Plario
Plario is a unique adaptive learning system currently focused on mathematics. We aim to increase learning outcomes and achieve this efficiently with proprietary Machine Learning algorithms.
Description
Adaptive learning system Plario has been created as an online platform. It’s totally new system that considers modern students’ behavior and habits. Plario provides personalized learning.
The reason behind Plario creation was the demand to improve academic math knowledge in junior university students.
As an adaptive learning system Plario’s main task is to solve the challenge of teacher’s expertise scalability. This provides efficiency of mastering academic materials by students. And it can be compared to the efficiency of having individual sessions with the teacher. Plario utilizes Machine Learning algorithms: genetic algorithm, enhanced version of BKT (Bayesian Knowledge Tracing). Those algorithms help to assess student’s initial knowledge level. BKT allows to evaluate level of mastering in real-time and create dynamic personalized learning track.
At present moment Plario has its focus on one basic math section: Algebraic expressions simplification.
This section was decomposed and presented as a domain ontology/ graph of interconnected skills (competencies), which serves as basis for assessment and adaptive algorithms. The best mathematics teachers from Tomsk State University have created educational content with the help of special content graining technologies for each competency (individually and in practically significant combinations). Content consists of theoretical material in microdoses and practical exercises with different complexity level. System architects, software engineers and Data Scientists from ENBISYS have developed solution for efficient knowledge mastering considering individual distinctions in each student.
Gamification elements in the product have led to high engagement among students.
Adaptive learning system Plario effectively increases learning outcomes. Further task is expansion of the competencies to wider range of mathematics sections. Larger volume of redundant content (which is required for adaptive system) will be created. The plan for near future is to scale up the system up to 8000 simultaneous users.
