Academic cheating poses a significant challenge to conducting fair online assessments. One common way is collusion, where students unethically share answers during the assessment. While several researchers proposed solutions, there is lack of clarity regarding the specific types they target among the …

Rapid progression in generative artificial intelligence technology facilitates faster and easier conversational agent design. However, deploying conversational agents is challenging and can easily have adverse effects. To this end, more conceptual clarity on how to design for, for example, trust, in …

Bumping Elbows explores a workflow integrating 3D body scanning technology with robotic knitting to create personalized garments. Traditional 3D knitting development relies on 2D drafts and panels, rooted in industrial flatbed knitting practices. Our approach leverages accurate topology measurements …

Anyone who has watched a child play with soft semi-liquid materials like honey, frosting, or slime, sees the fascinating interplay between design and physics. Many of us remember these experiences from our own childhood (or maybe not that long ago). These materials dribble and coil as they stack upon …

A core principle of privacy protection is to minimize the amount of personal data in data sets to the level needed for the intended usage. The rapid growth of data and data-driven applications demands for using efficient software tools to minimize personal data to the needed level. However, applying …

Sensors in offices mainly measure environmental data, missing qualitative insights into office workers’ perceptions. This opens the opportunity for active individual participation in data collection. To promote reflection on office well-being while overcoming experience sampling challenges in terms of …

Maintaining the child-robot relationship after a significant break, such as a holiday, is an important step for developing sustainable social robots for education. We ran a four-session user study (n = 113 children) that included a nine-month break between the third and fourth session. During the study, …

We developed an application which allows learners to construct qualitative representations of dynamic systems to aid them in learning subject content knowledge and system thinking skills simultaneously. Within this application, we implemented a lightweight support function which automatically generates …

Post-training quantization reduces the computational demand of Large Language Models (LLMs) but can weaken some of their capabilities. Since LLM abilities emerge with scale, smaller LLMs are more sensitive to quantization. In this paper, we explore how quantization affects smaller LLMs’ ability to perform …

Maintaining the child-robot relationship after a significant break, such as a holiday, is an important step for developing sustainable social robots for education. We ran a four-session user study (n = 113 children) that included a nine-month break between the third and fourth session. During the study, …