DAKS-package: Data Analysis and Knowledge Spaces: The R Package DAKS
In DAKS: Data Analysis and Knowledge Spaces

Description Details Author(s) References

The package DAKS implements three inductive item tree analysis algorithms for deriving quasi orders from binary data, the original, corrected, and minimized corrected algorithms. It provides functions for computing population and estimated asymptotic variances of the diff fit measures, and for switching between test item and knowledge state representations. Other features are a Hasse diagram drawing device, a data and quasi order simulation tool based on a finite mixture latent variable model, and a function for computing response pattern and knowledge state frequencies.

Package:	DAKS
Type:	Package
Version:	2.1-3
Date:	2016-06-05
License:	GPL (>= 2)

Knowledge space theory is a recent psychometric test theory based on combinatorial mathematical structures (order and lattice theory); see Doignon and Falmagne (1999). Solvability dependencies between dichotomous test items play an important role in knowledge space theory. Utilizing hypothesized dependencies between items, knowledge space theory has been successfully applied for the computerized, adaptive assessment and training of knowledge. For instance, see the ALEKS system, a fully automated math tutor on the Internet (http://www.aleks.com/).

The package DAKS is implemented based on the S3 system. It comes with a namespace and consists of the following functions (all functions are external, there are no internal functions): corr_iita, hasse, iita, imp2state, ind_gen, mini_iita, ob_counter, orig_iita, pattern, pop_iita, pop_variance, print.iita, print.pat, print.popiita, print.summpopiita, print.ztest, simu, state2imp, summary.iita, summary.popiita, variance, and z_test. There is an empirical dataset, pisa, accompanying the package DAKS. This dataset is part of the 2003 Programme for International Student Assessment (PISA; http://www.pisa.oecd.org/).

Anatol Sargin, Ali Uenlue

Maintainer: Ali Uenlue ali.uenlue@tum.de

Doignon, J.-P. and Falmagne, J.-C. (1999) Knowledge Spaces. Berlin, Heidelberg, and New York: Springer-Verlag.

Sargin, A. and Uenlue, A. (2009) Inductive item tree analysis: Corrections, improvements, and comparisons. Mathematical Social Sciences, 58, 376–392.

Schrepp, M. (1999) On the empirical construction of implications between bi-valued test items. Mathematical Social Sciences, 38, 361–375.

Schrepp, M. (2003) A method for the analysis of hierarchical dependencies between items of a questionnaire. Methods of Psychological Research, 19, 43–79.

Uenlue, A. and Sargin, A. (2010) DAKS: An R package for data analysis methods in knowledge space theory. Journal of Statistical Software, 37(2), 1–31. URL http://www.jstatsoft.org/v37/i02/.

DAKS documentation built on May 2, 2019, 6:43 a.m.