Acceptance of Google Classroom for Learning English Exit Test

2020 ◽  
Vol 4 (1) ◽  
pp. 67
Author(s):  
Tuan Sarifah Aini Syed Ahmad ◽  
Zarina Suriya Ramlan ◽  
Shashi Kumar Krishnan
Keyword(s):  
Online Learning ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
The Social ◽  
Acceptance Model ◽  
The University ◽  
Learning English

Online learning has been implemented at the tertiary level by using many platforms such as the university learning management system, massive open online courses (MOOCs) and mobile applications. Online learning permits personalization and autonomous learning. However, this is not the case for the English Exit Test. An initiative was made to provide an online platform for students to practice using the language via Google Classroom. Google Classroom can be accessed as a mobile application on a smartphone or on the web by using a computer. It is essential to support the students’ learning in preparation for the test since it is the requirement of graduation for degree students at Universiti Teknologi MARA. This study aimed at determining the level of acceptance in using Google Classroom for learning English Exit Test among students. The sample was selected using purposive sampling. The data were collected using a survey designed based on the Technology Acceptance Model (TAM) and went through data cleansing using Statistical Packages for the Social Sciences (SPSS) Version 21. The data were then analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results indicate that students positively accepted the use of Google Classroom in preparation for the English Exit Test.

The adoption of e-learning beyond MOOCs for higher education

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maggie Liu ◽  
Chunhui Liu
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Content Type ◽  
Factors Influencing ◽  
E Learning ◽  
Acceptance Model ◽  
First Time

Purpose This paper aims to explore factors influencing university students’ intent to take formal lectures completely through e-learning with cloud meetings. Design/methodology/approach This study has surveyed Chinese students who have experienced e-learning with cloud meetings as well as traditional massive open online courses (MOOC) without live dialogues. The data are analysed based on structural equation modelling to assess factors influencing students’ intent to choose e-learning with cloud meetings. Findings The findings show that as per the technology acceptance model, e-learning students who find learning to be easier with cloud meetings than MOOCs believe cloud meeting courses to be more beneficial and thus are more willing to take e-learning with cloud meetings. Originality/value This study compares e-learning with cloud meetings with MOOCs without live dialogues for the first time to highlight the value of open dialogues in real time for effective e-learning.

scholarly journals STUDENT AND TEACHER PERSPECTIVES ON FACTORS TO SUCCESS AND ATTRITION IN ENGINEERING MINI-MOOC USING TECHNOLOGY ACCEPTANCE MODEL (TAM)

2019 ◽  
Vol 7 (1) ◽  
pp. 310-315
Author(s):  
Gwyneth Ka Yee Lee
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Control Group ◽  
Contributing Factors ◽  
Engineering Discipline ◽  
External Variables ◽  
Acceptance Model ◽  
Experimental Group

Purpose: To keep abreast of the latest educational development and to enrich student learning. Vocational Training Council (VTC) is among the first vocational institutions in Hong Kong for piloting massive open online courses (MOOCs) (which are being referred as mini-MOOCs here) on various disciplines. This paper examines one of the mini-MOOCs we have developed for the Engineering discipline. The aim of this study is to gather information and investigate the influencing factors that contribute to the success and attrition in the Engineering mini-MOOC. Methodology: These insights come from the empirical study conducted in a mini-MOOC titled “Unauthorized Buildings Works” (UBWs), which was being implemented as a blended activity in the module. Two groups of second-year students from the higher diploma in construction were selected to participate in non-MOOC (i.e., the control group) and MOOC (i.e., the experimental group) classes over two years. The mini-MOOC subjects were invited to complete questionnaires and attend a focus group interview upon completion of the activity. Main Findings: The analysis yielded striking results, which led to a discussion on the contributing factors to success and attrition in the Engineering mini-MOOC using Technology Acceptance Model (TAM). Implications: Due to limited resources in the research, the methods of data collection were different over two years of study. An implication of this is that an enhanced methodology is needed to determine the academic effectiveness of the mini-MOOC and achieve the consistency of the findings. Novelty/Originality: The present study contributes to significant findings in how TAM factors and external variables influenced the usage of mini-MOOC from the perspectives of both learners and teachers.

Application Of Technology Acceptance Model Of Unified Payment Interface Services Adoption In Mysuru City: An Exploratory Study

2019 ◽  
Vol 118 (6) ◽  
pp. 25-35
Author(s):  
Vinay S
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Banking Sector ◽  
Primary Data ◽  
Equation Modeling ◽  
Security Issues ◽  
Acceptance Model ◽  
Structured Questionnaire

Continuous development of technological innovations especially in the banking sector have stirred competition which has changed the way businesses operate resulting in the introduction of Unified Interface Payment (UPI) services. This study was conducted in order to analyse the adoption of UPI services through Technology Acceptance Model (TAM) in Mysuru. Objectives of study were framed to determine the demographic factors that influence the practices of UPI by the customers, to examine the role of banks in integrating UPI services and products and to assess the various security issues affecting the usage of UPI services by Mysuru customers. Based on these objectives a structured questionnaire was prepared and primary data was collected from 165 respondents. Data was analysed making use of SPSS and other models namely Structural Equation Modeling with Analysis of Moment Structures (AMOS) Software. Finally the researchers identifies that there is a need for convergence of customer’s preference for safe and easy banking transactions. This study revealed that the customer’s model have to be well integrated for progress in UPI operations.

Analyzing Factors Influencing Behavior Intention to Use Snapchat and Instagram Stories

2017 ◽  
Vol 4 (2) ◽  
pp. 75-81 ◽  
Author(s):  
Vincent Valiant Coa ◽  
Johan Setiawan
Keyword(s):  
Structural Equation Modeling ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Social Presence ◽  
Structural Equation ◽  
Equation Modeling ◽  
Intention To Use ◽  
Generation Z ◽  
Acceptance Model ◽  
Behavioral Intention To Use

Snapchat, and Instagram are two social networks which recently gain their users after adopting such a feature called "Story" which allows a certain post to be disappeared after a certain time. This research takes up this technology trends analyzing the factors that probably affect the behavioral intention to use Snapchat and Instagram stories among generation Z. Factors are analyzed using Structural Equation Modeling, with basis model and variables from Technology Acceptance Model. Data collection was targeted to finished within 1 week using online questionnaire with respondent from Jakarta and Tangerang for 100 respondent that are using both Snapchat stories and Instagram Stories. There are two tools researcher usually use to analyze Structural Equation Modeling: SPSS AMOS and LISREL. In this research, researchers choose AMOS. From six hypothesis proposed for Snapchat analysis, four hypothesis is accepted, while the other two are rejected. Meanwhile, on Instagram Stories analysis, five hypothesis is accepted and one hypothesis is rejected. This study finds out the Social Presence is an exogenous variable which has a major role in affecting other variables. While Perceived Enjoyment influenced the behavioral intention to use Snapchat and Instagram Stories the most. Index Terms—Structural Equation Modeling, Technology Acceptance Model, influence, generation Z, Snapchat, Instagram REFERENCES [1] L. Chin and Z. Ahmad, "Perceived Enjoyment and Malaysian Consumers’ Intention to Use a Single Platform EPayment", SHS Web of Conferences, vol. 18, 2015. [2] M. Ariff, T. Shan, N. Zakuan, N. Ishak and M. Wahi, "Examining Users' E-Satisfaction in the Usage of Social Networking Sites; Contribution from Utilitarian and Hedonic Information Systems", IOP Conference Series: Materials Science and Engineering, vol. 58, 2014. [3] K. Hassanein and M. Head, "Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping", International Journal of HumanComputer Studies, vol. 65, no. 8, pp. 689-708, 2007. [4] P. Surendran, "Technology Acceptance Model: A Survey of Literature", 2012. [5] F. Davis, "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology", MIS Quarterly, vol. 13, no. 3, p. 319, 1989

scholarly journals Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior

2021 ◽  
Author(s):  
Svenja Mohr ◽  
Rainer Kühl
Keyword(s):  
Artificial Intelligence ◽  
Theory Of Planned Behavior ◽  
Technology Acceptance ◽  
Planned Behavior ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Perceived Behavioral Control ◽  
Labor Costs ◽  
Online Questionnaire ◽  
Acceptance Model

AbstractThe use of Artificial Intelligence (AI) in agriculture is expected to yield advantages such as savings in production resources, labor costs, and working hours as well as a reduction in soil compaction. However, the economic and ecological benefits of AI systems for agriculture can only be realized if farmers are willing to use them. This study applies the technology acceptance model (TAM) of Davis (1989) and the theory of planned behavior (TPB) of Ajzen (1991) to investigate which behavioral factors are influencing the acceptance of AI in agriculture. The composite model is extended by two additional factors, expectation of property rights over business data and personal innovativeness. A structural equation analysis is used to determine the importance of factors influencing the acceptance of AI systems in agriculture. For this purpose, 84 farmers were surveyed with a letter or an online questionnaire. Results show that the perceived behavioral control has the greatest influence on acceptance, followed by farmers’ personal attitude towards AI systems in agriculture. The modelled relationships explain 59% of the total variance in acceptance. Several options and implications on how to increase the acceptance of AI systems in agriculture are discussed.

scholarly journals Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

2021 ◽  
Vol 13 (10) ◽  
pp. 5471
Author(s):  
Chuan-Yu Mo ◽  
Te-Hsin Hsieh ◽  
Chien-Liang Lin ◽  
Yuan Qin Jin ◽  
Yu-Sheng Su
Keyword(s):  
Online Learning ◽  
Technology Acceptance ◽  
Family Support ◽  
Technology Acceptance Model ◽  
Online Teaching ◽  
Ease Of Use ◽  
Critical Factors ◽  
Factors Affecting ◽  
E Learning ◽  
Acceptance Model

In order to enable online learning to continue developing when the COVID-19 pandemic passes, this study aimed to identify the critical factors that affected the use of e-learning by university students during the pandemic. These critical factors will help to increase the efficiency of future development and deployment of online learning systems. Through a literature review, this study employed the technology acceptance model, social support, and task–technology fit as the theoretical basis to establish the framework of the online learning environment with regards to the technology acceptance model in the context of emergency management. A questionnaire survey was administered to students in universities that had implemented online teaching during the pandemic, and 552 valid responses were collected. The survey explored the factors affecting the willingness of higher education institution students to continue using online learning, and the following conclusions were drawn. (1) The easier an online learning platform was to navigate, the better it was perceived by the students, and thus the students were more willing to use it. (2) Ease of use and usefulness were associated with the teachers’ choice of platform and their ability to achieve a satisfactory fit between the course design and platform navigation, which thereby affected the students’ learning outcomes and attitude towards use. (3) The positive attitude of teachers towards teaching increased the students’ perceived ease of use of online learning. (4) During the pandemic, family support—a major support for teachers in online teaching—enhanced teachers’ attitudes towards, and willingness to provide, online teaching. A high level of support showed that the parents urged the students to learn and complete online learning tasks as instructed by the teachers, implying that family support could affect the students’ habits towards, adaptation to, and identification of online learning. The study results provide insights into the factors affecting the willingness of teachers and students to continue using e-learning platforms.

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