POSSIBILITY OF IMPROVING THE TRAINING COURSES CONTENT BASED ON STATISTICAL ANALYSIS OF THE COLLECTED POINTS

Abstract

  The research looks into the methods of visual representation of points accumulated by students in a single study course that are employed in modern data science. Statistical indicators and prospects for improving the subject based on them are discussed: which parts of the subject should be adjusted to increase the training course's quality. Data processing and display methods that the course instructor can employ effectively in the process of observing continuous visualisation of scores are discussed.
  The article introduces a novel approach for enhancing the content of a training course through statistical analysis and visual representation of student scores, utilising React.js technology. The proposed platform empowers course instructors to incorporate various assessment methods such as quizzes, presentations, mid-term exams, and final exams and subsequently display students' grades based on each assessment method. The platform employs advanced statistical indicators and robust visual presentation capabilities to calculate and illustrate the points achieved. This enables instructors to easily identify desired evaluation methods, observe the distribution of points, and simultaneously track multiple evaluation methods to monitor the dynamic progression of the training course. Consequently, this holistic approach enables instructors to identify and address problematic sections within the course content, leading to meaningful improvements.