An Investigation into the Pedagogical Features of Documents

TL;DR

This paper introduces the concept of pedagogical roles in documents to computationally analyze their educational utility, creating an annotated corpus and testing baseline prediction methods for these roles.

Contribution

It defines pedagogical roles, creates the first annotated corpus for these roles, and evaluates baseline NLP techniques for automatic role prediction.

Findings

Successfully annotated a corpus of pedagogical roles

Baseline models can predict pedagogical roles with moderate accuracy

Provides a foundation for future research on educational document analysis

Abstract

Characterizing the content of a technical document in terms of its learning utility can be useful for applications related to education, such as generating reading lists from large collections of documents. We refer to this learning utility as the "pedagogical value" of the document to the learner. While pedagogical value is an important concept that has been studied extensively within the education domain, there has been little work exploring it from a computational, i.e., natural language processing (NLP), perspective. To allow a computational exploration of this concept, we introduce the notion of "pedagogical roles" of documents (e.g., Tutorial and Survey) as an intermediary component for the study of pedagogical value. Given the lack of available corpora for our exploration, we create the first annotated corpus of pedagogical roles and use it to test baseline techniques for automatic prediction of such roles.