At the nexus of learning and innovation

Abelardo Pardo: Using data for better student feedback

Abelardo Pardo, co-coordinator of the learning analytics SIG, has just published a new paper in The Journal for Assessment and Evaluation in Higher Education. This paper explores feedback in education and how this can play out and be extended in data rich learning environments. 

Understanding the flipped classroom with learning analytics

In the last couple decades, one of the most talked about ideas in education has been that of the "flipped classroom"—see for example In a traditional classroom, we receive a lecture on a topic, then get practice in applying the topic for homework. A flipped classroom "flips" this structure. In other words, we watch a video of a lecture at home and then practice and apply the concept in the classroom. The advantage of a video lecture is that one can pause or rewatch sections of a video if one fails to understand, all without time pressure or peer pressure (e.g. not being confident enough to ask a question). The advantage of 'homework' in the classroom is that the teacher can more actively support the students during formative stages of applying a concept and intervene more immediately when needed.

Making sense of Learning Analytics in English as a Second Language

Here is a short offering on my endeavours in the recent past...PhD wise that is.

Under the supervision of Prof. Peter Reimann, my research is investigating current practices and sense making of student data presented as Learning Analytics Visualisations (LAV) in the teaching of English as a Second Language (ESL). Existing knowledge of data use in this context will be advanced by examining and tracking teacher learning. This will be achieved by observing teachers’ ability to interpret, engage with and make sense of student data via the concept of expansive learning trajectories (Barab, Hay & Yamagata-Lynch, 1999; Cobb, 1996) in correlation with descriptive frameworks measuring the interplay of ESL pedagogy, technology, and the sense making process.

Widely discussed in the literature is the current and potential influence of digital technology in mainstream education. Opportunities now exist to enhance the teaching and learning experience through an expansive data trail generated by digital device users. In language instruction, the development of Computer Assisted Language Learning (CALL) as a field of research is indicative of this. At an institutional level, the collection and analysis of data is referred to as Academic Analytics, and through learning and teaching spaces, Learning Analytics.