Empowering Vocational Training for Middle-Aged, Elderly, and Low-Educated Individuals: A Design Approach for Entertainment-Based Learning.
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| Title: | Empowering Vocational Training for Middle-Aged, Elderly, and Low-Educated Individuals: A Design Approach for Entertainment-Based Learning. |
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| Authors: | Fan, Jianxiong (AUTHOR), Wu, Rouqin (AUTHOR), Tang, Chaolan (AUTHOR), Yang, Xian (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Mar2026, Vol. 42 Issue 6, p4025-4049. 25p. |
| Subjects: | Occupational training, Educational entertainment, Adult students, TikTok (Web resource), Hazardous substance transportation, Education of older people |
| Abstract: | This study addresses the challenges of vocational training for Middle-aged, Elderly, and Low-educated Individuals (MELI) in hazardous materials transport. We developed an entertainment-based learning approach using TikTok-style short videos to engage this demographic. A customized training app was created, and over 300 videos were developed for a six-month program with 500+ participants. Using a TPB-TAM integrated framework, we analyzed 333 responses with Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings include: Behavioral attitude (BA) has a significant impact on behavioral intentions (BI); Subjective norms (SN) significantly influence BI through perceived ease of use (PEOU) and perceived usefulness (PU); PEOU significantly influences BI through BA and PU; and PU not only directly influences BI but also significantly impacts BI through BA. This study provides design guidelines for adapting social media formats to vocational training and enhancing engagement for underserved populations. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | This study addresses the challenges of vocational training for Middle-aged, Elderly, and Low-educated Individuals (MELI) in hazardous materials transport. We developed an entertainment-based learning approach using TikTok-style short videos to engage this demographic. A customized training app was created, and over 300 videos were developed for a six-month program with 500+ participants. Using a TPB-TAM integrated framework, we analyzed 333 responses with Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings include: Behavioral attitude (BA) has a significant impact on behavioral intentions (BI); Subjective norms (SN) significantly influence BI through perceived ease of use (PEOU) and perceived usefulness (PU); PEOU significantly influences BI through BA and PU; and PU not only directly influences BI but also significantly impacts BI through BA. This study provides design guidelines for adapting social media formats to vocational training and enhancing engagement for underserved populations. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10447318 |
| DOI: | 10.1080/10447318.2025.2536624 |
