How does online social interaction promote students’ continuous learning intentions?

Zhang, Shunan; Che, ShaoPeng; Nan, Dongyan; Kim, Jang Hyun

doi:10.3389/fpsyg.2023.1098110

Cited by 12 publications

(7 citation statements)

References 62 publications

(59 reference statements)

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“…Performance expectations was measured using three items taken from Aronson and Carlsmith (1962), which includes statements such as "I think using ChatGPT will help me solve the problem better. " The reliability of this scale has been previously confirmed (Nan et al, 2022;Zhang et al, 2023a).…”

Section: Performance Expectations (Cronbach's α = 0908)mentioning

confidence: 55%

Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior

Zhang,

Zhao,

Zhou

et al. 2024

Int J Educ Technol High Educ

Self Cite

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Although previous studies have highlighted the problematic artificial intelligence (AI) usage behaviors in educational contexts, such as overreliance on AI, no study has explored the antecedents and potential consequences that contribute to this problem. Therefore, this study investigates the causes and consequences of AI dependency using ChatGPT as an example. Using the Interaction of the Person-Affect-Cognition-Execution (I-PACE) model, this study explores the internal associations between academic self-efficacy, academic stress, performance expectations, and AI dependency. It also identifies the negative consequences of AI dependency. Analysis of data from 300 university students revealed that the relationship between academic self-efficacy and AI dependency was mediated by academic stress and performance expectations. The top five negative effects of AI dependency include increased laziness, the spread of misinformation, a lower level of creativity, and reduced critical and independent thinking. The findings provide explanations and solutions to mitigate the negative effects of AI dependency.

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Section: Performance Expectations (Cronbach's α = 0908)mentioning

confidence: 55%

Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior

Zhang,

Zhao,

Zhou

et al. 2024

Int J Educ Technol High Educ

Self Cite

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“…Historical context videos, another facet of multimedia-enhanced content, offer learners a broader perspective on the socio-cultural and historical backdrop of the literature they are translating. Such contextual understanding is paramount when translating ancient texts, as it provides insights into the author's intent, the cultural nuances, and the idiomatic expressions of the time [15]. This holistic approach ensures that translations are not just linguistically accurate but also culturally and historically faithful.…”

Section: Literature Reviewmentioning

confidence: 99%

Multimedia Integration in the Teaching of Ancient Chinese Literature Translation

Xiao

2024

Advances in Transdisciplinary Engineering

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In the realms of education and translation, the profound historical, cultural, and linguistic complexities of ancient Chinese literature constitute a one-of-a-kind challenge. The purpose of this research was to investigate the possible advantages of incorporating multimedia components into the instruction of these traditional classics as well as their translations. This study used a quantitative technique to evaluate the influence that multimedia-enhanced content has on translation ability, understanding, and enjoyment of literary situations. The sample for this research was comprised of students who were enrolled in tertiary education programs. The findings demonstrated a significant increase in the number of participants who interacted with information that was enhanced by multimedia, demonstrating the power of this method as a teaching instrument. However, the research also highlights how important it is to integrate multimedia in a strategic manner, arguing in favor of a strategy that strikes a healthy balance between employing conventional research techniques and modern digital technologies. This research, in its core, gives insights into the transformational potential of multimedia in reviving and improving the educational experience of translating ancient Chinese literature.

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“…We designed a survey based on participants' single immersive experience with the MDTM platform to assess their initial reactions and intentions to use it, thereby inferring their likelihood of continued use [86,87]. The empirical case selected for this study is the IES Goya Museum on the Spatial.io platform (Figure 2).…”

Section: Questionnaire Developmentmentioning

confidence: 99%

A Study of the Key Factors Influencing Young Users’ Continued Use of the Digital Twin-Enhanced Metaverse Museum

Wu,

Gao,

Lee

et al. 2024

Electronics

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This research investigates the key factors influencing young users’ continuous use of digital twin-enhanced metaverse museums. Attracting young users to use the metaverse museum for a more extended period consistently contributes to increasing the frequency of visits and content usage and promoting its sustainable development and innovation. However, there is a lack of research on the key factors influencing young users’ continuous use of digital twin-enhanced metaverse museums, which makes the theoretical basis for the in-depth design of user motivation for metaverse museums insufficient. This study constructed a model covering four dimensions—hedonic, utilitarian, social, and technological—based on communication’s uses and gratification theory (UGT). It was validated in the Metaverse Digital Twin Museum (MDTM). Using Spatial.io’s IES Goya Museum as the experimental platform, the research team conducted Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4.0 software through experiments and surveys with 307 participants aged 18 to 30. Quantitative analyses revealed that MDTM’s hedonic gratification (hope), utilitarian gratification (information and self-presentation), social gratification (social interaction and social presence), and technological gratification (immersion) significantly influenced young users’ continued intention. The findings reveal that these six key factors can be the focus of MDTM’s future development to enhance user experience. This study fills the gap in applying UGT in the field of metaverse museums, provides metaverse museum managers with references to the key factors that can prolong users’ continued intention to use, and points out the key factors that need further attention in future research and practice.

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How does online social interaction promote students’ continuous learning intentions?

Cited by 12 publications

References 62 publications

Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior

Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior

Multimedia Integration in the Teaching of Ancient Chinese Literature Translation

A Study of the Key Factors Influencing Young Users’ Continued Use of the Digital Twin-Enhanced Metaverse Museum

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