It is possible to define Computational Thinking briefly as having the knowledge, skill and attitudes necessary to be able to use the computers in the solution of the life problems for production purposes. Computational thinking is a method of problem solving, system designing and also a method of understanding the human behaviors by drawing attention to the basic concepts of the science of computer. Computational thinking also covers the acquainted concepts such as analysis, data demonstration and modeling and also the ideas that are less known such as binary search, repetition and parallelization. When the fact that computational thinking has a border and general frame is taken into consideration, it is a valid basic skill not only for the computers, but al so for everybody and it is considered that it shall take place in the basic skills (reading, writing and arithmetic) used by everyone in the near future. According to Bundy, computational thinking affects the studies in almost all the disciplines in both the human sciences and the natural sciences. The researchers make use of the cognitive metaphors for the purpose of enriching the theories such as protein science and mindbody problem. The science of computer has made the researchers gain the skills of asking new questions such as the ones requiring the data process with substantial amount and forming new solutions. Today, there is almost no environment in which there is no computer and no computer is used. The daily usage is mostly limited to communication, surfing in the Internet or office applications. Whereas, the concept of computational thinking is far deeper than them and forces the ordinary thinking way to change. Such that, it is claimed that a person who would like to understand the 21st century is firstly obliged to understand the computational thinking. It is possible to say that computational thinking is a problem solving approach that reinforces the unity of technology and thinking. According to ISTE, this skill does not take the place of creativity, logical thinking and critical thinking; but it increases the capacity of a computer in the solution of a problem of a human being by taking benefit of the human creativity and critical thinking by putting these skills forth while revealing the problem solving ways in a way that the computers could help. Computational thinking that is a kind of analytical thinking according to Wing makes use of the common points with the mathematical thinking at the stage of problem solving, with the engineering while designing and assessing a complex system and with the scientific thinking in understanding the concepts such as calculatability, mind, brain and human behaviors. Similarly, Curzon defines the computational thinking as a basic skill that comes to the meaning of problem solving for the human beings and points out that it is necessary to understand what the problem is before thinking of the solutions while solving a problem according to a certain point of view. According to ISTE, computational thinking covers the skills of creativity, algorithmic thinking, and critical thinking, problem solving, establishing communication and establishing cooperation. Because of this importance of it, the purpose of this study was specified as the investigation of individuals" computational thinking skill levels in terms of school type, program, grade level/graduation status, gender, and age variables. This study is in the form of descriptive survey. The participants of the study are 1306 individuals, who are the students studying in associate, bachelor, and master"s degree distance and traditional education programs of Amasya University. Within the current study, the data about computational thinking skills of the participants were collected through "Computational Thinking Skills Scale". It was developed as a five-point Likert-type scale, which consists of five factors and 29 items. The factor named as "Creativity" has 8 items and internal consistency coefficient of 0,843; "Algorithmic Thinking" factor has 6 items and internal consistency coefficient of 0,869; "Cooperativity" factor has 4 items and internal consistency coefficient of 0,865; "Critical Thinking" factor has 5 items and internal consistency coefficient of 0,784; and "Problem Solving" factor has 6 items and internal consistency coefficient of 0,727. The internal consistency coefficient for the complete scale is 0,822. The factors explain 56.1% of the variance. Mean, standard deviation, mode, median, frequency, t, ANOVA, LSD, and Correlational analyses were conducted on the collected data, the level of significance were accepted as 0.05, and the following results were revealed: The perceptions of the half of the participants pertaining to their computational thinking skills are at a high level, and that of the other half are at medium level. The programs in the School of Technology and Graduate School have more contribution to the computational thinking skill levels of the students at a significant level than the ones in the other schools of the university. It is also revealed that the programs in Mathematics, Science, and Technology departments have more contribution to the computational thinking skill levels of the students at a significant level than the ones in the other departments. As the students" grade levels increase or after the graduation, the computational thinking skills, in contrast to the expectation of increase, decrease. Gender has an influence merely on critical thinking skills. As the age level increases, individuals" computational thinking levels significantly increase.