CfP Special Issue: Learning Computational Thinking

Special Issue Guest Editors:

Nina Bonderup Dohn, Yasmin Kafai, Anders Mørch, Marco Ragni


Our call is informed by the ever-increasing digitalization and integration of AI into everyday life. Computational thinking (CT) is the use of problem-solving processes to enable humans to design creative and computational solutions to many of the wicked problems which the world faces today. Utilizing computational thinking is an integral part of developing AI systems – and the AI developers of tomorrow are the learners of today. CT is not restricted to algorithmic thinking, computer visualizations, and programming, but includes as well analogue representations and even aspects of embodied cognition.
We call for papers that develop cognitive, educational, and computational models, report psychological studies, in situ case studies of design activities, children’s engagement in computational participation and critical reflection on IT and AI, and investigate pedagogical designs that support the learning of CT and AI using a range of different tools and methods, e.g., computer visualizations, simulation programs, analogue algorithmic thinking, bodily interactions, or physical things that can be programmed, or using all methods from AI. We aim to integrate researchers from all disciplines to present novel research to advance the understanding of CT.
All submissions will be peer-reviewed.
The topics of interest for the special issue include, but are not limited to:
* Theoretical investigations of CT compared with other types of thinking
* Any form of AI support for AI thinking and developing AI thinking
* Analysis of AI models for taxonomy of AI thinking abilities
* Comparison of analogue and digital forms of CT
* Multimodal interactions of users and systems
* Comparison of successful educational methods for AI and CT (Fachdidaktik)
* In situ experiments with learning designs supporting the learning of CT and AI
* Practice- or design-based research on CT in different disciplines
* Case studies of learners engaged in CT activities, computational participation
and critical reflection on AI in formal and informal learning
* AI interfaces or Apps for enabling learners to engage in AI and CT

Contributions can be from the following categories (for more detailed information please refer to the author instructions for each of these categories):

Technical Contribution; System Descriptions; Project Reports; Dissertation and Habilitation Abstracts; AI Transfer; Discussion


If you are interested in submitting a paper please contact one of the guest editors:

Nina Bonderup Dohn, SDU, Denmark, nina@sdu.dk

Yasmin Kafai, EdD University of Pennsylvania, USA, kafai@upenn.edu

Anders Mørch, University of Oslo, Norway, anders.morch@iped.uio.no

Marco Ragni, DIAS, SDU, Denmark, ragni@sdu.dk


Handling Editor, Editorial Board:

Marco Ragni, DIAS, SDU, Denmark


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