Using an improved association rules mining optimization algorithm in web-based mobile-learning system

2009 ◽  
Author(s):  
Yin Huang ◽  
Jianhua Chen ◽  
Shaojun Xiong
Keyword(s):  
Mobile Learning ◽  
Association Rules ◽  
Optimization Algorithm ◽  
Learning System ◽  
Web Based ◽  
Association Rules Mining ◽  
Mobile Learning System

scholarly journals Telepresence and Interactivity in Mobile Learning System: Its Relation with Open Innovation

2021 ◽  
Vol 7 (1) ◽  
pp. 78
Author(s):  
Na Wei ◽  
ZhongWu Li
Keyword(s):  
Technology Acceptance ◽  
Mobile Learning ◽  
Open Innovation ◽  
Online Survey ◽  
Mediating Effect ◽  
Learning System ◽  
Equation Modeling ◽  
Flow Experience ◽  
Mobile Learning System ◽  
System Characteristics

Mobile learning applications enable people to spend fragmented time to improve their knowledge and competitiveness. Enterprises aim to design innovative applications and create a new learning mode for the public, and the open innovation strategies may help companies achieve their goals. In the current study, the English learning application “LAIX” was investigated, and an online survey was used to obtain data from 289 university students in Guangzhou. This study combines the technology acceptance model (TAM) with flow theory (FT), investigating the psychological experience factors and the system characteristics that influence users’ behavior intentions. The exploration of perceptual variables will promote the establishment of an open innovation model of mobile learning applications. The aim of the study was to establish a theoretical framework to more deeply explore users’ intentions in mobile learning applications. Structural equation modeling (SEM) was used to help measure the relationship between variables and determine the model fit. This research reveals that telepresence is the most important variable that impacts user intentions to use mobile learning applications. In addition, the mediating effect of the flow experience was tested. Telepresence and interactivity indirectly influence behavioral intention through the variable “flow”. Users appear to be more concerned with the flow experience, which shows the highest correlation with intention to use the application. This study may assist companies to innovate system characteristics and improve customers’ user experience, for instance, by integrating virtual reality (VR) technology into the mobile learning system to improve their open innovation level and market popularity.

Devised Mobile Learning System Based on Campus

2011 ◽  
Vol 271-273 ◽  
pp. 1160-1163
Author(s):  
Yan Xin Hu
Keyword(s):  
Mobile Learning ◽  
Learning System ◽  
Learning Content ◽  
Function Module ◽  
Basic Features ◽  
Mobile Learning System

Introduced the mobile learning content, analyzed the basic features of mobile learning, designed mobile leaening system based on campus, and each function module of mobile learning system.

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