From The Training Room to the Classroom: Applying Concepts of Corporate Training and Tertiary Education in Secondary Education

The COVID-19 pandemic has changed the nature of secondary education and encouraged teaching through blended and e-learning. This article explores how the author integrated concepts he previously applied in tertiary education and corporate training, particularly Finks Taxonomy of Significant Learning and P3 Task Taxonomy, through blended and e-Learning to a secondary education context. These ideas developed into a teaching methodology for a business curriculum and were delivered in an international Christian school in Cambodia. The teaching methodology helped streamline curriculum development, adapt to the changing conditions, and improve overall lesson delivery. The study recommends that the teaching methodology be explored further and be developed as a framework to support new and developing teaching staff.

Rapidly Learning Generalizable and Robot-Agnostic Tool-Use Skills for a Wide Range of Tasks

Many real-world applications require robots to use tools. However, robots lack the skills necessary to learn and perform many essential tool-use tasks. To this end, we present the TRansferrIng Skilled Tool Use Acquired Rapidly (TRI-STAR) framework for task-general robot tool use. TRI-STAR has three primary components: 1) the ability to learn and apply tool-use skills to a wide variety of tasks from a minimal number of training demonstrations, 2) the ability to generalize learned skills to other tools and manipulated objects, and 3) the ability to transfer learned skills to other robots. These capabilities are enabled by TRI-STAR’s task-oriented approach, which identifies and leverages structural task knowledge through the use of our goal-based task taxonomy. We demonstrate this framework with seven tasks that impose distinct requirements on the usages of the tools, six of which were each performed on three physical robots with varying kinematic configurations. Our results demonstrate that TRI-STAR can learn effective tool-use skills from only 20 training demonstrations. In addition, our framework generalizes tool-use skills to morphologically distinct objects and transfers them to new platforms, with minor performance degradation.

New Impressions in Interaction Design: A Task Taxonomy for Elastic Displays

Novel shape-changing interfaces promise to provide a rich haptic experience for human-computer interaction. As a specific instance of shape-changing interfaces, Elastic Displays provide large interaction surfaces that can be temporally deformed using force-touch. The unique property of these displays is that they automatically return to their initial flat state. Recently, several review and position papers have stimulated a discussion towards consolidating the knowledge about shape-changing interfaces. The knowledge about Elastic Displays is similarly scattered across multiple publications from recent years. This paper contributes a task taxonomy based on productive uses of Elastic Displays found in literature, on the web, and in our interaction lab. This taxonomy emphasizes tasks, but also encompasses general aspects regarding content types, visualization technology, and interaction styles. All aspects of the taxonomy are illustrated using case studies from literature.

Building a Framework for a Dual Task Taxonomy

The study of dual task interference has gained increasing attention in the literature for the past 35 years, with six MEDLINE citations in 1979 growing to 351 citations indexed in 2014 and a peak of 454 cited papers in 2013. Increasingly, researchers are examining dual task cost in individuals with pathology, including those with neurodegenerative diseases. While the influence of these papers has extended from the laboratory to the clinic, the field has evolved without clear definitions of commonly used terms and with extreme variations in experimental procedures. As a result, it is difficult to examine the interference literature as a single body of work. In this paper we present a new taxonomy for classifying cognitive-motor and motor-motor interference within the study of dual task behaviors that connects traditional concepts of learning and principles of motor control with current issues of multitasking analysis. As a first step in the process we provide an operational definition of dual task, distinguishing it from a complex single task. We present this new taxonomy, inclusive of both cognitive and motor modalities, as a working model; one that we hope will generate discussion and create a framework from which one can view previous studies and develop questions of interest.