34.2203, Confs: 17th International Congress 2024 of the German Semiotic Association “Signs.Cultures.Digitality“

[The LINGUIST List]

LINGUIST List: Vol-34-2203. Thu Jul 13 2023. ISSN: 1069 - 4875.

Subject: 34.2203, Confs: 17th International Congress 2024 of the German Semiotic Association “Signs.Cultures.Digitality“

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Date: 13-Jul-2023
From: Daniel Rellstab [daniel.rellstab at ph-gmuend.de]
Subject: 17th International Congress 2024 of the German Semiotic Association “Signs.Cultures.Digitality“


17th International Congress 2024 of the German Semiotic Association
“Signs.Cultures.Digitality“

Date: 24-Sep-2024 - 28-Sep-2024
Location: RPTU in Landau, Germany
Contact: Daniel Rellstab
Contact Email: daniel.rellstab at ph-gmuend.de
Meeting URL:
https://www.semiotik.eu/zeichen.kulturen.digitalitaet-2024

Linguistic Field(s): Applied Linguistics; Discourse Analysis; Language
Acquisition; Philosophy of Language; Pragmatics

Meeting Description:

The German Semiotic Association organizes conferences, colloquia,
workshops, courses, and lecture series on core areas of its research
fields to achieve its goals. Moreover, every three years, the
association organizes an international congress.

"AI in Education. Automated generation and mediation of sign processes
in education -  the end of learning?"

So-called artificial intelligence is increasingly involved in everyday
semiotic processes and, thus, also in education. The data on which
machine generation processes are based are generated from previous
user behavior or their semiotic traces in databases and digital
networks. For some time now, these "intelligent" systems have found
their way into everyday and professional musical, pictorial,
cinematic, and graphic, i.e., multimodal, sign production. They all
draw on an immense data pool of pre-existing and algorithmically
ordered presets that provide samples, filters, and content. Algorithms
perform data generation, collection, analysis, sorting, and
communication in an endless cycle. The ostensible goal is to achieve
continuous performance optimization for the machines and their users.

AI has long been harnessed in formal and informal teaching-learning
contexts and on specific platforms such as Maths-Whizz, Google
Classroom, or Duolingo. Teachers use AI to correct assignments and
exams or analyze students’ learning behavior. On a macro level, AI is
used to coordinate curricula or room allocation or to design lessons
according to curricula, class level, and didactic appropriateness. On
a micro level, AI can organize individual assignments and learning
paths based on personal performance analysis. In this respect, AI
seems to increase the efficiency of educational and organizational
processes in educational institutions.

Yet the skeptical voices remain. One of the arguments against AI is
that education needs interpersonal interaction. Teachers and learners
create learning cultures through communicative reciprocity in concrete
situations, constituting meaning interactively, intersubjectively, and
situationally. Subjectively appropriated bodies of knowledge are
produced by teachers and learners through the joint production and
interpretation of signs. The potential shift of the output of
sign-like knowledge stocks into automated AI processes requires
adapting educational tools and practices. It fundamentally challenges
the outlined traditional forms of learning cultures.

In our panel, we want to explore from sign-theoretical and applied
perspectives the questions of how AI is used in education, how these
applications can also be semiotically explicated, and to what extent
learning needs to be rethought and conceptualized in the age of AI.
Thus, we welcome presentation ideas that address, for example, the
following problems:
- Which AI applications are used today in formal and informal
teaching-learning contexts, and how can these applications be analyzed
from a semiotic perspective?
- How can learning processes in the age of AI be grasped from a
semiotic perspective?
- What does digital literacy mean or imply for teachers and learners
concerning current AI applications?
- To what extent can culture be implemented as a meaningful reference
world for data generation, analysis, and evaluation using AI
technology in teaching/learning scenarios?
- Which didactic-methodological procedures are suitable from a
semiotic perspective and why?
- How can new AI-specific sign practices, such as prompting, be
semiotically classified in the teaching/learning context?



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