Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|

item information function | 0.46 | 0.8 | 5877 | 38 | 25 |

item | 0.53 | 0.1 | 3218 | 77 | 4 |

information | 0.07 | 0.4 | 6913 | 71 | 11 |

function | 0.96 | 0.8 | 242 | 8 | 8 |

Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|

item information function | 0.02 | 0.8 | 3722 | 25 |

irt item information function | 1.79 | 0.9 | 8061 | 13 |

Under a 2PL model, the item information function is defined as: where a i is the discrimination parameter for item i. You can see that the 1PL is exactly the same as a 2PL model when the value of the discrimination ( a parameter) is set to 1.

θ is the ability level of interest. D is the constant of 1.702 Under a 2PL model, the item information function is defined as: where a i is the discrimination parameter for item i.

The item response function. The IRF gives the probability that a person with a given ability level will answer correctly. Persons with lower ability have less of a chance, while persons with high ability are very likely to answer correctly; for example, students with higher math ability are more likely to get a math item correct.

It is to be noted that the amount of information at a given ability level is the inverse of its variance, hence, the larger the amount of information provided by the item, the greater the precision of the measurement. As item information is plotted against ability, a revealing graph depicts the amount of information provided by the item.