Adaptive Testing Model as the Method of Quality Knowledge Control Individualizing

EasyChair Preprint no. 994

Abstract

The mission of the work is to develop and theorize the efficiency of application of the knowledge control system on the basis of adaptive testing technology, which combines the specifics of the professional and educational activity and the monitoring of the quality of training and the possibility of self-control of students, to develop a set of test assignments in the discipline "Artificial Intelligence Systems". Object of research is a software tool for monitoring students' knowledge in higher educational establishment. The subject of research is the development of software for an adaptive knowledge control system using machine learning device. Research goals: to develop a set of test case of different levels of complexity; to determine the structure, architecture and specificity of the application of the machine learning algorithm for the formation of a variable level of testing complexity for each student; develop appropriate software, guidelines and recommendations for adjusting and distributing issues by level of complexity. The result of the work is a complex of split-level application-oriented tasks for current and module control in the discipline "Artificial Intelligence Systems", web-oriented software that allows you to quickly monitor the quality of students' knowledge and is appropriate for use in online and mixed mode of training

Keyphrases: adaptive testing, machine learning, Psychological types of personality

@Booklet{EasyChair:994,
  author = {Nonna Shapovalova and Olena Rybalchenko and Iryna Dotsenko and Svitlana Bilashenko and Andrii Striuk and Levan Saitgareev},
  title = {Adaptive Testing Model as the Method of Quality Knowledge Control Individualizing},
  howpublished = {EasyChair Preprint no. 994},

  year = {EasyChair, 2019}}