This seminar explores the relevance and uses of NLP in the context of language learning, combining conceptual discussion with hands-on programming tasks.

We distinguish two broad uses of NLP related to language learning (cf. Meurers 2020): On the one hand, NLP can be used to analyze learner language, i.e., words, sentences, or texts produced by language learners. This includes the development of NLP techniques for the analysis of learner language by intelligent tutoring systems in Intelligent Computer-Assisted Language Learning, automated scoring in language testing, as well as the analysis and annotation of learner corpora for researech and learning analytics. On the other hand, NLP for the analysis of native language can also play an important role in the language learning context. Applications in this second domain support the search for and the enhanced presentation of native language reading material for language learners as well as the generation of exercises and tests based on authentic materials.

Complementing the conceptual side, where we delineate the uses of NLP, motivate the relevance, and discuss current research strands, we will develop web-based applications in hands-on sessions. While for these tasks we envisage heterogeneous student teams combining different backgrounds, some programming experience is required for successful participation.

Detmar Meurers (2020). Natural Language Processing and Language Learning. The Concise Encyclopedia of Applied Linguistics, edited by Carol A. Chapelle. Wiley. 817-831. http://purl.org/dm/papers/Meurers-19.pdf

Please enroll in this course by logging into this moodle course with your ordinary ZDV university login.

Nature of course and our expectations: This is an overview-oriented Hauptseminar, in which we jointly introduce and explore the topic, perspectives and approaches. You are expected to

Academic conduct and misconduct: Research is driven by discussion and free exchange of ideas, motivations, and perspectives. So you are encouraged to work in groups, discuss, and exchange ideas. At the same time, the foundation of the free exchange of ideas is that everyone is open about where they obtained which information. Concretely, this means you are expected to always make explicit when you’ve worked on something as a team – and keep in mind that being part of a team always means sharing the work.

For text you write, you always have to provide explicit references for any ideas or passages you reuse from somewhere else. Note that this includes text “found” on the web, where you should cite the url of the web site in case no more official publication is available.

References

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