Debopriyo Roy
ABSTRACT
Based on the fundamentals of content and language integrated learning (CLIL), this article provides a holistic overview of how different technological applications such as Google Maps, social network analysis (SNA), and in general, crowdsourcing of spatial and location-specific data could help identify poverty, and local socio-economic and lifestyle-oriented problems, and trigger a discussion about community decision making. Such use of technology could potentially help make a convincing case for the type of poverty; including exact issues in the area, proximity to resource hubs, lack of basic facilities, and employment and so on. The primary focus in this article is on how content language integrated learning (CLIL) combines content areas such as mechanism and technology for poverty identification and analysis on the way to learning the target language. Use of such technological applications in a foreign language-learning course for policy decision-making and community engagement is rather unique. We need for students to have a rich experience with different combinations of text-graphics-video modality including hands-on engagement, and language acquisition is expected to happen as a result. Technical communication could be an important focus for such courses with report writing, feasibility and recommendation studies, email communication, writing commentaries, chats, text captions, interviewing etc. With such use of technology and documentation, the aim is to empower students in revitalization efforts in the community.
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Index Terms
- A Model for Language Learning with Crowdsourcing and Social Network Analysis for Community Decision-Making
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