Acquiring Pragmalinguistic Competences Through by Kaggle | Technology and IT

About this Dataset

Acquiring Pragmalinguistic Competences Through

Acquiring Pragmalinguistic Competences Through Italian-German CMC

Investigating Language Acquisition Through Computer-Mediated Communication

About this dataset

This dataset is an invaluable resource for researchers across disciplines analyzing the acquisition of Italian pragmalinguistic competences by German-speaking learners. Through a careful collection of emails, instant messages and their associated sociolinguistic data, this corpus provides valuable insights into anything from language fluency to communication habits. As such, it captures a unique snapshot of linguistics as it shapes our understanding to global communication in today's world. By delving into this collection with its comprehensive columns on Time, Message 1 Situation Tessera Biblioteca, Level of Italian Language Competence, Age and socio-demographics like Sex and Mother Tongue among others - this dataset promises to offer up intriguing results whatever the research goal may be!

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How to use the dataset

This dataset provides a great opportunity to analyze the acquisition of Italian pragmalinguistic competences by German-speaking learners of Italian. The dataset contains emails and instant messages from German learners and Italian natives as well as related sociolinguistic data. To help you use this dataset effectively, we have outlined the following steps.

Familiarize yourself with the variables and their labels in the dataset: Understand each of the variables present in the data set, including Time, Message 1 Situation tessera biblioteca, Level of Italian, Age, Sex etc.. This will provide a better perspective on how to analyze this data for your own purposes.

Consult existing research around this topic: It would be beneficial to read existing research around acquiring pragmalinguistic competences through CMC (Computer Mediated Communication). This can help you understand what should be done while analyzing your own dataset so that you can make sure your analysis is correct and valid.

Analyze your results against existing studies: You must ensure that what you find or conclude through analysis of your own study matches with pre-existing studies on this topic using social-science methodology methods such as surveys or observations etc.. If there are any discrepancies between existing studies' results and yours then it's important to note them and explain why you think there could have been any discrepancies (if possible).

Draw meaningful conclusions: Once you have gone through all necessary aforementioned steps then finally draw meaningful conclusions from whatever conclusion can be deduced from all collected information on Pragmalinguistic Competences in CMC environments (relevant to both native Italians & non-native Germans). It is important here not just list out whichever findings/conclusions but instead bring together multiple aspects related to communication competency & articulate how they're tied together into one coherent understanding which was enabled due specifically exposure to Computer Mediation Communications (CMC) environment in Italian language learning process!

Research Ideas

Identifying and analyzing language trends across different age groups.

Examining the impact of foreign language learning on native-language levels of proficiency for Spanish-speakers in different geographical areas, such as cities and countries.

Establishing correlations between mother tongue, home country, experience with foreign languages abroad and ability to communicate fluently in Italian

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: Instant Messaging Corpus.csv

Column name	Description
Time	The time the message was sent. (Date/Time)
Message 1 Situation tessera biblioteca	The first message sent by the participant in the tessera biblioteca situation. (String)
Level of Italian	The participant's self-reported level of Italian. (String)
Age	The participant's age. (Integer)
Sex	The participant's gender. (String)
High-school place	The participant's high school location. (String)
Mother tongue	The participant's native language. (String)
Knowledge of foreign languages	The participant's self-reported knowledge of foreign languages. (String)
University student	Whether or not the participant is a university student. (Boolean)
University place	The participant's university location. (String)
Experience of consistent exposure to foreign languages abroad	The participant's self-reported experience of consistent exposure to foreign languages abroad. (String)
Interviewer	The interviewer who conducted the interview. (String)

File: Mail Corpus.csv

Column name	Description
Time	The time the message was sent. (Date/Time)
Level of Italian	The participant's self-reported level of Italian. (String)
Age	The participant's age. (Integer)
Mother tongue	The participant's native language. (String)
High-school place	The participant's high school location. (String)
University place	The participant's university location. (String)
Knowledge of foreign languages	The participant's self-reported knowledge of foreign languages. (String)
Interviewer	The interviewer who conducted the interview. (String)
Message 1 Situation tessera biblioteca	The first message sent by the participant in the tessera biblioteca situation. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Instant Messaging Corpus

@kaggle.thedevastator_acquiring_pragmalinguistic_competences_through_i.instant_messaging_corpus

115.55 KB
1203 rows
16 columns


CREATE TABLE instant_messaging_corpus (
  "time" BIGINT,
  "personal_code" VARCHAR,
  "message_1_situation_tessera_biblioteca" VARCHAR,
  "level_of_italian" VARCHAR,
  "age" VARCHAR,
  "sex" VARCHAR,
  "high_school_place" VARCHAR,
  "mother_tongue" VARCHAR,
  "knowledge_of_foreign_languages" VARCHAR,
  "usage_of_whatsapp_or_other_messaging_services" VARCHAR,
  "current_place_of_residence" VARCHAR,
  "university_student" VARCHAR,
  "university_place" VARCHAR,
  "experience_of_consistent_exposure_to_foreign_languages_abroad" VARCHAR,
  "interviewer" VARCHAR,
  "situation" DOUBLE
);

Mail Corpus

@kaggle.thedevastator_acquiring_pragmalinguistic_competences_through_i.mail_corpus

69.8 KB
233 rows
10 columns


CREATE TABLE mail_corpus (
  "time" VARCHAR,
  "email_1" VARCHAR,
  "level_of_italian" VARCHAR,
  "age" VARCHAR,
  "mother_tongue" VARCHAR,
  "high_school_place" VARCHAR,
  "university_place" VARCHAR,
  "knowledge_of_foreign_languages" VARCHAR,
  "interviewer" VARCHAR,
  "situation" BIGINT
);