The method of student's query analysis while intelligent computer tutoring in SQL

Recently, IT specialties have become one of the most demanded specialties in the world labor market. Simultaneously the traditional teaching in conditions of mass production, even with a professional teacher, has a significant drawback – the fundamental impossibility of adapting to each student. Since the 60s of the twentieth century, researchers worldwide have been developing various computer-tutoring tools that have, less or more, adaptive functions. Nevertheless, the task of the perfect computer tutor development is still far from being solved. The article's research subject is the process of student requests analyzing during intelligent computer tutoring in SQL. The main goal is to develop a method for analyzing the student's SQL queries. The purposes: to form a general scheme and features of the method for analyzing student’s SQL queries based on the principles of technical diagnostics and methods of lexical, syntactic analysis of computer programs; to develop methods for parse tree construction; to create methods for comparing reference and real SQL queries according to their similarity rate; to demonstrate the function ability of the developed methods on specific examples. The methods used computer programs the automatic testing method, the computer programs lexical and syntactic analysis methods, the computer programs parsing trees construction methods, the objects diagnosing method based on comparison with a reference, the strings analysis methods, the method of q-grams. The following results were obtained: the student’s SQL queries analysis method was formed based on a system approach including automatic testing on real data, building query-parsing trees, comparison with a reference, and comprehensive determination of the queries similarity rate. The scientific novelty is the improvement of the method for the student's SQL query analysis during intelligent computer training in SQL query composition.

Perancangan Aplikasi Pencarian Guru Les Privat Komputer Berbasis Android

The purpose of this research is to help students get learning outside the school environment, this is a better education because in addition to school children also get education from private lessons. In addition, this application also functions as a forum for private tutors to boost the economy. Gathering the information students need to do computer learning which is currently all done is easier. So it is hoped that with the design of this private computer tutoring application, it can help students get learning outside the school environment and around the student's residence. The research method used is grounded research, which is a research method based on facts and uses comparative analysis with the aim of making empirical generalizations, establishing concepts, proving theories, developing theories, collecting and analyzing data at the same time. After the author analyzes and collects data, finally the writer can draw the conclusion that with this application system, it can help students get the learning they need easily and efficiently.

Refuting misconceptions: Computer tutors for fraction arithmetic

Fractions, known to be difficult for both children and adults, are especially prone to misconceptions and erroneous strategy selection. The present study investigated whether a computer tutor improves fraction arithmetic performance in adults and if supplementing problem solving with erroneous examples is more beneficial than problem solving alone. Seventy-five undergraduates solved fraction arithmetic problems using a computer tutoring system we designed. In a between-subjects design, 39 participants worked with a problem-solving tutor that was supplemented with erroneous examples and 36 participants worked with a traditional problem-solving tutor. Both tutors provided hints and feedback. Overall, participants improved after the tutoring interventions, but there were no significant differences in gains made by the two conditions. For students with low prior knowledge about fraction arithmetic, the numerical gains were higher in the erroneous-example group than the problem-solving group, but this effect was not significant. Thus, computer tutors are useful tools for improving fraction knowledge. While erroneous examples may be particularly beneficial for students with low prior knowledge who may hold more misconceptions, more research is needed to make this conclusion.

Genetic variation interacts with experience to determine interindividual differences in learned song

Learning reflects the influence of experience on genetically determined circuitry, but little is known about how experience and genetics interact to determine complex learned phenotypes. Here, we used vocal learning in songbirds to study how experience and genetics contribute to interindividual differences in learned song. Previous work has established that such differences in song within a species depend on learning, but in principle some of these differences could also depend on genetic variation. We focused on song tempo, a learned and quantifiable feature that is controlled by central neural circuitry. To identify genetic contributions to tempo we computer-tutored juvenile Bengalese finches (Lonchura striata domestica) from different genetic backgrounds with synthetic songs in which tempo was systematically varied. Computer-tutored birds exhibited unexpectedly strong heritability for song tempo and comparatively weak influence of experience. We then tested whether heritability was fixed and independent of experience by providing a second group of birds with enriched instruction via live social tutoring. Live tutoring resulted in not only a significant increase in the influence of experience on tempo but also a dramatic decrease in the influence of genetics, indicating that enriched instruction could overcome genetic biases evident under computer tutoring. Our results reveal strong heritable genetic contributions to interindividual variation in song tempo but that the degree of heritability depends profoundly on the quality of instruction. They suggest that for more complex learned phenotypes, where it can be difficult to identify and control relevant experiential variables, heritability may similarly be contingent on the specifics of experience.