Different types of analytics can be used if we relate learning design to learning analytics.
Some analytics are summative looking at work that has been completed. Some can be formative with an aim of shaping and developing the learning process.
Lockyer et al. (2013), Informing pedagogical action: aligning learning analytics with learning design introduces social network analytics which provide a way to visualise and understand the interactions between people in a situation. They also introduce two broad types of analytic in checkpoint and process analytics.
Checkpoint analytics provide the snapshot data that shows that a student has met the prerequisites for learning by accessing the relevant resources of the learning design.
- log-ins into the online course
- downloads of a file for reading
- signing up to a group for a collaborative assignment
Checkpoint analytics don’t work in isolation of other data to provide insight into learning and understanding. However, they measure access to the resources included in a learning design. The real value of checkpoint analytics is to provide teachers with a broad insight into whether or not their students have accessed the required resources for their learning, and if they are progressing through the planned learning activities.
Process analytics data and analysis provide a direct insight into learner information processing and knowledge applications (Elias, 2011) within the tasks that the student completes as part of a learning design. Social network analytics of a student’s level of engagement on a topic through a discussion forum can highlight potential support structures in place or needed. The inclusion of content analytics adds scope for determining levels of understanding.
Support available within the learning design helps to interpret the process analytics. Supports give an indication of what roles teachers and learners take within the collaborative spaces such as the discussion forum.
When can they be applied?
- At the beginning of a task – checkpoint (to establish if student has logged in and accessed the relevant information and resources).
- During a discussion task in relation to point 1 – process (to check engagement)
- During a whole class discussion – process
- Project proposal task – process
- Project developmental task – checkpoint for example to verify students have accessed a particular resource and/or process to visualise group collaboration during the development of the project.
- Reflection task – checkpoint can be used to verify that a student has accessed the relevant resource for reflection or uploaded it with their changes. Process can provide the information from the reflection which maps changes in student over time.
This activity has made me focus on the development of learning design. It is important to consider the learning resources and how they are used if the learner is to meet the prerequisites needed for learning. Checkpoint analytics are useful for this but they need to be considered along with other analytics such as process analytics which can inform student progress within learning activities, collaboration and reflection which are all important indicators in the learning cycle. Checkpoint analytics can highlight which students have completed tasks and which have not to allow teacher intervention. Process analytics can provide information, based on the support requirements built into the learning design, which help determine the role that teachers and learners take within collaborative spaces to ensure the learning is focused on the learning outcomes.
I think that these classifications make the consideration of data or pedagogy driven questions easier to identify and use within the learning design process or when considering the types of analytics needed and types of tools that can be used.
Elias, T. (2011). Learning analytics: Definitions, processes and potential, in Lockyer, L., Heathcote, E. and Dawson, S. (2013) ‘Informing pedagogical action: aligning learning analytics with learning design’, American Behavioral Scientist, vol. 57, no. 10 [online] available at http:// learninganalytics.net/LearningAnalyticsDefinitionsProcessesPotential.pdf
Lockyer, L., Heathcote, E. and Dawson, S. (2013) ‘Informing pedagogical action: aligning learning analytics with learning design’, American Behavioral Scientist, vol. 57, no. 10; also available online at http://dx.doi.org/10.1177/0002764213479367 (accessed 12 July 2016).
Collaborating available at http://www.vansoestzuid.nl
Starting available at http://moodle.pakuranga.school.nz
Reflection available at http://uangspot.com/blog/page/2