Developmental Robots - A New Paradigm

It has been proved to be extremely challenging for humans to program a robot to such a sufficient degree that it acts properly in a typical unknown human environment. This is especially true for a humanoid robot due to the very large number of redundant degrees of freedom and a large number of sensors that are required for a humanoid to work safely and effectively in the human environment. How can we address this fundamental problem? Motivated by human mental development from infancy to adulthood, we present a theory, an architecture, and some experimental results showing how to enable a robot to develop its mind automatically, through online, real time interactions with its environment. Humans mentally “raise” the robot through “robot sitting” and “robot schools” instead of task-specific robot programming

Team Learning: A Theoretical Integration and Review

With the increasing emphasis on work teams as the primary architecture of organizational structure, scholars have begun to focus attention on team learning, the processes that support it, and the important outcomes that depend on it. Although the literature addressing learning in teams is broad, it is also messy and fraught with conceptual confusion. This chapter presents a theoretical integration and review. The goal is to organize theory and research on team learning, identify actionable frameworks and findings, and emphasize promising targets for future research. We emphasize three theoretical foci in our examination of team learning, treating it as multilevel (individual and team, not individual or team), dynamic (iterative and progressive; a process not an outcome), and emergent (outcomes of team learning can manifest in different ways over time). The integrative theoretical heuristic distinguishes team learning process theories, supporting emergent states, team knowledge representations, and respective influences on team performance and effectiveness. Promising directions for theory development and research are discussed

Mediating Cognitive Transformation with VR 3D Sketching during Conceptual Architectural Design Process

Communications for information synchronization during the conceptual design phase require designers to employ more intuitive digital design tools. This paper presents findings of a feasibility study for using VR 3D sketching interface in order to replace current non-intuitive CAD tools. We used a sequential mixed method research methodology including a qualitative case study and a cognitive-based quantitative protocol analysis experiment. Foremost, the case study research was conducted in order to understand how novice designers make intuitive decisions. The case study documented the failure of conventional sketching methods in articulating complicated design ideas and shortcomings of current CAD tools in intuitive ideation. The case study’s findings then became the theoretical foundations for testing the feasibility of using VR 3D sketching interface during design. The latter phase of study evaluated the designers’ spatial cognition and collaboration at six different levels: “physical-actions”, “perceptualac ons”, “functional-actions”, “conceptual-actions”, “cognitive synchronizations”, and “gestures”. The results and confirmed hypotheses showed that the utilized tangible 3D sketching interface improved novice designers’ cognitive and collaborative design activities. In summary this paper presents the influences of current external representation tools on designers’ cognition and collaboration as well as providing the necessary theoretical foundations for implementing VR 3D sketching interface. It contributes towards transforming conceptual architectural design phase from analogue to digital by proposing a new VR design interface. The paper proposes this transformation to fill in the existing gap between analogue conceptual architectural design process and remaining digital engineering parts of building design process hence expediting digital design process

Designing online role plays with a focus on story development to support engagement and critical learning for higher education students

Online role plays, as they are designed for use in higher education in Australia and internationally, are active and authentic learning activities (Wills, Leigh & Ip, 2011). In online role plays, students take a character role in developing a story that serves as a metaphor for real-life experience in order to develop a potentially wide range of subject-related and generic learning outcomes. The characteristics of these stories are rarely considered as factors in the design―and success―of these activities. The unspoken cultural assumptions, norms and rules in the stories that impact on the meanings students make from their experiences are also rarely scrutinised in the online role play literature. This paper presents findings from a case study of an asynchronous text-based online role play involving politics and journalism students from three Australian universities. The findings highlight the centrality of students’ collaborative story-building activity to their engagement and learning, including their development of critical perspectives. The study underlines the importance of certain aspects of the role play\u27s design to support students\u27 story-building activity

Computational and Robotic Models of Early Language Development: A Review

We review computational and robotics models of early language learning and development. We first explain why and how these models are used to understand better how children learn language. We argue that they provide concrete theories of language learning as a complex dynamic system, complementing traditional methods in psychology and linguistics. We review different modeling formalisms, grounded in techniques from machine learning and artificial intelligence such as Bayesian and neural network approaches. We then discuss their role in understanding several key mechanisms of language development: cross-situational statistical learning, embodiment, situated social interaction, intrinsically motivated learning, and cultural evolution. We conclude by discussing future challenges for research, including modeling of large-scale empirical data about language acquisition in real-world environments. Keywords: Early language learning, Computational and robotic models, machine learning, development, embodiment, social interaction, intrinsic motivation, self-organization, dynamical systems, complexity.Comment: to appear in International Handbook on Language Development, ed. J. Horst and J. von Koss Torkildsen, Routledg