Our Approach

All solutions created by Knowledge AI are rooted in proven educational research methodology. Our theoretical framework supports every feature that we offer in our KAIT@HOME, KAIT@SCHOOL, and KAIT TEST PREP products.

In-Class Effectiveness

Individualizing Education

Mastery Learning

Research-Based Approach

Mastery Learning Loop and Bloom’s 2-Sigma

When students are acquiring new knowledge and skills, the single most significant factor that will determine their success is the amount, timing, and quality of the feedback they receive.

The graph below, from Benjamin Bloom’s ‘2-sigma problem’ research in 1984, plots the impact on academic performance based on 3 cohorts of students: conventional, mastery learning, and tutorial. Students in the conventional learning control group were learning in a traditional classroom with a 30 to 1 student-to-teacher ratio. Students in the mastery learning experimental group also had a 30 to 1 student to teacher ratio, however, the students received individualized and frequent feedback from their teacher. These students outperformed the students in the conventional learning control group by 1-sigma, I.e., the resulting distribution is one standard deviation better. Finally, the students in the tutorial experimental group were taught one-on-one and were given the quality and frequent feedback. These students outperformed the students in the conventional learning control group by 2-sigma, or the resulting distribution is two standard deviations better.

Formative Assessments

Instead of waiting for an end of unit or even end-of-chapter test, KAIT products allow for a formative assessment loop to monitor student progress. Every time an assessment is given our program analyzes student behavior, utilizes cognitive and behavioral metrics (CBM) to accurately identify performance level, and then our AI algorithm automatically generates individualized interventions throughout the mastery learning process.

Memory and Retention

Drawing suggestions from the Ebbinghaus’ forgetting curve*, teachers can design their schedules for lessons, tests, and informal assessments for their students. Technology solutions offer the potential to create learning environments with these principles that can be a valuable aid to teachers and students.

The graph below depicts Ebbinghaus’s forgetting curve which portrays the decline of memory retention in time. This image also shows how information is lost over time when there is no attempt to retain it. However, the more one attempts to retrieve the information from memory in a scheduled and well-thought-out way, the longer the new information is retained.

Ebbinghaus’s Forgetting Curve

(How much of something do we forget each day?)

Typical Forgetting Curve for Newly Learned Information

Additionally, it’s been found that retention increases when the process of knowledge acquisition happens within an active versus passive environment. KAIT products are cross-platform, interactive, and individualized to ensure active engagement with content for maximum retention.

Learning Pyramid. Retention Rate.

Individualized Learning – Zone of Proximal Development

Even with a mastery learning loop, spaced repetition, and active learning for retention, the content itself must be at an appropriate level for each learner for them to advance in subject matter knowledge. Information that is too easy is already known, while information that is too difficult is ignored. To teach a student effectively, the curriculum must fall within a student’s Zone of Proximal Development (ZPD). KAIT’s formative assessment cycle and CBM continuously and automatically identifies every student’s ZPD and suggests the exact Conceptual Building Blocks needed to support growth.

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