What is personalised learning and how can it improve student outcomes?
Personalised and adaptive learning are not necessarily new terms, dating back to the 1960s and 1970s respectively, but even today there is no blanket definition for either, meaning the line drawn between the two can often be blurred
Whilst personalisation is primarily focused on responding to a student’s input and offering guidance around their learning behaviours, adaptivity offers each student a different assessment depending on their competencies.
Acrobatiq by VitalSource was born out of the Open Learning Initiative (OLI) from Carnegie Mellon University and employs the methodology that both approaches should be used in tandem to drive deeper learning. Whilst everyone has their own individual way of defining adaptivity, Acrobatiq believes that core content should remain just that, with adaptive assessments being deployed alongside to give students the scaffolding they need when they need it. All students will receive the necessary, fundamental material along with adaptive content both during the course and before it starts. This adaptivity can be presented in several ways:
● Number of questions presented
● Topical area targeted
● Delivery of remediation lessons/assets
● Focus on underperforming competencies or sub-skills
● Additional scaffolding around low competence topics.
But why is now the time to start paying attention to these improved methods of teaching? In 2017, research undertaken at the Western Governors University’s (WGU) psychology programme used final exam data before and after Acrobatiq adoption to find the correlation between personalised learning and improved outcomes.
The most notable improvement was that of students receiving the Pell Grant, a subsidy from the US federal government that pays for students to attend college, largely assisting undergraduates from low-income families who would fall into the widening participation bracket in the UK. Before the Acrobatiq adoption, there was a 14-point difference of pass rate between these students and those not receiving the grant, but this difference could hardly be seen when using Acrobatiq, raising their final exam scores and effectively closing the gap experienced by Pell students.
With dropout rates now more prevalent than ever with their inclusion as a Teaching Excellence Framework metric, it is important to remember that 50% of students in the United Kingdom are first-generation students – making them historically more likely to drop out of university – and that non-continuation rates overall continue to rise in the UK. The WGU research student profile heavily consisted of first-generation students, with 46% of the 1,898 participants sitting within this demographic.
There was an eight-point difference in percentage of the 1,204 who used Acrobatiq, and the remaining 694 who were in the control group. This statistic, alongside the indicators that the Pell gap is closed, go to show how important personalised and adaptive learning can be for underrepresented and first-generation students when it comes to retention and outcomes.
Another notable aspect of Acrobatiq is the robust learning data that can provide course and student insights to faculty. Instructors can easily choose the data they wish to see based on their interests.
Data points such as “Which objectives are my students having difficulty with?” and “Which students are having difficulties?” allow instructors in-depth understanding into study habits, students’ mastery of objectives, and those who are likely to drop out.
The beauty of personalised learning is that if student A is excelling at Module 1 but student B is falling behind, instructors can deploy added learning materials to only student B, ensuring all students feel like individuals. With students in a recent survey saying they want lecturers “to treat and talk to [them] as though [they are] a person”, and the demand on institutions increasing to satisfy student satisfaction and success, personalised learning and the analytics that come with it seem to be the perfect duo to combat this.
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What is personalised learning and how can it improve student outcomes?
Keri Beckingham
Whilst personalisation is primarily focused on responding to a student’s input and offering guidance around their learning behaviours, adaptivity offers each student a different assessment depending on their competencies.
Acrobatiq by VitalSource was born out of the Open Learning Initiative (OLI) from Carnegie Mellon University and employs the methodology that both approaches should be used in tandem to drive deeper learning. Whilst everyone has their own individual way of defining adaptivity, Acrobatiq believes that core content should remain just that, with adaptive assessments being deployed alongside to give students the scaffolding they need when they need it. All students will receive the necessary, fundamental material along with adaptive content both during the course and before it starts. This adaptivity can be presented in several ways:
● Number of questions presented
● Topical area targeted
● Delivery of remediation lessons/assets
● Focus on underperforming competencies or sub-skills
● Additional scaffolding around low competence topics.
But why is now the time to start paying attention to these improved methods of teaching? In 2017, research undertaken at the Western Governors University’s (WGU) psychology programme used final exam data before and after Acrobatiq adoption to find the correlation between personalised learning and improved outcomes.
The most notable improvement was that of students receiving the Pell Grant, a subsidy from the US federal government that pays for students to attend college, largely assisting undergraduates from low-income families who would fall into the widening participation bracket in the UK. Before the Acrobatiq adoption, there was a 14-point difference of pass rate between these students and those not receiving the grant, but this difference could hardly be seen when using Acrobatiq, raising their final exam scores and effectively closing the gap experienced by Pell students.
With dropout rates now more prevalent than ever with their inclusion as a Teaching Excellence Framework metric, it is important to remember that 50% of students in the United Kingdom are first-generation students – making them historically more likely to drop out of university – and that non-continuation rates overall continue to rise in the UK. The WGU research student profile heavily consisted of first-generation students, with 46% of the 1,898 participants sitting within this demographic.
There was an eight-point difference in percentage of the 1,204 who used Acrobatiq, and the remaining 694 who were in the control group. This statistic, alongside the indicators that the Pell gap is closed, go to show how important personalised and adaptive learning can be for underrepresented and first-generation students when it comes to retention and outcomes.
Another notable aspect of Acrobatiq is the robust learning data that can provide course and student insights to faculty. Instructors can easily choose the data they wish to see based on their interests.
Data points such as “Which objectives are my students having difficulty with?” and “Which students are having difficulties?” allow instructors in-depth understanding into study habits, students’ mastery of objectives, and those who are likely to drop out.
The beauty of personalised learning is that if student A is excelling at Module 1 but student B is falling behind, instructors can deploy added learning materials to only student B, ensuring all students feel like individuals. With students in a recent survey saying they want lecturers “to treat and talk to [them] as though [they are] a person”, and the demand on institutions increasing to satisfy student satisfaction and success, personalised learning and the analytics that come with it seem to be the perfect duo to combat this.
To read our research brief and book a demo of Acrobatiq, visit: https://news.acrobatiq.com/ET
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