FB1 Sozial- und Bildungswissenschaften
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This research investigated how German-speaking children learn color words, both in terms of centroid mappings and boundary delineation, and how they construct the color lexicon as a connected system. The results were compared to those of Japanese children to draw insights on general mechanisms that underlie the acquisition of words in the color lexicon. For both languages, input frequency and category size contributed to the ease of learning. In contrast, in both language groups, naming (in)consistency in adults predicted the adult-like boundary delineation.
This paper describes a novel emotionally intelligent cognitive assistant to engage and help older adults with Alzheimer’s disease (AD) to complete activities of daily living (ADL) more independently. Our new system combines two research streams. First, the development of cognitive assistants with artificially intelligent controllers using partially observable Markov decision processes (POMDPs). Second, a model of the dynamics of emotion and identity called Affect Control Theory that arises from the sociological literature on culturally shared sentiments. We present background material on both of these research streams, and then demonstrate a prototype assistive technology that combines the two. We discuss the affective reasoning, the probabilistic and decision-theoretic reasoning, the computer-vision based activity monitoring, the embodied prompting, and we show results in proof-of-concept tests.
This paper presents an exploratory study conducted to understand how audio-visual prompts are understood by people on an emotional level as a first step towards the more challenging task of designing emotionally aligned prompts for persons with cognitive disabilities such as Alzheimer’s disease and related dementias (ADRD). Persons with ADRD often need assistance from a caregiver to complete daily living activities such as washing hands, making food, or getting dressed. Artificially intelligent systems have been developed that can assist in such situations. This paper presents a set of prompt videos of a virtual human ‘Rachel’, wherein she expressively communicates prompts at each step of a simple hand washing task, with various human-like emotions and behaviors. A user study was conducted for 30 such videos with respect to three basic and important dimensions of emotional experience: evaluation, potency, and activity. The results show that, while people generally agree on the evaluation (valence: good/bad) of a prompt, consensus about power and activity is not as socially homogeneous. Our long term aim is to enhance such systems by delivering automated prompts that are emotionally aligned with individuals in order to help with prompt adherence and with long-term adoption.
Any-Cubes
(2019)
Here we present Any-Cubes, a prototype toy with which children can intuitively and playfully explore and understand machine learning as well as Internet of Things technology. Our prototype is a combination of deep learning-based image classification [12] and machine-to-machine (m2m) communication via MQTT. The system consists of two physical and tangible wooden cubes. Cube 1 ("sensor cube") is inspired by Google's teachable machine [14,15]. The sensor cube can be trained on any object or scenery. The machine learning functionality is directly implemented on the microcontroller (Raspberry Pi) by a Google Edge TPU Stick. Via MQTT protocol, the microcontroller sends its current status to Cube 2, the actuator cube. The actuator cube provides three switches (relays controlled by an Arduino board) to which peripheral devices can be connected. This allows simple if-then functions to be executed in real time, regardless of location. We envision our system as an intuitive didactic tool for schools and maker spaces.
We describe how we use social simulation as a core method in a new master’s program designed to teach future leaders of urban change to deal with the complexity inherent in current societal transformations. We start by depicting the challenges with regard to cross-disciplinary knowledge integration and overcoming value-based, rigid thinking styles that inevitably arise in the process of solving ecological, technological, or social problems in cities new and old. Next, we describe a course based on urban modeling and participatory approaches, designed to meet those challenges. We reflect on our first experience with this approach and discuss future developments and research needs.
We review Affect Control Theory (ACT) as a promising basis for equipping computational agents in social simulations with a sense of sociality. ACT is a computational theory that integrates sociological insights about the symbolic construction of the social order with psychological knowledge about cognitive-affective mechanisms. After explaining the theoretical foundations of ACT and applications of the theory at the dyadic and group level, we describe a case study applying the theory from an ongoing research project examining self-organized online collaboration in software development.
Erzählen wir uns was
(2015)