Game playing is one method through which psychological factors of a student can be assessed. Hence, it is highly essential for the counsellors to assess the psychological factors of a student before suggesting a suitable career. A major reason may be that the psychology of the student may not match with the psychology that is expected for the chosen career. After studies, when the student gets employment in his/her selected career, at times, the student may find it very difficult to continue in his/her career.
A career counsellor may assess a student by considering his/her academic record and the scores obtained in IQ tests, reasoning, quantitative-aptitude, etc. Our findings include that (a) assessing difficulty is also very difficult for human experts, and (b) algorithms designed to estimate difficulty should interpret the complexity of a game tree in the light of knowledge-based patterns that human players are able to detect in a chess problem.Ĭareer assessment is extremely important for a student to choose the best career in his/her life. Understanding the connection between players' estimation of difficulty and the properties of the search trees of variations considered is essential, but not sufficient, for modeling the difficulty of tactical problems. We also aim to identify the attributes of tactical positions that affect the difficulty of the problem. Performance data (time and accuracy) are used as indicators of subjectively perceived difficulty. In an eye tracking experiment, the subjects' solutions to chess problems and the moves that they considered are analyzed. In experiments with tactical chess problems, the experts' estimations of difficulty are compared to the statistic-based difficulty ratings on the Chess Tempo website. The final aim is to find formalized measures of difficulty that could be used in automated assessment of the difficulty of a task. We investigate experts' ability to assess the difficulty of a mental task for a human.
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