A Model of the Continual Adaptive Online Knowledge Assessment System

Abstract

This chapter presents a model of a novel adaptive online knowledge assessment system and tests the efficiency of its implementation. System enables continual and cumulative knowledge assessment, comprised of sequence of at least two interconnected assessments, carried-out throughout a reasonably long period of time. Important characteristics of the system are: (a) introduction of new course topics in every subsequent assessment, (b) re-assessment of earlier course topics in every subsequent assessment iteration, (c) in an adaptive manner, based on student’s achievements during previous assessments. Personalized post-assessment feedback guides each student in preparations for upcoming assessments. The efficiency has been tested on a sample of 78 students. Results indicate that the proposed adaptive system is efficient on an individual learning goal level.

Automated Transformation from Competency List to Tree: Way to Competency-Based Adaptive Knowledge E-Evaluation

“…Tasks are categorized according to the level of difficulty into easy, medium, difficult, etc. [4][5][6]. In such cases, a threshold level is used, and, if a student passes it, he or she gets to a more difficult level of tasks or material.…”