All teachers of programming find that their results display a 'double hump'. It is as if there are two populations: those who can [program], and those who cannot [program], each with its own independent bell curve. Almost all research into programming teaching and learning have concentrated on teaching: change the language, change the application area, use an IDE and work on motivation. None of it works, and the double hump persists. We have a test which picks out the population that can program, before the course begins. We can pick apart the double hump. You probably don't believe this, but you will after you hear the talk. We don't know exactly how/why it works, but we have some good theories.
The team found that students remembered the pairs much better when they first tried to retrieve the answer before it was shown to them. In a way this pretesting effect is counterintuitive: Studying a pair for 13 seconds produces worse recall than studying the pair for 5 seconds, if students in the latter condition spent the previous 8 seconds trying to retrieve or guess the answer. But the effect averaged about 10 percent better recall, and occurred both immediately after study and after a delay averaging 38 hours.
Short introduction to Vector Space Model (VSM) In information retrieval or text mining, the term frequency - inverse document frequency also called tf-idf, is
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.