Predicting Item Difficulty in a Reading Comprehension Test with an Artificial Neural Network

Predicting Item Difficulty in a Reading Comprehension Test with an Artificial Neural Network [electronic resource] / Kyle Perkins and Others.

This paper reports the results of using a three-layer backpropagation artificial neural network to predict item difficulty in a reading comprehension test. Two network structures were developed, one with and one without a sigmoid function in the output processing unit. The data set, which consisted...

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Bibliographic Details
Online Access: Full Text (via ERIC)
Main Author: Perkins, Kyle
Format: Electronic eBook
Language:English
Published: [S.l.] : Distributed by ERIC Clearinghouse, 1994.
Subjects:
Artificial Intelligence.
Computer Assisted Testing.
Expert Systems.
Item Analysis.
Linguistic Theory.
Neurolinguistics.
Predictive Measurement.
Predictive Validity.
Reading Comprehension.
Test Items.
Test Reliability.

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