scholarly journals Determining the Relationship Between Self-directed Learning Readiness and Acceptance of E-learning and Academic Achievement of Students

2017 ◽  
Vol 30 (106) ◽  
pp. 11-22
Author(s):  
N Khatib Zanjani ◽  
AA Ajam ◽  
S Badnava ◽  
◽  
◽  
...  
Keyword(s):  
Academic Achievement ◽  
Self Directed Learning ◽  
Learning Readiness ◽  
E Learning ◽  
Directed Learning ◽  
The Relationship

scholarly journals Online Distance Learning in Higher Education: E-learning Readiness as a Predictor of Academic Achievement

Open Praxis ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 191
Author(s):  
Emel Dikbas Torun
Keyword(s):  
Academic Achievement ◽  
Online Learning ◽  
Self Efficacy ◽  
Learner Control ◽  
Study Data ◽  
Self Directed Learning ◽  
Learning Readiness ◽  
E Learning ◽  
Directed Learning ◽  
Computer Self Efficacy

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.

Garrison's Model of Self-Directed Learning: Preliminary Validation and Relationship to Academic Achievement

2010 ◽  
Vol 13 (2) ◽  
pp. 586-596 ◽  
Author(s):  
Sabry M. Abd-El-Fattah
Keyword(s):  
Academic Achievement ◽  
Self Management ◽  
Path Modeling ◽  
Self Directed Learning ◽  
Self Monitoring ◽  
Psychological Constructs ◽  
Mediation Analyses ◽  
Preliminary Validation ◽  
Directed Learning ◽  
The Relationship

In this project, 119 undergraduates responded to a questionnaire tapping three psychological constructs implicated in Garrison's model of self-directed learning: self-management, self-monitoring, and motivation. Mediation analyses showed that these psychological constructs are interrelated and that motivation mediates the relationship between self-management and self-monitoring. Path modeling analyses revealed that self-management and self-monitoring significantly predicted academic achievement over two semesters with self-management being the strongest predictor. Motivation significantly predicted academic achievement over the second semester only. Implications of these findings for self-directed learning and academic achievement in a traditional classroom setting are discussed.

scholarly journals The Relationship between Understanding of E-Learning with Self-Directed Learning among Students

2020 ◽  
Vol 15 (2) ◽  
pp. 12-22
Author(s):  
Normala Ismail ◽  
Mohamad Kamil Ariff Khalid
Keyword(s):  
Social Sciences ◽  
Positive Relationship ◽  
Test Results ◽  
Self Directed Learning ◽  
Level Of Education ◽  
Significant Difference ◽  
E Learning ◽  
Directed Learning ◽  
Level Of Understanding ◽  
The Relationship

The main purpose of this study is to identify the students’ understanding of e-learning and their readiness for self-directed learning. A total of 306 Diploma level students of a various program from three faculties at Universiti Teknologi MARA (UiTM) Pahang Raub Campus have been surveyed. The data were obtained through questionnaires distributed and analyzed using the Statistical Package for Social Sciences (SPSS) version 23. The findings show that the respondents’ level of understanding of the concept and their responsibility on e-learning is high while their readiness for self-directed learning is low. The correlation test results show that there is a significant positive relationship between the respondents’ level of understanding to e-learning and their willingness for self-directed learning but the correlation is weak. The findings also showed that the respondents’ level of education and study grade have a significant difference in their readiness for self-directed learning.

scholarly journals Online Learning Readiness of Junior High School Students in Denpasar

2020 ◽  
Vol 7 (2) ◽  
pp. 172-188
Author(s):  
Kadek Erlita Dwiyanti ◽  
I Putu Yogi Pratama ◽  
Ni Putu Ines Marylena Candra Manik
Keyword(s):  
High School ◽  
Online Learning ◽  
Junior High School ◽  
Mixed Method ◽  
Quantitative Data ◽  
Self Directed Learning ◽  
Learning Readiness ◽  
E Learning ◽  
Directed Learning ◽  
Online Learning Readiness

ABSTRACTThe Covid-19 pandemic has caused learning to be carried out online. Not all students, however, are ready for online learning. This study aims to examine the level of readiness of eighth-grade students at a junior high school through an explanatory sequential mixed method design consisting of quantitative and qualitative phases. Student readiness for online learning in this study was reviewed from five dimensions: self-directed learning, motivation for learning, computer/internet self-efficacy, learner control, and online communication self-efficacy. The Online Learning Readiness Scale (OLRS) survey proposed by Hung (2010) with a five-point-Likert scale was used to collect quantitative data. The data were analyzed quantitatively, and the level of readiness was measured utilizing the e-learning readiness assessment model suggested by Aydin and Tasci (2005). Follow-up interviews were then held to support the quantitative data. The results showed that the majority of students entered the level of "ready but needs a few improvements". However, there was one item in the dimension of self-directed learning that was included in the level of "not ready needs some work". The implication of this study is the need to encourage students to actively communicate in online learning, especially for shy students.ABSTRAKPandemi Covid-19 menyebabkan pembelajaran dilakukan secara online. Namun, tidak semua siswa siap dengan pembelajaran online. Penelitian ini bertujuan untuk menguji tingkat kesiapan siswa kelas VIII sebuah sekolah menengah pertama melalui penelitian explanatory sequential mixed method yang terdiri dari tahap kuantitatif dan kualitatif. Kesiapan siswa untuk pembelajaran online ditinjau dari lima dimensi: pembelajaran mandiri, motivasi belajar, efikasi diri komputer / internet, kontrol peserta didik, dan efikasi diri komunikasi online. Survei Online Learning Readiness Scale (OLRS) yang digagas oleh Hung (2010) dilengkapi dengan skala Likert lima poin digunakan untuk mengumpulkan data kuantitatif. Data kemudian dianalisis dengan menggunakan analisis deskriptif kuantitatif dan tingkatannya diukur dengan model penilaian kesiapan E-learning yang dikemukakan oleh Aydin dan Tasci (2005). Wawancara kemudian dilakukan untuk mengumpulkan data guna mendukung data kuantitatif. Hasil penelitian menunjukkan bahwa secara keseluruhan siswa memasuki level “siap, tetapi perlu sedikit perbaikan”. Namun, ada satu item dalam dimensi pembelajaran mandiri yang termasuk dalam tingkat "belum siap, perlu peningkatan". Implikasi dari penelitian ini adalah perlunya mendorong siswa untuk aktif berkomunikasi dalam pembelajaran online, khususnya bagi siswa yang pemalu.

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