Solid paper on personalised learning

A solid paper on the advantages for of self-paced learning. The promise of AI is to deliver personalised learning, sensitive to the learner’s AR (acquisition rate). 

The acquisition rate in learning refers to the speed or efficiency with which a learner acquires new knowledge, skills, or behaviors. It is a measure of how quickly a person can grasp new information or master new concepts. This rate can vary significantly depending on factors such as the complexity of the material, the learner’s prior knowledge, motivation, cognitive abilities, and the methods of instruction being used.

STUDY

tested different ways of teaching multiplication tables (6s, 7s, and 8s) to 3rd & 4th graders

split into three groups: 

• Group 1: learned 2 facts at a time

• Group 2: learned 8 facts at a time

• Group 3: learned facts based on their personal "acquisition rate" (how much they could handle)

RESULTS

Key Findings (from the table and text):

Learning time varied a lot: 

• 2 facts group: 3 minutes

• Personal pace group: 7 minutes

• 8 facts group: 14 minutes

What worked best: 

• Personal pace method (acquisition rate) worked really well

• Teaching 8 facts at once was least effective (only 39% remembered)

• Teaching 2 facts at a time was middle ground (47% remembered)

• Students remembered 76% of facts when taught at their personal pace

One size does not fit all when it comes to learning multiplication facts. The average student could handle learning about 4 new facts at a time. Tailoring the number of facts to each student's learning capacity was most effective. Personalised, self-paced learning works.

Bloom's lesser known research

Bloom is known for his pyramid (he never drew one and it is hopelessly simplistic) but researched this in detail. His other research, rarely known, led him to believe, in Human Characteristics and School Learning (1976), that learners could master knowledge and skills given enough time. It is not that learners are good or bad but fast and slow. The artificial constraint of time in timed periods of learning, timetables and fixed-point final exams, is a destructive filter on many. The solution is to loosen up on time to democratise learning to suit the many not the few. Learning is a process not a timed event. Learning, free from the tyranny of time, allows learners to proceed at their own pace.

Bloom proposed three things could make mastery learning fulfil its potential:

1. Entry diagnosis and adaption (50%) - diagnose, predict and recommend. David Asubel made the point that “The most important single factor influencing learning is what the learner already knows” yet pre-testing is relatively rare form of assessment.

2. Address maturation (25%) - personalise and adapt. AI can deliver personalised learning based on continuous assessment and adaption.

3. Instructional methods (25%) - match to different types of learning experiences and time. Sensitivity to the type of learning, a far more complex issue that Blook thought with his falsely progressive pyramid and tripartite distinction of Cognitive domain (knowledge-based), Psychomotor (action-based) and Affective (emotion-based)

https://www.researchgate.net/figure/Retention-and-Efficiency-Data-by-Condition_tbl1_281801350