Exploring the impact of integrated design on employee learning engagement in the ubiquitous learning context: A deep learning-based hybrid multistage approach

被引:0
|
作者
机构
[1] [1,SHANG, Dawei
[2] ZHANG, Caiyi
[3] JIN, Li
基金
中国博士后科学基金;
关键词
Deep neural networks;
D O I
10.1016/j.chb.2024.108468
中图分类号
学科分类号
摘要
Learning engagement has received the attention of academics and practitioners; however, studies on employee learning engagement are limited. Based on an integrated hardware-software-value-design perspective and domain-specific innovativeness theory, we developed and tested a theoretical framework using a novel and hybrid multistage approach combining a partial least squares (PLS) structural equation model (SEM) and artificial neural networks from deep learning. We used multigroup analysis (PLS-MGA-ANN), which examines key integrated design elements and domain-specific innovativeness drivers of employee learning engagement in ubiquitous learning context. According to a sample of learners’ responses, the linear PLS-SEM results demonstrated that (a) integrating design elements, including perceived compatibility, familiarity, value, and user interface design, had a direct impact on domain-specific innovativeness; (b) domain-specific innovativeness had a direct impact on employee learning engagement and played a mediating role in the relationship between integrating design elements and employee learning engagement; and (c) copresence moderated the relationships between domain-specific innovativeness and employee learning engagement. Furthermore, through the evaluation of nonlinear models of the neural network, perceived compatibility and value revealed nonlinear average importance. Practical and theoretical implications are discussed. © 2024
引用
收藏
相关论文
共 50 条
  • [1] Deep Learning-Based Student Engagement Classification in Online Learning
    Mandia, Sandeep
    Singh, Kuldeep
    Mitharwal, Rajendra
    International Journal of Pattern Recognition and Artificial Intelligence, 2024, 38 (15)
  • [2] The design and implementation of a meaningful learning-based evaluation method for ubiquitous learning
    Huang, Yueh-Min
    Chiu, Po-Sheng
    Liu, Tzu-Chien
    Chen, Tzung-Shi
    COMPUTERS & EDUCATION, 2011, 57 (04) : 2291 - 2302
  • [3] Employee's ubiquitous learning engagement: Impact of innovativeness-oriented learning system design factors and the mediating role of imagery
    Shang, Dawei
    Wu, Weiwei
    TELEMATICS AND INFORMATICS, 2019, 41 : 156 - 167
  • [4] Deep Learning-Based Design of Uplink Integrated Sensing and Communication
    Qi, Qiao
    Chen, Xiaoming
    Zhong, Caijun
    Yuen, Chau
    Zhang, Zhaoyang
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (09) : 10639 - 10652
  • [5] A Hybrid Deep Learning-Based Approach for Brain Tumor Classification
    Raza, Asaf
    Ayub, Huma
    Khan, Javed Ali
    Ahmad, Ijaz
    Salama, Ahmed S.
    Daradkeh, Yousef Ibrahim
    Javeed, Danish
    Rehman, Ateeq Ur
    Hamam, Habib
    ELECTRONICS, 2022, 11 (07)
  • [6] The effectiveness of the meaningful learning-based evaluation for different achieving students in a ubiquitous learning context
    Huang, Yueh-Min
    Chiu, Po-Sheng
    COMPUTERS & EDUCATION, 2015, 87 : 243 - 253
  • [7] A deep learning-based approach for the inverse design of the Helmholtz resonators
    Dogra, Sourabh
    Singh, Lokendra
    Nigam, Aditya
    Gupta, Arpan
    MATERIALS TODAY COMMUNICATIONS, 2023, 37
  • [8] Deep Learning-based Hybrid Fuzz Testing
    Gao F.-J.
    Wang Y.
    Situ L.-Y.
    Wang L.-Z.
    Ruan Jian Xue Bao/Journal of Software, 2021, 32 (04): : 988 - 1005
  • [9] A deep learning-based hybrid approach for the solution of multiphysics problems in electrosurgery
    Han, Zhongqing
    Rahul
    De, Suvranu
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2019, 357
  • [10] hybrid deep learning-based approach for rolling bearing fault prognostics
    Neto, Domicio
    Petrella, Lorena
    Henriques, Jorge
    Gil, Paulo
    Cardoso, Alberto
    IFAC PAPERSONLINE, 2023, 56 (02): : 6588 - +