This version of the course guide is provisional until the period for editing the new course guides ends.

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Language Technologies Applied to English Studies

Code: 45347 ECTS Credits: 5
2024/2025
Degree Type Year
3500084 English Studies: Linguistic, Literary and Sociocultural Perspectives OB 1

Contact

Name:
Ana Maria Fernandez Montraveta
Email:
ana.fernandez@uab.cat

Teachers

Laura Jane Styles
Carmen Font Paz

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

There are no prerequisites for this course.


Objectives and Contextualisation

This course is an introduction to how the use of technology can affect the different subject areas addressed in this master's degree. Firstly, we will study useful applications and tools in the field of language teaching that facilitate the modification of classroom dynamics to achieve student-centered learning and thus promote student autonomy. Secondly, tools that help in the linguistic analysis of texts from the perspective of corpus linguistics, which will allow different types of approaches, from a stylistic analysis to a purely formal or discursive analysis. Finally, students will also become familiar with tools and technologies used in the editing and online publication of content, as well as in the search for digital documentary sources, both primary and secondary.

 


Learning Outcomes

  1. CA06 (Competence) Create educational proposals based on the use of digital tools to improve motivation among English as a foreign language students.
  2. CA07 (Competence) Apply the basic knowledge acquired about the function and opportunities offered by various digital tools in specific academic and professional environments.
  3. CA08 (Competence) Use digital files in a specific project to locate literary and cultural primary sources.
  4. KA06 (Knowledge) Distinguish the basic concepts of corpus linguistics for the stylistic analysis of primary literary and cultural sources.
  5. KA07 (Knowledge) Describe the main theories and new educational models for teaching second or foreign languages through the application of technology.
  6. KA08 (Knowledge) Recognise the different databases relevant to the student's specialisation and learn about their internal organisation.
  7. SA09 (Skill) Codify linguistic and literary data based on various questions and research objectives.
  8. SA10 (Skill) Critically assess the reliability of digital data and sources.
  9. SA11 (Skill) Apply relevant criteria to the search for linguistic and literary data in coded databases to produce intersectional analyses.
  10. SA12 (Skill) Use the appropriate techniques and technological tools for data analysis according to the area of specialisation, the chosen methodology and the type of data.

Content

Part 1 (Laura Styles): 

- Overview of teaching approaches with a focus on CLT and TBLT

- Material design and CEFR alignment 

- Technology mediated language teaching (mode, CALL) 

- Gamification and serious games

Sessions: Mondays, 11:30-13:00 (30 Sep - 25 Nov)

Part 2 (Ana Fernández Montraveta):

- Introduction to Corpus Linguistics (CL)

- How to analyze a corpus

- Build a corpus

- Practical uses of CL

Sessions: Tuesdays, 13:00-14:30 (08 Oct - 26 Nov)

Part 3 (Carme Font):

-Principles of digital editing

-Database search content for specific purposes

-Digital exhibits 

Sessions: Tuesdays, 13:00-14:30 (29 Nov - 13 Dec)/Fridays, 8:30-10:00 (29 Nov - 13 Dec) 


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Discussions on assigned readings and topics 31.25 1.25 CA07, KA06, KA07
Type: Supervised      
Practical Exercises 25 1 CA08, KA08, SA09, SA10, SA11, SA12
Type: Autonomous      
Material Design 63 2.52 CA06, CA07, CA08, SA09, SA10, SA11, SA12

The methodology will be based on the execution of practical exercises which will be carried out in groups or individually and class discussion.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Design and implementation of an analysis of linguistic data based on CL 40% 2 0.08 KA06, SA09, SA11, SA12
Creating a suitable LMS space for a group that follows the CLT or TBLT method 40% 2 0.08 CA06, CA07, KA07, SA12
Search data with Omeka, digital editing or design an art exhibition with Google 20% 1.75 0.07 CA08, KA08, SA10

Part 1: Language Teaching

Assessment would be setting up an LMS space and creating+uploading material which is suitable for a target group and follows either CLT or TBLT. 

Part 2: Corpus Linguistics

Assessment will be carrying out the analysis of linguistic data based on CL

Part 3: Digital Humanities

a) editing a text digitally with Transkribus; or

b) conduct a data quest with Omeka; or

c) designing a Google arts exhibit.

Please note:

  1. This subject/module does not incorporate single assessment.
  2. Students will obtain a Not assessed/Not submitted course grade unless they have submitted more than 1/3 of the assessment items.

Procedure for Reviewing Grades Awarded

On carrying out each evaluation activity, lecturers will inform students (on Moodle) of the procedures to be followed for reviewing all grades awarded, and the date on which such a review will take place.

Reassessment

To participate in the reassessment, students must have been previously evaluated in a set of activities equivalent to a minimum of 2/3 of the total grade.

Plagiarism

In the event of a student committing any irregularity that may lead to a significant variation in the grade awarded to an assessment activity, the Student will be given a zero for this activity, regardless of any disciplinary process that may take place. In the event of several irregularities in assessment activities of the same subject, the student will be given a zero as the final grade for this subject.

Irregularities refer, for instance, to copying in an exam, copying from sources without indiacting authorship, or a misuse of AI such as presenting work as original that has been generated by an AI tool or programme. These evaluation activities will not be re-assessed. 

 


Bibliography

 

  • Csomay, Eniko, Crawford, William J. (2015). Doing Corpus Linguistics. Routledge. Taylor & Francis Group.
  • Driscoll, Matthew James, Elena Pierazzo. Digital Scholarly Editing: Theories and Practices. London: Open Book Publishers, 2016. Available in Open Access: https://www.openbookpublishers.com/books/10.11647/obp.0095
  • Farr, F., & Murray, L. (Eds.). (2016). The Routledge handbook of language learning and technology. Routledge.
  • Flanders, Julia, Fotis Jannidis. The Shape of Data in Digital Humanities: Modeling Texts and Text-based Resources. London, New York: Routledge, 2019.
  • González-Lloret, M. (2017). Technology for Task-based Language Teaching. In The Handbook of Technology and Second Language Teaching and Learning (eds C.A. Chapelle and S. Sauro). https://doi.org/10.1002/9781118914069.ch16
  • Larsen-Freeman, D. (2013). Techniques and principles in language teaching (3rd ed.). Oxford University Press.
  • Levenberg, Lewis, David Rheams. Research Methods for the Digital Humanities. London: Palgrave, 2018.
  • Svensson, Patrik, David Theo Goldberg. Between Humanities and the Digital. Cambridge, MA: The MIT Press, 2015. Available in Open Access: https://direct.mit.edu/books/edited-volume/4494/Between-Humanities-and-the-Digital

Software

Omeka (Omeka)

Sketch Engine (Create and search a text corpus | Sketch Engine)


Language list

Name Group Language Semester Turn
(TEm) Theory (master) 1 English first semester morning-mixed