Using learning analytics to deliver differentiated, contextualised and personalised teaching, learning and assessment
Teachers use virtual learning environments to author and distribute content to their students to facilitate independent study, blended or distributive learning.
The limitations of most virtual learning environments mean that teachers are only able to author and distribute a homogenous set of content to their students; regardless of their students’ academic abilities, prior learning, prior assessment scores or their chosen progression pathways.
This means that most online courses contradict the best practice models of the classroom which promote differentiated, contextualised and personalised teaching, learning and assessment.
Many of the world’s largest MOOCs also fall foul of the same problem when they present the same content to their tens of thousands of online learners. The same can also be said for many of the courses that are hosted on Bolton College’s Moodle virtual learning environment.
The growing use of learning analytics to inform teaching, learning, assessment and student support at Bolton College has enabled the College’s ILT Team to devise a solution to this issue that gives teachers the ability to deliver differentiated, contextualised and personalised teaching, learning and assessment via Moodle.
The two main elements that make Bolton College’s Moodle virtual learning environment adaptive are:
- Adaptive course delivery: Seeks to use a student’s personal characteristics and requirements to deliver bespoke content to that student.
- Adaptive student assessment: Seeks to use a student’s prior qualifications or recent assessment scores to deliver tailoured assessment activities to that student.
In the following example I explain how Bolton College’s adaptive learning environment works in the context of a cross College online employaility unit entitled ‘Interview Skills’.
Example: Employability – Interview Skills
Adaptive Course Delivery
Bolton College has eight academic departments which reflect the various vocational programmes offered by the College such as computing, construction, hair dressing, healthcare or engineering. Students from across the College are enrolled on an employability course.
As students from the different vocational areas open a Moodle scorm package on interview skills they all see the same introductory slides within the tutorial but as they progress through the tutorial they begin to see content which has been authored, adapted or differentiated to match their vocational area.
For example, construction students see content relating to being interviewed for a job on a building site; and healthcare students see content that relates to being interviewed for a post as a hospital nurse. Additional slides may be viewed by students across all vocational areas and other slides may be vocationally specific.
Adaptive Student Assessment
Students see assessment activities that relate to their vocational area. The points scored on the initial part of the assessment inform the type of questions or activities that are presented to a student in the second part of the assessment activity.
A student that does well in the first part of the assessment activity is given questions and activites that further stretch and challenge the student. A student who scores poorly on the first part of the assessment activity is presented with subsequent questions and activities that reflect his or her initial assessment score.
At all times the student is presented with online feedback that is based on medal and mission.
The Broader Picture
The variables that can be used to inform each scorm package are broad and they originate from multiple datasets within the College such as the College’s Moodle virtual learning environment, our Personal Learning Environment and the College’s information management system.
The list of potential variables include departmental names, course name, vocational interests, student name, gender, age, learning support needs, prior grades and assessment scores, career plans and content preferences; such as video, text, animation or interactive elements.
One of the major benefits that can be derived from Bolton College’s adaptive learning environment is the ability to personalise content on the larger courses that are undertaken by students and colleagues from across the College; such as induction, employability, maths, English, English for Speakers of Other Languages (ESOL) or computing.
This is another example were the application of a wider dataset at Bolton College has either transformed existing services or created new services that benefit students, teachers and support teams.
Aftab Hussain, Strategic ILT Lead, Bolton College
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