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Found 8 papers, 2 papers with code
Learning How To Learn NLP: Developing Introductory Concepts Through Scaffolded Discovery
We present a scaffolded discovery learning approach to introducing concepts in a Natural Language Processing course aimed at computer science students at liberal arts institutions.
Reading KITTY: Pitch Range as an Indicator of Reading Skill
While affective outcomes are generally positive for the use of eBooks and computer-based reading tutors in teaching children to read, learning outcomes are often poorer (Korat and Shamir, 2004).
Harvey Mudd College at SemEval-2019 Task 4: The D.X. Beaumont Hyperpartisan News Detector
We use the 600 hand-labelled articles from SemEval Task 4 to hand-tune a classifier with 3000 features for the Hyperpartisan News Detection task.
Harvey Mudd College at SemEval-2019 Task 4: The Carl Kolchak Hyperpartisan News Detector
In particular, some of the features we look at are bag-of-words features, the title{'}s length, number of capitalized words in the title, and the sentiment of the sentences and the title.
Harvey Mudd College at SemEval-2019 Task 4: The Clint Buchanan Hyperpartisan News Detector
We investigate the recently developed Bidirectional Encoder Representations from Transformers (BERT) model for the hyperpartisan news detection task.
Generating Memorable Mnemonic Encodings of Numbers
The major system is a mnemonic system that can be used to memorize sequences of numbers.
