Nobody can deny we are moving towards a “data driven world.” Our ability to collect data and our capability to mine and scrutinise information to generate useful insights have grown exponentially. Every industry recognises the positive implication of using data to understand users better and find the most appropriate ways to meet their needs. And more and more organizations are embracing this approach (just think that more data has been collected and analysed in the past two years than in the entire history of human race).
When it comes to the opportunity of understanding and serving user needs better, education is (or should be) no exception. Nowadays, technology plays an integral role in teaching and learning, with the Learning Management Systems already collecting information about student interactions while canvassing through all course material and ancillary content. This information may be analyzed to understand student’s learning gaps and, with the use of specific learning tools, to define educational pathways that will help close those gaps.
These tools are known as “adaptive eLearning systems” and are related to three main areas:
- Adaptive Content: Consists of offering additional specific content based on quantified student progress determined by information collected through their experience digesting course materials (feedback, hints or extra exercises fall within this category).
- Adaptive Assessment: Consists of selecting the questions to be presented, to a given student, based on previous answers and on the perceived level of his/her understanding of a set of target topics.
- Adaptive Sequence: Content and sequencing are decided on a student by student basis, making use of machine learning algorithms and predictive analytics. This is the most complex process.
A lot of field research reveals that adaptive e-learning has a real impact on students’ success. For example, a white paper published by Education Growth Advisors at Arizona State University reports an 18 percent increase in pass rates and a 47 percent decrease in withdrawals in adaptive math courses. Another interesting case is from the University of New South Wales where the introduction of adaptive tutorials in a foundational first-year Engineering Mechanics course led to a decline in the course drop-out rate from 31 percent to 14 percent.
Interestingly, also controlled studies carried out by six public universities on an Introductory Statistics Course found that online adaptive students completed the course 25 percent faster than students in a face-to-face version while achieving similar performance levels.
“iAdLearning uses existing course content and is accessible through the Partner Cloud
or ‘Content Market’ within the Blackboard Learn and Moodlerooms ecosystem.”
Considering the growing importance of adaptive eLearning solutions, we recently entered into a Signature Partnership with IADLearning to enable their software to be accessible and deployed across Blackboard LMS users worldwide.
Owned by iTop Training, a specialist provider of elearning software, analytics and services, IADLearning essentially implements adaptive sequencing strategies that in summary:
- Provides students with personal content recommendations based on their profile and the analysis of all learning experiences taken place using the same course content.
- Provides teachers and institutions with invaluable insights on the efficacy of their learning processes and course content.
- Offers comprehensive eLearning analytics allowing instructors to track student progress and development.
IADLearning uses existing course content and is accessible through the Partner Cloud or ‘Content Market’ within the Blackboard Learn and Moodlerooms ecosystem.
Do you want to learn more about IADLearning and help you achieve your eLearning goals? Click here to request a demo.
Interested in becoming a Blackboard partner? Click here.