skills on circuit design. Data science identifies 3 predictive models of the use of flipped classroom through the decision tree technique. Finally, teachers can improve the learning process, develop the skills of students, build new educational spaces and carry out creative activities through flipped classroom.

scholarly journals Development of Youtube integrated google classroom based e-learning media for the light-weight vehicle engineering vocational high school

2018 ◽  
Vol 8 (1) ◽  
pp. 53 ◽  
Author(s):  
Willy Prastiyo ◽  
As’ari Djohar ◽  
P Purnawan
Keyword(s):  
Learning Outcomes ◽  
Qualitative Data ◽  
Research Result ◽  
Descriptive Statistics ◽  
Light Weight ◽  
Vocational High School ◽  
Vehicle Engineering ◽  
E Learning ◽  
Addie Model ◽  
Vehicle Chassis

The purpose of this research is to produce the e-learning media for the Light-Weight Vehicle Chassis and Powertrain Maintenance Subject. The type of this research is the research and development. The procedure applied in this research is the ADDIE model. Construct testing by the expert is done by curriculum expert, practitioner and teaching media expert. Construct testing and content testing were also conducted to 23 students as the user. Qualitative data were analyzed using an iterative step that is reading/memoing, describing, and classifying. Quantitative data were analyzed with descriptive statistics. The research result shows that YouTube Integrated Google Classroom Based E-Learning Media has been produced and tested for Light-Weight Vehicle Chassis and Powertrain Maintenance subjects. The construct testing shows that this e-learning media is decent based on an expert's judgment, and based on the user response shows that the reliability of the construct is good. The content testing shows that students who use the YouTube Integrated Google Classroom Based E-Learning Media have significantly greater learning outcomes compared with students who use the internet to access the website without control.

scholarly journals USE OF THE FLIPPED CLASSROOM TO DESIGN CREATIVE AND ACTIVE ACTIVITIES IN THE FIELD OF COMPUTER SCIENCE

2020 ◽  
Vol 13 (1) ◽  
pp. 136-151
Author(s):  
Ricardo Adán Salas Rueda
Keyword(s):  
Machine Learning ◽  
Computer Science ◽  
Quantitative Research ◽  
Flipped Classroom ◽  
Data Science ◽  
Collaborative Work ◽  
Educational Process ◽  
School Activities ◽  
Teaching Learning ◽  
The Impact

The objective of this quantitative research is to analyze the impact of the flipped classroom in the educational process on computer science considering data science and machine learning. This study proposes the consultation of YouTube videos (before class), collaborative work through MySQL software (during class) and individual work through MySQL software (after class) in the database subject. The results of machine learning (linear regression) indicate that school activities before, during and after the class positively influence the assimilation of knowledge and development of skills on the administration of the database. Likewise, data science identifies 6 predictive models on the use of the flipped classroom in the educational process by means of the decision tree technique. Finally, the flipped classroom improves the teaching-learning conditions through the performance of creative and active activities.

Impact of the WampServer application in Blended learning considering data science, machine learning, and neural networks

2020 ◽  
Vol 17 (3) ◽  
pp. 199-217 ◽  
Author(s):  
Ricardo-Adán Salas-Rueda
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Blended Learning ◽  
Learning Process ◽  
Data Science ◽  
Educational Process ◽  
School Activities ◽  
Web Programming ◽  
Teaching Learning ◽  
The Impact

This quantitative research aims to analyze the impact of the WampServer application in Blended learning during the educational process of computing through data science, machine learning, and neural networks. WampServer is a free application that allows the creation of websites considering the use of the database. This research proposes the use of Blended learning in the Development of applications subject in order to facilitate the teaching–learning process in the Database unit. The students discuss and reflect the concepts on the database in the classroom and carry out various school activities on the construction of websites at home through the use of the WampServer application. The sample consists of 28 students who took the Development of applications subject during the 2016 school year. The results of machine learning (linear regression) with 50, 60, and 70% of training indicate that the use of PHP, HTML, and SQL languages in the WampServer application positively influences the assimilation of knowledge and development of skills on web programming. Data science identifies six predictive models about the use of WampServer in the educational process of computing. On the other hand, neural networks determine the factors that influence the assimilation of knowledge and development of skills on web programming. This research recommends the incorporation of the WampServer application in the school activities related to the computer field to create new educational spaces and facilitate the teaching–learning process. Teachers can transform the educational context through the organization and realization of creative activities inside and outside the classroom. Finally, the use of WampServer in Blended learning allows creating new spaces for teaching and learning of computer science because this application favors the assimilation of knowledge and development of skills on web programming.

scholarly journals IMPACT OF THE WEB APPLICATION FOR THE EDUCATIONAL PROCESS ON THE COMPOUND INTEREST CONSIDERING DATA SCIENCE

2020 ◽  
pp. 77-93
Author(s):  
Ricardo-adan SALAS-RUEDA ◽  
Erika-patricia Salas-rueda SALAS-RUEDA ◽  
Rodrigo-david SALAS-RUEDA
Keyword(s):  
Web Application ◽  
Data Science ◽  
Educational Process ◽  
Compound Interest ◽  
The Web

scholarly journals Machine Learning for sport results prediction using algorithms

2021 ◽  
Vol 3 (3) ◽  
pp. 148-155
Author(s):  
Said Lotfi ◽  
Mohamed Rebbouj
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Data Collection ◽  
Performance Prediction ◽  
Data Science ◽  
Recent Trend ◽  
Model Data ◽  
Analysis Technique ◽  
And Performance ◽  
Essential Contribution

This paper describes the use of machine learning in sports. Given the recent trend in Data science and sport analytics, the use of Machine Learning and Data Mining as techniques in sport reveals the essential contribution of technology in results and performance prediction. The purpose of this paper is to benchmark existing analysis methods used in literature, to understand the prediction processes used to model Data collection and its analysis; and determine the characteristics of the variables controlling the performance. Finally, this paper will suggest the reliable tool for Data mining analysis technique using Machine Learning.

scholarly journals Unsafe Tract Revelation and Inspection Using Machine Learning

2020 ◽  
pp. 127-133
Keyword(s):  
Machine Learning ◽  
Data Science ◽  
Real Life ◽  
Model Data ◽  
Satisfactory Precision ◽  
The Town ◽  
Crime Reports ◽  
And Training ◽  
Day By Day

Towns of diverse provinces are getting more unsafe day by day. The data following varied crime reports are available for these unsafe towns but, even such reports captioned are not perceived to 80% inhabitants of the town. The intent of this article is to decipher datasets which comprise of two distinct types of the dataset, one stands from real-life established crime dataset taken from police and another one stands from Safety Audit (survey) dataset which is performed by inhabitants of the town and using these pairs, anticipating tracts that may come to be unsafe in the future hinging upon numerous circumstances. In this article, we would be employing the procedure of Machine Learning and Data Science for unsafe tract revelation using the Indore city crime dataset as well as the Safety Audit dataset. The crime data has been obtained from the cyber website portal of Indore city’s police. It comprises of criminal parameter evidences like geolocation caption, classification of different criminal activities, duration i.e. date & time. Before the building and training of the processing model, data pre-processing would be mounted. Onto the next step, drafting of useful extracted features and scaling up of them would be performed which on the precision obtained would be increased further. The various distinct algorithms (such as KNN, Linear & Logistic Regression, SVC etc.) would be tested for unsafe tract revelation and an odd one with satisfactory precision would be opted for analysis. Anticipation of the dataset would be performed in terms of graphical depiction of many cases. For example, at what duration the frequency of criminal rates are high or at which sight the criminal undertaking are high. Safety Audit dataset contains information about various circumstances of a locale such as Light, Visibility, Transport, Security, Walk path, People, Time. The sole intent of this project is to give just an idea of how Machine Learning could be used to provide useful information about unsafe tracts to the user. It is not only restricted to Indore City but could also be used in other provinces being sure of upon the availability of the dataset.

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Ferdinand Filip ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Data Science ◽  
State Of The Art ◽  
Science Methods ◽  
Learning Models ◽  
Diverse Range ◽  
Hybrid Machine ◽  
Economics Research

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods

2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Data Science ◽  
Learning Methods ◽  
Comprehensive Review
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