Teaching NLP outside Linguistics and Computer Science classrooms: Some challenges and some opportunities

• URL: http://arxiv.org/abs/2105.00895v1
• Date: Mon, 3 May 2021 14:30:32 GMT
• Title: Teaching NLP outside Linguistics and Computer Science classrooms: Some challenges and some opportunities
• Authors: Sowmya Vajjala
• Abstract summary: People using NLP methods in a range of academic disciplines from Asian Studies to Clinical Oncology. We also notice the presence of NLP as a module in most of the data science curricula within and outside of regular university setups. This paper takes a closer look at some issues related to teaching NLP to these diverse audiences based on my classroom experiences.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: NLP's sphere of influence went much beyond computer science research and the development of software applications in the past decade. We see people using NLP methods in a range of academic disciplines from Asian Studies to Clinical Oncology. We also notice the presence of NLP as a module in most of the data science curricula within and outside of regular university setups. These courses are taken by students from very diverse backgrounds. This paper takes a closer look at some issues related to teaching NLP to these diverse audiences based on my classroom experiences, and identifies some challenges the instructors face, particularly when there is no ecosystem of related courses for the students. In this process, it also identifies a few challenge areas for both NLP researchers and tool developers.

Related papers

• The Nature of NLP: Analyzing Contributions in NLP Papers [77.31665252336157]
  We quantitatively investigate what constitutes NLP research by examining research papers. Our findings reveal a rising involvement of machine learning in NLP since the early nineties. In post-2020, there has been a resurgence of focus on language and people.
  arXiv  Detail & Related papers  (2024-09-29T01:29:28Z)
• Training an NLP Scholar at a Small Liberal Arts College: A Backwards Designed Course Proposal [3.669471689849522]
  Two types of students that NLP courses might want to train. "NLP engineer" able to flexibly design, build and apply new technologies in NLP. "NLP scholar" able to pose, refine and answer questions in NLP and how it relates to the society.
  arXiv  Detail & Related papers  (2024-08-11T00:50:59Z)
• Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trends [26.90343340881045]
  We review recent advances in NLP with the focus on solving problems relevant to the education domain. We present a taxonomy of NLP in the education domain and highlight typical NLP applications including question answering, question construction, automated assessment, and error correction. We conclude with six promising directions for future research, including more datasets in education domain, controllable usage of LLMs, intervention of difficulty-level control, interpretable educational NLP, methods with adaptive learning, and integrated systems for education.
  arXiv  Detail & Related papers  (2024-01-15T07:48:42Z)
• UKP-SQuARE: An Interactive Tool for Teaching Question Answering [61.93372227117229]
  The exponential growth of question answering (QA) has made it an indispensable topic in any Natural Language Processing (NLP) course. We introduce UKP-SQuARE as a platform for QA education. Students can run, compare, and analyze various QA models from different perspectives.
  arXiv  Detail & Related papers  (2023-05-31T11:29:04Z)
• Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good [115.1507728564964]
  We introduce NLP4SG Papers, a scientific dataset with three associated tasks. These tasks help identify NLP4SG papers and characterize the NLP4SG landscape. We use state-of-the-art NLP models to address each of these tasks and use them on the entire ACL Anthology.
  arXiv  Detail & Related papers  (2023-05-09T14:16:25Z)
• A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing [68.37496795076203]
  We provide guidance for NLP researchers and practitioners dealing with imbalanced data. We first discuss various types of controlled and real-world class imbalance. We organize the methods by whether they are based on sampling, data augmentation, choice of loss function, staged learning, or model design.
  arXiv  Detail & Related papers  (2022-10-10T13:26:40Z)
• Meta Learning for Natural Language Processing: A Survey [88.58260839196019]
  Deep learning has been the mainstream technique in natural language processing (NLP) area. Deep learning requires many labeled data and is less generalizable across domains. Meta-learning is an arising field in machine learning studying approaches to learn better algorithms.
  arXiv  Detail & Related papers  (2022-05-03T13:58:38Z)
• The interdisciplinary quantum information classroom: Themes from a survey of quantum information science instructors [0.0]
  Interdisciplinary introduction to quantum information science (QIS) courses are proliferating at universities across the US. We report on the findings of a survey of instructors teaching introduction to QIS courses at institutions across the US.
  arXiv  Detail & Related papers  (2022-02-12T00:37:58Z)
• Systematic Inequalities in Language Technology Performance across the World's Languages [94.65681336393425]
  We introduce a framework for estimating the global utility of language technologies. Our analyses involve the field at large, but also more in-depth studies on both user-facing technologies and more linguistic NLP tasks.
  arXiv  Detail & Related papers  (2021-10-13T14:03:07Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.