Assessing learner's understanding via node-link analysis: an information theory approach

Abstract

Cognition or thinking involves mental activities or thought process. The complexness of thought process is represented by the complexness of textual information that consists of more distinct pieces of information. Textual information which is in the form of language and symbol are means in representing and communicating information, experiences and ideas. In our research, the textual information is converted into a node-link representation and the development of the node and link is based on the word co-occurrence and meaning. This process enables us to uncover the hidden knowledge structure. An expert model is used as a referent to enable a precise assessment on learner's understanding or known information on a specific subject. Initial results show that the more complex the relationships among the terms (pieces of information), the higher the amount of bits generated, as a measurement of the learner's understanding.