MyCLOUD is a mobile- and cloud-based seamless language learning approach with the aim of nurturing a social network-mediated learning community for young learners of Chinese as a second language. The intention is to sustain a language learning environment for the learners to utilize Chinese language in their day-to-day life through an extensive period of creation and sharing of social media and online interactions in the target language. In this paper, we concentrate upon exploring corpus-based analysis with a particular interest in determining the patterns of vocabulary usage, as vocabulary competency is regarded by scholars as an indicator of language competency. By facilitating the activities over a period of 13 months, we observed that the students gradually established their habit-of-mind in autonomously making meaning through interacting with their living spaces. That resulted in the utilization of richer vocabulary and the application of the language, particularly the use of significantly more “less frequent words” in the informal learning spaces. In the light of our findings, we stretch the theoretical explications of situated learning and authentic learning by connecting them with the students' intentionality in learning, with the “joint mediation” of the contextual affordances (the triggers for meaning making), social media network (to give students the sense of "communication with a purpose") and the their handhelds (the tool for artifact creation and a reminder of their involvements in MyCLOUD) to sustain their intentionality and therefore the cumulative growth of their language competences.
|Publication status||Published - Nov 2015|
CitationWong, L.-H., Chai, C. S., King, R. B., & Liu, M. (2015, November). Implications of students’ vocabulary growth in a seamless language learning environment mediated by handhelds and social media. Paper presented at the 23rd International Conference on Computers in Education (ICCE 2015): Transforming education in the big data era, The First World Hotel, Hangzhou, China.
- Seamless language learning
- Mobile-assisted vocabulary learning
- Contextual affordances
- Corpus analysis
- Learning analytics