Título: Design of Collaborative Computational Ecosystems for the Development of STEAM Competencies in Schools

Congreso: INTED2019. 13th International Technology, Education and Development Conference

Lugar y Fecha: Valencia, 11 y 12 de Marzo de 2019

Abstract:

This paper presents the objectives, design principles and structure of a project for the integration of  STEAM in the classroom. It reviews the fundamental causes that have limited until now this integration in pioneer countries such as the United States or the United Kingdom. This project describes three proposals: 1) a fundamental modernization of STEAM, from traditional algebra-based model to a computational-based model; 2) a learning methodology based on the cognitive scope of the human mind, that we labeled Inertial Learning; and 3) a methodology, based on computational environments, called computational ecosystems, to address the three limitations of algebraic-STEAM: school curriculum; human cognition; and computation in complex systems. Finally, it details some implementation aspects of the project, including an academic social network.

Inertial Learning: Cognitive System-1

1. The cognitive processes of the human mind are globally classified according to the cognitive system in which they are developed: System-1 and System-2 [1,2].
2. System-1 is characterized by its ability to maintain multiple processes simultaneously. It operates in parallel mode with multiple processes. And these processes cooperate in the resolution of hierarchically superior tasks.
3. System-2 performs cognitive tasks that require logical and sequential processing. It is limited to  implement  one task at a time. It manipulates data stored in short-term memory. For these two reasons, the computational complexity of the tasks that System-2 can implement is very limited. In addition, the maintenance of data in short-term memory requires attention and energy. The attention interferes with other potential tasks, and the energy required produces the fatigue associated with System-2 tasks.
4. In this project we propose the development of “Inertial Learning” as a set of principles for education that identify System-1 as the almost exclusive cognitive engine of the students [3]. Its name, Inertial, refers to the physical concept of inertia of Newton's First Law of Motion: the ability of a body to keep moving without requiring additional forces.
5. In the same way that a free body maintains its velocity vector infinitely in the absence of obstructing forces, System-1 maintains its inertial cognitive moment due to the following fundamental cognitive properties: 1) it has an immediate and effortless access to permanent memory; and 2) it operates parallel processes without effort by delegating computation to hierarchically lower computational layers.
6. Extending the inertial metaphor, System-2 is plagued with countless opposing forces that require constant renewing effort for the conservation of the inertial cognitive moment. These opposing forces experience by System-2 have their root in evolutionary biological processes. Regarding memory, System-2 lacks any useful set of data storage primitives, requiring an inefficient memory rehearsal process that limits human short-memory to seven items [4,5]. Regarding data processing, System-2 lacks direct commanding access to lower computational layers.
7. Processes such as the recognition of people and objects, speaking and understanding the native language, walking, or driving a car, require an initial effort that System-1 uses to achieve a level of permanent mastery and execution without apparent effort.
8. Multiplying mentally three-digit numbers or remembering series of digits requires the use of System-2, which even in computationally simple tasks has great difficulty. Evolutionarily, System-2 has been created as a catalyst or training stage in the incorporation of new knowledge into System-1, and not as a fundamental cognitive tool of the human being.
9. Inertial learning proposes a paradigm and a set of fundamental principles in which System-2 is used in cooperation of computational ecosystems for the acquisition of new knowledge. The new knowledge will be structured as cognitive virtual machines running on System-1 that will harness its existing multi-layer, parallel processing structure, and the immediate, automatic, and effortless access to permanent longterm memory [3].