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The advent of the Internet and a large number of digital technologies hasbrought with it many different challenges. A large amount of data is found onthe web, which in most cases is unstructured and unorganized, and thiscontributes to the fact that the use and manipulation of this data is quite adifficult process. Due to this fact, the usage of different machine and deeplearning techniques for Text Classification has gained its importance, whichimproved this discipline and made it more interesting for scientists andresearchers for further study. This paper aims to classify the pedagogicalcontent using two different models, the K-Nearest Neighbor (KNN) from theconventional models and the Long short-term memory (LSTM) recurrent neuralnetwork from the deep learning models. The result indicates that the accuracyof classifying the pedagogical content reaches 92.52 % using KNN model and87.71 % using LSTM model.

Classification of Pedagogical content using conventional machine learning and deep learning model