Contours of Inclusion: Inclusive Arts Teaching and Learning

The purpose of this publication is to share models and case examples of the process of inclusive arts curriculum design and evaluation. The first section explains the conceptual and curriculum frameworks that were used in the analysis and generation of the featured case studies (i.e. Understanding by Design, Differentiated Instruction, and Universal Design for Learning). Data for the cases studies was collected from three urban sites (i.e. Los Angeles, San Francisco, and Boston) and included participant observations, student and teacher interviews, curriculum documentation, digital documentation of student learning, and transcripts from discussion forum and teleconference discussions from a professional learning community.The initial case studies by Glass and Barnum use the curricular frameworks to analyze and understand what inclusive practices look like in two case studies of arts-in-education programs that included students with disabilities. The second set of precedent case studies by Kronenberg and Blair, and Jenkins and Agois Hurel uses the frameworks to explain their process of including students by providing flexible arts learning options to support student learning of content standards. Both sets of case studies illuminate curricular design decisions and instructional strategies that supported the active engagement and learning of students with disabilities in educational settings shared with their peers. The second set of cases also illustrate the reflective process of using frameworks like Universal Design for Learning (UDL) to guide curricular design, responsive instructional differentiation, and the use of the arts as a rich, meaningful, and engaging option to support learning. Appended are curriculum design and evaluation tools. (Individual chapters contain references.

Artificial Intelligence: Robots, Avatars, and the Demise of the Human Mediator

Published in cooperation with the American Bar Association Section of Dispute Resolutio

Artificial Intelligence: Robots, Avatars, and the Demise of the Human Mediator

Published in cooperation with the American Bar Association Section of Dispute Resolutio

Artificial Intelligence: Robots, Avatars and the Demise of the Human Mediator

As technology has advanced, many have wondered whether (or simply when) artificial intelligent devices will replace the humans who perform complex, interactive, interpersonal tasks such as dispute resolution. Has science now progressed to the point that artificial intelligence devices can replace human mediators, arbitrators, dispute resolvers and problem solvers? Can humanoid robots, attractive avatars and other relational agents create the requisite level of trust and elicit the truthful, perhaps intimate or painful, disclosures often necessary to resolve a dispute or solve a problem? This article will explore these questions. Regardless of whether the reader is convinced that the demise of the human mediator or arbitrator is imminent, one cannot deny that artificial intelligence now has the capability to assume many of the responsibilities currently being performed by alternative dispute resolution (ADR) practitioners. It is fascinating (and perhaps unsettling) to realize the complexity and seriousness of tasks currently delegated to avatars and robots. This article will review some of those delegations and suggest how the artificial intelligence developed to complete those assignments may be relevant to dispute resolution and problem solving. “Relational Agents,” which can have a physical presence such as a robot, be embodied in an avatar, or have no detectable form whatsoever and exist only as software, are able to create long term socio-economic relationships with users built on trust, rapport and therapeutic goals. Relational agents are interacting with humans in circumstances that have significant consequences in the physical world. These interactions provide insights as to how robots and avatars can participate productively in dispute resolution processes. Can human mediators and arbitrators be replaced by robots and avatars that not only physically resemble humans, but also act, think, and reason like humans? And to raise a particularly interesting question, can robots, avatars and other relational agents look, move, act, think, and reason even “better” than humans

Artificial Intelligence Fairness in the Context of Accessibility Research on Intelligent Systems for People who are Deaf or Hard of Hearing

We discuss issues of Artificial Intelligence (AI) fairness for people with disabilities, with examples drawn from our research on human-computer interaction (HCI) for AI-based systems for people who are Deaf or Hard of Hearing (DHH). In particular, we discuss the need for inclusion of data from people with disabilities in training sets, the lack of interpretability of AI systems, ethical responsibilities of access technology researchers and companies, the need for appropriate evaluation metrics for AI-based access technologies (to determine if they are ready to be deployed and if they can be trusted by users), and the ways in which AI systems influence human behavior and influence the set of abilities needed by users to successfully interact with computing systems

The Development of Social Cognition in Filipino Deaf and Hearing Individuals

This thesis examined the nature and pattern of development of social cognition in Filipino deaf and hearing individuals. Predictive factors and social consequences of social cognition were also studied. Prior studies are restricted due to the focus on specific skills, the poverty on work in non-Western deaf samples, and the limited understanding of the relationship between social cognition and social behaviour. To establish parity with extant research, the five studies reported in this thesis examined the abilities of Filipino deaf individuals 8 to 22 years and hearing children 3 to 14 years on well-established measures of Theory of Mind (ToM) and emotion knowledge. Results revealed that hearing children outperformed the deaf in ToM and emotion understanding (EU). Yet, affective recognition and labelling (ARL) scores were comparable. Findings also showed that the nature of ToM development is the same between deaf and hearing children. Similar to children from Western cultures, Filipino children’s ToM understanding follows the following sequence: diverse desires > diverse beliefs > knowledge access > false belief > hidden emotions. In contrast, two slightly patterns of EU emerged. Furthermore, language ability was robustly associated with ToM, EU, and ARL. However, parents’ predominant use of signed communication led to poorer ToM scores in the deaf. Finally, EU and language ability were found to be predictive of prosocial actions of deaf individuals. These findings were thought to be linked to certain cultural values and parenting practices that influence the kinds of interpersonal and communicative interactions Filipino deaf children experience. Further research is needed to examine closely specific cultural variables and naturally occurring discourse between Filipino parents and their deaf children that could potentially impact deaf children’s understanding of mind and emotions

Emotional expressions reconsidered: challenges to inferring emotion from human facial movements

It is commonly assumed that a person’s emotional state can be readily inferred from his or her facial movements, typically called emotional expressions or facial expressions. This assumption influences legal judgments, policy decisions, national security protocols, and educational practices; guides the diagnosis and treatment of psychiatric illness, as well as the development of commercial applications; and pervades everyday social interactions as well as research in other scientific fields such as artificial intelligence, neuroscience, and computer vision. In this article, we survey examples of this widespread assumption, which we refer to as the common view, and we then examine the scientific evidence that tests this view, focusing on the six most popular emotion categories used by consumers of emotion research: anger, disgust, fear, happiness, sadness, and surprise. The available scientific evidence suggests that people do sometimes smile when happy, frown when sad, scowl when angry, and so on, as proposed by the common view, more than what would be expected by chance. Yet how people communicate anger, disgust, fear, happiness, sadness, and surprise varies substantially across cultures, situations, and even across people within a single situation. Furthermore, similar configurations of facial movements variably express instances of more than one emotion category. In fact, a given configuration of facial movements, such as a scowl, often communicates something other than an emotional state. Scientists agree that facial movements convey a range of information and are important for social communication, emotional or otherwise. But our review suggests an urgent need for research that examines how people actually move their faces to express emotions and other social information in the variety of contexts that make up everyday life, as well as careful study of the mechanisms by which people perceive instances of emotion in one another. We make specific research recommendations that will yield a more valid picture of how people move their faces to express emotions and how they infer emotional meaning from facial movements in situations of everyday life. This research is crucial to provide consumers of emotion research with the translational information they require