Syllabi Information Literacy Miner

Abstract

Syllabi Information Literacy Miner Hosted on Google Colab https://colab.research.google.com/drive/1N778ot87GI-wJSQHpjRJWkplL4NL5HWb?usp=sharing Purpose: Automatically mine academic syllabi for information literacy (IL) components in order to identify opportunities for liaison librarians to engage with courses. While this Jupyter Notebook can be used as a standalone tool, Baylor University Libraries also maintains a Power BI report that also identifies which courses liaison libraries are already providing instruction. This allows liaison librarians to to identify new IL opportunities with some measure of precision. Overview of Jupyter Notebook Procedures: Load syllabi by uploading files or providing URL to .zip archive Convert syllabi to text format (using textract) IL components are identified by finding verb fragments with the presence of nouns within the specified number of context words The types of IL learning is then identified based on the verb. Types include Library Basics, Research Basics, Research in the Disciplines. Outputs: Pie chart showing proportion of the three IL learning types Column chart showing counts of IL components (verbs with context nouns) Table showing the types of learning identified for each syllabi Table showing each granular IL component for each syllabi. This table is also automatically downloaded as an Excel spreadsheet. Permissions (Copyright 2021 Baylor University Libraries) Use: Licensed under the MIT License - https://opensource.org/licenses/MIT. Citation: Publications and research reports should include the following citation: Joshua Been, Amy James, and Beth Farwell. Syllabi Information Literacy Miner. Waco, TX: Baylor University Libraries. 2021.