  The advent of the Internet and a large number of digital technologies has
brought with it many different challenges. A large amount of data is found on
the web, which in most cases is unstructured and unorganized, and this
contributes to the fact that the use and manipulation of this data is quite a
difficult process. Due to this fact, the usage of different machine and deep
learning techniques for Text Classification has gained its importance, which
improved this discipline and made it more interesting for scientists and
researchers for further study. This paper aims to classify the pedagogical
content using two different models, the K-Nearest Neighbor (KNN) from the
conventional models and the Long short-term memory (LSTM) recurrent neural
network from the deep learning models. The result indicates that the accuracy
of classifying the pedagogical content reaches 92.52 % using KNN model and
87.71 % using LSTM model.
