Using AI Methods for Health Behavior Change

Artificial intelligence (AI) has been applied to health behavior change research for over a decade. Current research programs include machine learning for delivering just-in-time adaptive interventions, computational modeling of behavior change processes, and the use of social AI for communication and persuasion. With new advances in AI, we propose an international workshop to bring together experts from all related disciplines to discuss and explore the potentials of AI for behavior change research. We discuss in this proposal the aims, planned activities, expected outcomes, and a promotion strategy for the workshop.</p

SARSCEST (human factors)

People interact with the processes and products of contemporary technology. Individuals are affected by these in various ways and individuals shape them. Such interactions come under the label 'human factors'. To expand the understanding of those to whom the term is relatively unfamiliar, its domain includes both an applied science and applications of knowledge. It means both research and development, with implications of research both for basic science and for development. It encompasses not only design and testing but also training and personnel requirements, even though some unwisely try to split these apart both by name and institutionally. The territory includes more than performance at work, though concentration on that aspect, epitomized in the derivation of the term ergonomics, has overshadowed human factors interest in interactions between technology and the home, health, safety, consumers, children and later life, the handicapped, sports and recreation education, and travel. Two aspects of technology considered most significant for work performance, systems and automation, and several approaches to these, are discussed

Design patterns for an interactive storytelling robot to support children's engagement and agency

In this paper we specify and validate three interaction design patterns for an interactive storytelling experience with an autonomous social robot. The patterns enable the child to make decisions about the story by talking with the robot, reenact parts of the story together with the robot, and recording self-made sound effects. The design patterns successfully support children's engagement and agency. A user study (N = 27, 8-10 y.o.) showed that children paid more attention to the robot, enjoyed the storytelling experience more, and could recall more about the story, when the design patterns were employed by the robot during storytelling. All three aspects are important features of engagement. Children felt more autonomous during storytelling with the design patterns and highly appreciated that the design patterns allowed them to express themselves more freely. Both aspects are important features of children's agency. Important lessons we have learned are that reducing points of confusion and giving the children more time to make themselves heard by the robot will improve the patterns efficiency to support engagement and agency. Allowing children to pick and choose from a diverse set of stories and interaction settings would make the storytelling experience more inclusive for a broader range of children

Õpilaste kaasamine STEM-haridusse

In this manuscript we focus on how to develop STEM learning environments, and how STEM can be implemented in K-12 schools. We focus on the following question: “How can we support students in building a deep, integrated knowledge of STEM so that they have the practical knowledge and problem solving skills necessary to live in and improve the world?” We also discuss criteria for evaluating STEM learning environments and the challenges teachers face in implementing STEM. We define STEM as the integration of science, engineering, technology, and mathematics to focus on solving pressing individual and societal problems. Engaging students in STEM also means engaging learners in the design process. Design is integral to student thinking in the STEM world. The design process is very non-linear and iterative in its nature but requires clearly articulating and identifying the design problem, researching what is known about the problem, generating potential solutions, developing prototype designs (artifacts) that demonstrate solutions, and sharing and receiving feedback. With the integration of design, STEM education has the potential to support students in learning big ideas in science and engineering, as well as important scientific and engineering practices, and support students in developing important motivational outcomes such as ownership, agency and efficacy. Moreover, students who engage in STEM learning environments will also develop 21st century capabilities such as problem solving, communication, and collaboration skills

Using AI Methods for Health Behavior Change

Artificial intelligence (AI) has been applied to health behavior change research for over a decade. Current research programs include machine learning for delivering just-in-time adaptive interventions, computational modeling of behavior change processes, and the use of social AI for communication and persuasion. With new advances in AI, we propose an international workshop to bring together experts from all related disciplines to discuss and explore the potentials of AI for behavior change research. We discuss in this proposal the aims, planned activities, expected outcomes, and a promotion strategy for the workshop

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Adolescence, autism and technology: how technology can impact the social lives and wellbeing of adolescents with an autism diagnosis

Section A Section A is a narrative review of social skills interventions that have been used to enhance the social skills of adolescents with a diagnosis of autism. The review examined the types of interventions used as well as their efficacy, acceptability and generalisability. Exploration of the research revealed some limited evidence supporting the use of technology-delivered social skills interventions. Interventions offered little benefit over in-person interventions and limited generalisability. However, such interventions were positively received by young people which may improve intervention adherence. Clinical and research implications are provided. Section B Section B is a mixed-methods study examining the social media experiences of 222 adolescents with and without autistic traits. Participants’ views on the advantages and disadvantages of using social media and its impact on their social life were collected. A number of hypotheses concerning social media’s impact on social capital and wellbeing were tested, including the moderating role of autistic traits. Results show that social media use can have a positive impact on adolescents’ social lives and improve online social capital. Its impact on wellbeing appeared to vary depending on autistic traits. Findings are discussed in terms of their implications for clinical practice. Limitations are considered and implications for future research are provided