Physics textbooks and its network structures

We can observe self-organised networks all around us. These networks are, in general, scale-invariant networks described by the Barabasi-Albert model. The self-organised networks show certain universalities. These networks, in simplified models, have scale-invariant distribution (power law distribution) and the characteristic parameter α of the distribution has value between 2 and 5. Textbooks are an essential part of the learning process; therefore, we analysed the curriculum in secondary school textbooks of physics from the viewpoint of semantic network structures. We converted the textbook into a tripartite network, where the nodes represented sentences, terms and formulae. We found the same distribution as for self-organised networks. Cluster analysis was applied on the resulting network and we found individual modules—clusters. We obtained nine clusters, three of which were significantly larger. These clusters presented kinematics of point mass, dynamics of point mass and gravitational field with electric field.&#x0D; Keywords: Physics textbook, scale-invariant distribution, semantic network.</jats:p

THE CONCEPTUAL STRUCTURE OF PHYSICS TEXTBOOKS FOR SECONDARY SCHOOLS

Textbooks are an essential part of the learning process, therefore they need to be written in a way that is easy to understand. In real life, we often come across complex systems with scale invariant (power law) distributions, which display a surprising degree of tolerance against errors, i.e. degree of robustness. We are confident that knowledge organized in this manner is better for usage in textbooks and promotes easier learning as content would be more intelligible. Initially, we talk about the evolution of some networks, and then we deal with the differences between Poisson and scale invariant distribution in real networks. In conclusion, we are looking for connection between scale invariant distribution and Zipf’s law.</jats:p

MODIFICATION OF SCORING SCHEMES USING DECOMPOSITION PROCEDURES ON STATISTICAL DATA

This paper presents a method of modifying original scores to obtain independent random variables. It includes an analysis of the consequences of using such a method. The paper also describes the mathematical background of the method in detail and discusses the possible use of the method in identifying student or participant assessments that are over- or underrated. The method distinguishes performances of students and assesses their written solutions using a scoring scheme. In this study, it is used to analyze the competence of participants in the Physics Olympiad competition. Scoring schemes that are appropriately set by an author for a physics problem present the participant scores as independent random variables. The assessment solutions are analyzed using analytical tools (such as covariant matrix) for the dependence of random variables. The evaluators of the participants’ solutions were highly qualified professionals. Nevertheless, the study found statistical evidence of minor distortion in the evaluations, though this was found to only marginally affected the ranking of participants</jats:p

LONG TERMS AND READABILITY OF PHYSICS SCHOOL TEXT

This article presents a comparison of two physics school texts from the perspective of readability and use of specific terms. The study uses the survival function to associate the readability of physics school text to the length of terms used in the text. First, the study compares the survival functions of two full texts and that of the terms in these texts, and then analyzes the associated relative readability. Next, the results of two cloze tests involving 150 students are compared. The last step investigates the randomness of the differences between the results. The results show a strong correlation between the test scores and the probability distributions of terms used in the school texts. The difference between the probability distribution of the compared texts corresponds with the differences between the appropriate survival functions, where random fluctuations in the frequency of terms are suppressed.</jats:p