scholarly journals LearningML: A Tool to Foster Computational Thinking Skills Through Practical Artificial Intelligence Projects

2020 ◽  
Vol 20 (63) ◽  
Author(s):  
Juan David Rodríguez García ◽  
Jesús Moreno-León ◽  
Marcos Román-González ◽  
Gregorio Robles
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Lessons Learned ◽  
Supervised Machine Learning ◽  
Hands On ◽  
The Face ◽  
Multiple Levels ◽  
Critical Citizens

El uso de sistemas de inteligencia artificial en múltiples niveles de la sociedad ofrece nuevas y prósperas oportunidades, pero también introduce nuevos riesgos y cuestiones éticas que deben abordarse. Sostenemos que la introducción de contenidos de inteligencia artificial en las escuelas a través de proyectos prácticos es el camino a seguir para educar ciudadanos conscientes y críticos, para despertar vocaciones entre los jóvenes, y para fomentar las habilidades de pensamiento computacional de los estudiantes. Sin embargo, la mayoría de las plataformas educativas de programación existentes carecen de algunas características necesarias para desarrollar proyectos completos de IA y, en consecuencia, se requieren nuevas herramientas. En este artículo presentamos LearningML, una nueva plataforma dirigida al aprendizaje automático supervisado, una de las técnicas de IA más exitosas que se encuentra en la base de casi todas las aplicaciones actuales de IA. Este trabajo describe las principales funcionalidades de la herramienta y discute algunas decisiones tomadas durante su diseño, para el que hemos tenido en cuenta las lecciones aprendidas al revisar trabajos anteriores realizados para introducir la IA en la escuela y el análisis de otras soluciones que permiten proyectos prácticos de IA. También se presentan los próximos pasos en el desarrollo de LearningML, que se centran en la validación, tanto aparente como instruccional, de la herramienta. The use of artificial intelligence systems in multiple levels of society offers new and thriving opportunities, but also introduces new risks and ethical issues that should be dealt with. We argue that the introduction of artificial intelligence contents at schools through practical, hands-on, projects is the way to go in order to educate conscientious and critical citizens, to awaken vocations among youth people, as well as to foster students’ computational thinking skills. However, most existing programming platforms for education lack some required features to develop complete AI projects and, consequently, new tools are required. In this paper we present LearningML, a new platform aimed at learning supervised Machine Learning, one of the most successful AI techniques that is in the basis of almost every current AI application. This work describes the main functionalities of the tool and discusses some decisions taken during its design, for which we took into account the lessons learned while reviewing previous works carried out for introducing AI in school and from the analysis of other solutions that enable practical AI projects. The next steps in the development of LearningML are also presented, which are focused on both the face and instructional validation of the tool.

Developing Preschoolers' Computational Thinking Skills Through Digital Gameplay

2021 ◽  
pp. 312-343
Author(s):  
Heather Lavigne ◽  
Jillian Orr ◽  
Marisa Wolsky ◽  
Borgna Brunner ◽  
Amanda Wright
Keyword(s):  
Theoretical Model ◽  
Digital Media ◽  
Classroom Instruction ◽  
Developmentally Appropriate ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Lessons Learned ◽  
Classroom Research ◽  
Math Instruction ◽  
Hands On

This chapter provides an overview of how digital media can be leveraged to support the exploration of developmentally appropriate computational thinking (CT) skills for preschoolers. These skills, named CT Core Ideas in the project team's framework, support children's abilities to tackle problems or goals using systematic, computational strategies. The authors describe a theoretical model that outlines the ways in which CT aligns with preschool math instruction, and how children can apply their CT skills through digital gameplay. This chapter also shares lessons learned from classroom research with teachers and children and describes several game prototypes that children played to practice their CT skills. At the end of the chapter, they provide recommendations for how educators can support young children's CT by integrating hands-on gameplay into classroom instruction.

scholarly journals Educing AI-Thinking in Science, Technology, Engineering, Arts, and Mathematics (STEAM) Education

2019 ◽  
Vol 9 (3) ◽  
pp. 184 ◽  
Author(s):  
Meng-Leong How ◽  
Wei Loong David Hung
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Thinking Skills ◽  
Supervised Machine Learning ◽  
Controlled Experiments ◽  
Machine Learn ◽  
Science Technology ◽  
Steam Education ◽  
Computer Scientists ◽  
And Mathematics

In science, technology, engineering, arts, and mathematics (STEAM) education, artificial intelligence (AI) analytics are useful as educational scaffolds to educe (draw out) the students’ AI-Thinking skills in the form of AI-assisted human-centric reasoning for the development of knowledge and competencies. This paper demonstrates how STEAM learners, rather than computer scientists, can use AI to predictively simulate how concrete mixture inputs might affect the output of compressive strength under different conditions (e.g., lack of water and/or cement, or different concrete compressive strengths required for art creations). To help STEAM learners envision how AI can assist them in human-centric reasoning, two AI-based approaches will be illustrated: first, a Naïve Bayes approach for supervised machine-learning of the dataset, which assumes no direct relations between the mixture components; and second, a semi-supervised Bayesian approach to machine-learn the same dataset for possible relations between the mixture components. These AI-based approaches enable controlled experiments to be conducted in-silico, where selected parameters could be held constant, while others could be changed to simulate hypothetical “what-if” scenarios. In applying AI to think discursively, AI-Thinking can be educed from the STEAM learners, thereby improving their AI literacy, which in turn enables them to ask better questions to solve problems.

scholarly journals PopBots: Designing an Artificial Intelligence Curriculum for Early Childhood Education

2019 ◽  
Vol 33 ◽  
pp. 9729-9736 ◽  
Author(s):  
Randi Williams ◽  
Hae Won Park ◽  
Lauren Oh ◽  
Cynthia Breazeal
Keyword(s):  
Artificial Intelligence ◽  
Young Children ◽  
Computational Thinking ◽  
Social Robot ◽  
Kindergarten Children ◽  
Learning Needs ◽  
Teaching Approaches ◽  
Childhood Education ◽  
Hands On ◽  
Specific Learning

PopBots is a hands-on toolkit and curriculum designed to help young children learn about artificial intelligence (AI) by building, programming, training, and interacting with a social robot. Today’s children encounter AI in the forms of smart toys and computationally curated educational and entertainment content. However, children have not yet been empowered to understand or create with this technology. Existing computational thinking platforms have made ideas like sequencing and conditionals accessible to young learners. Going beyond this, we seek to make AI concepts accessible. We designed PopBots to address the specific learning needs of children ages four to seven by adapting constructionist ideas into an AI curriculum. This paper describes how we designed the curriculum and evaluated its effectiveness with 80 Pre-K and Kindergarten children. We found that the use of a social robot as a learning companion and programmable artifact was effective in helping young children grasp AI concepts. We also identified teaching approaches that had the greatest impact on student’s learning. Based on these, we make recommendations for future modules and iterations for the PopBots platform.

A Block-Based Arduino Programming Platform for Developing Computational Thinking Skills for K-12 Students

2021 ◽  
Author(s):  
Binsen Qian ◽  
Harry H. Cheng
Keyword(s):  
Real World ◽  
Autonomous Vehicles ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Critical Set ◽  
Programming Students ◽  
Hands On ◽  
Block Based ◽  
K 12 ◽  
And Robotics

Abstract As a critical set of skills in the 21st century, computational thinking has attracted increasing attention in K-12 education. Microcontrollers, combined with LEDs, actuators, and a variety of sensors, provide students countless real-world projects, such as autonomous vehicles, smart homes, and robotics. By solving those projects through programming, students will not only learn computational skills but also benefit from the hands-on activities to get some experience on solving real-world problems. It makes microcontroller projects a perfect tool to develop the computational thinking skills of K-12 students. Our previous work has proposed a solution for higher graders to program Arduino through Ch, a C/C++ interpreter. It is necessary, however, to develop a platform for lower graders (K-6) since most of them do not have the ability to type through the keyboard. This paper extends our previous work such that students can program Arduino on RoboBlockly, a block-based programming platform. In the paper, we will present two case studies to demonstrate how to build blocks to control the Arduino board and what concepts students will learn from those projects. In addition, the proposed platform also provides an interactive way of transitioning students from the block-based program to a text-based program in Ch.

scholarly journals Inquiry and critical thinking skills for the next generation: from artificial intelligence back to human intelligence

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Jonathan Michael Spector ◽  
Shanshan Ma
Keyword(s):  
Artificial Intelligence ◽  
Critical Thinking ◽  
21St Century ◽  
Thinking Skills ◽  
Critical Thinking Skills ◽  
Habits Of Mind ◽  
Human Intelligence ◽  
Developmental Approach ◽  
Multiple Levels ◽  
Definition Of

Abstract Along with the increasing attention to artificial intelligence (AI), renewed emphasis or reflection on human intelligence (HI) is appearing in many places and at multiple levels. One of the foci is critical thinking. Critical thinking is one of four key 21st century skills – communication, collaboration, critical thinking and creativity. Though most people are aware of the value of critical thinking, it lacks emphasis in curricula. In this paper, we present a comprehensive definition of critical thinking that ranges from observation and inquiry to argumentation and reflection. Given a broad conception of critical thinking, a developmental approach beginning with children is suggested as a way to help develop critical thinking habits of mind. The conclusion of this analysis is that more emphasis should be placed on developing human intelligence, especially in young children and with the support of artificial intelligence. While much funding and support goes to the development of artificial intelligence, this should not happen at the expense of human intelligence. Overall, the purpose of this paper is to argue for more attention to the development of human intelligence with an emphasis on critical thinking.

Computational Thinking and Robotics

2020 ◽  
pp. 90-115
Author(s):  
Carol Munn
Keyword(s):  
21St Century ◽  
Computational Thinking ◽  
Essential Element ◽  
Thinking Skills ◽  
Robotics Education ◽  
Hands On ◽  
Unique Framework ◽  
And Mathematics ◽  
And Robotics ◽  
Mathematics And Science

This chapter explores a unique framework that expresses freshness and innovation within revolutionary learning experiences. The chapter focuses on the implementation of computational thinking skills as an essential element of a robotics education program that was driven by hands-on activities instilling the notion of imagination through innovative projects. Engineering design applications with robotics created an atmosphere in which students applied abstract mathematics and science concepts. The robot and its technology imploding in the field of education created excitement in the minds of students with renewed, revitalized interest, and curiosity stretching across the areas of science, technology, engineering, and mathematics (STEM). Robotics education along with computational thinking skills are primary keys for unlocking the unlimited creative and innovative potential with engaging hands-on activities. Robots, a fascinating learning instrument, rejuvenate, animate, and revive 21st century skills in tech-savvy language familiar with today's students.

scholarly journals RESEARCH BASED LEARNING (RBL) TO IMPROVE CRITICAL THINKING SKILLS

2019 ◽  
Vol 1 (2) ◽  
pp. 466
Author(s):  
Tiyara Mahardini ◽  
Firdaus Khaerunisa ◽  
Indah Wahyu Wijayanti ◽  
Moh Salimi
Keyword(s):  
Critical Thinking ◽  
Learning Strategies ◽  
Thinking Skills ◽  
Field Education ◽  
Critical Thinking Skills ◽  
Social Culture ◽  
Hands On ◽  
The Face ◽  
Prospective Educators ◽  
Relationship Of

<em>The era disruption carrying a lot of changes, both from field of social, culture, economic and education. In the field education in the face of the disruption, educators must be able to develop four skills, namely communication, collaboration, critical thinking, and creativity. Teachers and prospective educators need to develop critical thinking skills by using learning strategies. So we need a method which appropriated with developing of critical thinking skills. Aims of study are describe concept of Research Based Learning (RBL), concept of critical thinking skills, and relationship of RBL and critical thinking skills. The results of Research Based Learning (RBL) can improve critical thinking skills because in this learning method uses authentic learning, problem-solving, cooperative learning, contextual (hands on &amp; minds on) and inquiry-discovery approaches. </em>

Computational Thinking and Robotics

2022 ◽  
pp. 1-20
Author(s):  
Carol Munn
Keyword(s):  
21St Century ◽  
Computational Thinking ◽  
Essential Element ◽  
Thinking Skills ◽  
Robotics Education ◽  
Hands On ◽  
Unique Framework ◽  
And Mathematics ◽  
And Robotics ◽  
Mathematics And Science

This chapter explores a unique framework that expresses freshness and innovation within revolutionary learning experiences. The chapter focuses on the implementation of computational thinking skills as an essential element of a robotics education program that was driven by hands-on activities instilling the notion of imagination through innovative projects. Engineering design applications with robotics created an atmosphere in which students applied abstract mathematics and science concepts. The robot and its technology imploding in the field of education created excitement in the minds of students with renewed, revitalized interest, and curiosity stretching across the areas of science, technology, engineering, and mathematics (STEM). Robotics education along with computational thinking skills are primary keys for unlocking the unlimited creative and innovative potential with engaging hands-on activities. Robots, a fascinating learning instrument, rejuvenate, animate, and revive 21st century skills in tech-savvy language familiar with today's students.

scholarly journals Engineering Courses on Computational Thinking Through Solving Problems in Artificial Intelligence

2017 ◽  
Vol 7 (3) ◽  
pp. 34
Author(s):  
Piyanuch Silapachote ◽  
Ananta Srisuphab
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Machine Intelligence ◽  
Collaborative Problem Solving ◽  
Learning To Learn ◽  
Dynamic Learning ◽  
Analytical Thinking ◽  
Mathematical Foundations

Computational thinking sits at the core of every engineering and computing related discipline. It has increasingly emerged as its own subject in all levels of education. It is a powerful cornerstone for cognitive development, creative problem solving, algorithmic thinking and designs, and programming. How to effectively teach computational thinking skills poses real challenges and creates opportunities. Targeting entering computer science and engineering undergraduates, we resourcefully integrate elements from artificial intelligence (AI) into introductory computing courses. In addition to comprehension of the essence of computational thinking, practical exercises in AI enable inspirations of collaborative problem solving beyond abstraction, logical reasoning, critical and analytical thinking. Problems in machine intelligence systems intrinsically connect students to algorithmic oriented computing and essential mathematical foundations. Beyond knowledge representation, AI fosters a gentle introduction to data structures and algorithms. Focused on engaging mental tool, a computer is never a necessity. Neither coding nor programming is ever required. Instead, students enjoy constructivist classrooms designed to always be active, flexible, and highly dynamic. Learning to learn and reflecting on cognitive experiences, they rigorously construct knowledge from collectively solving exciting puzzles, competing in strategic games, and participating in intellectual discussions.

scholarly journals Pemikiran Komputasi (Computational Thinking) dalam Pemecahan Masalah

2020 ◽  
Vol 3 (1) ◽  
pp. 111-126
Author(s):  
Miksan Ansori
Keyword(s):  
Problem Solving ◽  
Rapid Development ◽  
Computational Thinking ◽  
Thinking Skills ◽  
Learning Practices ◽  
The Face ◽  
School Learning

Computational thinking is a very necessary capability in the face of the rapid development of ICT and complex. Besides, the 4.0 industrial era also requires computerization in all areas. Nevertheless, there are still not many learning practices aimed at enhancing computational thinking skills for students. Even in Indonesia, the study of Computitatioan thinking is still very minimal. Using a library review, this article will discuss the computational thinking skills in problem-solving and examples of implementation in school learning.

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