“…Computer Adaptive Testing -CAT- (Chen, Chao and Chen, 2019) has revolutionized the traditional way of evaluating, since it dynamically selects and manages the most appropriate questions depending on the previous answers given by the examinees. One of the central components of a CAT is the item selection criterion (Miyazahua and Ueno, 2019), although the most widely used criterion is Fisher's Maximum Information (Albano et al, 2019), it presents several weaknesses that generate a certain degree of mistrust, for example, bias in the item selection, estimation errors at the start of the exam, or the same question being displayed repeatedly to the tested one (Sheng, Bingwei and Jiecheng, 2018;Du, Li and Chang, 2018;Lin and Chang, 2019;Yigit, Sorrel and de la Torre, 2019;Ye and Sun, 2018). Therefore, in this paper the development of a CAT system that uses association rules for the selection of items is proposed, focusing on using the potential advantages of association rules to find relationships between the questions answered correctly or incorrectly and the questions answered correctly, and thus present the most appropriate questions (most likely to answer correctly) in the tests, according to the responses of the evaluated, considering the best rules (stored in the database of students who submitted the same test previously) with greater support and confidence.…”