scholarly journals Online Educational Activities of Students: Readiness and Self-Efficacy

2021 ◽  
Vol 25 (4) ◽  
pp. 661-680
Author(s):  
Natalia A. Lyz

Introduction. The widespread use of telelearning raises the issue of ensuring its effectiveness. Researchers consider various factors, but student readiness for such learning has not yet become the subject of systemic research in domestic science. The objectives of the article are: to reveal personality predictors of online learning success, to identify the components of student readiness for such learning (on the basis of foreign works); to characterize the readiness and self-efficacy of students’ online educational activities drawing on empirical data. Materials and Methods The researchers utilized the methods of theoretical analysis of the problem and the survey method. The author’s questionnaire was used to collect the data on the online activity of the students, self-assessment of readiness and effectiveness of online learning. 252 first- and second-year IT-students participated in the survey. Results. Five components of students’ readiness for online learning have been identified: attitude towards online learning, self-directed learning, time management, communicative competence, and technical competence. The students’ attitudes towards online learning are ambivalent. The students understand the importance of such training, but they are not willing to invest enough time and effort into it. Two interrelated components (self-directed learning and time management) contribute most to the overall online learning readiness. Online learning self-efficacy is related to technical competence and attitudes towards online learning. Discussion and Conclusion. The results will be useful for further research of the factors and ways improving online learning effectiveness. The research prospects are the development of psychodiagnostic tools for assessing the online learning experience and readiness of students and the diversification of the sampling by adding students from different programme tracks and with different experiences in online educational activities.

2021 ◽  
Vol 8 (1) ◽  
pp. 27-47
Author(s):  
Adaninggar Septi Subekti

The present study aimed to investigate Indonesian second language (L2) learners’ level of resilience and the relationship between their resilience and their self-directed learning (SDL) in an online learning setting at the time of the Covid-19 pandemic. The present study used a survey method by distributing Google Form questionnaires. The participants were 187 university student participants taking English for Academic Purposes (EAP) classes online in their respective departments. It was conducted to fill the void in resilience literature in the Indonesian L2 context and to find out the Indonesian learners’ resilience in the online learning setting as well as to know whether learners’ resilience was associated with their SDL, a critical element to succeed in online learning. The study found that learners possessed a high level of resilience. Learners were found to have a high level of realistic optimism and self-discipline, prominent characteristics of resilience. However, they reported a slightly lower level of capability in handling multiple tasks at the same time. The study further found that learners’ resilience was significantly, moderately, and positively correlated with their SDL. Based on the findings, possible contributions and implications are stated alongside the limitations of the study and possible directions for future research.


2020 ◽  
Vol 3 (2) ◽  
pp. 66-78
Author(s):  
Zöhre Serttaş ◽  
Aslı Kasabalı

The aim of this study is to evaluate students ' readiness for online learning at the Near East University English Preparatory School and to provide suggestions on how they can be further supported to strengthen their online learning.  202 adult students participated in the study were fall semester students of the 2019-2020 Academic year.  As the data collection tool, Online Learning Readiness Scale (OLRS) by Hung et al. (2010) was used.  The  dimensions of the scale are; self-directed learning, motivation, learner control, computer-Internet self-efficacy, and online communication self-efficacy.  The data obtained showed that the participants were ready in all dimensions with some variations within the dimensions.  In the self-directed learning dimension, the participants were observed to lack the ability to manage time in their studies however they were willing to ask for help when they need help. Although the scores were above the average, Computer / Internet self-efficacy was found to have the lowest scores compared to the other dimensions.  Participants stated that they were distracted by other online applications while studying for their online course.  Results for computer / internet self-efficacy dimension showed that participants did not have a very high readiness in using basic Microsoft Office Programs, reaching information easily via online search and using online applications.  Motivation and Online Communication self-efficacy dimensions were found to be the dimensions where all the items received a high score.      Keywords: Online learning, online learning readines, english preparatory school    


Open Praxis ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 191
Author(s):  
Emel Dikbas Torun

The purpose of this study was to examine the relationship between e-learning readiness and academic achievement in an online course in higher-level education. The survey method was employed when collecting the study data, and the data-collection instrument used was the E-Learning Readiness Scale. The scale comprises 33 items and six sub-dimensions, including (1) computer self-efficacy, (2) internet self-efficacy, (3) online self-efficacy, (4) self-directed learning, (5) learner control, (6) motivation toward e-learning. The study participants comprised 153 freshmen who were taking an online English as a Foreign Language course. A relational model is proposed in this study to measure the predicted levels of readiness on academic achievement in online learning. Reliability analysis, Pearson correlation, linear regression analysis, and structural equation modelling were used to analyze and model the study data. Results indicated that self-directed learning is the strongest predictor of academic achievement, while motivation toward e-learning was found to be another predictor of academic achievement. Internet/online/computer self-efficacy and learner control were not found to be among significant predictors of academic achievement. It is concluded that, especially with the spread of Covid-19 worldwide, education is currently switching from face-to-face to online learning in an immediate and unexpected way; therefore e-learning readiness has to be carefully taken into consideration within this new educational paradigm.


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