38,952 research outputs found
Challenges in Transcribing Multimodal Data: A Case Study
open2siComputer-mediated communication (CMC) once meant principally text-based communication mediated by computers, but rapid technological advances in recent years have heralded an era of multimodal communication with a growing emphasis on audio and video synchronous interaction. As CMC, in all its variants (text chats, video chats, forums, blogs, SMS, etc.), has become normalized practice in personal and professional lives, educational initiatives, particularly language teaching and learning, are following suit. For researchers interested in exploring learner interactions in complex technology-supported learning environments, new challenges inevitably emerge. This article looks at the challenges of transcribing and representing multimodal data (visual, oral, and textual) when engaging in computer-assisted language learning research. When transcribing and representing such data, the choices made depend very much on the specific research questions addressed, hence in this paper we explore these challenges through discussion of a specific case study where the researchers were seeking to explore the emergence of identity through interaction in an online, multimodal situated space. Given the limited amount of literature addressing the transcription of online multimodal communication, it is felt that this article is a timely contribution to researchers interested in exploring interaction in CMC language and intercultural learning environments.Cited 10 times as of November 2020 including the prestigious
Language Learning Sans Frontiers: A Translanguaging View
L Wei, WYJ Ho - Annual Review of Applied Linguistics, 2018 - cambridge.org
In this article, we present an analytical approach that focuses on how transnational and
translingual learners mobilize their multilingual, multimodal, and multisemiotic repertoires,
as well as their learning and work experiences, as resources in language learning. The …
Cited by 23 Related articles All 11 versionsopenFrancesca, Helm; Melinda DoolyHelm, Francesca; Melinda, Dool
Mashing up Visual Languages and Web Mash-ups
Research on web mashups and visual languages
share an interest in human-centered computing. Both
research communities are concerned with supporting
programming by everyday, technically inexpert users.
Visual programming environments have been a focus for
both communities, and we believe that there is much to
be gained by further discussion between these research
communities. In this paper we explore some connections
between web mashups and visual languages, and try to
identify what each might be able to learn from the other.
Our goal is to establish a framework for a dialog
between the communities, and to promote the exchange
of ideas and our respective understandings of humancentered
computing.published or submitted for publicationis peer reviewe
Social media analytics: a survey of techniques, tools and platforms
This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing
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