Design Ethnography Research Papers - Academia.edu (original) (raw)
A basic premise underpinning the new research paradigm presented in this thesis and demonstrated by the FLAX project (Flexible Language Acquisition flax.nzdl.org), is that open data-driven language learning systems design as an approach... more
A basic premise underpinning the new research paradigm presented in this thesis and demonstrated by the FLAX project (Flexible Language Acquisition flax.nzdl.org), is that open data-driven language learning systems design as an approach is learner-centric and operates with the interface to the learner. Whether the learner is operating fully online in non-formal or informal learning mode or in a blended modality that is based both within and beyond the formal language classroom, this approach requires that the tools and interfaces, and indeed the corpora, be openly accessible and remixable for development or adaptation to meet this specific learner requirement. This method is different from existing data-driven learning (DDL) approaches which assume specialised knowledge or experience with DDL tools, interfaces and strategies, operating on mostly inaccessible corpora in terms of cost or design, or alternatively assuming training to, hopefully, compensate for this lack of knowledge and experience.
From a research and development (R&D) standpoint, the paradigm presented here also operates with the interface to knowledge organisations (universities, libraries, archives) and researchers who are engaging with open educational practices to push at the parameters of open policy for the non-commercial reuse and remix of authentic research and pedagogic content that is increasingly abundant in digital open access format for text and data-mining (TDM) purposes. This open access content is highly relevant to learning features of specialist varieties of English from across the academy but is otherwise off limits for development into proprietary learning materials by the commercial education publishing industry. Indeed, the open corpus development work presented in this thesis would not have been possible had it not been for the campaigners for copyright reform, the Internet activists, the open policy makers, the open-source software developers, and the advocates for open access, open data and open education that have made these resources available for reuse and remix.
This paradigm leads down several paths, including research into understanding how users actually perceive, appropriate and use the approach based on the open tools and resources provided. This inquiry informs their design and development, in an R&D process that is presented here through the methodological lens of design-based research and design ethnography. This approach will be fundamentally different than if we assume the user is actually a DDL or linguistics expert or that such an expert will be the learner's interface to the system, by preparing output for the learner to experience and learn from. This approach will also be necessarily different than if we assume the user is always a formally registered student at a university with access to English for Academic Purposes (EAP) support that may or may not offer DDL or linguistics expertise for learning the language features of specific discourse communities from across the academy.
The assumption behind this new paradigm that the right tools and resources can allow the end-learner to drive the processes autonomously is fundamentally revolutionary. This premise goes to the original contribution to knowledge of this thesis, but also challenges and directs researchers and practitioners in the field to consider and take up this new direction with open data-driven language learning systems design for applications that can be scaled in higher education to meet the increasing numbers of learners who are coming online.
The focus on domain-specific terminology learning support via data-driven approaches is of course also decidedly different from the current EAP paradigm which in mainstream practice has been steadily evolving away from its roots in English for Specific Purposes (ESP), domain specificity and DDL processes towards the generic skills and knowledge programs currently in vogue that are arguably being steered by generic EAP course book publications from the commercial education publishing industry. Thus, this is also a new paradigm based on DDL approaches, driving domain-specific terminology learning support for EAP across formal, non-formal and informal learning modalities in higher education. It will transform, potentially, the focus of DDL systems design developments in language support and learning in general toward the non-specialist end-learner, but also hopefully help re-establish the centrality of language specificity to the field of EAP.
The new paradigm is necessarily rooted in greater inter- or multi-disciplinarity. Given the goal of facilitating, in particular, the increasing number of learners who are coming online, and users of large-scale MOOC platforms who are trying to function in domain-specific subject areas that are invariably offered in the English language, the approach requires collaboration and cooperation among platform providers, subject academics and instructors, educational technologists, software developers, educational researchers, EAP practitioners, linguists with expertise in corpus-based and DDL approaches, and policy makers in knowledge organisations (libraries, universities, archives).
This doctoral thesis presents three studies in collaboration with the open source FLAX project. This research makes an original contribution to the fields of language education and educational technology by mobilising knowledge from computer science, corpus linguistics and open education, and proposes a new paradigm for open data-driven language learning systems design in higher education. Furthermore, the research presented in this thesis uncovers and engages with an infrastructure of open educational practices (OEP) that push at the parameters of policy for the reuse of open access research and pedagogic content in the design, development, distribution, adoption and evaluation of data-driven language learning systems.