Latent Semantic Analysis for Notional Structures Investigation

The research on the effects of study is hindered by the limitations of the techniques and methods of registering, measuring and assessing the actually formed knowledge. The problem has been solved using latent semantic analysis for comparison and assessment of scientific texts and knowledge, expressed in the form of free verbal statements. Education at higher schools has the specific objective to develop knowledge and experience both of which have two fundamental dimensions: the first is expertise training in a well-defined occupational or disciplinary domain, and the second — learning strategies and skills to be an effective learner. Various trends for stimulation of deep learning, transferring in practice the achievements of the cognitive psychology, have been developed during the last decade. Here we present a research on the cognitive activity of university students and its results in the dimension of declarative knowledge. In practice a comparative analysis is made between the input system of notions from the learning texts and the formed mental structures of the students. The research includes a sequence of actions and procedures for: facilitation of the formation of stable concepts structures (preparation of learning materials, its content, structure and visual presentation, organisation of learning, etc.); feedback output on the preservation of knowledge of certain number of key notions; and assessment of manifested knowledge. The data used is verbal learning texts, linguistic descriptions of notions contained in them and all these are rendered in an open format by the people observed while posing indirect questions. The nature of the processed material (input stimuli and preserved knowledge), decided on the application of Latent Semantic Analysis (LSA) as a research method on the information data. This statistical technology permitted the formation of a model of semantic connections between the researched notions in the output and the general representation of the results. Latent Semantic Analysis for Notional Structures Investigation Abstract. The paper presents a comparison method for input system of notions from the learning texts and the formed mental structures of students based on latent semantic analysis. The data used is verbal – learning texts, linguistic descriptions of notions contained in them and all these are rendered in an open format by respondents while posing indirect questions. This statistical technology permitted the formation of a model of semantic connections between the researched notions in the output space against whose background is made an assessment of the individual achievements and the general representation of the results. The paper presents a comparison method for input system of notions from the learning texts and the formed mental structures of students based on latent semantic analysis. The data used is verbal – learning texts, linguistic descriptions of notions contained in them and all these are rendered in an open format by respondents while posing indirect questions. This statistical technology permitted the formation of a model of semantic connections between the researched notions in the output space against whose background is made an assessment of the individual achievements and the general representation of the results.