Using a neural network to predict student responses

Susan Mengel, William Lively

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations


One of the important components in an intelligent tutoring system is the student model. This model is used to predict what the student may do next as well as to serve as a repository of past student solutions. The student model is important in that it can help to direct the student to unknown material when enough concepts have been mastered and to material that needs to be reviewed when the student is unsure. Some student models have tried to predict student solution steps by restricting the interface to the point where the student cannot make an unknown move. Others do not concentrate on prediction, but instead concentrate on remedying errors in problem solutions. Since the problem of prediction is difficult, another tool, the neural network, should prove useful. Neural networks have the ability to generalize over a set of student answers. This ability gives the network the capacity to answer as the student would on problems that the network have never seen before. Given this exciting possibility, research has been started using the backpropagation model of neural networks to learn a student's method in performing subtraction. The preliminary results reported in this paper are encouraging and serve to show the promise of neural networks in the student model of intelligent tutoring systems.

Original languageEnglish
Title of host publicationApplied Computing
Subtitle of host publicationTechnological Challenges of the 1990's
PublisherPubl by ACM
Number of pages8
ISBN (Print)089791502X, 9780897915021
StatePublished - 1992
EventProceedings of the 1992 ACM/SIGAPP Symposium on Applied Computing SAC '92 - Kansas City, KS, USA
Duration: Mar 1 1992Mar 3 1992

Publication series

NameApplied Computing: Technological Challenges of the 1990's


ConferenceProceedings of the 1992 ACM/SIGAPP Symposium on Applied Computing SAC '92
CityKansas City, KS, USA


Dive into the research topics of 'Using a neural network to predict student responses'. Together they form a unique fingerprint.

Cite this