User profiles for Christina Schneegass

Christina Schneegass

Delft University of Technology
Verified email at tudelft.nl
Cited by 221

What is" intelligent" in intelligent user interfaces? a meta-analysis of 25 years of IUI

ST Völkel, C Schneegass, M Eiband… - Proceedings of the 25th …, 2020 - dl.acm.org
This reflection paper takes the 25th IUI conference milestone as an opportunity to analyse in
detail the understanding of intelligence in the community: Despite the focus on intelligent UIs…

Safeguarding crowdsourcing surveys from chatgpt with prompt injection

…, V Kostakos, Z Sarsenbayeva, C Schneegass… - arXiv preprint arXiv …, 2023 - arxiv.org
ChatGPT and other large language models (LLMs) have proven useful in crowdsourcing tasks,
where they can effectively annotate machine learning training data. However, this means …

Informing the design of user-adaptive mobile language learning applications

C Schneegass, N Terzimehić, M Nettah… - Proceedings of the 17th …, 2018 - dl.acm.org
Smartphones enable people to learn new languages whenever and wherever they want. This
popularized mobile language learning apps (MLLAs) and in particular micro learning that …

Understanding challenges and opportunities of technology-supported sign language learning

…, C Schneegass, U Gruenefeld, S Schneegass - Proceedings of the …, 2022 - dl.acm.org
Around 466 million people in the world live with hearing loss, with many benefiting from
sign language as a mean of communication. Through advancements in technology-supported …

The Future of Cognitive Personal Informatics

C Schneegass, ML Wilson, HA Maior… - Proceedings of the 25th …, 2023 - dl.acm.org
While Human-Computer Interaction (HCI) has contributed to demonstrating that physiological
measures can be used to detect cognitive changes, engineering and machine learning will …

Comparing concepts for embedding second-language vocabulary acquisition into everyday smartphone interactions

C Schneegass, S Sigethy, M Eiband… - Proceedings of Mensch …, 2021 - dl.acm.org
We present a three-week within-subject field study comparing three mobile language learning
(MLL) applications with varying levels of integration into everyday smartphone interactions…

Designing task resumption cues for interruptions in mobile learning scenarios

C Schneegass, F Draxler - Technology-Augmented Perception and …, 2021 - Springer
Learning on a mobile device in everyday settings makes users particularly susceptible for
interruptions. Guidance (memory) cues can be implemented to support users in resuming a …

Broadening the mind: how emerging neurotechnology is reshaping HCI and interactive system design

C Schneegass, ML Wilson, J Shaban, J Niess… - i-com, 2024 - degruyter.com
People are increasingly eager to know more about themselves through technology. To date,
technology has primarily provided information on our physiology. Yet, with advances in …

BrainCoDe: Electroencephalography-based comprehension detection during reading and listening

C Schneegass, T Kosch, A Baumann, M Rusu… - Proceedings of the …, 2020 - dl.acm.org
The pervasive availability of media in foreign languages is a rich resource for language
learning. However, learners are forced to interrupt media consumption whenever …

UnlockLearning–Investigating the Integration of Vocabulary Learning Tasks into the Smartphone Authentication Process

C Schneegass, S Sigethy, T Mitrevska, M Eiband… - i-com, 2022 - degruyter.com
Frequent repetition of vocabulary is essential for effective language learning. To increase
exposure to learning content, this work explores the integration of vocabulary tasks into the …