Faculty of Language, Literature and Humanities - German in Multilingual Contexts

Language Situations: A method to elicit comparable, naturalistic data across registers and speaker groups

This site provides general information, references, and links to resources including open-access stimuli used in different previous applications of the method, a training video for elicitors, and corpora based on data elicited with the method.

Background

"Language Situations" addresses the challenge of eliciting actual language use, while at the same time controlling participants’ productions enough to obtain comparable data suitable for specific research questions.

  • Experimental set-ups yield controlled, targeted data, but they usually have the disadvantage of involving unnatural settings that might not tap into speakers’ actual linguistic practices, including their broader repertoires. 
  • Recording spontaneous language provides ecologically valid linguistic data, but it is time-consuming and difficult to conduct, does not yield comparable, targeted data, and might only capture some aspects of speakers’ repertoires.

"Language Situations" provides a set-up that is easy to implement and yields controlled, yet naturalistic data suitable for comparisons across and within speakers, speaker repertoires, and speaker groups.

For more details, please refer to the following publication:
  • Wiese, Heike (2020). Language Situations: A method for capturing variation within speakers' repertoires. In: Yoshiyuki Asahi (ed.), Methods in Dialectology XVI. Peter Lang, pp. 105-117.

Main features

  • combines the advantages of controlled elicitations with those of spontaneous data collection: naturalistic, ecologocally valid setting which allows control over communicative situation(s), topics, and extraneous variables 
  • systematically taps into speakers’ repertoires: captures naturalistic productions across different communicative situations, e.g., informal and formal settings, and written and spoken modes
  • allows comparisons across different registers and modalities within and across speakers
  • can be easily adapted for different research questions, by manipulating topics, modalities, registers, speaker populations, speech communities and languages
  • easy and fast to conduct

General design and set-up

  • Stimulus: video clip or photo story, depicting a ficitional event (e.g., a minor traffic accident)
  • Participants watch the story and imagine themselves as a witness to this event
  • Participants act out different communicative situations with different communication partners, telling them about the event they just witnessed (e.g., in a phone call to a friend, a messenger text to a friend, a written report to the police, or a phone call to the police).

Different settings can target different domains of linguistic repertoires, e.g., through choice of addressee (e.g., friend – informal; police officer – formal), and modality (e.g., spoken vs. written)

The same event is reported in different conditions, allowing systematic comparisons within and across registers, languages, speaker groups (e.g., age groups, monolinguals vs. bilinguals, heritage vs. majority language speakers), etc.

Illustrations of elicited data

English
  formal informal

written

The soccer ball got out of his hands and the dog of a woman, who was packing away her gorceries into her car, ran after the ball and caused the driver a car that was pulling into brake and the driver of the car behind him crashed into his car.

Anyway it went out in front of a car and a lady's dog ran after it making the car brake and the car behind him CRASHED INTO HIM

spoken

um the dog ran after the ball and a car that was uh coming in s/ - uh braked really quickly - and the car behind him couldn't stop fast enough an(d) crashed into the car in front

and as soon as th/ the guy like saw the dog run after the ball obviously he stopped but then there was a car behind him that crashed into him because he couldn't stop right away
Turkish
  formal informal

written

Gelen araç ani firen yapıp arkasından gelen aracın kendisine çarpmasına sebep oldu

Araba ani firen yapıp arkasındaki arabanın kendisine çarpmasına sebep oldu 😱

spoken

ıı elindeki topu kaçırdı ve araba yoluna e girmiş oldu top

tabi ki de elinden kaçırdı bu top da ıı arabaların geçtiği alanı girmiş oldu

Resources

Training Video

A video for training elicitors, produced for data collection by the RUEG group.

Decorative frame from training video
To the video
Stimuli used in previous applications

This photo story contains 6 pictures depicting a car accident. There are several versions of the photo story for use in different countries. This version was used in Germany. For other versions, see the other examples.

The stimuli were used to elicit data from monolingual and bilingual speakers in a pilot study by the RUEG group.

Click the example picture to download the stimulus set.

Woman riding bike
Download

This photo story contains 6 pictures depicting a car accident. There are several versions of the photo story for use in different countries. This version was used in Russia. For other versions, see the other examples.

Click the example picture to download the stimulus set.

Woman riding bike
Download

The video story was used by the RUEG group to elicit data from bilingual (heritage) and monolingual speakers.

Dog chasing ball in front of car
To the video

This photo story contains 10 pictures depicting a car accident on a parking lot. It has been used to elicit Namibian German by Wiese et al. (2017) and Zimmer et al. (2020). Click the example picture to download the stimulus set.

Woman standing in front of an approaching car
Download
Open-access corpora with LangSit data
  • RUEG Corpus
    Wiese, Heike, Artemis Alexiadou, Shanley Allen, Oliver Bunk, Natalia Gagarina, Kateryna Iefremenko, Esther Jahns, Martin Klotz, Thomas Krause, Annika Labrenz, Anke Lüdeling, Maria Martynova, Katrin Neuhaus, Tatiana Pashkova, Vicky Rizou, Christoph Schroeder, Luka Szucsich, Rosemarie Tracy, Wintai Tsehaye, Sabine Zerbian, and Yula Zuban. 2019f. RUEG Corpus [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3236069
  • DNam Corpus
    Christian Zimmer, Heike Wiese, Horst J. Simon, Marianne Zappen-Thomson, Janosch Leugner, Yannic Bracke, Britta Stuhl, Laura Perlitz & Thomas Schmidt: DNam Korpus.

Previous applications

"Language Situations" is used by research groups in different countries, working with a range of languages, communicative settings, and speaker populations: