Masterclasses

Program

		Room1	Room2	Room3	Room4
Day 1 – June 17	Morning	DC	WS5	WS1	WS3
	Afternoon			WS6
Day 2 – June 18	Morning	MC1	WS2	WS4	WS8
	Afternoon	MC2	WS7

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MC1: The practice-centered research program in CSCW

Kjeld Schmidt
Copenhagen Business School, Denmark & University of Siegen, Germany

Abstract

As a research area, CSCW was formed in response to the early development and use of collaboration technologies, as researchers from different disciplines and in different practical domains began to try to understand the potentials and issues of these new technologies. Accordingly, CSCW was from the outset a rather heterogeneous research area, spanning not only computer science and social science but also a manifold of distinctly different research paradigms. In important ways, CSCW is still characterized by such heterogeneity, not least because the challenges emerging from new collaborative technologies give rise to new potentials and issues, but also because collaborative technologies become applied in new work domains and use contexts. At the same time, however, in the midst of this persistent heterogeneity, a research program has been articulated and developed that attempts to build, from the bottom up, a conceptual framework for our understand of the design and use of collaboration technologies in actual work practices.

Based on an initial overview of the emergence and history of the CSCW research areas, the master class will focus on outlining the practice-centered research program in CSCW:

1. The unit of analysis of CSCW research: coordinative practices and artifacts.
2. The key challenge CSCW research: The problematic nature of collaborative
   technology: the problematic nature of constructing and embeddng models of
   social relations in computational artifacts.
3. The analytic axis of CSCW research: The notion of ‘plans and situated action’
   or ‘theory and practice’.

How to Apply

To apply, participants ARE REQUIRED TO ENROLL themselves in the masterclass by using the following form: https://forms.gle/fLK5Hmd2VxT8cTzTA.

The masterclass is introductory and is designed for graduate students and junior researchers (master students as well as PhD students and postdocs) interested in, entering, or engaged in CSCW research.

No specific initial knowledge of CSCW is required, but participants are recommended to read, or look into, some recent publications by lecturer, such as

Ciolfi, Luigina; Myriam Lewkowicz; and Kjeld Schmidt (2023). Computer-Supported Cooperative Work. In J. Vanderdonckt; P. Palanque; and M. Winckler (eds): Handbook of Human Computer Interaction. Cham, Switzerland, etc.: Springer. https://doi.org/10.1007/978-3-319-27648-9_30-1. Preprint: https://www.academia.edu/101022435/CSCW_History_Core_Issues_and_Approaches_in_Computer_Supported_Cooperative_Work

Schmidt, Kjeld (2024 [In press]). “The discipline of steel”: Technical knowledge in the coordinative practices of steelmaking. Computer Supported Cooperative Work (CSCW). Vol. 33. Preprint:
https://www.academia.edu/113011850/The_discipline_of_steel_Technical_knowledge_in_the_coordinative_practices_of_steelmaking

Schmidt, Kjeld (2024 [In press]). The concept of ‘practice’ and its complications. In M. Dybowski; W. Dzięgielewska; and W. Rzepiński (eds): Practices in Legal and Social Theories. Milton Park, UK: Routledge. Preprint :
https://www.academia.edu/116037345/The_concept_of_practice_and_its_complications

Organizer’s Bio

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MC2: Beyond Charts & Graphs: creating Data Visualizations to enhance knowledge

Chiara Ceccarini
Department of Computer Science and Engineering
University of Bologna

Abstract

In an era characterized by a continual increase in the volume of information and data from diverse sources and presented in various formats, the challenge of effectively representing them and enabling users to derive meaningful insights becomes relevant. This underscores the growing significance of Data Visualization, defined as the systematic representation of data to convey information clearly and impactfully, leveraging human cognitive abilities. The objective is to create a valuable decision-making tool, spotlighting patterns or anomalies within the data. Moreover, Data Visualization enhances data processing in the human brain more efficiently than textual information, fostering comprehension of heterogeneous and large data sets, improving collaboration, and providing an adept ad-hoc data analysis tool.

This masterclass aims to empower participants with the skills and insights necessary for creating visualization. Focusing on the principles of data visualization, participants will explore diverse techniques to transform information into data representations, combining theoretical lessons with hands-on group activities.

The theoretical sessions cover the fundamentals, techniques, and best practices in data visualization, allowing participants to gain a solid understanding of the field. Complementing the theoretical aspect, practical group activities offer participants the chance to apply learned concepts in real-world scenarios and foster teamwork.

How to Apply

To apply, participants ARE REQUIRED TO ENROLL themselves in the masterclass using the following form: https://forms.gle/YqVZ4Pb1ntRxcEqj6.

The Masterclass is designed for all students: master students, as well as PhD students, who would like to learn more about using visualization and visual tools in scientific or professional contexts.

No previous knowledge is required and no software installation is needed for the activities.

Organizer’s Bio