99815 - Languages and Teaching Lab

Learning outcomes

The student knows the basic principles of teaching specific languages and/or language-related subjects in one or more settings; s/he is able to identify relevant learning and/or evaluation objectives, plan activities, and create didactic materials with the support of appropriate tools

Course contents

The activities of this seminar revolve around the research carried out as part of the PRIN project "UNITE –UNiversally Inclusive Technologies to practice English".

The aim of UNITE is to explore the applications of Dialogue Systems (DS) as agents to practice English as a Foreign Language (EFL). DS include, among others, chatbots based on large language model such as ChatGPT e Pi.ai. The ultimate objective of UNITE is to produce teaching and learning materials which favour the uptake of DS as tools for autonomous language learning by university students, including those with disability and specific learning disorders.

At present, the project has led to the creation of a learner corpus of over 300 interactions between learners and DS, collected with the help of SpecTra and TraTec students from the 2023/24 and 2024/25 academic year (more information here).

Course participants will be actively involved in ongoing activities carried out within the project, including:

• testing of chatbots for language learning;
  
• linguistic analysis of learner-DS interactions based on the annotated corpus;
  
• design and creation of teaching materials based on the corpus analysis for the use of chatbots as tools for language learning.

Readings/Bibliography

• Bibauw, S., W. Van Den Noortgate, T. François and P. Desmet (2022). Dialogue systems for language learning: a meta-analysis. Language Learning & Technology, 26(1). https://doi.org/10.4324/9781351117586-12
• Huang, W., K. Foon Hew and L. Fryer (2022). Chatbots for language learning — Are they really useful?. Journal of Computer Assisted Learning, 38(1). https://doi.org/10.1111/jcal.12610
• Gilquin, G. (2020). Learner corpora. In M. Paquot and S.Th. Gries (eds.), A Practical Handbook of Corpus Linguistics. Springer, 283-304.
• Lüdeling, A. and H. Hirschmann (2015). Error annotation systems. In S. Granger, G. Gilquin and F. Meunier (eds.), The Cambridge Handbook of Learner Corpus Research. Cambridge University Press, 135-158.

Teaching methods

The seminar combines frontal lectures and practice-based sessions.

Theoretical and methodological contents (e.g. on language learning through the use DS, corpus annotation and learner language) are delivered through presentations by the lecturer.

The practical sessions consist of hands-on activities, which are carried out collaboratively in class or individually as assignments, and are followed by group discussion. The activities are aimed at constantly monitoring progress in the development of the research and technological skills that make the object of the seminar.

All students must attend Module 1 and 2 on Health and Safety online.

Assessment methods

Assessment will be partly in itinere and partly based on a final project.

The in itinere assessment is based on observation of students' participation in the course activities (including assignments to be handed in during the semester). For those who do not hand in assignments, the final mark is entirely based on the final project.

The final project, whose content and format will be agreed upon with the instructors, will involve creating teaching materials based on authentic language data (drawn from corpora), accompanied by a brief technical report or an oral presentation with slides.

Assessment criteria:

• 30-30L: excellent project work, displaying very high technical quality, presented in a very clear and detailed way.
• 28-29: excellent project work, displaying high technical quality, presented in a clear and detailed way.
• 26-27: good project work, displaying adequate technical quality; some aspects of the presentation could be improved.
  
• 23-25: fair project work, displaying technical shortcomings; some aspects of the presentation could be improved.
• 20-22: project work displays technical shortcomings; presentation has gaps or is unclear at several points.
• 18-20: project work displays several major technical shortcomings; presentation has many gaps and/or is mostly unclear.
• <18: insufficient or severely insufficient project work.

Students with specific learning difficulties (SpLD) or with disabilities that can affect their ability to attend courses are invited to contact the University service for students with disabilities and SLD at the earliest opportunity – ideally before the start of the course). The University service will suggest possible adjustments to the course work and/or exam, which must then be submitted to the course leader so they can assess their feasibility, in line with the learning objectives of the course. Please note that adjustments to the exam must be requested at least two weeks in advance.

Teaching tools

Hardware: PC and overhead projector.

Software: Web-based and mobile Dialogue Systems; text editors to process textual data; corpus consultation software; graphic content creation software (e.g. Canva).

Office hours

See the website of Adriano Ferraresi