With the development of technology-enhanced language learning, there have been increasingly more studies on mobile-Assisted vocabulary learning with multimedia annotations. However, little research has been conducted to explore working adults use of multimedia annotations in authentic mobile learning environments, investigate their perceptions of diverse types of multimedia annotations, or discuss the factors that may influence their perceptions of multimedia annotations. To fill in these research gaps, the researchers of this project developed a multimedia-Annotation-enhanced vocabulary learning app, iWORDS, and invited 24 working adults in Hong Kong to learn vocabulary using this app. After experiencing mobile-Assisted vocabulary learning with four types of multimedia annotations (i.e., the textual, the pictorial, the text-plus-GIF and the text-plus-video annotations), the participants were interviewed about their perceptions and preferences. The results indicated that working adults used textual annotations most frequently but showed strongest preference for text-plus-GIF annotations. Four factors, content quality, attractiveness, efficiency and cognitive stimuli, played important roles in influencing working adults preferences and perceptions of multimedia annotations. Based on the research results, we proposed some suggestions for the development, selection and usage of multimedia annotations in mobile-Assisted vocabulary learning.
|Number of pages||16|
|Journal||International Journal of Mobile Learning and Organisation|
|Early online date||22 Jul 2020|
|Publication status||Published - 2020|
Bibliographical noteFunding Information:
This research received grants from the Standing Committee on Language Education and Research (EDB(LE)/P&R/EL/175/2), the Education Bureau of the Hong Kong Special Administrative Region, the Funding Support to ECS Proposal Rated 3.5 (RG16/2018-2019R), Internal Research Fund (RG 1/2019-2020R) and the Internal Research Grant (RG93/2018-2019R), The Education University of Hong Kong.
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- Computer-Assisted language learning
- Mobile-Assisted learning
- Multimedia annotations
- Multimedia learning
- Technology-enhanced learning
- Vocabulary learning