What can we learn from learning analytics? A case study based on an analysis of student use of video Home : Annual Conference 2016

Public Group active 2 years, 5 months ago

Tue, Sep 6 2016, 11:30am – 1:00pm
Authors: Moira Sarsfield, and John Conway
Room: Ensemble
Theme: Connect
Type: Long Session

Description

Big data is becoming more relevant in today’s environment. It underpins many enterprises and the strategic decisions organisations make in response to customer needs. The term ‘analytics’ is used to describe the process of extracting meaningful insight from these large data sets and thereby reaching objective conclusions, which can be actioned as part of a wider strategy. Analytics can also contribute to improvements to the overall service delivery and ensure an effective use of resources.

This need to extract meaning from big data also exists within Higher Education. We are now seeing greater interest in applying these forms of analytics within HEIs, to better inform strategic decisions in terms of pedagogy, service delivery and return on investment.

Specific areas in HE where analytics can have an impact include:

* improving course design,

* improving the learning experience and

* Improving student outcomes

During the academic year 2014-15 we captured the students use of video recordings on over 20 modules across five different degree streams using server click data. The initial aim of the project was to answer the following questions:

* How much use is made of video recordings by students?

* Is the use of recordings different on different modules/degrees?

* Is the use of recordings different for different groups of students, e.g. students with learning differences or English as a second language, students with different levels of attainment?

* Is the use of recordings different for different types of content, e.g. recordings of traditional lectures, flipped lectures, post-lecture summaries, work-through of tutorial questions, etc?

* How does the use of recordings in a course vary over time, e.g. immediately after the lecture or during the revision period before exams?

Based on this analysis we plan to derive ‘actionable insights’ (Cooper 2012), which will lead to a greater adoption of evidence-based approaches to our teaching and learning practice.

The presentation will begin by describing how the project was planned and implemented, including details of our technical approach, (Miller & Mork, 2013), and how we dealt with ethical and privacy concerns (Sclater, 2014). Next we will present some of the results of the analysis: answers to the research questions above, insights obtained from these answers and other unexpected insights derived from the analysis.

Finally we will discuss what lessons can be learnt from this project for wider application of learning analytics as a tool to improve learning and teaching.

References

Adam Cooper (Nov 2012) What is Analytics? Definition and Essential Characteristics, Vol. 1, No. 5. CETIS Analytics Series, Cooper, A.,http://publications.cetis.ac.uk/2012/521, page 4

Sclater, N. (2014). Learning Analytics: The Current State of Play in UK Higher and Further Education. Bristol. Page 6

Miller, H. G., & Mork, P. (2013). From data to decisions: a value chain for big data. IT Professional, 15 (1), pages 57-59

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