Call for papers for the International Journal of Learner Corpus Research (Benjamins):
Special issue on Cumulative knowledge building and replication in Learner Corpus Research
Guest editors: Tove Larsson & Doug Biber (Northern Arizona University)
Compared to other subfields of linguistics, Learner Corpus Research (LCR) has a relatively short history. For this and other reasons, most of the studies that get published in the field are exploratory in nature and focus on topics that have yet to receive prolonged attention. Such studies no doubt make valuable contributions to the field. However, LCR is arguably mature enough as a field to also have accumulated enough knowledge on certain topics for researchers to be able to instead adopt a cumulative approach.
In the cumulative approach to knowledge building, individual studies are viewed as building blocks, carefully pieced together to help us form an increasingly better understanding of a topic. There are three distinguishing characteristics of this approach: First, the literature review focuses on what we have actually learned from previous research on the topic, rather than merely cataloging individual studies. Second, the research ‘gap’ refers to an important missing element in our cumulative knowledge, rather than to a research angle that has not been explored yet; that is, the literature review is used to identify a missing piece in an existing puzzle, rather than to justify starting a new one. And finally, results of the new study are explicitly compared to previous findings, to discuss the state of our knowledge based on all studies taken together. Through this big-picture thinking, we can collectively refine our understanding of the topic, and further our knowledge in a systematic matter. Put differently, this approach enables us to build a state-of-the-art in the field by moving beyond the results of individual studies.
With this call, we invite studies of two kinds:
* Empirical studies that set out to test hypotheses arrived at from an existing body of research with the explicit aim of adding to our knowledge on a given topic that has received ample attention in LCR. Examples of topics that may be ripe for studies of this kind include, but are not limited to, linguistic complexity and the formulaic nature of learner language.
* Empirical studies that replicate findings from an existing body of research and, importantly, that focus on strengthening and/or tweaking existing generalizations in LCR. Examples of topics include, but are not limited to, claims of the spoken-like nature of learners’ written production.
Timeline:
* August 1, 2022: Abstract and title due * September 1, 2022: Authors are notified * September 1, 2023: Full manuscript due
Please send submissions to tove.larsson@nau.edumailto:tove.larsson@nau.edu
---
Tove Larsson, Ph.D.
Assistant Professor of Applied Linguistics
English Department
Northern Arizona University
Dear Corpora-List members,
I was wondering whether anyone of you has some experience with using chatbots for collecting production data in a (pseudo) social media context.
The concrete scenario I have in mind is the simulation of a text message chat (as in WhatsApp, for instance) with a human informant interacting with the chatbot during an exchange on a set topic (e.g. the first line of the chatbot could be something like: "what are your plans for this afternoon?"). The idea is to elicit informal digital conversation.
In an ideal case, there would be the opportunity to store the production data by the human informant in a format that can be used for subsequent analysis with standard corpus software (such as AntConc, WordSmith or SketchEngine). I'm aware that there are several (also partly free) chatbots available for commercial purposes (as presented on chatbots.org, for example) but they don't really seem to allow data export in the way described above.
Any pointers would be highly appreciated!
Valentin
Have you looked at slurk from the Uni Potsdam group? https://github.com/clp-research/slurk
I'm currently collecting data for Scottish Gaelic using a modified version of one of their tasks to get two humans to interact in an information seeking/answering paradigm.
Peace, Dave ---- David M. Howcroft https://www.davehowcroft.com
On Wed, Jul 6, 2022 at 10:49 AM Valentin Werner < valentin.werner@uni-bamberg.de> wrote:
Dear Corpora-List members,
I was wondering whether anyone of you has some experience with using chatbots for collecting production data in a (pseudo) social media context.
The concrete scenario I have in mind is the simulation of a text message chat (as in WhatsApp, for instance) with a human informant interacting with the chatbot during an exchange on a set topic (e.g. the first line of the chatbot could be something like: "what are your plans for this afternoon?"). The idea is to elicit informal digital conversation.
In an ideal case, there would be the opportunity to store the production data by the human informant in a format that can be used for subsequent analysis with standard corpus software (such as AntConc, WordSmith or SketchEngine). I'm aware that there are several (also partly free) chatbots available for commercial purposes (as presented on chatbots.org, for example) but they don't really seem to allow data export in the way described above.
Any pointers would be highly appreciated!
Valentin
-- PD Dr. Valentin Werner Otto-Friedrich-Universität Bamberg Englische Sprachwissenschaft D-96045 Bamberg
Corpora mailing list -- corpora@list.elra.info https://list.elra.info/mailman3/postorius/lists/corpora.list.elra.info/ To unsubscribe send an email to corpora-leave@list.elra.info