# kassess: Assess Individuals In kst: Knowledge Space Theory

## Description

Assigns individuals to their corresponding knowledge states.

## Usage

 1 kassess(x, rpatterns=NULL, method="deterministic")

## Arguments

 x An R object of class kstructure. rpatterns A binary data frame or matrix where each row specifies the response pattern of one individual to the set of domain problems in x. method The desired assessment method. Currently only "deterministic" assessment is implemented.

## Details

kassess assigns individuals to their corresponding knowledge state in a knowledge structure.

Assessing individuals based on a "deterministic" procedure starts by determining a domain problem a, which is contained in approximately half of the available knowledge states. If the individual being assessed has successfully solved the respective domain problem a, all knowledge states that do not contain domain problem a are removed from the set of potential knowledge states of the individual. If, on the other hand, the individual has not solved the respective domain problem a, all knowledge states that do contain domain problem a are removed from the set of potential knowledge states of the individual. From the remaining knowledge states a domain problem b, which again is contained in approximately half of the still available knowledge states, is selected. If the individual has successfully solved the respective domain problem b, all knowledge states that do not contain domain problem b are removed from the set of potential knowledge states of the individual. If, on the other hand, the individual has solved the respective domain problem b, all knowledge states that do contain domain problem b are removed from the set of potential knowledge states of the individual. This procedure is repeated until only one knowledge state is left. This is the knowledge state the individual is currently located in.

## Value

A list where each element represents the knowledge state of one respondent.

## References

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

## Examples

 1 2 3 4 5 6 # deterministic assessment kst <- kstructure(set(set("a"), set("a","b"), set("a","c"), set("d","e"), set("a","b","d","e"), set("a","c","d","e"), set("a","b","c","d","e"))) rp <- data.frame(a=c(1,1,0,1,1,1,1,0,0,0),b=c(0,1,0,1,0,1,0,1,0,0), c=c(0,0,0,0,1,1,1,0,1,0),d=c(0,0,1,1,1,1,0,0,0,1), e=c(0,0,1,1,1,1,0,0,0,0)) kassess(kst, rpatterns=rp, method="deterministic")

### Example output

Attaching package: 'proxy'

The following objects are masked from 'package:stats':

as.dist, dist

The following object is masked from 'package:base':

as.matrix

\$Respondent1
{"a"}

\$Respondent2
{"a", "b"}

\$Respondent3
{"d", "e"}

\$Respondent4
{"a", "b", "d", "e"}

\$Respondent5
{"a", "c", "d", "e"}

\$Respondent6
{"a", "b", "c", "d", "e"}

\$Respondent7
{"a", "c"}

\$Respondent8
{"a", "b"}

\$Respondent9
{"a", "c"}

\$Respondent10
{"d", "e"}

kst documentation built on April 13, 2018, 5:06 p.m.