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Exploring Perceived Fits, Attitudes, and Self-Efficacy: A case of Digital Natives’ Online Learning Behavior
Author(s) -
Binti Muchsini,
. Siswandari,
Soetarno Joyoatmojo,
Wiranto
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1842/1/012013
Subject(s) - online learning , psychology , perception , descriptive statistics , enthusiasm , computer science , mathematics education , social psychology , multimedia , statistics , mathematics , neuroscience
Some pre-service teachers who are studying give less effective perceptions regarding the implementation of online learning during the Pandemic period. Pre-service teachers today belong to a generation of digital natives (DNG) who are very familiar with technology and have unique characteristics, so it is very important to analyze their online learning behavior to design effective online learning. The purpose of this study was to analyze the online learning behaviors of digital natives reviewed from perceived fits, attitudes, and self-efficacy. Survey research was used to analyze the phenomenon of DNG’s online learning behavior and identify the factors that influence it. The instrument in the form of a questionnaire consists of 49 statement items on a scale of 5. Of the 152 polls collected, only 148 were valid. Quantitative and qualitative descriptive analysis was used for data analysis. The results of this study showed that all components of DNG’s online learning behavior had relatively high average scores except the interaction component through online discussion forums. The causes of low interaction through online discussion forums were DNG less active, lack of enthusiasm, easy to give up, difficult to move on, and network constraints. The conclusion of this study was an in-depth analysis related to perceived fits, attitudes, and self-efficacy producing phenomena and are variables capable of explaining the variables of DNG online learning behavior. The results of this study can be used as the basis for further research, namely related to the development of online learning models for the DNG.

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