Educational Strategies and Academic Gains
Issues:
- Many youth are significantly behind academically but don’t have access to coursework that fits their skill level
- Only High School level courses are offered.
- Vocational instruction is offered. But without basic math and reading skills, youth have difficulty meeting vocational goals or obtaining employment.
Example profile at one male residential program
- Average age of youth is 17.2 years old
- Mean ELA Grade Level: 3.7
- Mean Math Grade Level: 2.4
- Teachers are tasked with having to teach a classroom made up of youth with a variety of skill levels because they are grouped by dorm or behavior concerns rather than academic ability.
- Without the basic foundations of math and reading, subsequent coursework becomes more difficult
Solution: Data Driven Education Model
- Utilize precision teaching methods to increase the rate of learning for students who are behind.
- Use advanced data analytics (i.e., micro, meso, macro, meta analysis) to pinpoint deficiencies and create an environment that supports outcome-based learning.
- Train and coach teachers to utilize differentiated instruction techniques in programs where they are teaching large groups of students of all different abilities.
Student 1 Example:
- 18 year old male at residential program:
- Baseline rate = 25 math facts per minute x1.1 learning rate
- Fluency instruction 4-5xs per week: 70 math fact per minute.
- Accelerated learning rate by more than x2
Typical “good student’s” average rate of learning is 1.4
At this rate this student would make up 2 grade levels worth of learning with this intervention |