A computer-implemented method for training of a machine learning model for generating a trained machine learning model to determine a confidence value during at least one test cycle of a vision testing procedure, wherein the computer-implemented method is implemented as at least one computer program, wherein the confidence value is designated for determining at least one action in at least one subsequent test cycle of the vision testing procedure; comprising the following steps, which are performed by using the computer program: a) providing training data, comprising - first information about at least one behavior of a person during at least one test cycle of a vision testing procedure, wherein the at least one behavior of the person as provided by the first information is recorded from an observation of the person during a time interval after the person is queried to solve at least one task by providing an expected response; - second information about at least one known confidence value; b) determining at least one confidence value of the person, wherein the confidence value is a measure of a confidence level of the person at providing the expected response, by analyzing the first information, using the machine learning model, and determining a deviation between the determined confidence value and the at least one known confidence value as provided by the second information; c) adjusting the machine learning model in order to minimize the deviation between the determined confidence value and the at least one known confidence value by changing at least one parameter of the machine learning model; wherein the steps a) to c) are repeated until a determination criterion is met that, when met, leads to a termination of the training of the machine learning model, wherein the at least one parameter of the machine learning model that resulted by determining a minimal deviation is used in the trained machine learning model. a) providing training data, comprising - first information about at least one behavior of a person during at least one test cycle of a vision testing procedure, wherein the at least one behavior of the person as provided by the first information is recorded from an observation of the person during a time interval after the person is queried to solve at least one task by providing an expected response; - second information about at least one known confidence value; - first information about at least one behavior of a person during at least one test cycle of a vision testing procedure, wherein the at least one behavior of the person as provided by the first information is recorded from an observation of the person during a time interval after the person is queried to solve at least one task by providing an expected response; - second information about at least one known confidence value; b) determining at least one confidence value of the person, wherein the confidence value is a measure of a confidence level of the person at providing the expected response, by analyzing the first information, using the machine learning model, and determining a deviation between the determined confidence value and the at least one known confidence value as provided by the second information; c) adjusting the machine learning model in order to minimize the deviation between the determined confidence value and the at least one known confidence value by changing at least one parameter of the machine learning model;