Method for self-adaptively evaluating of a testee

Abstract

The invention discloses a method for self-adaptively evaluating the knowledge state of a testee. The method comprises a first stage of calling a single-layer function for assessing the knowledge stateof a testee at the first layer, judging the knowledge state of the testee, and outputting the possible knowledge state of the testee, including the internal boundary and the external boundary of theknowledge state; Second stage, calling a function of single-layer evaluation of the tested knowledge state to evaluate the possible knowledge state of the testee at the second layer from the masteredknowledge state to the external boundary, outputting the possible knowledge state of the testee, including the internal boundary and the external boundary of the knowledge state, and moving to the next layer of the learning space to continue evaluation until the number of layers of the learning space is completely traversed. The accurate knowledge state of the testee can be obtained, the obtainedresult is simple and efficient for the content and specific reasons of knowledge points which are not mastered by the testee, and the method has more substantial significance for evaluating the testee.

Description

technical field [0001] The invention relates to a method for assessing subjects, in particular to a method for self-adaptively assessing the knowledge status of the subjects. According to the theory of learning space, the knowledge status of the subjects is self-assessed hierarchically. Background technique [0002] KS-CAT (Computerized Adaptive Testing, CAT) is a computerized adaptive test based on learning space theory. The learning space first analyzes the knowledge of a field into a set of questions, each question has a correct answer, and secondly uses a set of questions that a student can correctly answer in a certain domain under ideal conditions to present his "knowledge status". ", the collection of all possible (according to subject logic, determined by experts) knowledge states is called learning space. The computerized adaptive test (CAT) is proposed to solve the shortcomings of the "peak shape" and "rectangular" paper-and-pencil tests that all students use the ...

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Problems solved by technology

[0004] However, MARKOV PROCESS has very big problems in practical application. On the one hand, for beginners, the learning space with 15,000 knowledge points in junior high school mathematics is in line with the learning rules of students, but in such a single-layer learning space condition Next, if you want to measure the knowledge status of a graduating class of students, using such a small point to measure the number of questions that need to be tested is relatively large; on the other hand, the learning space used by MARKOV PROCESS is a single layer, which means that no matter For excellent students or poor students, the size of the test knowledge points is the same, so the excellent students will feel that the test is too trivial, and the poor students will feel that the test jumps too much

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