Reflections on remixing open access content into open educational resources: A new paradigm for sustainable data-driven language learning systems design in higher education

This chapter presents a new paradigm for sustainable data – driven language learning systems design in higher education that draws on qualitative reflections spanning a decade (2012–2022) with stakeholders from an ongoing global research study with the FLAX (Flexible Language Acquisition) and F-Lingo projects at the University of Waikato in Aotearoa New Zealand (Fitzgerald (2019) A new paradigm for open data-driven language learning systems design in higher education; König et al. (2022)SmartCALL). Design considerations are presented for remixing domain specific open access content into Open Educational Resources (OER) for academic English language provision across formal and non-formal higher education contexts. Primary stake holders in the research collaboration include the following three groups: (1) Knowledge organisations that provide open access to academic content—libraries and archives, including the British Library and the Oxford Text Archive, universities in collaboration with MOOC providers and the CORE (COnnecting REpositories) open access aggregation service at the UK Open University; (2) Researchers who mine and remix academic content into corpora and open data-driven language learning systems—converging from the fields of open education, computer science and applied corpus linguistics; (3) Knowledge users who re-use and remix academic content into OER—English for Academic Purposes (EAP) practitioners from university language centres. Automated content analysis was carried out on a corpus of interview and focus discussion data with the three stakeholder groups in this research. We discuss themes arising from the research data that reflect the different stakeholders’ experiences of remixing open access research content that has been produced within the academy for re-use as open educational content for teaching and learning features of academic language within open data-driven language learning systems. These open learning systems have been specifically designed to scale with OER expansion and traction in mind for their sustainable uptake both within and beyond the brick and mortar of the traditional university. The new paradigm presented in this chapter challenges, as the OER movement must, established business models and deeply embedded cultural or institutional norms that present obstacles to OERexpansion and traction and the sustainability of the movement. One persistent challenge concerns the lack of open education policy across the higher education sector for full open access (for use, modification, adaptation) via Creative Commons licensing to content produced within the academy. Thus, while this research has theoretical and practical implications in applied linguistics, computer science, language teaching and learning and open education, more generally, it also has significant cultural, business model and policy implications for higher education

Generation Y’s Behavioural Usage of Small Businesses’ Retail Websites in Canada

This research delves into the factors that influence Generation Y’s usage of Canadian small businesses’ retail websites in order to suggest how they can be attracted to use them more. Based on the Use of Technology Two (UTAUT2) theory, questionnaire survey and semi-structured interviews revealed linkages between Behavioural Intention, Habit, Facilitating Conditions and Use Behaviour with demographic variables moderating some relationships. Improving the website designs and social media marketing can entice Generation Y consumers

EUSN 2021 Book of Abstracts, Fifth European Conference on Social Networks

Book of abstract of the fifth European conference on Social Networks EUSN 202

BK 10-15:

Over the years 2010-2015 TU Delft's Faculty of Architecture and the Built Environment (in Dutch: Bouwkunde or BK) made good progress with its research by: merging the Architecture faculty and the Built Environment research institute; streamlining its PhD research by setting-up a graduate school for doctoral education; co-founding an institute for metropolitan solutions in Amsterdam together with MIT and Wageningen University (targeted yearly budget: 25 M€); implementing good research management; increasing the scientific output; managing a project portfolio with a yearly income of 1.5 M€ in research grants, 5 M€ in contract research and up to 2 M€ in other external funding; ranking 3rd in the QS World University Rankings by Subject 2015 - Architecture / Built Environment. Presented in this book is an overview of research data and policies, together with a selection of our finest research results: activities, organisations, facilities/assets, output, including indications of their use and recognition. Now it is not the time to become complacent. Instead, we should look ahead to face new academic and societal challenges and opportunities, knowing we can always do better

Spatio-temporal clustering in application

The importance of machine learning methods in the data analysis of both academic research and industry applications has advanced rapidly in recent years. This thesis will investigate how a method of unsupervised machine learning known as clustering can be employed to analyse spatial and spatio-temporal data from different fields of application. Spatio-temporal data present a particular challenge. In spatial contexts, the notion of dependency among geographically close elements needs to be considered when analysing the geographic distance as well as other spatial components. The temporal dimension of the data makes traditional dissimilarity metrics unsuitable due to the sequential ordering of data points. For this reason, this thesis will present ways of overcoming the shortcomings in existing methodologies when applied to these data types. By doing so, it will contribute to the literature on clustering through innovative extensions, adaptations, and considerations. The flexibility of clustering will be demonstrated in three different application contexts in health, finance, and marketing. As such, this thesis will also contribute to the academic literature in these areas and offer valuable insights into applicable machine learning methodology for practitioners

Midterm evaluation Research 2016-2018:

The research of TU Delft’s Faculty of Architecture and the Built Environment (Faculteit Bouwkunde) covers the full spectrum of design, engineering, planning, and management of the built environment. Its research portfolio comprises the research that is conducted by four departments: Architecture Architectural Engineering + Technology (AE+T) Management in the Built Environment (MBE) Urbanism The faculty’s research focusses specifically at improving the design and performance of buildings, districts, cities and regions in order to better meet the requirements and expectations of their users and communities. From that perspective, much of the research that is conducted can be understood as applied science, appealing to the curiosity and the needs of other researchers, practitioners and the broader public alike. The research is a blend of humanities, social and engineering sciences. The humanities are strongest represented in the Architecture department, social sciences in the MBE and Urbanism departments, while the engineering sciences find their strongest representation in AE+T