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Purpose – The purpose of this paper is to present an approach where a novel user modeling wizard for people with motor impairments is used to gain a deeper understanding of very specific (touch-based and touchless) interaction patterns. The findings are used to set up and fill a user model which allows to automatically derive an application- and user-specific configuration for natural user interfaces. Design/methodology/approach – Based on expert knowledge in the domain of software/user interfaces for people with special needs, a test-case –based user modeling tool was developed. Task-based user tests were conducted with seven users for the touch-based interaction scenario and with five users for the touchless interaction scenario. The participants are all people with different motor and/or cognitive impairments. Findings – The paper describes the results of different test cases that were designed to model users’ touch-based and touchless interaction capabilities. To evaluate the tool’s findings, experts additionally judged the participants’ performance (their opinions were compared to the tool’s findings). The results suggest that the user modeling tool could quite well capture users’ capabilities. Social implications – The paper presents a tool that can be used to model users’ interaction capabilities. The approach aims at taking over some of the (very time-consuming) configuration tasks consultants have to do to configure software according to the needs of people with disabilities. This can lead to a wider accessibility of software, especially in the area of gesture-based user interaction. Originality/value – Part of the approach has been published in the proceedings of the Interactional Conference on Advances in Mobile Computing and Multimedia 2014. Significant additions have been made since (e.g. all of the touchless interaction part of the approach and the related user study).

Interest in hybrid collaboration and meetings (HCM), where several co-located participants engage in coordinated work with remote participants, is gaining unprecedented momentum after the rapid shift in working from home due to the COVID-19 pandemic. However, while the interest is new, researchers have been exploring HCM phenomena for decades, albeit dispersed across diverse research traditions, using different terms, definitions, and frameworks. In this article, we present a systematic literature review of the contexts and tools of HCM in the ACM Digital Library. We obtained approximately 1,200 results, which were narrowed down to 62 key articles. We report on the terms, citations, venues, authors, domains, study types, and data of these publications and present a taxonomic overview based on their reported hybrid settings' actual characteristics. We discuss why the SLR resulted in a relatively small number of publications, and then as a corollary, discuss how some excluded high-profile publications flesh out the SLR findings to provide important additional concepts. The SLR itself covers the ACM until November 2019, so our discussion also includes relevant 2020 and 2021 publications. The end result is a baseline that researchers and designers can use in shaping the post-COVID-19 future of HCM systems.

We present Domino, a descriptive framework for hybrid collaboration and hybrid coupling styles in partially distributed teams. Domino enables researchers to describe, analyze, and understand real-world hybrid collaboration practices, i.e., collaborative practices that involve simultaneous co-located and remote collaboration with phases of both synchronous and asynchronous work that spans multiple groupware applications and devices. It also helps to categorize collaborative activities based on yet undocumented hybrid coupling styles between the members of multiple partially distributed or co-located subgroups. Our Domino framework was derived from initial observations of real-world practice and refined by the detailed analysis of participants' behavior and working styles during a simulation of a complex hybrid collaboration task with six partially distributed teams of four users in our lab. The resulting framework allows researchers to view collaboration through a new analytical lens, use new analytical tools, and also derive implications for the design of collaborative tools.

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