Algoritmos de machine learning en la identificación de competencias académicas: Una revisión sistemática de la literatura

La alta competitividad laboral en diversos sectores de la industria son un motivo de preocupación de diversas instituciones educativas, las cuales buscan perfilar a sus egresados en base a un conjunto de competencias que el área profesional del estudiante requiere. La metodología aplicada para la revisión sistemática de la literatura (RSL) se divide en cuatro etapas: la elaboración de las preguntas de investigación y bibliométricas a partir de una plantilla GQM (Goal, Question Metric), la elaboración de términos y conectores lógicos, formulación de criterios de inclusión y exclusión para la búsqueda avanzada en repositorios digitales y por último, la evaluación de los criterios de calidad. En los resultados, se encontró que el modelo de red neuronal más frecuentemente utilizado es el Deep Neural Network (DNN), el tipo de aprendizaje más común es el Aprendizaje Supervisado y el algoritmo de machine learning más utilizado es el Backpropagation (BP); asimismo, se respondieron las preguntas bibliométricas de donde se observó que existe un interés equilibrado por este estudio entre los años 2017 hasta el 2019.LIMAEscuela Profesional de Ingeniería de SistemasInfraestructura Tecnológica - inteligencia artificia

Improved Lion Optimization based Enhanced Computation Analysis and Prediction Strategy for Dropout and Placement Performance Using Big Data

Background: Predicting the undergraduate’s placement performance is vital as it impacts the credibility of educational institutions. Hence, it is significant to predict their performance based on placement in the early days of degree program. Objectives: The study intends to predict the undergraduate’s placement performance through the introduced ANN-R (Artificial Neural Network based Regression) as it is able to handle fault tolerance. For efficient prediction, relevant feature selection is needed that is performed by the proposed ILO (Improved Lion Optimization) algorithm as it has the ability to find nearest probable optimal solution. Methodology: Initially, the parameters and population are initialised. Subsequently, first best-agent is stated in accordance with fitness function. Subsequently, position of present search agent is updated. This iteration continues until all the features are selected and optimized result is attained. Here best score is computed using the proposed ILO for feature selection. Finally, the dropout analysis and placement performance of students is predicted using the introduced ANN-R through a train and test split. Results/Conclusion: Performance of the proposed system is analysed in accordance with loss metrics. Additionally, internal comparison is performed to find the extent to which the actual and predicted values correlate with one another during prediction using the existing and proposed system. The outcomes revealed that the proposed system has the ability to predict the student’s placement performance along with domain of interest with minimum errors than the traditional system. This makes the proposed system to be highly suitable for predicting student’s performance

Improved Lion Optimization based Enhanced Computation Analysis and Prediction Strategy for Dropout and Placement Performance Using Big Data

Background: Predicting the undergraduate’s placement performance is vital as it impacts the credibility of educational institutions. Hence, it is significant to predict their performance based on placement in the early days of degree program. Objectives: The study intends to predict the undergraduate’s placement performance through the introduced ANN-R (Artificial Neural Network based Regression) as it is able to handle fault tolerance. For efficient prediction, relevant feature selection is needed that is performed by the proposed ILO (Improved Lion Optimization) algorithm as it has the ability to find nearest probable optimal solution. Methodology: Initially, the parameters and population are initialised. Subsequently, first best-agent is stated in accordance with fitness function. Subsequently, position of present search agent is updated. This iteration continues until all the features are selected and optimized result is attained. Here best score is computed using the proposed ILO for feature selection. Finally, the dropout analysis and placement performance of students is predicted using the introduced ANN-R through a train and test split. Results/Conclusion: Performance of the proposed system is analysed in accordance with loss metrics. Additionally, internal comparison is performed to find the extent to which the actual and predicted values correlate with one another during prediction using the existing and proposed system. The outcomes revealed that the proposed system has the ability to predict the student’s placement performance along with domain of interest with minimum errors than the traditional system. This makes the proposed system to be highly suitable for predicting student’s performance

McNair Research Journal

Full issue of the Georgia Southern University McNair Journal presented by the Ronald E. McNair Post-Baccalaureate Achievement Program at Georgia Southern University. Fifty Years of Brown: An analysis of the impact of Brown on the educational system in Statesboro, Georgia Reece Anthony The Use of Natural Transformation in Actinobacillus pleuropnemoniae to Generate Confirmatory Mutants in a Stereotype 1 Strain Leandra D. Burwell Global outsourcing: A study of attitudes held by Georgia Southern Students Patricia Dugan A Comparison of Theweleit\u27s Red Nurse/White Nurse Figures with the Jezebel/Mammy figures of African Slave Women in the Southern, Ante-Bellum Plantation System Aziza el-Shair The Effects of Technological Advancements on Ethical Principles Kendrick J. Hamilton Survivor Guilt and First-Generation College Students: The role of family support Dia Y. Harden Early Warning Signs of Fraudulent Financial Reporting in the Healthcare Industry Shaketa Jackson BET on Black: A content analysis of African American representation in commercials on BET Gloria T. Morgan Who will be affected by the Proposed Changes to the HOPE Scholarship Rebecca Perkins The Environmental pH Affect on Actinobacillus pleuropnemoniae ApxI Toxin Production Earnest V. Powell The Seeker Sensitive Message of Contemporary Protestant Christianity Richard Preville Quantitative Precipitation Forecast Using Neural Networks Jamison Smallwood Sister-to-sister Connections: Fostering healthy relationships among Black Women Brandee A. Thomas Portraying John Brown in the New York Times: A content analysis Patricia Thomas Racial Identity and Satisfaction at Georgia Southern University Takeshia Toles Representation of African Americans in Contemporary Popular Children\u27s Picture Books Pamela Walker A Measurement of Physical Activity and Fitness of Undergraduate Georgia Southern University Students Kamilah Whippl

Critical Thinking Skills Profile of High School Students In Learning Science-Physics

This study aims to describe Critical Thinking Skills high school students in the city of Makassar. To achieve this goal, the researchers conducted an analysis of student test results of 200 people scattered in six schools in the city of Makassar. The results of the quantitative descriptive analysis of the data found that the average value of students doing the interpretation, analysis, and inference in a row by 1.53, 1.15, and 1.52. This value is still very low when compared with the maximum value that may be obtained by students, that is equal to 10.00. This shows that the critical thinking skills of high school students are still very low. One fact Competency Standards science subjects-Physics is demonstrating the ability to think logically, critically, and creatively with the guidance of teachers and demonstrate the ability to solve simple problems in daily life. In fact, according to Michael Scriven stated that the main task of education is to train students and or students to think critically because of the demands of work in the global economy, the survival of a democratic and personal decisions and decisions in an increasingly complex society needs people who can think well and make judgments good. Therefore, the need for teachers in the learning device scenario such as: driving question or problem, authentic Investigation: Science Processes

2016 Oklahoma Research Day Full Program

This document contains all abstracts from the 2016 Oklahoma Research Day held at Northeastern State University

Annual Report of the University, 1999-2000, Volumes 1-4

The Robert O. Anderson School and Graduate School of Management at The University of New Mexico Period of Report: July 1, 1999 to June 30, 2000 Submitted by Howard L. Smith, Dean The Anderson Schools of Management is divided into four distinct divisions- the Department of Accounting; the Department of Finance, International and Technology Management; the Department of Marketing, Information and Decision Sciences; and the Department of Organizational Studies. This structure provides an opportunity for The Anderson Schools to develop four distinct areas of excellence, proven by results reported here. I. Significant Developments During the Academic Year The Anderson Schools of Management • As a result of the multi-year gift from the Ford Motor Company, completed renovation of The Schools\u27 Advisement and Placement Center, as well as all student organization offices. • The Ford gift also provided for $100,000 to support faculty research, case studies and course development. • The Schools revised the MBA curriculum to meet the changing needs of professional, advanced business education. • The Schools updated computer laboratory facilities, with the addition of a 45-unit cluster for teaching and student work. • The faculty and staff of The Schools furthered outreach in economic development activities by participating directly as committee members and leaders in the cluster workgroups of the Next Generation Economy Initiative. • The faculty, staff and students of The Schools contributed to the development of the Ethics in Business Awards; particularly exciting was the fact that all nominee packages were developed by student teams from The Anderson Schools. • The Schools continue to generate more credit hours per faculty member than any other division of the UNM community. The Accounting Department • Preparation and presentation of a progress report to accrediting body, the AACSB. The Department of Finance, International and Technology Management • The Department continued to focus on expansion of the Management of Technology program as a strategic strength of The Schools. The Department of Marketing. Information and Decision Sciences • Generated 9022 credit hours, with a student enrollment of 3070. The Department of Organizational Studies • Coordinated the 9th UNM Universidad de Guanajuato (UG) Mexico Student Exchange