IMPACT OF INTERNET ON THE MENTAL HEALTH OF YOUNG ADULTS IN VISAKHAPATNAM

Objective: The extreme and constant use of internet use has been reported to be associated with depression and other adverse physical health conditions. The purpose of this research is to investigate the relationship between the frequency of internet usage among the university students of Visakhapatnam, India, and their health problems and depression levels. Methods: The study sample consists of 100 university students studying at a university in Visakhapatnam, India. Distribution of the sample by gender was 43 males and 50 females. Questionnaires were administered to students in groups, in a class environment, by the author. Participation was voluntary. In total, 100 students participated in this study. Seven of them had to be excluded for not responding properly to all questionnaires, so the final sample consisted of 93 participants. Results: The results indicate a significant association between depression and the intense internet usage (>5–7 h/daily), with Chi-square value 23.80 and p<0.01. Furthermore, as the internet usage increases, there is a significant rise in systolic blood pressure with F=3.74 and p<0.05. Conclusion: This study indicates that intense internet usage is definitely leading to mental health problems like depression and also other physical health issues like increased blood pressure.

Classifying clinically actionable genetic mutations using KNN and SVM

Cancer is one of the major causes of death in humans. Early diagnosis of genetic mutations that cause cancer tumor growth leads to personalized medicine to the decease and can save the life of majority of patients. With this aim, Kaggle has conducted a competition to classify clinically actionable gene mutations based on clinical evidence and some other features related to gene mutations. The dataset contains 3321 training data points that can be classified into 9 classes. In this work, an attempt is made to classify these data points using K-nearest neighbors (KNN) and linear support vector machines (SVM) in a multi class environment. As the features are categorical, one hot encoding as well as response coding are applied to make them suitable to the classifiers. The prediction performance is evaluated using log loss and KNN has performed better with a log loss value of 1.10 compared to that of SVM 1.24.

Investigation of stressors teachers face in schools

Teachers have to face many different stressful situations in schools. In this context serious attention has been paid, and much research has been carried out, to investigate the issue of potential stressors occurring in school or class environment. Although pre-service teacher training does not usually include training related to the development of the teachers` competence to solve stressful situations in lessons, as soon as teachers start their teaching career, they are automatically considered to be equipped with this competence. In the research, presented in this paper, the main goal was to identify the most frequent stressors that primary and secondary school teachers face in their everyday teaching. Two methods were used to collect necessary research data: a semi-structured interview with teachers, and observation of teachers during the lessons they taught. Based on the interview data analyses the following nine stressors were identified as the most frequent and most serious (in order): difficult students, mismatch between students’ performance requirements and their abilities, disruptive behavior of students, inadequate student attention, social and emotional factors of the environment in which students live, use of mobile phones during lessons, overwork and fatigue of teachers, insufficient school equipment and lack of teaching aids, conflicts among students. The aim of the observation was to confirm in practice, the types of the stressors identified from the interview data. Analysis of the records from observations, confirmed some of the previously (in interviews) identified stressors and also identified some further stressors.

Shaping student confidence and their perception of learning in undergraduate chemistry and biochemistry courses

This study examined factors influencing student confidence and their perception of learning in the context of undergraduate chemistry and biochemistry courses. Anonymous online surveys were used to measure the extent to which small group work influenced student confidence in solving problems compared to working individually, as well as how various course factors and the amount of effort and pleasure students experienced during their coursework influenced their perception of learning. Upon examining over 2500 student responses to more than 150 unique problems/exercises across 3 different courses, student confidence in solving problems improved to an average of approximately 8 out of 10 when they worked in small groups, compared to that of 6.5 out of 10 when working alone. Students ranked (i) opportunities to revisit assessments, (ii) the class environment, and (iii) instructor feedback as course factors that were most influential on their learning. There was little if any correlation between student effort and their perception of learning, and their perception of learning only slightly correlated with the amount of pleasure they experienced during their coursework. Taken together, these data highlight the importance of facilitating regular small group work, multistage assessments, good feedback and a pleasurable learning environment for students.

An Alternative Educational Tool Through Interactive Software over Facebook in the Era of COVID-19

During the COVID-19 period, education has been required to reform and adapt to a modern, imposed paradigm in which all of its activities must be delivered in a completely digital format. As a result, in light of this pressing need, educational institutions should either repurpose existing facilities, such as learning management systems, or develop new online education options in a timely manner. In view of the above, this paper proposes an alternative educational tool over Facebook by exploiting the technology of social networking. This Facebook-based application was used as the sole platform for supporting asynchronous learning of high school students in the tutoring of mathematics during the COVID-19 lockdown. This modern educational approach through Facebook encompasses interactive software which involves an e-class environment with social characteristics, multimedia-based learning material delivery and learning activities and assessment of different types. The presented Facebook-based interactive educational software has been evaluated by school students with very encouraging results.

Shaping student confidence and their perception of learning in undergraduate chemistry and biochemistry courses

This study examined factors influencing student confidence and their perception of learning in the context of undergraduate chemistry and biochemistry courses. Anonymous online surveys were used to measure the extent to which small group work influenced student confidence in solving problems compared to working individually, as well as how various course factors and the amount of effort and pleasure students experienced during their coursework influenced their perception of learning. Upon examining over 2500 student responses to more than 150 unique problems/exercises across 3 different courses, student confidence in solving problems improved to an average of approximately 8 out of 10 when they worked in small groups, compared to that of 6.5 out of 10 when working alone. Students ranked (i) opportunities to revisit assessments, (ii) the class environment, and (iii) instructor feedback as course factors that were most influential on their learning. There was little if any correlation between student effort and their perception of learning, and their perception of learning only slightly correlated with the amount of pleasure they experienced during their coursework. Taken together, these data highlight the importance of facilitating regular small group work, multistage assessments, good feedback and a pleasurable learning environment for students.

Afectaciones en la motivación hacia el aprendizaje de los estudiantes de la Licenciatura en Educación Primaria de la Escuela Normal de Sinaloa en tiempos de pandemia

Durante el ciclo escolar 2019-2020, la pandemia por COVID-19, forzó al Sistema Educativo en México a operar en clases no presenciales. El objetivo de esta investigación es analizar los factores que afectaron la motivación hacia el aprendizaje de los estudiantes de la Licenciatura en Educación Primaria de la Escuela Normal de Sinaloa. Es un estudio descriptivo, de tipo estadístico, usando escala tipo Likert. Resultando que los factores con mayor afectación están relacionados con la motivación extrínseca, por lo que, se debe fortalecer el desarrollo de habilidades personales y sociales en los estudiantes para favorecer su motivación intrínseca. Esencial para su aprendizaje. Abstract During 2019-2020 school year, the COVID 19 pandemic forced Mexico’s educational system to operate outside an in-class environment. The objective of this research is the analysis of factors which affected academic motivation in undergraduate Primary Teachers from the Teacher’s College of Sinaloa. It is a descriptive research with a statistical treatment using a Likert scale; results show that factors with greater affectation are related to extrinsic motivation, which is why we should strengthen the development of social and personal skills in students to enhance intrinsic motivation that is essential for learning.

Implementation of an Integrated Online Class Model using Open-Source Technology and SNS

Before Covid-19, the class model was divided into online, offline, and blended learning. Due to Covid-19, we have the only online class environment. We need a new online class model under the new circumstances. In the new model, all technology and educational methods need to be well-adapted, organized and harmonized to compensate for the absence of offline learning sessions. In this paper, we propose a new online class model. Because of the absence of offline sessions, the model emphasizes the integration of synchronous and asynchronous activities seamlessly and effectively. The model also emphasizes the instructor's role as a content prosumer because the instructor in the new model is either reusing other's and the one's own contents or supplying those contents for others. This model uses open-source solutions or free services like Moodle, OBS, Tubestory, and Snap Camera for both budget-saving and stability purposes. It actively uses Moodle's monitoring capability and adopts various learning technologies. It consists of three activity sessions: a pre-Zoom session, a Zoom session, and a post-Zoom session. Each session is composed of modules that describe the process and action for the class. The process, methods, and techniques for each module are explained in this paper. The official students survey for class evaluation held by Kongju national university showed that the new class model's application obtained a higher score than the same class of the previous year that is performed by conventional teaching.