An evaluation of learning analytics to identify exploratory dialogue in online discussions

Abstract

Social learning analytics are concerned with the process of knowledge construction as learners build knowledge together in their social and cultural environments. One of the most important tools employed during this process is language. In this paper we take exploratory dialogue, a joint form of co-reasoning, to be an external indicator that learning is taking place. Using techniques developed within the field of computational linguistics, we build on previous work using cue phrases to identify exploratory dialogue within online discussion. Automatic detection of this type of dialogue is framed as a binary classification task that labels each contribution to an online discussion as exploratory or non-exploratory. We describe the development of a self-training framework that employs discourse features and topical features for classification by integrating both cue-phrase matching and k-nearest neighbour classification. Experiments with a corpus constructed from the archive of a two-day online conference show that our proposed framework outperforms other approaches. A classifier developed using the self-training framework is able to make useful distinctions between the learning dialogue taking place at different times within an online conference as well as between the contributions of individual participants.

Learning in the Wild: Coding Reddit for Learning and Practice

“…We expect this kind of talk to support informal learning because online textual discussions involve active processes of co-reasoning, constant negotiation, and knowledge, idea or resource sharing [11]. In terms of individual learning, we make the assumption that if we find exploratory talk, we expect learning to have occurred.…”

“…In Stage 1, we adopted Ferguson et al's cue phrases framework that includes the following seven categories ( [11]. Ferguson et al's cue phrases were developed and piloted in 2011 in a series of studies that added a qualitative layer to quantitative data through self-trained (automatic) detection and analysis of exploratory and non-exploratory dialogue [10,43].…”

“…al's [11] coding used in the previous two stages. In this third cycle of refinement, we simplified the categories to facilitate coders' use of the codes, standardize multi-coder agreement, and address more specifically the types of exploratory learning dialogue that we were observing on Reddit.…”

Extraction of Relevant Terms and Learning Outcomes from Online Courses

“…Authors in [22] explored the dialogue produced on the forum. Unnecessary dialogue for learning such as discussion is discarded and the technique is able to analyze the exploratory dialogue commonly associated PAPER EXTRACTION OF RELEVANT TERMS AND LEARNING OUTCOMES FROM ONLINE COURSES with the construction of knowledge.…”

MOOCs and Open Education Around the World

“…The European Union as well as the National Research Council of Canada are each separately funding several large research projects to develop personal learning environments by using data (as well as visualizing traces of data) that learners have left behind in their online activities to support their learning (Downes, 2013;Duval, 2011). At the same time, the Open University in the UK is working on discourse analysis techniques to enhance learning (Ferguson Wei, He, & Buckingham Shum, 2013). Moreover, a research group at Carnegie Mellon University is just starting to work on using machine-learning techniques to personalize the learning experience (Spice, 2014).…”