scholarly journals Modelos predictivos de riesgo académico en carreras de computación con minería de datos educativos

2021 ◽  
Vol 21 (66) ◽  
Author(s):  
Enrique Ayala Franco ◽  
Rocío Edith López Martínez ◽  
Víctor Hugo Menéndez Domínguez
Keyword(s):  
Early Detection ◽  
Educational Intervention ◽  
Educational Data Mining ◽  
Educational Institutions ◽  
Academic Risk ◽  
Entrance Exam ◽  
Computer Tools ◽  
Poor School Performance ◽  
Intervention Measures ◽  
Prediction Techniques

Los problemas de bajo rendimiento académico y rezago son recurrentes en instituciones educativas de nivel superior, especialmente al inicio de los estudios universitarios. En el contexto local, análisis diagnósticos han mostrado altos índices de reprobación y bajo rendimiento académico. En este trabajo, se utilizaron datos sociodemográficos y resultados de exámenes de admisión de 415 alumnos de las carreras del área de computación de la Universidad Autónoma de Yucatán (México), inscritos entre 2016 y 2019. El objetivo es generar modelos predictivos de riesgo académico, empleando métodos de la minería de datos educativa, que sirvan como herramientas de detección temprana de condiciones de riesgo académico y faciliten el despliegue de estrategias de intervención educativa. Se siguieron las etapas del Proceso de Extracción de Conocimiento en Bases de Datos, concretamente, se aplicaron técnicas de clasificación para el análisis, obtención y validación de los modelos. Los resultados muestran que el mejor modelo corresponde al algoritmo LMT, con un valor de precisión de 75.42% y un 0.805 para el área bajo la curva ROC. Se logró identificar a los mejores atributos predictores, particularmente las pruebas del examen de ingreso a licenciatura fueron muy significativas. Se propone el desarrollo de herramientas informáticas para la detección precoz de riesgo académico y estrategias de intervención educativa oportuna. The problems of poor academic performance and lag are recurrent in higher-level educational institutions, especially at the beginning of university studies. The early detection of academic risk conditions enables the implementation of educational intervention measures to address factors of poor school performance, associated with the particular contexts of the students. The purpose of this study was to generate predictive models of academic risk, using educational data mining methods, specifically classification or prediction techniques, for the analysis, obtaining and validation of the models. The data used correspond to admission exam results and sociodemographic data of 415 students of the computer science majors at the Autonomous University of Yucatán (Mexico), enrolled between 2016 and 2019. The results show that the best model corresponding to the algorithm of LMT classification, with a precision value of 75.42% and 0.805 for the area under the ROC curve. It was possible to identify the best predictive attributes, particularly the bachelor entrance exam tests were very significant. The development of computer tools for the early detection of academic risk and strategies for timely educational intervention is proposed.

An Enhancement of Feature Selection Algorithm for EDM: A Review

2018 ◽  
Vol 8 (5) ◽  
pp. 29
Author(s):  
Manpreet Kaur ◽  
Chamkaur Singh
Keyword(s):  
Feature Selection ◽  
Educational Data Mining ◽  
Problem Formulation ◽  
Research Area ◽  
Education Quality ◽  
Educational Institutions ◽  
Selection Algorithm ◽  
Positive Role ◽  
Data Set ◽  
Selection Algorithms

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention.

Abstract 2608: Lung cancer prevention and an early detection educational intervention in minority and underserved communities

2021 ◽  
Author(s):  
Samantha J. Sojourner ◽  
Marlo M. Vernon ◽  
Ghadeer Albashir ◽  
Justin X. Moore ◽  
Stephen W. Looney ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Early Detection ◽  
Cancer Prevention ◽  
Educational Intervention ◽  
Underserved Communities ◽  
Lung Cancer Prevention

scholarly journals Enhancing the Knowledge of Cervical Cancer Screening among Female Nursing Students: An Interventional Educational Program

2020 ◽  
Author(s):  
Hayam Fathey A. Eittah ◽  
Khalid Abdullah S. Aljohani ◽  
Mohammed Saeed E. Aljohani
Keyword(s):  
Cervical Cancer ◽  
Saudi Arabia ◽  
Nursing Students ◽  
Early Detection ◽  
Cancer Prevention ◽  
Educational Intervention ◽  
Educational Program ◽  
Pap Smear ◽  
Cervical Cancer Prevention ◽  
Study Results

Background: Cervical cancer is a growing health risk facing women worldwide with the human papillomavirus (HPV) as the primary underlying cause. Pap smear is a simple screening test that can detect early changes in cervical cells, which might develop into cancer cells. Raising awareness of cervical cancer prevention has a significant impact on decreasing the burden of the disease. The aim of the study is to assess female nursing students' knowledge on early detection and screening of cervical cancer, and to determine the effectiveness of an educational program. Methods: A quasi-experimental research design (one group for pre- and post-tests) was utilized with a convenience sample of 130 female nursing students in one of the nursing colleges in Saudi Arabia. The study’s educational intervention included information about anatomy of genital tract and the importance of regular check-ups. The pre- and post-tests were applied to identify changes after intervention measures. Results: The mean age of the participants were 21.32 years (SD: 1.34). The findings revealed a significant improvement of post-test students’ knowledge in all items related to risk factors, signs and symptoms, occurrence, identification of HPV as causative agent, vaccination against HPV, and finally Pap smear for early detection and screening of cervical cancer. Conclusion: The study results support implementing educational intervention to improve nursing students' knowledge and awareness about cervical cancer prevention. Furthermore, it is imperative that cervical cancer awareness education modules should be developed and integrated within the nursing curriculum. Further studies with large sample size are recommended to increase generalization of the results.  Key words: cervical cancer, education program, primary prevention, nursing students, Saudi Arabia

Incidencia de factores académicos en el fracaso escolar. Reflexiones derivadas de la experiencia de profesores jubilados

2017 ◽  
Vol 21 (2) ◽  
pp. 191-211
Author(s):  
Estefanía Martínez Valdivia ◽  
Enriqueta Molina Ruiz
Keyword(s):  
Data Analysis ◽  
Secondary Education ◽  
Educational Intervention ◽  
Qualitative Methodology ◽  
School Failure ◽  
Educational Institutions ◽  
Educational Context ◽  
Extensive Experience ◽  
Retired Teachers

Resumen:El estudio trata el tema del fracaso escolar centrado en el contexto educativo como posible marco generador del mismo, interesando averiguar el papel que tanto la escuela, -en cuanto institución mediante su organización y funcionamiento-, como el profesor, -a través de su actuación en el aula-, puedan jugar en su presencia y desarrollo. Se aborda desde una metodología cualitativa pretendiendo comprender el problema del fracaso escolar en profundidad, situándonos en Educación Secundaria Obligatoria y apoyándonos en relatos de profesores jubilados con amplia experiencia en situaciones de fracaso escolar. Los instrumentos de recogida de datos han sido las entrevistas. El análisis de los datos se ha realizado con ayuda del programa QRS Nvivo 11 Plus. Los resultados presentan posibles factores que, desde las propias instituciones educativas, pueden contribuir a generar fracaso escolar. Aparecen organizados en dos bloques: derivados de la escuela y su organización; derivados de la intervención docente.Resumen: El estudio trata el tema del fracaso escolar centrado en el contexto educativo como posible marco generador del mismo, interesando averiguar el papel que tanto la escuela, -en cuanto institución mediante su organización y funcionamiento-, como el profesor, -a través de su actuación en el aula-, puedan jugar en su presencia y desarrollo. Se aborda desde una metodología cualitativa pretendiendo comprender el problema del fracaso escolar en profundidad, situándonos en Educación Secundaria Obligatoria y apoyándonos en relatos de profesores jubilados con amplia experiencia en situaciones de fracaso escolar. Los instrumentos de recogida de datos han sido las entrevistas. El análisis de los datos se ha realizado con ayuda del programa QRS Nvivo 11 Plus. Los resultados presentan posibles factores que, desde las propias instituciones educativas, pueden contribuir a generar fracaso escolar. Aparecen organizados en dos bloques: derivados de la escuela y su organización; derivados de la intervención docente.Abstract:The study addresses the issue of school failure focused on the educational context as possible under the same generator, interesting to figure out the role that both the school as an institutionin through their organization and operation-, as the teacher, -through its performance in the classroom-, they can play in their presence and development. It is approached from a qualitative methodology pretending to understand the problem of school failure in depth, placing ourselves in Secondary Education and relying on accounts of retired teachers with extensive experience in situations of school failure. The instruments were the interviews. The data analysis was performed using the QRS NVivo 11 Plus program. The results show possible factors, from the educational institutions can contribute to the generation school failure. They are organized in two blocks: derived from the school and its organization; derived from the educational intervention.

scholarly journals Monitoring Students at the University: Design and Application of a Moodle Plugin

2020 ◽  
Vol 10 (10) ◽  
pp. 3469 ◽  
Author(s):  
María Consuelo Sáiz-Manzanares ◽  
Raúl Marticorena-Sánchez ◽  
César Ignacio García-Osorio
Keyword(s):  
At Risk ◽  
Early Detection ◽  
At Risk Students ◽  
Machine Learning Techniques ◽  
Dropout Rates ◽  
Dynamic Learning ◽  
Academic Risk ◽  
University Environment ◽  
Student Dropout ◽  
The University

Early detection of at-risk students is essential, especially in the university environment. Moreover, personalized learning has been shown to increase motivation and lower student dropout rates. At present, the average dropout rates among students following courses leading to the award of Spanish university degrees are around 18% and 42.8% for presential teaching and online courses, respectively. The objectives of this study are: (1) to design and to implement a Modular Object-Oriented Dynamic Learning Environment (Moodle) plugin, “eOrientation”, for the early detection of at-risk students; (2) to test the effectiveness of the “eOrientation” plugin on university students. We worked with 279 third-year students following health sciences degrees. A process for extracting information records was also implemented. In addition, a learning analytics module was developed, through which both supervised and unsupervised Machine Learning techniques can be applied. All these measures facilitated the personalized monitoring of the students and the easier detection of students at academic risk. The use of this tool could be of great importance to teachers and university governing teams, as it can assist the early detection of students at academic risk. Future studies will be aimed at testing the plugin using the Moodle environment on degree courses at other universities.

Overview of computer technologies used in descriptive geometry teaching

10.12737/792 ◽  
2013 ◽  
Vol 1 (2) ◽  
pp. 54-58 ◽  
Author(s):  
Ваванов ◽  
D. Vavanov ◽  
Иващенко ◽  
A. Ivashchenko
Keyword(s):  
Distance Learning ◽  
Computer Technology ◽  
Descriptive Geometry ◽  
Educational Institutions ◽  
The Internet ◽  
Learning Material ◽  
Computer Tools ◽  
Computer Technologies ◽  
High Educational

The problem related to adequate use of computer technology and the Internet as supporting tools in the descriptive geometry course is arising in connection with the spread of distance learning practice in different disciplines. The analysis of computer tools used for teaching the students of technical high educational institutions in descriptive geometry is offered in this paper. The classification of used computer means according to learning material assimilation has been cited.

The Integrated Skin Exam film: An educational intervention to promote early detection of melanoma by medical students

2014 ◽  
Vol 70 (1) ◽  
pp. 115-119 ◽  
Author(s):  
Amit Garg ◽  
Joyce Wang ◽  
Shalini B. Reddy ◽  
Jennifer Powers ◽  
Reza Jacob ◽  
...  
Keyword(s):  
Medical Students ◽  
Early Detection ◽  
Educational Intervention

scholarly journals Poor school performance in offspring of patients with schizophrenia: what are the mechanisms?

2011 ◽  
Vol 42 (1) ◽  
pp. 111-123 ◽  
Author(s):  
J. Jundong ◽  
R. Kuja-Halkola ◽  
C. Hultman ◽  
N. Långström ◽  
B. M. D'Onofrio ◽  
...  
Keyword(s):  
Early Detection ◽  
School Performance ◽  
Cognitive Deficits ◽  
Environmental Effects ◽  
Genetic Factors ◽  
Genetic Relatedness ◽  
Tailored Interventions ◽  
Poor School Performance ◽  
Extended Families ◽  
Schizophrenic Patients

BackgroundOffspring of patients with schizophrenia exhibit poorer school performance compared with offspring of non-schizophrenic parents. We aimed to elucidate the mechanisms behind this association.MethodWe linked longitudinal national population registers in Sweden and compared school performance among offspring of schizophrenic parents with offspring of non-schizophrenic parents (1 439 215 individuals with final grades from compulsory school 1988–2006). To investigate the mechanisms, we studied offspring of schizophrenic patients and controls within the same extended families. We investigated genetic effects by stratifying analyses of parent–child associations according to genetic relatedness (half-cousins, full cousins and half-siblings). Environmental effects were investigated by comparing school performance of offspring of schizophrenic fathers and of schizophrenic mothers, respectively, and by stratifying the analyses according to environmental relatedness while controlling genetic relatedness (paternal and maternal half-cousins, paternal and maternal half-siblings).ResultsOffspring of parents with schizophrenia had poorer overall school performance than unrelated offspring of non-schizophrenic parents (−0.31 s.d.). Variability in genetic relatedness greatly moderated the strength of the within-family association (β=−0.23 within exposure-discordant half-cousins, β=−0.13 within exposure-discordant full cousins, β=0.04 within exposure-discordant half-siblings), while no evidence was found that the environment affected offspring school performance.ConclusionsGenetic factors account for poorer school performance in children of parents with schizophrenia. This supports that cognitive deficits found in individuals with schizophrenia and their relatives might be genetically inherited. Early detection of prodromal signs and impaired functioning of offspring of patients with schizophrenia could lead to earlier and better tailored interventions.

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