What if you could see, at a glance, which students have watched that video you posted on topic 5? Or are not finding the learning material for topic 7 useful? With learning analytics, you can. Learning analytics provides the perfect blend of data and insights for you to gauge how optimised your teaching approach is and identify areas of improvement. With the continued permeation of digital transformation into the education environment, the addition of learning analytics can offer unparalleled value to educators and students alike.
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What is Learning Analytics?
As part of one of the three core components of the aleX platform, learning analytics collects and analyses student data to track their learning engagement. Through the use of quantitative analytics tools and Power BI, educators are equipped to better understand each student’s learning needs and optimise their teaching approach.
Particularly useful for eLearning experiences, learning analytics records detailed information related to learners’ interactions with aspects of online courses. Learning analytics enables vital pieces of data such as session duration, module progress, and discussion forum activity that were previously unbeknownst and inaccessible to educators available for analysis. Lecturers and tutors are empowered with a comprehensive view of how each student is performing academically, their grasp of concepts, and their overall engagement. Such data can be invaluable to determining the learning needs of each student, making predictions on their future performance, and personalising content to be more relevant and appropriate.
Why you need Learning Analytics
Traditionally, teaching was conducted in a one-way communication of learning material where students are expected to sit and listen. However, this approach that involves memorisation and recitation can hinder a student’s ability to develop their critical thinking and problem-solving skills. The modern teaching environment has changed from a physical classroom setting to one that has been digitally infused with a focus on collaboration and feedback. With modern reforms, the learning environment is also no longer static whereby technology is integrated into the education space to give both instructors and students the tools they need to succeed in wherever location they are based.
As opposed to passive learning, active learning has been demonstrated to significantly improve how students learn and process the educational materials they are engaging with. Students are empowered to develop their critical thinking skills by undertaking a variety of problem-solving activities, group discussions, and hands on analysis. When multiple aspects of a student’s brain such as their cognitive, emotional and social components are activated, their learning potential is greatly enhanced due to their proactive engagement with new information. The responsibilities of teachers in raising the levels of collaboration and engagement are vital for students’ ongoing learning success and this can only be achieved through active intervention.
The observation of students’ activity in an online learning environment should be frequently conducted at different stages of the learning process so that the teaching approach can be changed according to the emerging behavioural patterns. Similar to the changing learning environment, the roles of educators have also become multidimensional whereby they are now required to simultaneously be a facilitator, moderator, observer, and collaborator.
The data generated from learning analytics can provide detailed insight for educators into how students are performing based on their teaching approach. Students come from a multitude of socio-cultural, economical, and educational backgrounds which requires different levels of learning support. As each student learns in their own unique manner, there is no one size fits all learning model. By monitoring their performance and engagement, educators can segment students according to their interests and tailor their teaching to these specific groups. By customising the learning experience for each student, they will be able to comprehend and work through course materials at their own pace.
With a student’s network size directly affecting how well they perform with their studies, it is essential that educators drill down on students’ participation and activity with QBot and Teams to identify their level of connection. Individuals with similar social network sizes tend to pursue the same academic goals and expectations. Hence, when connected with students of the same clique, the shared standard of mutual achievement motivation can influence their level of self-esteem and subsequent academic performance. The ability for educators to scrutinise student engagement with course material and their social networks allows them to identify individuals at risk of dropping out early and implement corrective action as soon as possible.
The more students are immersing themselves in their learning environment, the better their performances are likely to be. Active digestion and application of information enables students to solidify their learnings by strengthening their higher-level thinking. This means learners who would otherwise be struggling are provided opportunities to connect with their cohort and participate in stimulating discussions that develops their sense of belonging.
What makes Learning Analytics great?
Powered by Power BI, learning analytics uncovers real time insights of how students are interacting with one another and who they are interacting with. The insights are displayed in dynamic visualisations that make it incredibly easy to see a snapshot view of all the students and educators’ engagement with the aleX platform.
Learning analytics equips educators with the tools to discover the progress of each individual student’s education journey and analyse how active and well connected they are with the Teams and QBot platforms. The bird’s eye view provides real time insights into how well students are engaging with one another, the top engagement leaders, and how well QBot is assisting with learning queries. The interactive dashboard provides educators the mechanisms to filter and explore student data at a granular level to uncover previously hidden insights such as responsiveness, collaborative efforts, and user activity.
Real time insights and comprehensive activity reports allows you to make predictions on students’ future performance and probability of dropping out, so corrective action can be swiftly implemented. Be empowered with the foresight to determine if a student is likely to pass or fail a course based on their social network size and activity levels. By digging deep into key data insights, you have the opportunity to play an active role in your learners’ ongoing educational journey and success.
Learning analytics enables you to:
- See a quick overview of how students and educators are engaging with QBot on Microsoft Teams
- Identify which students are highly engaged or disengaged and personalise the teaching approach to better suit their needs
- Develop strategies to improve student performance and assist those at high risk of dropping out of a course
- Recognise which questions are commonly asked and deliver aid that targets those query topics
- Make predictions on future academic performance based on student mastery of content and interactions with QBot and their peers
Interested to see what learning analytics can do for your students?
We can help you deploy learning analytics as part of the aleX educational platform and enable you to maximise the student learning experience. The nature of education is changing and it is vital that you are equipped with the tools to optimise the teaching approach that offers invaluable benefits to learners.
For more information about learning analytics and the aleX platform, contact Antares on +61 2 8275 8811.