How can we best estimate the amount of time a keyword is discussed in a course?
The function loads the lecture transcripts for a specific MADS course (using the course ID) from the database. Each function estimates the keyword’s frequency using different algorithms
WG#: Experimental Group
Perry Samson, Kevyn Collins-Thompson, Thomas Horak
and Vanessa Woods
Figure 1: Perry, Samson. LearningClues Vision Statement. PDF file. August, 2022
ALGORITHMS
ACKNOWLEDGEMENTS & CITATIONS
CLUE: Contextual Linkaging for Undergraduate Education
INTRODUCTION
The LearningClues project consists of a database of class sessions, utilizing Natural Language Processing to analyze the lecture's transcripts to identify words and phrases that are mentioned in class. It plays a key role in the students' learning environment as links are automatically generated between the keywords and phrases that refer to specific instances in the course textbook, articles, other activities and educational resources. This learning aid makes access to relevant information more readily available as the search engine provides further support and improves studying efficiency. Think Google for the classroom. This solution will give academic institutions a mechanism to dynamically link learning tools according to context, increasing the quality and effectiveness of their current curriculum.
TASK OVERVIEW
FUTURE DIRECTIONS
Marina Butitova
frequency.py:
Figure 1:
EX:
https://hgrckqfo4f.execute-api.us-east-2.amazonaws.com/dev/api/search/?canvasSiteId=197&q=climate
1st draft: