Learning Robotics, with Robotics, by Robotics

Educational Robotics

Ilaria Gaudiello, Elisabetta Zibetti

• Publisher: Wiley-ISTE
• Year: 2016
• ISBN:
  9781119335733
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Robotics
• Index: Technology & Engineering

The relationship between technological and pedagogical innovation has recently created a new field of research at the crossroads between Psychology, Educational Sciences and Artificial Intelligence: Educational Robotics (ER).

Through analysis of the achievable educational goals based on the technological status and specific learning modes of different types of robots, it is possible to define three pedagogical paradigms: learning robotics, learning with robotics, and learning by robotics.

In this book we address these three paradigms through three themes: human representations of robots, the acceptance and trust shown when interacting with a humanoid, and learning favored by the development and programming of robots in an educational context. These themes allow the authors to fully explore, define and delimit this novel field of research for future application in educational and social contexts.

Finally, the book discusses contributions and limitations which have emerged from different methodologies of research, potential educational applications, and concepts of human–robot interaction for the development of the above paradigms.

1
Learning Robotics: Users’ Representation of Robots

1.1. Introduction: the ontological and pedagogical status of robots

In recent years, there has been a growing interest in users’ representations of robots within several complementary fields of study: cognitive psychology [KAH 06, JIP 07, BER 08, BER 11], science and technology education [e.g. SLA 11] and anthropology [GRI 12]. The reason for this interest lies in a shared wonder at a new technology which, despite being a manmade entity, i.e. an artifact, has enough power to surpass people in the accomplishment of several physical and decision-making tasks. This mixed definition of the robot, as an entity that possesses at the same time something that is greater than and something that is less than living and non-living beings, seems to challenge traditional ontological categories [SEV 10]. The difficulty involved in assigning robots either to the category of living entities or to that of non-living entities has led researchers from different fields not only to postulate the creation of a completely new category of objects but also to revise the traditional concept of “being alive” itself. In the words of MacDorman and colleagues [MAC 09, p. 486]:

“Among all human artifacts, perhaps robots share the most in common with their maker. Like computers, and in fact because they are controlled by computers, they can process huge amounts of information. Like powered equipment, they can manipulate their environment and move within it. And like dolls, mannequins and other effigies, they can resemble us – either abstractly or down to the dimples of our cheeks. Nevertheless, the differences between machine and maker are profound. Metabolism, life span, sexual reproduction, ancestry, culture and consciousness for now distinguish us from robots. Thus, the similarities and differences between us and them circumscribe a chasm that is at once narrow and deep”.

Robotics kits, in particular, have an interesting status. On the one hand, they are engineering objects that Slangen et al. [SLA 11] describe as “a system, that is, any group of interrelated parts designed collectively to achieve a designed goal. The system maintains its fundamental structure notwithstanding the possibility of infinite transformations. Systems have input, processes, and output. In order to perform a task a robot integrates solutions to sub-problems from different technological domains (e.g. mechanics, electronics, pneumatics, calculation) into one machine. The robot is a construction and consists of a frame with static components (bricks, pins, beams), dynamic mechanical components (gears, axles), electronic components (sensors, display, bulbs) and electro-mechanical components (motors). Robots should be well designed and constructed with the right components, and be stable and strong enough to enable the execution of the function(s). This requires understanding of concepts like stability, sturdiness, motion, etc. (…) The robot is controlled by means of software designed to enable the robot to function. (…) The performance of a robot is based on the three basic capabilities of sensing (S), reasoning (R) and acting (A), which repeat in succession and form the so-called S-R-A loop [VAN 06]. A robot that is able to sense, reason and act needs hardware components like sensors, a PLC, and actuators (motors, bulbs, speakers, displays)”.

On the other hand, there is something unique about robotics kits. To explain this uniqueness, we refer to the work of Severson and Carlson [SEV 10], who first applied the expression “creative control” to robots, meaning that users of this kind of robot experience a form of simulation, projection and personification similar to that experienced by children during imaginative play. That is, the fact that this kind of robot has to be physically created from scratch through assembly procedures and progressively “tamed” through algorithms, implies that users are simultaneously engineers and interpreters of robots’ behavior [ACK 91]. This, we believe, requires an imaginative effort consisting of shaping a representation and reshaping it through time, as the robot is developed by its users.

1.2. What do we mean by robot representation?

Representations have a pivotal role in cognitive psychology research. They are generally described as mental constructs that may concern the physical world, but also social and mental entities [LE 05]. They can be permanent or occasional, that is stable or triggered by some specific activity or context [STE 09]. Within the robotics literature, the term “representation” often occurs as an umbrella concept that incorporates different meanings. These meanings have been investigated using methods that are traditionally employed to find out how users perceive innovative technologies, but, interestingly, also to examine the status of imaginary or fictional entities such as made-up companions or the characters of cartoon movies [SEV 10], as well as of strangers...