Huang Yan, Xu Wei, Sukjairungwattana Paisan, Yu Zhonggen
School of Foreign Languages, East China Normal University, 200241, Shanghai City, China.
School of English Language, Zhejiang Yuexiu University, Shaoxing City, 312000, Zhejiang Province, China.
Heliyon. 2024 Mar 17;10(6):e28104. doi: 10.1016/j.heliyon.2024.e28104. eCollection 2024 Mar 30.
Confronted with the unprecedented COVID-19 pandemic, millions of learners have received, are receiving, or will receive multimodal language learning education. This study aims to explore the relationships between various factors influencing learners' continuance intention by proposing an innovative multiple linear regression model in multimodal language learning education. Participants were randomly recruited (N = 334) in China who had received multimodal language learning education by combining Massive Open Online Courses, Rain Classroom, and WeChat. The research instrument, a comprehensive questionnaire, was sent through the online system named Questionnaire Star developed by technical experts. A multiple linear regression analysis was adopted to test the proposed hypotheses and fit the research model. This study confirms the relationships between the Technology Acceptance Model-inclusive constructs such as perceived ease of use, perceived usefulness, attitudes toward multimodal language learning education, and continuance intention of participating in multimodal language learning education. The Technology Acceptance Model is also associated with other constructs, e.g. Task-technology fit, Individual-technology fit, Openness, and Reputation of multimodal language learning educational institutes, and personal investment in multimodal language learning education. However, personal investment neither directly nor indirectly predicts continuance intention. Educators and designers could make every effort to improve multimodal language learning education to enhance personal investment and foster its association with continuance intention of learners.
面对前所未有的新冠疫情，数百万学习者已经、正在或将会接受多模态语言学习教育。本研究旨在通过提出一个创新的多模态语言学习教育多元线性回归模型，探索影响学习者持续意愿的各种因素之间的关系。在中国随机招募了334名通过结合大规模开放在线课程、雨课堂和微信接受多模态语言学习教育的参与者。研究工具是一份综合问卷，通过技术专家开发的名为问卷星的在线系统发送。采用多元线性回归分析来检验所提出的假设并拟合研究模型。本研究证实了技术接受模型中包含的构念之间的关系，如感知易用性、感知有用性、对多模态语言学习教育的态度以及参与多模态语言学习教育的持续意愿。技术接受模型还与其他构念相关，例如任务-技术适配、个人-技术适配、开放性以及多模态语言学习教育机构的声誉，以及个人在多模态语言学习教育中的投入。然而，个人投入既不能直接也不能间接预测持续意愿。教育工作者和设计者可以尽一切努力改进多模态语言学习教育，以增加个人投入并促进其与学习者持续意愿的关联。
