1,720,999 research outputs found
Sviluppo e Applicazioni di Modelli Formali per la Valutazione Adattiva della Conoscenza e dell'Apprendimento nell'Ambito della Knowledge Space Theory
Full text linkThe five studies presented in this thesis have been carried out in the area of knowledge space theory (KST), a recent mathematical theory providing an important framework for the formal development of computerized web-based systems aimed at assessing individual knowledge and learning. The basic concept at the core of the entire theory is that of knowledge state, that is the set of problems that a student is able to solve, in a certain filed of knowledge. The collection of all knowledge states that occurs in a population of students is called the knowledge structure. A knowledge structure is a deterministic model of the organization of knowledge in a particular domain. Its empirical validation is possible by a probabilistic assessment of its plausibility. The basic local independence model (BLIM) is a probabilistic model developed to this aim. Despite it is the most widely used model in KST, issues relating its applicability were open. The overall objective of the first three studies presented in this thesis was to solve some of these problems, in order to improve the validity of empirical applications of the model. In the KST framework, the notion of knowledge state does not provide cognitive interpretations. Instead, in the competence-based KST (CbKST) the main objective of the assessment becomes that of identifying the competence state of a student, which is the set of skills she masters. The other two studies that are introduced were developed within this extended theoretical framework. The general aim was to fill some gaps regarding both the probabilistic and the deterministic levels of CbKST's models
Rating, ranking or both? A joint application of two probabilistic models for the measurement of values
No full textFollowing the debate between the proponents of the ranking and rating methods for the measurement of values, this article considers the hypothesis that a person’s responses in ranking and rating tasks are governed by the same unidimensional latent trait. The hypothesis was tested through a probabilistic modeling approach. The results of a joint application of the rating scale and ranking models indicated that this latent common trait exists and seems to have a role in molding the relationship between the latent variable and the observable responses in both ranking and rating formats
Modeling Skill Dependence in Probabilistic Competence Structures
No full textIn knowledge space theory (KST) a competence structure is a set theoretical representation
of the dependencies among a given set of skills. A probabilistic model for
skill dependence is proposed which respects a precise correspondence requirement
between set theoretical and probabilistic representations of skill dependence. An
empirical application on integer subtraction problems at the primary school shows
that the proposed model fits the data pretty well. Moreover, in a comparison with
an unrestricted skill based version of the basic local independence model (BLIM),
the proposed model fits better than this last, indicating that the restrictions implied
by the correspondence requirement are not too strong
Extracting preference relations from data: Clustering with transitive centroids
Full text linkA clustering algorithm, named k-orders, is proposed to extract transitive relations from a data set. The k-orders algorithm differs from the original k-modes only in the adjustment step. Two adjustment procedures, named transitive centroid adjustment (TCA) and greedy TCA, are proposed that can be used to find clusters with transitive centroids. The proposed clustering approach finds application, especially in studies on preference, where this last may be heterogeneous across individuals, although transitive. The set of cluster centroids extracted by the algorithm from a data set can then be empirically tested via the estimation of a latent class model. The performance of the two versions of k-orders were compared to one another and with the canonical k-modes, in simulation studies. Results show that when centroids are transitive relations, both versions of k-orders outperform k-modes. Moreover, in experimental designs in which two-component options are considered, the TCA algorithm performs better than the greedy TCA. An empirical application was also carried out for exemplifying how k-orders can be useful for studying individual preferences
Algorithms for the adaptive assessment of procedural knowledge and skills
Full text linkProcedural knowledge space theory (PKST) was recently proposed by Stefanutti (British Journal of Mathematical and Statistical Psychology, 72(2) 185-218, 2019) for the assessment of human problem-solving skills. In PKST, the problem space formally represents how a family of problems can be solved and the knowledge space represents the skills required for solving those problems. The Markov solution process model (MSPM) by Stefanutti et al. (Journal of Mathematical Psychology, 103, 102552, 2021) provides a probabilistic framework for modeling the solution process of a task, via PKST. In this article, three adaptive procedures for the assessment of problem-solving skills are proposed that are based on the MSPM. Beside execution correctness, they also consider the sequence of moves observed in the solution of a problem with the aim of increasing efficiency and accuracy of assessments. The three procedures differ from one another in the assumption underlying the solution process, named pre-planning, interim-planning, and mixed-planning. In two simulation studies, the three adaptive procedures have been compared to one another and to the continuous Markov procedure (CMP) by Doignon and Falmagne (1988a). The last one accounts for dichotomous correct/wrong answers only. Results show that all the MSP-based adaptive procedures outperform the CMP in both accuracy and efficiency. These results have been obtained in the framework of the Tower of London test but the procedures can also be applied to all psychological and neuropsychological tests that have a problem space. Thus, the adaptive procedures presented in this paper pave the way to the adaptive assessment in the area of neuropsychological tests
Valutare l’apprendimento della teoria elementare della probabilità con il Gain-Loss Model
No full text- …
