Training an NLP Scholar at a Small Liberal Arts College: A Backwards Designed Course Proposal

TL;DR

This paper proposes a backwards-designed course framework tailored for small liberal arts colleges to train NLP scholars, emphasizing critical thinking, societal understanding, and effective communication in NLP education.

Contribution

It introduces a course design approach focused on developing NLP scholars' skills, tailored to the strengths of small liberal arts college students.

Findings

Course components aligned with NLP scholar skills

Backward design methodology applied to NLP education

Enhanced focus on societal and communication aspects

Abstract

The rapid growth in natural language processing (NLP) over the last couple years has generated student interest and excitement in learning more about the field. In this paper, we present two types of students that NLP courses might want to train. First, an "NLP engineer" who is able to flexibly design, build and apply new technologies in NLP for a wide range of tasks. Second, an "NLP scholar" who is able to pose, refine and answer questions in NLP and how it relates to the society, while also learning to effectively communicate these answers to a broader audience. While these two types of skills are not mutually exclusive -- NLP engineers should be able to think critically, and NLP scholars should be able to build systems -- we think that courses can differ in the balance of these skills. As educators at Small Liberal Arts Colleges, the strengths of our students and our institution favors an approach that is better suited to train NLP scholars. In this paper we articulate what kinds of skills an NLP scholar should have, and then adopt a backwards design to propose course components that can aid the acquisition of these skills.