Publications

Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning. Millions of students are already starting to benefit from the use of these technologies, but millions more around the world are not. If this trend continues, the first delivery of AI in Education could be greater educational inequality, along with a global misallocation of educational resources motivated by the current technological determinism narrative. In this paper, we focus on speculating and posing questions around the future of AI in Education, with the aim of starting the pressing conversation that would set the right foundations for the new generation of education that is permeated by technology. This paper starts by synthesising how AI might change how we learn and teach, focusing specifically on the case of personalised learning companions, and then move to discuss some socio-technical features that will be crucial for avoiding the perils of these AI systems worldwide (and perhaps ensuring their success). This paper also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We also emphasise the need for collectively designing human-centered, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as support new emerging pedagogies. Finally, we ask what would it take for this educational revolution to provide egalitarian and empowering access to education, beyond any political, cultural, language, geographical and learning ability barriers.

Extracting useful information from the user history to clearly understand informational needs is a crucial feature of a proactive information retrieval system. Regarding understanding information and relevance, Wikipedia can provide the background knowledge that an intelligent system needs. This work explores how exploiting the context of a query using Wikipedia concepts can improve proactive information retrieval on noisy text. We formulate two models that use entity linking to associate Wikipedia topics with the relevance model. Our experiments around a podcast segment retrieval task demonstrate that there is a clear signal of relevance in Wikipedia concepts while a ranking model can improve precision by incorporating them. We also find Wikifying the background context of a query can help disambiguate the meaning of the query, further helping proactive information retrieval.

The emerging possibilities of multisensory interactions provide an exciting space for disability and open up opportunities to explore new experiences for perceiving one's own body, it's interactions with the environment and also to explore the environment itself. In addition, dynamic aspects of living with disability, life transitions, including ageing, psychological distress, long-term conditions such as chronic pain and new conditions such as long-COVID further affect people's abilities. Interactions with this diversity of embodiments can be enriched, empowered and augmented through using multisensory and cross-sensory modalities to create more inclusive technologies and experiences. To explore this, in this workshop we will explore three related sub-domains: immersive multi-sensory experiences, embodied experiences, and disability interactions and design. The aim is to better understand how we can re-think the senses in technology design for disability interactions and the dynamic self, constructed through continuously changing sensing capabilities either because of changing ability or because of the empowering technology. This workshop will: (i) bring together HCI researchers from different areas, (ii) discuss tools, frameworks and methods, and (iii) form a multidisciplinary community to build synergies for further collaboration.

Maryam Bandukda, Aneesha Singh, Catherine Holloway, Nadia Berthouze, Emeline Brulé, Ana Tajadura-Jiménez, Oussama Metatla, Ana Javornik, and Anja Thieme. 2021. Rethinking the Senses: A Workshop on Multisensory Embodied Experiences and Disability Interactions. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 118, 1–5. DOI:https://doi.org/10.1145/341176...

Approximately 15% of the world's population has a disability and 80% live in low resource-settings, often in situations of severe social isolation. Technology is often inaccessible or inappropriately designed, hence unable to fully respond to the needs of people with disabilities living in low resource settings. Also lack of awareness of technology contributes to limited access. This workshop will be a call to arms for researchers in HCI to engage with people with disabilities in low resourced settings to understand their needs and design technology that is both accessible and culturally appropriate. We will achieve this through sharing of research experiences, and exploration of challenges encountered when planning HCI4D studies featuring participants with disabilities. Thanks to the contributions of all attendees, we will build a roadmap to support researchers aiming to leverage post-colonial and participatory approaches for the development of accessible and empowering technology with truly global ambitions.

Giulia Barbareschi, Dafne Zuleima Morgado-Ramirez, Catherine Holloway, Swami Manohar Swaminathan, Aditya Vashistha, and Edward Cutrell. 2021. Disability Design and Innovation in Low Resource Settings: Addressing Inequality Through HCI. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 124, 1–5. DOI:https://doi.org/10.1145/3411763.3441340