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Emerging trends and technologies: Part 2 – Learning Analytics

Emerging-trends-and-technologies-in-education-that-educational-leaders-should-keep-an-eye-on-Part-2-–-Learning-Analytics

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Today, leadership teams of educational organisations are under increasing pressure to make well-informed choices about their institution’s digital strategy. In their search for tools that will support them in achieving their organisation’s core mission, CIOs face a seemingly ever-changing list of software vendors and a steadily growing number of education-related technologies. In a series of blogs posts, this space introduces some of the emerging trends and new technologies that are worth keeping track of when devising an IT investment strategy for the future.

One emerging trend that CIOs should consider leveraging are the affordances of Learning Analytics in education.

Learning analytics is the collection and analysis of rich contextual data about learning interactions. Data about learners and their instructional and learning contexts is being collected, measured, analysed, and visualised with the goal of improving learning outcomes and environments. Using this data, educators are able to assess which activities and content lead to the desired outcomes as well as compare the effectiveness of different learning content and tasks.  Such metrics can improve the design of unit curriculum structures and learning activities by showing how to better align content with user needs and educational goals.  Reports generated in real time on measures such as attendance, access to online units, and marks can also help identify problems in student learning paths serving as early warning systems. When used effectively, these technologies enable students to self-assess and correct while at the same time allowing for early interventions in the form of appropriate assistance and recommendations by educators. Furthermore, predictive measures based on student information and learning patterns at the level of the individual, the course, and the program facilitate the design of personalised curricula and learning pathways. In view of these capacities, a report by Gartner (2016) recently predicted:

“As long as appropriate interventions are made […] the impact could be transformational in that we could see great improvements in student learning outcomes.”

Because of this huge potential, Learning Analytics is high on the priority list for many educational institutions, which are under increasing pressure to improve student outcomes and demonstrate evidence of learning, and the hype around analytical tools is growing. However, most institutions are still in the very early stages of adoption despite the widespread collection of large quantities of data by Student Information Systems (SIS) and Learning Management Systems (LMS).

Recently, the key findings of an internal pilot project into Learning Analytics as an innovative approach to enriching student success were presented at a local tertiary education institution in Western Australia. The aim of the pilot was twofold: to assist students in enhancing their motivation, academic self-efficacy, and performance as well as to help educators in improving the design of unit course structure and learning elements. For that, the pilot collected, measured, and analysed data of almost 2,000 students enrolled in nine units in six different faculties. Metrics included the time the students spent in the online unit based on time stamp data of first access and log out, performance marks and grades, number of interactions and submissions. Guided by a set of ethical principles, the results were reported and visualised as individual reports for students and as collective overviews for unit coordinators and tutors. The evaluation of the pilot provided some important insights into student experiences with learning, the use of the LMS, and their motivation to seek assistance. It also provided educators with feedback on the quality of their teaching and the learning design.

The study utilised online surveys, semi-structured interviews with focus groups and self-reflection exercises of individual project teams to gather data on participant’s experiences with Learning Analytics. In the feedback collected, students described how they particularly found the tool as valuable source for reflection and self-assessment as is enabled them to compare their data with the unit average as well as with high performing students. Educators, on the other hand, reported that the staff report provided to them offered valuable data about content items being accessed most, and correlations between number/timing of unit accesses, interactions and students’ final grade scores. Based on these promising results, further projects using Learning Analytics are planned by the institution. A particular focus point for future studies will be the exploration of the usage and benefits of Learning Analytics within the strategic and developing contexts of the organisation.

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