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Category: Data

Description: These data files are connected to a study on data-driven learning (DDL) with pedagogical and professional corpora that have been derived from the open content of two Massive Open Online Courses (MOOCs), (Harvard University with edX, and the University of London with Coursera), and one micro-networked course (Harvard Law School with the Berkman Klein Center for Internet and Society), to develop domain-specific language support for non-formal online learning. Most notably, the non-formal learner participants in this longitudinal research and development study had registered for courses in law; they had not signed up as language learners. This speaks volumes to the nature of many informal and non-formal online education offerings, especially MOOCs, the majority of which are offered in English with no or limited language support. In the era of big data and natural language processing, this study presents self-reported learner and teacher perceptions from surveys (N=174) on the interface designs and usability of an automated digital library scheme, FLAX (flax.nzdl.org), that goes beyond simple concordancing for mining salient linguistic features from augmented full-text corpora. These interfaces include advanced affordances for course content search and retrieval that transcend the MOOC platform and Learning Management System (LMS) standard. Furthermore, survey questions derived from an open education research bank from the Hewlett Foundation are reused in this study and presented against a larger dataset from the Hewlett Foundation (N=1921) on the uptake of open educational resources. This study aims to compare respondents’ reported experience of using open DDL resources alongside other learning support techniques for minimally guided instruction in informal and non-formal online learning.