Learning analytics
Learning analytics
The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs
The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs
Historically, some of the most common uses of learning analytics is the prediction of student academic success and identification of at-risk students in order to provide them with support. Data drawn from student interactions and online engagement can be used to improve teaching practices and resources.
Learn how to use learning analytics in Moodle and set up analytics in Moodle activities to improve your teaching.
Learn how to design learning tasks to include data and learn to review collected activity data.
Learn how to use the Moodle Analytics Graphs to identify and provide personalised and timely feedback to students.
Learn how to access analytics built into many learning technologies used at Monash University, which can provide insight into student engagement.
Learn how to access and use the Board of Examiner (BOE) Reports. Access to BOE reports is restricted to certain roles.
Two of the main purposes to learning analytics are the ability to support student awareness of their learning and to encourage their self-reflection. To achieve these two goals, students must have a basic understanding of
Increasing student awareness of the analytics that are collected by the tools utilised in a unit is the first step to supporting students with learning analytics. Explain to students what data is available and what data you may be accessing to inform your teaching.
Visual analytic dashboards such as the progress completion bar and Moodle engagement analytics provide students data about their engagement with Moodle activities. Using the bar and explaining what data is collected aids students’ self-regulation of engagement with a unit.
A learning analytics team collates high-level learning analytics information for units in a central location. Learning analytics outputs include:
To access such data, talk with an Associate or Deputy Dean Education about this.
Here are some relevant resources to help support you with utilising learning analytics in your teaching.
Multiple data points are required to triangulate and interpret learning analytics. SETU is another source of data that should be considered with all other sources of data before drawing conclusions.
Student Evaluation of Teaching and Units (SETU) is a way we get to hear from students about their experience of learning within a unit. The responses provide the University with a broad indicator of students' perceptions of teaching and their learning journey.
The Feed Forward Bento Box enables teaching staff to gain immediate feedback from students about their teaching and learning experiences during the teaching period. It is suggested to integrate this bento into Week 3 or Week 4 of teaching to provide an opportunity to act on formative feedback to improve the learning experience during the teaching period.
This bento consists of a set of sentiment questions in a Moodle questionnaire poll which have been prepopulated to align with annual Quality Indicators for Learning and Teaching (QILT) surveys. Results gathered from the poll will be utilised to design and implement an improvement plan for learning and teaching in the unit during the teaching period. A template is provided for sharing the results of the poll and subsequent unit improvements and actions.
The Society for Learning Analytics Research (SoLAR) is an interdisciplinary network of leading international researchers who are exploring the role and impact of analytics on teaching, learning, training and development. Monash University has an institutional membership in the Society for Learning Analytics Research (SoLAR) for Monash, which allows an unlimited number of staff and students to register as regular members free of charge. Contact educationtechnologies@monash.edu for the discount code.
Monash values the privacy of every individual and is committed to the protection of personal data. Therefore, any learning analytics collected should be stored and protected appropriately.
Monash has specific policies and procedures related to data protection and privacy. Take the time to review these to inform your teaching practice.
This procedure applies to personal information, sensitive information, health information and special category data.
This statement explains to students how the University can use the data it collects from students.
The Education Performance Standards identify the expectations of education practice at Monash – See the Education Performance Standards for more details.
Impact on student learning | Impact on educational knowledge | Impact on educational environment | |||||
Effective teaching and learning | Responsive program design | Student- centred orientation | Professional learning engagement | Pedagogical content knowledge | Education research performance | Education innovation | Education leadership |
✓ | ✓ | ✓ | ✓ | ||||
You could address these Practice Elements by providing evidence of how you: