Computerized adaptive test and decision trees: A unifying approach

Abstract

In the last few years, several articles have proposed decision trees (DTs) as an alternative to computerized adapted tests (CATs). These works have focused on showing the differences between the two methods with the aim of identifying the advantages of each of them and thus determining when it is preferable to use one method or another. In this article, Tree-CAT, a new technique for building CATs is presented. Unlike the existing work, Tree-CAT exploits the similarities between CATs and DTs. This technique allows the creation of CATs that minimise the mean square error in the estimation of the examinee's ability level, and controls the item's exposure rate. The decision tree is sequentially built by means of an innovative algorithmic procedure that selects the items associated with each of the tree branches by solving a linear program. In addition, our work presents further advantages over alternative item selection techniques with exposure control, such as instant item selection or simultaneous administration of the test to an unlimited number of participants. These advantages allow accurate on-line CATs to be implemented even when the item selection method is computationally costly.

Soft trees with neural components as image-processing technique for archeological excavations

“…Figure 8 presents sample results of CNN classification in decision classes on each level of soft tree. In each case for decision on the input data, we have used maximization function described in (7). The results of evaluation were compared with other results in the table to make decision.…”

“…2 In various excavation sites, many artifacts like sculptures or pottery are found, which, depending on the material of the work, the epoch from which they originate and the conditions in which they were until their discovery, need more or less professional care to classify and reconstruct them. In the above pictures, we can see artifacts from world famous places like Delphi in Greece related to Classical and Late Antiquity and artifacts from found in Malbork Castle in Poland related to Middle Ages [7] or develop incremental decision structures [24]. There are various applications like emergency management [10] or even inbound ships management which can be done with human-like intelligence [27].…”

Decision Tree Analysis for Estimating the Costs and Benefits of Disclosing Data

“…DTA is introduced for the first time in the nineteen sixties and primarily used in the data mining domain. The main role of using this method is to establish classification systems based on multiple covariates in developing a prediction of alternative variables [5,9]. A decision tree is a graphical representation of specific decisions with possible consequences of a series of related decision alternatives.…”

“…A decision tree is a graphical representation of specific decisions with possible consequences of a series of related decision alternatives. This theory allows an individual or organizations to trade-off possible actions against another action based on the probabilities of risks, benefits, and costs of a decision-making process [5,18]. DTA uses a tree-like model of decisions to drive informal discussion a method or algorithm that able to predict the alternative decisions into the numerical form [10].…”

“…The developed DTA consists of the following four steps [5,8], as follows: First, define a clear decision problem to narrow down the scope of the objective. Factors relevant to alternative solutions should be determined.…”