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Volume 10, Issue 11, 2022

Technostress Experiences from Online Learning
Original Research
The continuous development of new technologies could create many new, yet unforeseen jobs in the future. It "is a smart production method based on artificial intelligence and digital technology" however the result of multitasking in the application and continuous communication, repeated information, repeated system improvements and the resulting uncertainty, continuous re-learning and the resulting functional insecurity and technical problems associated with the ICT is the negative sides of technology for end-users. This study aimed to explore the technostress experiences and coping mechanism of participants in online learning. The participants of the research involved 26 students (2 males and 24 females) who are now enrolled in College of Teacher Education-Bachelor of Elementary Education at Quirino State University - Main Campus Diffun, Quirino. The qualitative inquiry method was used. Data were collected through focus group interviews and content analysis as data collection method.Narrative analysis was utilized. Data were analyzed by drawing on thematic analysis method that delivered key themes and patterns. Revealed in the study, the technostress experiences such as technical issue oriented, emotional aspect, and physical aspect. The findings suggest that the participants’ are brought together to collaboratively overcome challenges experienced in the online space and work together to overcome technological challenges.
American Journal of Educational Research. 2022, 10(11), 647-653. DOI: 10.12691/education-10-11-3
Pub. Date: November 22, 2022
Predicting Students’ Academic Performance Using Regression Analysis
Original Research
This study generally aimed to develop a predictive model for students' academic performance. Correlational research designs were employed in this study to explore the relationships between the students' sex, course, senior high school data, admission ability test, and first-year performance of the students. A statistical model for predicting first-year students' academic performance based on admission data and first-year academic performance was formulated. The study was conducted in one of the State Universities and Colleges (SUCs) in Cordillera Administrative Region (CAR). The population of the study was 521 first-year students enrolled during the first semester and completed up to the second semester of the school year 2019-2020. From the findings, the academic performance of the students is highly associated with their high school GWA, strand, admission ability, course, and sex. The academic performance of first-year students can be predicted using Multiple Linear Regression (MLR) analysis, a model that considers the high school GWA, strand, and admission general ability, of the students as significant predictors. The derived model has a predictive power of around 67.30% and the model was found a good model. It is then suggested that the highly associated data to students' academic performance like high school GWA and admission test results can be considered in the recruitment and admission of students, especially, in the programs with board examinations. The same predictors are suggested to be accommodated in developing programs and interventions which could improve the student's academic performance. Meanwhile, the administrators are encouraged to consider the use of the models to track the students and provide necessary interventions to those who are likely to perform poorly in their courses. The model can also be considered in crafting amendments to the admission and retention policy of the said college.
American Journal of Educational Research. 2022, 10(11), 640-646. DOI: 10.12691/education-10-11-2
Pub. Date: November 20, 2022
Learning Experiences AMID the COVID-19 Pandemic
Original Research
This study aimed to explore the experiences of married students and working students in flexible learning amidst pandemic. The participants of the research involved 17 married students and working students (2 males and 15 females) who are now enrolled in College of Teacher Education-Bachelor of Elementary Education and College of Information Technology and Computing Sciences at Quirino State University Main Campus. The qualitative inquiry method was used. Data were collected through individual interviews, focus group discussion, and document analysis used in this study. Narrative analysis was utilized and purposeful sampling technique was used. Employing a phenomenological analysis, the study explored the experiences of married students and working students in flexible learning amidst pandemic. Revealed in the study, the advantages of flexible learning were perseverance, time management, teacher factor, flextime, and prayer while the disadvantages were learning difficulties, poor connectivity, destructions, stress, and laziness. With these findings, the researcher recommends, raise awareness about the mental health continuum, reduce stigma associated with mental illness, promote help seeking behaviors and emotional well-being practices, and prevent suicide through individual education and outreach events. Stress management reset, recalibrate alarm system, and help mind and body adapt (resilience).
American Journal of Educational Research. 2022, 10(11), 632-639. DOI: 10.12691/education-10-11-1
Pub. Date: November 08, 2022