Proceedings of the Fifth Workshop on Teaching NLP

David Jurgens, Varada Kolhatkar, Lucy Li, Margot Mieskes, Ted Pedersen (Editors)


Anthology ID:
2021.teachingnlp-1
Month:
June
Year:
2021
Address:
Online
Venues:
NAACL | TeachingNLP
SIG:
Publisher:
Association for Computational Linguistics
URL:
https://aclanthology.org/2021.teachingnlp-1
DOI:
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PDF:
https://aclanthology.org/2021.teachingnlp-1.pdf

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Proceedings of the Fifth Workshop on Teaching NLP
David Jurgens | Varada Kolhatkar | Lucy Li | Margot Mieskes | Ted Pedersen

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Teaching a Massive Open Online Course on Natural Language Processing
Ekaterina Artemova | Murat Apishev | Denis Kirianov | Veronica Sarkisyan | Sergey Aksenov | Oleg Serikov

In this paper we present a new Massive Open Online Course on Natural Language Processing, targeted at non-English speaking students. The course lasts 12 weeks, every week consists of lectures, practical sessions and quiz assigments. Three weeks out of 12 are followed by Kaggle-style coding assigments. Our course intents to serve multiple purposes : (i) familirize students with the core concepts and methods in NLP, such as language modelling or word or sentence representations, (ii) show that recent advances, including pre-trained Transformer-based models, are build upon these concepts ; (iii) to introduce architectures for most most demanded real-life applications, (iii) to develop practical skills to process texts in multiple languages. The course was prepared and recorded during 2020 and so far have received positive feedback.

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Natural Language Processing 4 All (NLP4All): A New Online Platform for Teaching and Learning NLP ConceptsNLP4All): A New Online Platform for Teaching and Learning NLP Concepts
Rebekah Baglini | Hermes Hjorth

Natural Language Processing offers new insights into language data across almost all disciplines and domains, and allows us to corroborate and/or challenge existing knowledge. The primary hurdles to widening participation in and use of these new research tools are, first, a lack of coding skills in students across K-16, and in the population at large, and second, a lack of knowledge of how NLP-methods can be used to answer questions of disciplinary interest outside of linguistics and/or computer science. To broaden participation in NLP and improve NLP-literacy, we introduced a new tool web-based tool called Natural Language Processing 4 All (NLP4All). The intended purpose of NLP4All is to help teachers facilitate learning with and about NLP, by providing easy-to-use interfaces to NLP-methods, data, and analyses, making it possible for non- and novice-programmers to learn NLP concepts interactively.

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A New Broad NLP Training from Speech to KnowledgeNLP Training from Speech to Knowledge
Maxime Amblard | Miguel Couceiro

In 2018, the Master Sc. in NLP opened at IDMC-Institut des Sciences du Digital, du Management et de la Cognition, Universit de Lorraine-Nancy, France. Far from being a creation ex-nihilo, it is the product of a history and many reflections on the field and its teaching. This article proposes epistemological and critical elements on the opening and maintainance of this so far new master’s program in NLP.

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A Crash Course on Ethics for Natural Language Processing
Annemarie Friedrich | Torsten Zesch

It is generally agreed upon in the natural language processing (NLP) community that ethics should be integrated into any curriculum. Being aware of and understanding the relevant core concepts is a prerequisite for following and participating in the discourse on ethical NLP. We here present ready-made teaching material in the form of slides and practical exercises on ethical issues in NLP, which is primarily intended to be integrated into introductory NLP or computational linguistics courses. By making this material freely available, we aim at lowering the threshold to adding ethics to the curriculum. We hope that increased awareness will enable students to identify potentially unethical behavior.

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MiniVQA-A resource to build your tailored VQA competitionMiniVQA - A resource to build your tailored VQA competition
Jean-Benoit Delbrouck

MiniVQA is a Jupyter notebook to build a tailored VQA competition for your students. The resource creates all the needed resources to create a classroom competition that engages and inspires your students on the free, self-service Kaggle platform. InClass competitions make machine learning fun ‘.

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A Balanced and Broadly Targeted Computational Linguistics Curriculum
Emma Manning | Nathan Schneider | Amir Zeldes

This paper describes the primarily-graduate computational linguistics and NLP curriculum at Georgetown University, a U.S. university that has seen significant growth in these areas in recent years. We reflect on the principles behind our curriculum choices, including recognizing the various academic backgrounds and goals of our students ; teaching a variety of skills with an emphasis on working directly with data ; encouraging collaboration and interdisciplinary work ; and including languages beyond English. We reflect on challenges we have encountered, such as the difficulty of teaching programming skills alongside NLP fundamentals, and discuss areas for future growth.

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The Flipped Classroom model for teaching Conditional Random Fields in an NLP courseNLP course
Manex Agirrezabal

In this article, we show and discuss our experience in applying the flipped classroom method for teaching Conditional Random Fields in a Natural Language Processing course. We present the activities that we developed together with their relationship to a cognitive complexity model (Bloom’s taxonomy). After this, we provide our own reflections and expectations of the model itself. Based on the evaluation got from students, it seems that students learn about the topic and also that the method is rewarding for some students. Additionally, we discuss some shortcomings and we propose possible solutions to them. We conclude the paper with some possible future work.

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An Immersive Computational Text Analysis Course for Non-Computer Science Students at Barnard College
Adam Poliak | Jalisha Jenifer

We provide an overview of a new Computational Text Analysis course that will be taught at Barnard College over a six week period in May and June 2021. The course is targeted to non Computer Science at a Liberal Arts college that wish to incorporate fundamental Natural Language Processing tools in their re- search and studies. During the course, students will complete daily programming tutorials, read and review contemporary research papers, and propose and develop independent research projects.

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Learning How To Learn NLP : Developing Introductory Concepts Through Scaffolded DiscoveryNLP: Developing Introductory Concepts Through Scaffolded Discovery
Alexandra Schofield | Richard Wicentowski | Julie Medero

We present a scaffolded discovery learning approach to introducing concepts in a Natural Language Processing course aimed at computer science students at liberal arts institutions. We describe some of the objectives of this approach, as well as presenting specific ways that four of our discovery-based assignments combine specific natural language processing concepts with broader analytic skills. We argue this approach helps prepare students for many possible future paths involving both application and innovation of NLP technology by emphasizing experimental data navigation, experiment design, and awareness of the complexities and challenges of analysis.

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

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.