Test scores alone do not accurately represent students’ understanding or mastery of a topic. KAIT is able to identify the root cause for why a student makes mistakes based on eight cognitive and behavioral factors. These factors were designed by educators and learning science professionals and are calculated using the analog data collected with KAIT’s smartpen.
What we do
Cognitive & behavioral metrics enhance the student profile
Cognitive Factors
01. Number Sense
Flexibility of thoughts and calculations
02. Reasoning Skills
Critical thinking, logic, and problem-solving skills
03. Memory/Visualization
Ability to visualize, recognize patterns and memorize
04. Apply/Connections
Extending from the understanding of concepts to applying association skills
Behavioral Factors
01. Question Comprehension
Ability to understand and communicate issues, self control
02. Test Taking Skills
Ability to create strategies and manage time
03. Grit
Persistence and ability to deal with difficult questions without giving up
04. Concentration
Ability to focus on the task at hand
Individualized curriculums based on KAIT’s AI algorithm
Based on KAIT’s granular understanding of the student profile, machine learning is applied to recommend corrective actions to teachers and generate tailored assignments to meet the individual needs of students.
Practice questions are based on four factors
- Targeting the problem area
- Predicting future mistakes
- Mixing easy and difficult questions, and
- How far along the student is in the course
Mastery Loop: The Recipe for Lasting Knowledge Acquisition
The KAIT system utilizes a mastery learning loop – where a student must achieve a level of pre-requisite knowledge before moving on to another topic. If the student does not achieve mastery, the content is reviewed, and the student tested again until mastery is achieved. This guarantees a student has the appropriate prior knowledge to build a strong foundation as they move through the process of mastering a subject.
