Corpus-based �Constructional Analysis��Session1
Names of the teachers and universities involved
Taking Europe to the next level
Je propose la création d’universités européennes qui seront un réseau d’universités de plusieurs pays d’Europe ...
Ich schlage die Schaffung von europäischen Universitäten vor, die ein Netzwerk von Universitäten aus mehreren europäischen Ländern sein werden ...
I propose the creation of European universities which will be a network of universities from several European countries ...
Emmanuel Macron 2017
DIONE
Digitalising Mobility and International Networks with Open Education
Micro-collaboration
Empower all teachers
Democratise internationalisation
Make internationalisation massive and seamless
��MICRO-COLLABORATION PRESENTATION� �
Common course project
Micro-collaboration between University 1 & University 2 on Corpus-based Constructional Analysis
Collaboration between lecturers and students!
Organizational challenges: xxx
4 online sessions
of about 2h
Dates of the sessions
Course language: multilingual; slides in xxx with presentations in xxx
Organization of the 4 sessions
Session 1
Introduction
Getting to know
Presentation of the case study
Learning outcomes
Introduction to the corpus tool (SketchEngine)
Session 2
How to use Excel for data annotation and analysis
Selection of relevant criteria for the corpus analysis
Session 3
Data annotation
Q&A session: discussion of methodological problems and difficulties in the corpus analysis
Session 4
Group presentations and discussion of the results
Organization of the 4 sessions
Session 1
Introduction
Getting to know
Presentation of the case study
(Learning outcomes)
Introduction to the corpus tool (SketchEngine)
Session 2
How to use Excel for data annotation and analysis
Selection of relevant criteria for the corpus analysis
Session 3
Data annotation
Q&A session: discussion of methodological problems and difficulties in the corpus analysis
Session 4
Group presentations and discussion of the results
GETTING TO KNOW...
We are different...
Activity 1
logo of University 1
logo of University 2
But we are also the same!
Activity 2
logo of University 1
logo of University 2
Organization of the 4 sessions
Session 1
Introduction
Getting to know
Presentation of the case study
(Learning outcomes)
Introduction to the corpus tool (SketchEngine)
Session 2
How to use Excel for data annotation and analysis
Selection of relevant criteria for the corpus analysis
Session 3
Data annotation
Q&A session: discussion of methodological problems and difficulties in the corpus analysis
Session 4
Group presentations and discussion of the results
Case study
Construction: FORM ↔ ‘meaning’
Example of a common construction between Dutch, German and Croatian:
Case study: corpus examples
Case study: corpus examples
Case study: corpus examples
TASK
Which languages do you speak?
Do you find other examples of this construction in any of the languages you speak?
Case study
Dutch | German | Croatian |
pracht ‘beauty’ | Bild ‘picture’ | čudo ‘wonder‘ |
dijk ‘dike’ | Bär ‘bear’ | duša ‘soul‘ |
schat ‘treasure’ | Traum ‘dream’ | govno ‘shit‘ |
joekel ‘whopper’ | Berg ‘mountain’ | smeće ‘rubbish‘ |
droom ‘dream’ | Schatz ‘treasure’ | nula ‘zero‘ |
Special properties of the pattern
Which elements are fixed and which are variable?
What is the (semantic) head noun of the pattern?
What is the function of the other noun?
Can the meaning of the pattern be derived from the meaning of its separate components?
INTRODUCTION INTO CONSTRUCTION GRAMMAR
Some introductory videos:
Why this case study?
Interesting from a cross-linguistic perspective:
1
Interesting from a constructionist perspective:
2
Interesting from a corpus-based perspective:
3
Organization of the 4 sessions
Session 1
Introduction
Getting to know
Presentation of the case study
Learning outcomes
Introduction to the corpus tool (SketchEngine)
Session 2
How to use Excel for data annotation and analysis
Selection of relevant criteria for the corpus analysis
Session 3
Data annotation
Q&A session: discussion of methodological problems and difficulties in the corpus analysis
Session 4
Group presentations and discussion of the results
��LEARNING OUTCOMES AND COMPETENCES� �
Concrete outcomes
After this course you will be able to...
Competences
After these 4 sessions, students will have developed competences in different areas:
I can evaluate empirical research; I can explain the research cycle to others.
To some extent: I understand the limits of research; I understand different perspectives in science
Competences
Competences
I research a limited topic in at least two languages using digital tools.
Competences
I can identify my information needs and, with guidance, access secondary and selected primary sources with support using an appropriate research strategy.
I know a limited number of qualitative and quantitative methods. I can apply some methods independently.
I understand that the implementation has to follow the design and the two are in correlation
I strictly follow my design in implementation and understand that implementation can be a cycle
Competences
I collect empirical data consistently with digital tools. I know how to work around bias and observer paradox and do so with guidance.
I independently analyse my own simple data of selected data types according to given patterns, observing the research design.
I draw conclusions from my analysis within the framework of the given theory under guidance.
I independently draw conclusions from my analysis within the framework of a self-selected theory.
Competences
I can explain simple facts correctly in terms of terminology and with further knowledge and defend my point of view.
I can explain complex issues, explain and defend my point of view on them and reflect on the theoretical premises of my argumentation.
Organization of the 4 sessions
Session 1
Introduction
Getting to know
Presentation of the case study
(Learning outcomes)
Introduction to the corpus tool (SketchEngine)
Session 2
How to use Excel for data annotation and analysis
Selection of relevant criteria for the corpus analysis
Session 3
Data annotation
Q&A session: discussion of methodological problems and difficulties in the corpus analysis
Session 4
Group presentations and discussion of the results
FIND
PLAN
IMPLEMENT
SHARE
Organization of the 4 sessions
Session 1
Introduction
Getting to know
Presentation of the case study
(Learning outcomes)
Introduction to the corpus tool (SketchEngine)
Session 2
How to use Excel for data annotation and analysis
Selection of relevant criteria for the corpus analysis
Session 3
Data annotation
Q&A session: discussion of methodological problems and difficulties in the corpus analysis
Session 4
Group presentations and discussion of the results
INTRODUCTION TO THE CORPUS TOOL�
Corpus login
34
Sketch Engine: login
35
Select corpus
36
Simple query
37
1
2
3
CQL query
38
1
2
3
Sample
39
Random sample
40
2
1
Download
41
2
1
3
CORPUS TOOL
Video presentations on the formulation of queries in SketchEngine are available on Moodle
TASK
Dutch | German | Croatian |
+ pracht ('beauty') | + Bild ('picture') | +čudo ('wonder') |
+ dijk ('dike') | + Bär ('bear') | + duša ('soul') |
+schat ('treasure') | + Traum ('dream') | + govno ('shit') |
+joekel ('whopper') | + Berg ('mountain') | +smeće ('rubbish') |
+ droom ('dream') | + Hüne ('giant') | + nula ('zero') |
+ kanjer ('whopper') | + Schrank('wardrobe') | +gromada ('giant') |
+ draak ('dragon') | + Baum ('tree') | …. |
+ parel ('pearl') | +Schatz ('treasure') | |
+ knaller ('stunner') | + Kerl ('guy') | |
+ wolk ('cloud') | + Koloss('colossus') | |
... | ... | |
Look at the following examples and try to find out how they could be ranged into different semantic categories
Three semantic categories
Positive connotation ('good') | Negative connotation ('bad') | Augmentative function �('big') |
'wonder' | 'dragon' | 'giant' |
'soul' | 'monster' | 'tree' |
'dream' | 'shit' | 'bear' |
'beauty' | 'rubbish' | 'wardrobe' |
'treasure' | 'zero' | 'mountain' |
TASK�
��SEE YOU NEXT WEEK!