Pre-Learning Evaluation Technique (PLET)

  • Smartbots begins with an understanding that the learning is not uniform but unique
  • Smartbots is a way of offering the content to the individuals based on their level of understanding
  • Every learner will undergo self-evaluation
  • We can offer both customizable and canned test depending on the requirements
  • Individuals will be graded based on the test result

Evaluation Graded Learner (EGL)

  • The EGL module stores the PLET grades for each student for each learning object
  • EGL has the capability to provide the grading matrix
  • The relevant course content is mapped depending on the grade pursued by the student
  • Once the learner acquires the skill, there will be a continuous evaluation by way of assignments or tasks as per the learning program
  • The results will be saved within EGL and the revised grading is done

Smart Content Distributor (SCD)

  • The smart content distributor contains a pre-determined Grade-Content mapping for each learning object
  • The content is mapped to the students based on the Student Grading Matrix (SGM)
  • Higher level of content is offered depending on the level of acceptance by the student
  • The content distributor will offer the content grid. The course is mapped to the particular student depending on their grading

Smart Watch

  • The smart watch module will use the growth mapping based on grade movements and matches the same to the desired grade for the learning object
  • The smart watch also measures the effort on learning in terms of the time spent for learning
  • Based on the combination of both factors, the smart watch will provide the SCD inputs for content distribution and to the EGL for evaluation management
  • This iterative process ensures that every student will get a differentiated learning experience that best suits the students and thus ensures that every student benefits by engaging the mentors at the level of his capability
  • Review matrix has the following parameters: Redo, Learn more, Move next, High improvement
  • The result is sent to both student and mentor

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