Evidence map›Paper›PMID 36526887›Full record

ArticleBehavior research methods2023

Algorithms for the adaptive assessment of procedural knowledge and skills.

Andrea Brancaccio, Debora de Chiusole, Luca Stefanutti

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Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Andrea BrancaccioDepartment of Philosophy, Sociology, Pedagogy, and Applied Psychology, University of Padua, Via Venezia, 14, 35131, Padova, Italy. andrea.brancaccio@unipd.it.ORCID 0000-0001-5919-6990
Debora de ChiusoleDepartment of Philosophy, Sociology, Pedagogy, and Applied Psychology, University of Padua, Via Venezia, 14, 35131, Padova, Italy.
Luca StefanuttiDepartment of Philosophy, Sociology, Pedagogy, and Applied Psychology, University of Padua, Via Venezia, 14, 35131, Padova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Procedural 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.

Indexed as

AlgorithmsProblem SolvingComputer SimulationHumansMarkov ChainsMathematicsNeuropsychological TestsAdaptive assessmentMarkov modelsProblem spaceProcedural knowledge space theoryTower of London test

Identifiers

PMID36526887
PMCPMC10616228

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