Personalised learning paths
The adaptive learning engine creates a scalable, personalised experience to help each student succeed in their own way.
- Semantic engine automatically links concepts to content. It develops an active understanding of each student’s progress against learning objectives, and where they need extra help.
- Instructors can use the learning objectives, content, and questions they’ve already created for a course to set unique learning paths for each student.
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Course content and assessments are automatically tailored to each individual, helping deliver a personalised experience whether the class size is 10 or 1,000.
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Better outcomes for at-risk students
Predictive analytics and visual diagnostics can help instructors identify at-risk students in a course and take action to help them improve.
- Intuitive dashboards transform complex learner data into easily-identified patterns of student engagement and academic risk.
- Integrated workflows help instructors quickly take prescriptive action for at-risk and disengaged students.
- With a better understanding of what’s working and what isn’t, instructors can improve and optimise their course content and delivery over time.
Data-driven decisions
Rich data visualisations and advanced analytics reports give institutions the information that they need to make evidence-based decisions that will help improve student outcomes.
- Learner performance metrics such as logins, tool access, engagement, grades, content usage, and more, show where students are struggling or succeeding.
- High-performance reports visualise data from the VLE as well as from outside learning for a complete view into each learner’s progress.
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Providing flexible access to outcomes-based learning programmes
And making degree apprenticeships more engaging
Technology-based learning can help FE institutions provide a personalised learning experience to encourage registrations and retention through engaging course content and delivery