Applying machine learning to analyse teachers' instructional questions
by Anwar Ali Yahya; Mohammad Said El Bashir
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 6, No. 4, 2014

Abstract: This paper introduces machine learning approaches to a new application in the field of education. More specifically, it explores the effectiveness of three machine learning approaches, namely, k-nearest neighbours, naïve Bayes, and support vector machines with term frequency as term selection approach, on the task of evaluating teaching effectiveness by classifying teachers' classroom questions into different cognitive levels identified in Bloom's taxonomy. In doing so, a dataset of questions has been collected and annotated manually with Bloom's cognitive levels. Several steps of pre-processing have been applied to convert these questions into a representation suitable for machine learning approaches. Using the dataset, the performance of the machine learning approaches and the traditional rule-based approach have been evaluated. The obtained results lead to several conclusions: First, machine learning approaches have a superior performance over rule-based approach. Second, the term frequency as a term selection approach plays a crucial rule in the performance of machine learning approaches. Third, SVM shows a superior performance over k-nearest neighbour and naïve Bayes which shows a comparable performance in term of F-measure and accuracy. Finally, machine learning approaches show different levels of sensitivity to the number of terms used in question representation.

Online publication date: Sat, 24-Jan-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email