@inproceedings{joshi-etal-2024-striking-balance,
title = "Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy",
author = "Joshi, Aditya and
Renzella, Jake and
Bhattacharyya, Pushpak and
Jha, Saurav and
Zhang, Xiangyu",
editor = {Al-azzawi, Sana and
Biester, Laura and
Kov{\'a}cs, Gy{\"o}rgy and
Marasovi{\'c}, Ana and
Mathur, Leena and
Mieskes, Margot and
Weissweiler, Leonie},
booktitle = "Proceedings of the Sixth Workshop on Teaching NLP",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.teachingnlp-1.4",
pages = "23--32",
abstract = "While deep learning approaches represent the state-of-the-art of natural language processing (NLP) today, classical algorithms and approaches still find a place in NLP textbooks and courses of recent years. This paper discusses the perspectives of conveners of two introductory NLP courses taught in Australia and India, and examines how classical and deep learning approaches can be balanced within the lecture plan and assessments of the courses. We also draw parallels with the objects-first and objects-later debate in CS1 education. We observe that teaching classical approaches adds value to student learning by building an intuitive understanding of NLP problems, potential solutions, and even deep learning models themselves. Despite classical approaches not being state-of-the-art, the paper makes a case for their inclusion in NLP courses today.",
}
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%0 Conference Proceedings
%T Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy
%A Joshi, Aditya
%A Renzella, Jake
%A Bhattacharyya, Pushpak
%A Jha, Saurav
%A Zhang, Xiangyu
%Y Al-azzawi, Sana
%Y Biester, Laura
%Y Kovács, György
%Y Marasović, Ana
%Y Mathur, Leena
%Y Mieskes, Margot
%Y Weissweiler, Leonie
%S Proceedings of the Sixth Workshop on Teaching NLP
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F joshi-etal-2024-striking-balance
%X While deep learning approaches represent the state-of-the-art of natural language processing (NLP) today, classical algorithms and approaches still find a place in NLP textbooks and courses of recent years. This paper discusses the perspectives of conveners of two introductory NLP courses taught in Australia and India, and examines how classical and deep learning approaches can be balanced within the lecture plan and assessments of the courses. We also draw parallels with the objects-first and objects-later debate in CS1 education. We observe that teaching classical approaches adds value to student learning by building an intuitive understanding of NLP problems, potential solutions, and even deep learning models themselves. Despite classical approaches not being state-of-the-art, the paper makes a case for their inclusion in NLP courses today.
%U https://aclanthology.org/2024.teachingnlp-1.4
%P 23-32
Markdown (Informal)
[Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy](https://aclanthology.org/2024.teachingnlp-1.4) (Joshi et al., TeachingNLP-WS 2024)
ACL