We propose a “smart” language learning system for students to acquire domain-specific vocabulary while taking an online course. F-Lingo, a browser plugin, works on top of the FutureLearn MOOC platform to provide learners with opportunities to study the words, phrases, and concepts that are important to the course topic. F-Lingo comprises three components. The Material Gathering component crawls the web pages of the MOOC course the student has chosen, collecting the entire textual content (with some exceptions). The Vocabulary Extraction component identifies domain-specific words, phrases, and concepts, and hyperlinks in the MOOC page to draw the student’s attention to them. Clicking a link displays a dialog window in which lexico-grammatical features, and definitions, of the extracted items can be studied, including illustrations in example sentences retrieved from external resources such as Wikipedia and FLAX. The Progress Tracking component records the clicks that students make on hyperlinks and the time spent in the dialog windows. This allows us to build the student’s vocabulary learning profile under the assumption that the more time the student pays attention to an item, the more worthy the item to be included in a follow-up language activity. These statistical data provide evidence and reasoning in our current and ongoing work on automatically generating personalized language activities and vocabulary tests at the end of the MOOC course. F-Lingo has been made available in three Data Mining courses on the FutureLearn MOOC platform and has been used by 109 learners. This research is ongoing. Future work focuses on automatically generating personalized vocabulary tests and activities based on the student’s click statistics.
This chapter describes the automated FLAX language system (flax.nzdl.org) that extracts salient linguistic features from academic text and presents them in an interface designed for L2 students who are learning academic writing. Typical lexico-grammatical features of any word or phrase, collocations, and lexical bundles are automatically identified and extracted in a corpus; learners can explore them by searching and browsing, and inspect them along with contextual information. This chapter uses a single running example, the PhD abstracts corpus of 9.8 million words derived from the open access Electronic Theses Online Service (EThOS) at the British Library, but the approach is fully automated and can be applied to any collection of English writing. Implications for reusing open access publications for non-commercial educational and research purposes are presented for discussion. Design considerations for developing teaching and learning applications that focus on the rhetorical and lexico-grammatical patterns found in the abstract genre are also discussed.
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This chapter presents the open-source FLAX project (Flexible Language Acquisition, flax.nzdl.org), an automated digital library scheme, which has developed and tested an extraction method that identifies typical lexico-grammatical features of any word or phrase in a corpus for data-driven learning. Here in this study, FLAX will be described and discussed in relation to the reuse of openly licensed content available in the digital commons. Typically, the digital commons involves the creation and distribution of informational resources and technologies that have been designed to stay in the digital commons using various open licenses, including the GNU Public License and the Creative Commons suite of licenses (Wikipedia, 2016; see also the chapter by Stranger-Johannessen, this volume). One of the most widely used informational resources developed by and for the digital commons is Wikipedia. In response to the growing digital commons, we will provide insights into design considerations for the reuse of transcribed video lectures from Massive Open Online Courses (MOOCs) that have been licensed with Creative Commons as Open Educational Resources (OERs). We will demonstrate how OERs can be remixed with open corpora and tools in the FLAX system to support English for Specific Academic Purposes (ESAP) in classroom-based language education contexts. This research arose largely in response to the open education movement having recently gained traction in formal higher education and in the popular press with the advent of the MOOC phenomenon. The OpenCourseWare movement, which began in the late 1990s, preceded MOOCs with the release of free teaching and learning content onto the Internet by 2 well-known universities, most notably the Massachusetts Institute of Technology. Indeed, MOOCs are the latest in a long line of innovations in open and distance education. This chapter also draws attention to the OER movement, where the emphasis on 'open' signifies more than freely available teaching and learning resources for philanthropic purposes (open gratis). Here, we focus on the truly open affordance of flexible and customizable resources that can be retained, revised, repurposed, remixed, and redistributed by multiple stakeholders for educational purposes (open libre). In the present research with the FLAX project, open resources are specifically employed in the design and development of domain-specific language corpora for scaling data-driven learning (DDL, discussed below) approaches across informal MOOCs and formal language learning classrooms. The mainstreaming of open content, including OERs and open access publications, came swiftly on the back of the development of the Creative Commons suite of licenses by copyright lawyer, Larry Lessig, in collaboration with Internet activist and open education advocate, Aaron Swartz. Their collaboration resulted in six Creative Commons licenses that were released in 2002 to retain the copyright of authors for enabling 'Some Rights Reserved' in a movement away from the default 'All Righ...
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