In ball games, acquiring skills to change the direction becomes necessary. For revealing the mechanism of skill acquisition in terms of the relevant field, it would be necessary to take an approach regarding players' cognition as well as body movements measurable from outside. In the phase of change-of-direction performance that this study focuses on, cognitive factors including the prediction of opposite players' movements and judgements of the situation have significance. The purpose of this study was to reveal cognitive transformation in the skill acquisition process for change-of-direction performance. The survey was conducted for three months from August 29 to November 28, 2020, and those surveyed were seven university freshmen belonging to women's basketball club of M University. The way to analyze verbal reports collected in order to explore the changes in the players' cognition is described in Sect.2. In Sect.3, we made a plot graph showing temporal changes in respective factors based on coding outcomes for verbal reports. Consequently, as cognitive transformation in the skill acquisition process for change-of-direction performance, four items such as (1) goal setting for skill acquisition, (2) experience of change in running direction, (3) experience of speed and acceleration, and (4) experience of the movement of lower extremities such as legs and hip joints were suggested as common cognitive transformation. In addition, cognitive transformation varied by the degree of skill acquisition for change-of-direction performance. It was indicated that paying too much attention to body feelings including the position of and shift in the center of gravity in the body posed an obstacle to the skill acquisition for change-of-direction performance.

Among the problems that face ITS designers, the problem of measuring the student knowledge state after concept learning in order to initially adapt a skill acquisition session according to a student's own necessities is a hard one. Typical approaches are the use of some sort of test to assess the student knowledge and choose an initial set of parameters for a session, or use, regardless the particular necessities of a student, a pre-defined set of initial parameters. We consider the fromer to be disrupting for learning and the latter too simple to deal with the broad possibilities that are faced. It is known that students show different behaviors during concept learning depending on the experience, background and actual understanding (the way a student is understanding a concept) during concept learning. Our approach here is to classify the different behaviors through fuzzy proposition and link them with a student model through fuzzy rules to use in an expert system, and with it, select the most suitable problem-solving strategy for each particular student in order to clear his misunderstandings and facilitate the learning of problem-solving skills. The use of probabilistic reasoning (i.e. Bayesian statistics) instead of fuzzy logic is not suitable for the present situation because of the rigidity and precision of the rules that do not allow a proper manipulation of the vagueness involved in the student behavior. We apply this idea to a circuit analysis ITS where the concept learning session is carried out on a Hypertext environment and the skill acquisition session on an interactive problem-solving environment. By tracing the student use of the Hypertext environment we can know the student behavior and use it as a premise in the fuzzy inference.