The upsurge of deep learning for computer vision applicationsIJECEIAES
Artificial intelligence (AI) is additionally serving to a brand new breed of corporations disrupt industries from restorative examination to horticulture. Computers can’t nevertheless replace humans, however, they will work superbly taking care of the everyday tangle of our lives. The era is reconstructing big business and has been on the rise in recent years which has grounded with the success of deep learning (DL). Cyber-security, Auto and health industry are three industries innovating with AI and DL technologies and also Banking, retail, finance, robotics, manufacturing. The healthcare industry is one of the earliest adopters of AI and DL. DL accomplishing exceptional dimensions levels of accurateness to the point where DL algorithms can outperform humans at classifying videos & images. The major drivers that caused the breakthrough of deep neural networks are the provision of giant amounts of coaching information, powerful machine infrastructure, and advances in academia. DL is heavily employed in each academe to review intelligence and within the trade-in building intelligent systems to help humans in varied tasks. Thereby DL systems begin to crush not solely classical ways, but additionally, human benchmarks in numerous tasks like image classification, action detection, natural language processing, signal process, and linguistic communication process.
Teaching AI through Machine Learning Projectsbutest
This document summarizes work developing machine learning projects to unify an introductory artificial intelligence course. The projects aim to introduce machine learning elements, implement unifying laboratory experiences around core AI topics, and develop an adaptable framework emphasizing the relationship between AI and computer science. One project involves classifying web documents using machine learning techniques and data mining tools. The experiences using these projects in AI courses are also discussed.
This document discusses the emergence of smart e-education and e-learning. It describes how new technologies are enabling personalized, mobile, collaborative and analytics-based learning. It outlines the construction of smart learning environments including smart devices, classrooms, labs, campuses and educational clouds. Examples of smart e-learning applications in China include e-textbooks, e-schoolbags and smart campuses. Challenges to facilitating smart education include changes to pedagogy, educational technology leadership, and teachers' roles. National projects in China are addressing these challenges through competency standards and teacher training.
Emergence of Smart e-Learning and Education Zhu ZhitingEIFLINQ2014
This document discusses the emergence of smart e-learning and e-education. It describes how new technologies allow for instrumentation, interconnection, and intelligence infusion. Smart education creates intelligent learning environments using smart technologies to enable personalized and collaborative learning. The document outlines the construction of smart learning environments including smart devices, classrooms, labs, and educational clouds. It provides examples of smart education programs and applications being developed in countries like Australia, South Korea, and China. Finally, it discusses challenges of facilitating smart education including changes needed to pedagogical theory, teacher roles, and educational structures and ideologies.
Artificial intelligence in mobile learningDinesh More
This document discusses the application of artificial intelligence in mobile learning. It first defines mobile learning and artificial intelligence, noting that mobile learning allows learning anywhere and anytime using mobile devices. It then discusses five problems in mobile learning that make applying artificial intelligence necessary. Finally, it provides examples of specific artificial intelligence applications in mobile learning, including mobile intelligent teaching expert systems, decision support systems, information retrieval engines, and intelligent hardware networks.
This document outlines how AI could impact higher education in 10 ways: (1) natural language generation, (2) speech recognition, (3) virtual agents, (4) machine learning platforms, (5) AI optimized hardware, (6) decision management, (7) deep learning platforms, (8) biometrics, (9) robotic process automation, and (10) text analytics. It then provides examples of current AI activities in higher education, including automated feedback/grading, intelligent tutoring, learning analytics, student support services, adaptive group formation, virtual agents, virtual reality, and personalized adaptive learning. The document concludes by noting some key concerns with AI in education, such as explainability, bias, filter bubbles,
A cognitive robot equipped with autonomous tool innovation expertise IJECEIAES
Like a human, a robot may benefit from being able to use a tool to solve a complex task. When an appropriate tool is not available, a very useful ability for a robot is to create a novel one based on its experience. With the advent of inexpensive 3D printing, it is now possible to give robots such an ability, at least to create simple tools. We proposed a method for learning how to use an object as a tool and, if needed, to design and construct a new tool. The robot began by learning an action model of tool use for a PDDL planner by observing a trainer. It then refined the model by learning by trial and error. Tool creation consisted of generalising an existing tool model and generating a novel tool by instantiating the general model. Further learning by experimentation was performed. Reducing the search space of potentially useful tools could be achieved by providing a tool ontology. We then used a constraint solver to obtain numerical parameters from abstract descriptions and use them for a ready-to-print design. We evaluated our system using a simulated and a real Baxter robot in two cases: hook and wedge. We found that our system performs tool creation successfully.
The upsurge of deep learning for computer vision applicationsIJECEIAES
Artificial intelligence (AI) is additionally serving to a brand new breed of corporations disrupt industries from restorative examination to horticulture. Computers can’t nevertheless replace humans, however, they will work superbly taking care of the everyday tangle of our lives. The era is reconstructing big business and has been on the rise in recent years which has grounded with the success of deep learning (DL). Cyber-security, Auto and health industry are three industries innovating with AI and DL technologies and also Banking, retail, finance, robotics, manufacturing. The healthcare industry is one of the earliest adopters of AI and DL. DL accomplishing exceptional dimensions levels of accurateness to the point where DL algorithms can outperform humans at classifying videos & images. The major drivers that caused the breakthrough of deep neural networks are the provision of giant amounts of coaching information, powerful machine infrastructure, and advances in academia. DL is heavily employed in each academe to review intelligence and within the trade-in building intelligent systems to help humans in varied tasks. Thereby DL systems begin to crush not solely classical ways, but additionally, human benchmarks in numerous tasks like image classification, action detection, natural language processing, signal process, and linguistic communication process.
Teaching AI through Machine Learning Projectsbutest
This document summarizes work developing machine learning projects to unify an introductory artificial intelligence course. The projects aim to introduce machine learning elements, implement unifying laboratory experiences around core AI topics, and develop an adaptable framework emphasizing the relationship between AI and computer science. One project involves classifying web documents using machine learning techniques and data mining tools. The experiences using these projects in AI courses are also discussed.
This document discusses the emergence of smart e-education and e-learning. It describes how new technologies are enabling personalized, mobile, collaborative and analytics-based learning. It outlines the construction of smart learning environments including smart devices, classrooms, labs, campuses and educational clouds. Examples of smart e-learning applications in China include e-textbooks, e-schoolbags and smart campuses. Challenges to facilitating smart education include changes to pedagogy, educational technology leadership, and teachers' roles. National projects in China are addressing these challenges through competency standards and teacher training.
Emergence of Smart e-Learning and Education Zhu ZhitingEIFLINQ2014
This document discusses the emergence of smart e-learning and e-education. It describes how new technologies allow for instrumentation, interconnection, and intelligence infusion. Smart education creates intelligent learning environments using smart technologies to enable personalized and collaborative learning. The document outlines the construction of smart learning environments including smart devices, classrooms, labs, and educational clouds. It provides examples of smart education programs and applications being developed in countries like Australia, South Korea, and China. Finally, it discusses challenges of facilitating smart education including changes needed to pedagogical theory, teacher roles, and educational structures and ideologies.
Artificial intelligence in mobile learningDinesh More
This document discusses the application of artificial intelligence in mobile learning. It first defines mobile learning and artificial intelligence, noting that mobile learning allows learning anywhere and anytime using mobile devices. It then discusses five problems in mobile learning that make applying artificial intelligence necessary. Finally, it provides examples of specific artificial intelligence applications in mobile learning, including mobile intelligent teaching expert systems, decision support systems, information retrieval engines, and intelligent hardware networks.
This document outlines how AI could impact higher education in 10 ways: (1) natural language generation, (2) speech recognition, (3) virtual agents, (4) machine learning platforms, (5) AI optimized hardware, (6) decision management, (7) deep learning platforms, (8) biometrics, (9) robotic process automation, and (10) text analytics. It then provides examples of current AI activities in higher education, including automated feedback/grading, intelligent tutoring, learning analytics, student support services, adaptive group formation, virtual agents, virtual reality, and personalized adaptive learning. The document concludes by noting some key concerns with AI in education, such as explainability, bias, filter bubbles,
A cognitive robot equipped with autonomous tool innovation expertise IJECEIAES
Like a human, a robot may benefit from being able to use a tool to solve a complex task. When an appropriate tool is not available, a very useful ability for a robot is to create a novel one based on its experience. With the advent of inexpensive 3D printing, it is now possible to give robots such an ability, at least to create simple tools. We proposed a method for learning how to use an object as a tool and, if needed, to design and construct a new tool. The robot began by learning an action model of tool use for a PDDL planner by observing a trainer. It then refined the model by learning by trial and error. Tool creation consisted of generalising an existing tool model and generating a novel tool by instantiating the general model. Further learning by experimentation was performed. Reducing the search space of potentially useful tools could be achieved by providing a tool ontology. We then used a constraint solver to obtain numerical parameters from abstract descriptions and use them for a ready-to-print design. We evaluated our system using a simulated and a real Baxter robot in two cases: hook and wedge. We found that our system performs tool creation successfully.
This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
Mobile augmented reality using 3D ruler in a robotic educational module to pr...journalBEEI
Robotics education is gaining popularity among school children in line with the government desire to promote creative thinking in students through STEM based activities. However, the robots for educational games are usually made up of components and its description is usually one-way and static. Additionally, students find it difficult to visualize distances from robot movements when playing educational robotic games. Augmented reality (AR) technology is a viable tool to connect between in-context information and physical activities. The objective of this research is to design and develop an AR based application that can visualize the distance between two robots for supporting learning process in a game-based module. The application consists of three parts; the first part use AR in identification of components related to robots, while the second part involves the addition of real-time visualization in the form of AR, enabling students to learn the distance from the robot's movements. The third part used AR in providing the description of the robotic games through videos. The development of the application is based on the Agile model. The results show that the application has received positive feedbacks from students as it can increase their interest in playing robotic educational games.
Educational technology can be defined in various ways but generally refers to the process of applying tools and materials to education. It has evolved over time from a focus on audiovisual media and communications to encompass instructional systems, vocational training tools, and now computers and computer-based systems. Different organizations define educational technology according to their focus, such as the Association for Educational Communications and Technology (AECT) which focuses on audiovisual media, and the International Society for Technology in Education (ISTE) which emphasizes computers and computer systems.
E akshara - next generation ubiquitous smart learning platformeSAT Journals
Abstract Recent evolution in web technology has provided millions of resources that identify unparalleled challenges which can support
the collaborative learning of college students. This paper attempts to provide an insight into one of the web-based solutions-“e-
Akshara-Smart learning platform” which can catalyze the learning capability of the students. e-Akshara platform deploys a
smarty framework which simplifies compartmentalization and allows separation of front and back logic. This Smarty framework
is more flexible and secured with free and open source feature. This web-enabled platform provides continuous learning to
students which will connect their pedagogical and professional knowledge. The state-of-the-art platform provides students the
web interface to learn through practical labs and real time projects, surpassing the challenges associated with learner
technological skills, course content development and evaluation techniques. Students can apply for internships and job
placements through this portal. They can also submit their projects in public domain which will be reviewed and funded by the
venture capitalists. This idea will transform the new generation students into industry-ready professionals and future
entrepreneurs which will enrich the start-up culture of the country and generate more employment opportunities.
Keywords: eLearning, e-Akshara, SmartLab, SmartProject, Virtual Classrooms.
Widget and Smart Devices. A Different Approach for Remote and Virtual labsUNED
A vast number of learning content and tools can be found over Internet. Currently, most of them are ad-hoc solutions which are developed for a particular learning platform or environment. New concepts, such as Widgets, Smart devices, Internet of Thing and learning Clouds, are ideas whose goals is the creation of shareable online learning scenarios over different devices and environments.
This document discusses intelligent computing relating to cloud computing. It introduces applying artificial intelligence to cloud computing to develop self-managing computer systems. For example, developing software that regulates computer power consumption to reduce energy use. The document also discusses using affective computing and advanced intelligence to improve cloud computing efficiency by allowing applications to anticipate situations and make real-time decisions over the internet. Finally, it proposes that true cloud computing should be based on natural language understanding to allow access via lightweight devices like phones, not just traditional computers.
Artificial Intelligence Vs Machine Learning Vs Deep Learningvenkatvajradhar1
This technology is no longer a matter of science fiction. Instead, we see artificial intelligence in every part of our lives. Smart assistants are on our phones and speakers, helping us find information and complete everyday tasks. At work, chatbots are affiliated with the Customer Support Team, with estimates that they will be responsible for 85% of customer service by next year.
The presentation offers scenarios designed for the elementary and the secondary schools regarding modeling physical situations, manipulating with applications that go beyond the regular use of graphing calculators, augmenting textbooks for encouraging interactive reading and supporting classroom interactions.
https://www.learntek.org/blog/machine-learning-vs-deep-learning/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
https://www.learntek.org/blog/machine-learning-vs-deep-learning/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
OER in the Mobile Era: Content Repositories’ Features for Mobile Devices and ...eLearning Papers
Learning objects and open contents have been named in the Horizon reports from 2004 and 2010 respectively, predicting to have an impact in the short term due to the current trend of offering open content for free on the Web. OER repositories should adapt their features so their contents can be accessed from mobile devices. This paper summarizes recent trends in the creation, publication, discovery, acquisition, access, use and re-use of learning objects on mobile devices based on a literature review on research done from 2007 to 2012. From the content providers side, we present the results obtained from a survey performed on 23 educational repository owners prompting them to answer about their current and expected support on mobile devices. From the content user side, we identify features provided by the main OER repositories. Finally, we introduce future trends and our next contributions.
AI EXPLAINED Non-Technical Guide for PolicymakersBranka Panic
This guide is meant to help policymakers and citizens understand the basics of Artificial Intelligence (AI) and how it affects our society. It offers explanations and additional resources to help policymakers prepare for the current
and future AI developments.
Artificial Intelligence is advancing throughout the world. According to a study by Creative Strategies, 95% of mobile users are using AI-enabled voice assistance. It is hard to seek out a society that doesn’t use AI techniques. This technique brings numerous uses in a number of ways. It includes decision-making capabilities, diagnosis generation, identifying the connection between causes and consequences, forecasting events, controlling devices like smart sensors, mechanical arms, etc.
https://takeoffprojects.com/ai-based-projects
This document discusses educational technology, defining it as the process of applying tools and media for educational purposes. It outlines the evolution of educational technology from audiovisual communications and instructional systems to computers and computer-based systems. Key aspects covered include defining computer hardware and software, describing components like CPUs and memory, and examining the development of educational technology systems from mainframes to today's networked personal computers and applications. Current uses of educational technology systems focus on instructional software, interactive media, distance learning, productivity tools, and tools to help students with tasks.
GGULIVRR: Touching Mobile and Contextual LearningeLearning Papers
1) Project GGULIVRR explores using mobile technologies like NFC tags and QR codes to link physical objects and locations to digital educational games.
2) The project aims to develop 21st century skills through creating and playing contextual mobile games on topics like a city's underground infrastructure.
3) Games are built in a generic framework that allows non-technical users to author new games by combining multimedia content and scripted gameplay rules.
Presentation by Dr Jason Zagami to the Information Communication Technology Educators New South Wales (ICTENSW) conference on 15 March 2014 in Sydney, NSW.
This document discusses the impact of 3D animation on memory for visual communication learners. It notes that 3D animation can improve both short-term and long-term memory by making concepts more engaging and visually stimulating. The document also describes a study that tested the memory of 30 visual communication students after viewing 3D animated tutorials on 3D modeling software. The study found that 3D animation had a significant positive impact on the students' ability to recall and retain concepts, and that attributes like color, narration and design influence the effectiveness of 3D animated learning materials. In conclusion, the document advocates for using 3D animation in teaching visual communication topics to better engage students and develop their digital skills.
The document summarizes topics covered over 5 days in an education technology course, including universal design principles, technologies for students with learning disabilities and developmental delays, legislation related to assistive technology, and software and technologies to support written language development. Key areas discussed include the 7 principles of universal design, categories of learning disabilities and how technology can help students with LDs, and interventions for written language disorders including software programs and assistive technologies.
M-portfolios: Using Mobile Technology to Document Learning in Student Teacher...eLearning Papers
We briefly analyse the enhancement of eportfolio processes defined by Zubizarreta (2009) with the introduction of mobile technology. We give some examples of appropriation of mobile device usage in eportfolio processes carried out by student teachers. These examples become the evidence of the enhancement possibilities of one of the portfolio processes defined by Zubizarreta (2009), that of documentation.
Standing at the Crossroads: Mobile Learning and Cloud Computing at Estonian S...eLearning Papers
This paper studies the impact of mobile learning implementation efforts in Estonian school system – a process that has created a lot of controversy during the recent years. Best practices in mobile learning are available from the entire world, forcing schools to keep up the push towards better connectivity and gadgetry. Even in the best cases where the schools are provided with the necessary tools, the process has met a lot of scepticism from teachers who are afraid to implement new methods. Teachers are often cornered with the ‘comply or leave’ attitude from educational authorities, resulting in a multi-sided battle between involved parties.
We have surveyed students, teachers, parents and management at five Estonian front-runner schools to sort out the situation. The results show different attitudes among students, school leaders and staff – while all of them mostly possess necessary tools and skills, teachers almost completely lack motivation to promote mobile learning. We propose some positive and negative scenarios – for example, we predict major problems if teacher training will not change, e-safety policies are inadequately developed or authorities will continue the tendency to put all the eggs into one basket (e.g. by relying solely on closed, corporate solutions for mobile learning platforms).
Architecture for Integrating Real Objects with VirtualAcademic Communitiesgalex68
The Internet of Things (IoT) is a new concept that allows objects to be connected to Internet. This connectivity
allows the emergence of new forms of interaction between objects and people. In educational environments the IoT could be applied to improve teaching and learning experiences. This paper proposes a new architecture for integrating objects available in educational environments with virtual academic communities (VAC). This new architecture is based on the paradigm of layered architectures and architectural styles such as REST. The proposed architecture consists of four layers: hardware/communications, messaging, services, and application. Test of the proposed architecture were made through the implementation of a case study, which was focused on practical classes of a typical digital electronics course.
The Impacts Of Information And Communication Technology (ICT) On The Teaching...IOSR Journals
This document discusses the impacts of information and communication technology (ICT) on teaching and learning science and mathematics. It defines ICT and explains how ICT has transformed education by creating a more interactive learning environment. ICT allows for more effective demonstration of concepts and feedback on student progress. The use of ICT in classrooms enhances teaching and makes lessons more exciting for students. ICT also helps students become independent learners by developing critical thinking and problem-solving skills. For science and mathematics specifically, ICT is increasingly used in laboratories for data acquisition, handling, and analysis.
This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
Mobile augmented reality using 3D ruler in a robotic educational module to pr...journalBEEI
Robotics education is gaining popularity among school children in line with the government desire to promote creative thinking in students through STEM based activities. However, the robots for educational games are usually made up of components and its description is usually one-way and static. Additionally, students find it difficult to visualize distances from robot movements when playing educational robotic games. Augmented reality (AR) technology is a viable tool to connect between in-context information and physical activities. The objective of this research is to design and develop an AR based application that can visualize the distance between two robots for supporting learning process in a game-based module. The application consists of three parts; the first part use AR in identification of components related to robots, while the second part involves the addition of real-time visualization in the form of AR, enabling students to learn the distance from the robot's movements. The third part used AR in providing the description of the robotic games through videos. The development of the application is based on the Agile model. The results show that the application has received positive feedbacks from students as it can increase their interest in playing robotic educational games.
Educational technology can be defined in various ways but generally refers to the process of applying tools and materials to education. It has evolved over time from a focus on audiovisual media and communications to encompass instructional systems, vocational training tools, and now computers and computer-based systems. Different organizations define educational technology according to their focus, such as the Association for Educational Communications and Technology (AECT) which focuses on audiovisual media, and the International Society for Technology in Education (ISTE) which emphasizes computers and computer systems.
E akshara - next generation ubiquitous smart learning platformeSAT Journals
Abstract Recent evolution in web technology has provided millions of resources that identify unparalleled challenges which can support
the collaborative learning of college students. This paper attempts to provide an insight into one of the web-based solutions-“e-
Akshara-Smart learning platform” which can catalyze the learning capability of the students. e-Akshara platform deploys a
smarty framework which simplifies compartmentalization and allows separation of front and back logic. This Smarty framework
is more flexible and secured with free and open source feature. This web-enabled platform provides continuous learning to
students which will connect their pedagogical and professional knowledge. The state-of-the-art platform provides students the
web interface to learn through practical labs and real time projects, surpassing the challenges associated with learner
technological skills, course content development and evaluation techniques. Students can apply for internships and job
placements through this portal. They can also submit their projects in public domain which will be reviewed and funded by the
venture capitalists. This idea will transform the new generation students into industry-ready professionals and future
entrepreneurs which will enrich the start-up culture of the country and generate more employment opportunities.
Keywords: eLearning, e-Akshara, SmartLab, SmartProject, Virtual Classrooms.
Widget and Smart Devices. A Different Approach for Remote and Virtual labsUNED
A vast number of learning content and tools can be found over Internet. Currently, most of them are ad-hoc solutions which are developed for a particular learning platform or environment. New concepts, such as Widgets, Smart devices, Internet of Thing and learning Clouds, are ideas whose goals is the creation of shareable online learning scenarios over different devices and environments.
This document discusses intelligent computing relating to cloud computing. It introduces applying artificial intelligence to cloud computing to develop self-managing computer systems. For example, developing software that regulates computer power consumption to reduce energy use. The document also discusses using affective computing and advanced intelligence to improve cloud computing efficiency by allowing applications to anticipate situations and make real-time decisions over the internet. Finally, it proposes that true cloud computing should be based on natural language understanding to allow access via lightweight devices like phones, not just traditional computers.
Artificial Intelligence Vs Machine Learning Vs Deep Learningvenkatvajradhar1
This technology is no longer a matter of science fiction. Instead, we see artificial intelligence in every part of our lives. Smart assistants are on our phones and speakers, helping us find information and complete everyday tasks. At work, chatbots are affiliated with the Customer Support Team, with estimates that they will be responsible for 85% of customer service by next year.
The presentation offers scenarios designed for the elementary and the secondary schools regarding modeling physical situations, manipulating with applications that go beyond the regular use of graphing calculators, augmenting textbooks for encouraging interactive reading and supporting classroom interactions.
https://www.learntek.org/blog/machine-learning-vs-deep-learning/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
https://www.learntek.org/blog/machine-learning-vs-deep-learning/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
OER in the Mobile Era: Content Repositories’ Features for Mobile Devices and ...eLearning Papers
Learning objects and open contents have been named in the Horizon reports from 2004 and 2010 respectively, predicting to have an impact in the short term due to the current trend of offering open content for free on the Web. OER repositories should adapt their features so their contents can be accessed from mobile devices. This paper summarizes recent trends in the creation, publication, discovery, acquisition, access, use and re-use of learning objects on mobile devices based on a literature review on research done from 2007 to 2012. From the content providers side, we present the results obtained from a survey performed on 23 educational repository owners prompting them to answer about their current and expected support on mobile devices. From the content user side, we identify features provided by the main OER repositories. Finally, we introduce future trends and our next contributions.
AI EXPLAINED Non-Technical Guide for PolicymakersBranka Panic
This guide is meant to help policymakers and citizens understand the basics of Artificial Intelligence (AI) and how it affects our society. It offers explanations and additional resources to help policymakers prepare for the current
and future AI developments.
Artificial Intelligence is advancing throughout the world. According to a study by Creative Strategies, 95% of mobile users are using AI-enabled voice assistance. It is hard to seek out a society that doesn’t use AI techniques. This technique brings numerous uses in a number of ways. It includes decision-making capabilities, diagnosis generation, identifying the connection between causes and consequences, forecasting events, controlling devices like smart sensors, mechanical arms, etc.
https://takeoffprojects.com/ai-based-projects
This document discusses educational technology, defining it as the process of applying tools and media for educational purposes. It outlines the evolution of educational technology from audiovisual communications and instructional systems to computers and computer-based systems. Key aspects covered include defining computer hardware and software, describing components like CPUs and memory, and examining the development of educational technology systems from mainframes to today's networked personal computers and applications. Current uses of educational technology systems focus on instructional software, interactive media, distance learning, productivity tools, and tools to help students with tasks.
GGULIVRR: Touching Mobile and Contextual LearningeLearning Papers
1) Project GGULIVRR explores using mobile technologies like NFC tags and QR codes to link physical objects and locations to digital educational games.
2) The project aims to develop 21st century skills through creating and playing contextual mobile games on topics like a city's underground infrastructure.
3) Games are built in a generic framework that allows non-technical users to author new games by combining multimedia content and scripted gameplay rules.
Presentation by Dr Jason Zagami to the Information Communication Technology Educators New South Wales (ICTENSW) conference on 15 March 2014 in Sydney, NSW.
This document discusses the impact of 3D animation on memory for visual communication learners. It notes that 3D animation can improve both short-term and long-term memory by making concepts more engaging and visually stimulating. The document also describes a study that tested the memory of 30 visual communication students after viewing 3D animated tutorials on 3D modeling software. The study found that 3D animation had a significant positive impact on the students' ability to recall and retain concepts, and that attributes like color, narration and design influence the effectiveness of 3D animated learning materials. In conclusion, the document advocates for using 3D animation in teaching visual communication topics to better engage students and develop their digital skills.
The document summarizes topics covered over 5 days in an education technology course, including universal design principles, technologies for students with learning disabilities and developmental delays, legislation related to assistive technology, and software and technologies to support written language development. Key areas discussed include the 7 principles of universal design, categories of learning disabilities and how technology can help students with LDs, and interventions for written language disorders including software programs and assistive technologies.
M-portfolios: Using Mobile Technology to Document Learning in Student Teacher...eLearning Papers
We briefly analyse the enhancement of eportfolio processes defined by Zubizarreta (2009) with the introduction of mobile technology. We give some examples of appropriation of mobile device usage in eportfolio processes carried out by student teachers. These examples become the evidence of the enhancement possibilities of one of the portfolio processes defined by Zubizarreta (2009), that of documentation.
Standing at the Crossroads: Mobile Learning and Cloud Computing at Estonian S...eLearning Papers
This paper studies the impact of mobile learning implementation efforts in Estonian school system – a process that has created a lot of controversy during the recent years. Best practices in mobile learning are available from the entire world, forcing schools to keep up the push towards better connectivity and gadgetry. Even in the best cases where the schools are provided with the necessary tools, the process has met a lot of scepticism from teachers who are afraid to implement new methods. Teachers are often cornered with the ‘comply or leave’ attitude from educational authorities, resulting in a multi-sided battle between involved parties.
We have surveyed students, teachers, parents and management at five Estonian front-runner schools to sort out the situation. The results show different attitudes among students, school leaders and staff – while all of them mostly possess necessary tools and skills, teachers almost completely lack motivation to promote mobile learning. We propose some positive and negative scenarios – for example, we predict major problems if teacher training will not change, e-safety policies are inadequately developed or authorities will continue the tendency to put all the eggs into one basket (e.g. by relying solely on closed, corporate solutions for mobile learning platforms).
Architecture for Integrating Real Objects with VirtualAcademic Communitiesgalex68
The Internet of Things (IoT) is a new concept that allows objects to be connected to Internet. This connectivity
allows the emergence of new forms of interaction between objects and people. In educational environments the IoT could be applied to improve teaching and learning experiences. This paper proposes a new architecture for integrating objects available in educational environments with virtual academic communities (VAC). This new architecture is based on the paradigm of layered architectures and architectural styles such as REST. The proposed architecture consists of four layers: hardware/communications, messaging, services, and application. Test of the proposed architecture were made through the implementation of a case study, which was focused on practical classes of a typical digital electronics course.
The Impacts Of Information And Communication Technology (ICT) On The Teaching...IOSR Journals
This document discusses the impacts of information and communication technology (ICT) on teaching and learning science and mathematics. It defines ICT and explains how ICT has transformed education by creating a more interactive learning environment. ICT allows for more effective demonstration of concepts and feedback on student progress. The use of ICT in classrooms enhances teaching and makes lessons more exciting for students. ICT also helps students become independent learners by developing critical thinking and problem-solving skills. For science and mathematics specifically, ICT is increasingly used in laboratories for data acquisition, handling, and analysis.
https://jst.org.in/index.html
Our journal has Numbers tell stories, and in the world of research and development, mathematics is the universal language. Join us as we explore the elegant equations and mathematical models that underpin technological advancements and scientific breakthroughs.
Artificial intelligence in education and assessment methodsjournalBEEI
Today, artificial intelligence has proliferated to reach almost every wing of daily life, perhaps one of the most sensitive of these being education. While teaching, insofar as it involves training human minds, is still mostly a form of art rather than a regular science, the taking up of this elitist job by computers has triggered much debate and controversy, involving the teaching community as much as the select corporate AI giants who strive to create computers capable of teaching better than humans. This paper surveys the most relevant studies carried out in this field to date. First, it introduces AI and describes the different AI applications in field of education and course assessment. It then goes on to list the most common topics in the educational context that have been resolved through AI and machine learning techniques, and finally, some of the most promising future lines of research are discussed.
The document discusses the emergence and importance of artificial intelligence (AI) in education. It describes how AI can help both students and teachers gain knowledge about new techniques and provide better learning experiences. AI tools can be used to grade assignments, translate between languages to overcome barriers, and act as mentors. However, challenges remain around creating personalized mentors for all learners and developing cost-effective learning methods. The conclusion is that AI has great potential to improve education if implemented appropriately by skilled teachers.
The document discusses three emerging technologies - electronic books, gesture-based computing, and smart objects - and their potential future applications and benefits in education. It outlines some key learning advantages, such as interactivity, portability, collaboration, and accommodating different learning styles. However, it also notes challenges like eye fatigue, difficulty interpreting gestures, privacy issues, and high costs. The document concludes that while traditional teaching still has value, technology can enhance education by improving student learning if these issues are addressed.
The document summarizes a presentation given by Musstanser Tinauli on their research activities and experiments. It discusses their goals of understanding how interactive environments can be measured and how tools influence user behavior. It describes ongoing case studies of games, e-learning platforms and digital pens. It outlines their methodological approach and provides results from studies on a digital pen and paper system, including lessons learned. Recent publications and collaborations are also mentioned.
The document provides an introduction to teaching and learning with technology. It defines key terms related to information and communication technology (ICT) such as technology, digital literacy, educational technology, online and offline digital tools. It also discusses concepts like instructional technology, productivity tools, and web-based tools like blogs, wikis and webquests. The document aims to give readers a clear understanding of basic ICT concepts and terms to effectively communicate about technology in education.
1) The document discusses the impact of artificial intelligence (AI) on education, focusing on its application in administration, instruction, and learning.
2) AI has been extensively adopted by education institutions in different forms, initially through computers and later through online intelligent systems and humanoid robots.
3) AI is defined as the ability of machines to perform intelligent tasks like learning, problem-solving, and pattern recognition, and has the potential to significantly impact the education sector through improvements in administration, teaching, and student learning.
This storyboard discusses computer simulation and its use in education. It begins by defining computer simulation as a computer model that attempts to simulate a system. It then discusses the need for computer simulation in education by noting how it can provide hands-on experiments, reduce classroom barriers, support alternative learning, and increase content knowledge. The storyboard goes on to discuss the history and development of computer simulation, including early experiments in the 1960s and the emergence of virtual reality environments. It also outlines the innovation-decision process and discusses using computer simulation to enhance student performance in areas like science, business, and literacy. The storyboard concludes by discussing implementing computer simulation in K-12 classrooms and promoting its adoption among instructors.
This storyboard discusses computer simulation and its use in education. It begins by defining computer simulation as a computer model that attempts to simulate a system. It then discusses the need for computer simulation in education by noting how it can provide hands-on experiments, reduce classroom barriers, support alternative learning, and increase content knowledge. The storyboard goes on to discuss the history and development of computer simulation, including early experiments in the 1960s and the emergence of virtual reality environments. It also outlines the innovation-decision process and discusses using computer simulation to enhance student performance in areas like science, business, and literacy. The storyboard concludes by discussing implementing computer simulation in K-12 classrooms and promoting its adoption among instructors.
This document provides an overview of the field of Child-Computer Interaction (CCI). It discusses influential early pioneers like Seymour Papert and describes how CCI draws from fields like Human-Computer Interaction. Current research focuses include interaction techniques, evaluation methods, design practices, and applications to support learning. The document outlines key concerns in CCI around delivering empirical evidence, accounting for context, improving research methods, and clarifying values. It predicts technologies like tangibles and robots will continue entering the marketplace and that children's technologies and lives will be very different in the future.
A vast majority of students in computing and related disciplines expect to interact with their systems and computing devices using a graphical user interface. Any other means of interacting with a device is deemed unseemly and is quickly met with frustration and rejection. This can partly be attributed to the fact that most operating systems and the tools that run on these platforms offer a rich “point-and-click” interface in an effort to make their systems user friendly. However, in contrast, when it comes to the study of system and cyber security, a mastery over the console and the command-line interface is imperative. In our experience in teaching most courses on system and cyber security, students seem to have the greatest difficulty in using the console/command-prompt/shell. This issue is further exacerbated since many security and related open source forensics tools are designed to run in a Unix-based environment, typically a shell, and even fewer students are familiar with the UNIX environment and find the entire experience all the more daunting. Even the simple command-prompt, ubiquitous on all Microsoft Windows operating systems, is met with significant disdain by today's students, both at the graduate and undergraduate levels. There are several solutions that have been proposed and designed to alleviate this exact issue in the field of computer programming. Video tool, Dragon Drop Pictorial Programming, Alice and Jpie are various stand-alone tools introduced to ease the inherent challenges in learning a new programming language and environment. To alleviate this situation, in this paper, we propose the first tool of its kind, to the best of our knowledge, which aims to tutor a console application using a graphical interface and adapts to the students' progress. The ultimate aim is to eliminate students' dependence on graphical interfaces and convert her to a power user of a system. Our tool, called Interactive Bash Shell Adaptive Tutoring System (iBaTs), enables students to familiarize themselves with the UNIX environment and the Bash Shell on a Windows operating system. In this work, we discuss the architecture of our tutoring program and demonstrate that our system sports several innovative pedagogical features that makes it a unique, fun, encouraging and adaptive learning environment. To the best of our knowledge, this is the first such effort that aims to address this issue.
A PLATFORM FOR LEARNING INTERNET OF THINGS de Zorica Bogdanović, Konstantin Simić, Miloš Milutinović, Božidar Radenković and Marijana Despotović-Zrakić del Department for e-Business, Faculty of Organizational Sciences, University of Belgrade Jove Ilića 154, Belgrade, Serbia ... presentado en la International Conference e-Learning 2014
This document discusses intelligent personal assistants (IPAs) and their use of artificial intelligence. It provides examples of popular IPAs like Siri, Google Now, and Cortana. It explains that IPAs use natural language processing to understand user questions and respond appropriately. The document also discusses how IPAs could potentially be used to assist language learning by allowing practice and feedback without time or location constraints.
A STUDY ON ROBOTICS EDUCATION (MECHATRONICS) FOR SCHOOL STUDENTSCynthia Velynne
This document discusses a study on robotics education for school students. It begins by defining robotics as a multidisciplinary field involving mechanical, electrical, and computer engineering, called mechatronics. The study observes 40 primary school and 60 high school students who received one month of robotics training, finding they were able to master foundational programming concepts. Robotics education increases students' creativity, problem-solving, and engagement with STEM concepts. It also teaches perseverance in overcoming challenges. The document concludes that robotics education empowers students to understand basic engineering concepts while having fun.
This document discusses the use of robots in education. It begins by defining robots and robotics, and describes how robots are being used increasingly in fields like manufacturing, healthcare, military, and more. Educational robots help teach STEM concepts to students of all ages, playing roles like teaching assistants, tutors, and peer learners. The document outlines several applications of educational robots, from elementary to higher education and for students with special needs. Benefits include improving STEM learning, coding skills, and teamwork. Challenges include cost and engaging all genders. The conclusion is that robotics education should be compulsory to prepare students for robot-integrated careers and lives.
Adaptarse a las nuevas formas de crear y compartir contenidos digitales constituye un reto para la preparación de profesionales en los perfiles emergentes de disciplinas ajenas a la informática y la computación. Los lenguajes y las herramientas de creación digital no están muchas veces pensados para su utilización por parte de usuarios de estos campos. Un reto en el campo de la computación creativa es la posibilidad de incorporar capacidades interactivas multimodales, junto con realidad virtual y realidad aumentada, en las herramientas de autoría con las que se elaboran los materiales y diseños de aprendizaje. El objetivo general de la charla es motivar la investigación sobre la computación creativa, así como mostrar desarrollos diversos alrededor de un marco de trabajo que aspira a fomentar las habilidades de diseño, creación y despliegue de experiencias educativas con capacidades analíticas para el aprendizaje y la evaluación en un contexto multidisciplinar.
This document discusses the use of educational robotics as assistive tools for learning mathematics and science. It provides an overview of the advantages of using robots in education, such as developing cognitive and social skills. However, challenges also exist, such as teachers not being prepared to implement new technologies. The document also examines different robotics platforms and programming software used in education. Overall, educational robotics have been shown to improve student learning and motivation, especially for subjects like math, but support materials and training for teachers is needed for successful integration.
Robots Talk British Computer Society Northampton_17_4_2018Scott Turner
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Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
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Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Pengantar Penggunaan Flutter - Dart programming language1.pptx
Bicsme2015
1. 1
Preliminary Study on EducationalRobot Kit in Promoting Interest Toward
Science, Mathematics, Technology and Engineering (STEM)
Anna Felicia, Sabariah Sharif, Muralindran Mariappan, WK Wong
Faculty of Education and Social Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah,
Malaysia
Abstract: Robotics is an excellent platform in promotion of STEM (Science, Technology,
Engineering and Mathematics) due to its multidisciplinary combination of the various fields.
This paper presents preliminary results in promotion of robotic activity as an outreach
platform to promote STEM using a prototype Robotic Kit system that is cost effective and
involves only basic elements. Results showed that 90% of the participants would like to
participate more in after school such robotic classes indicating an increased interest in such
Robotic classes. This preliminary research showed that such robotic activity can be further
developed in the specified location as a platform to promote STEM.
Keywords: Educational Robotics, Robotic Curriculum, Open Source Graphical Visual
Programming
1. Introduction
Robotics is often adopted as a platform to introduce STEM (Science, Technology,
Engineering and Mathematics). Robotics platform enables the multidisciplinary combination
of all STEM elements can be viewed as a high immersive platform for learning and develop
interest in STEM. Hence, this study serves as a preliminary study to investigate the effect of
robotic activity in learning and the interest level towards such activities. The robotic platform
used in this research is an experimental platform developed using Arduino microcontroller
and S4A (Variant of the popular Scratch software) software as GUI (Graphic user interface).
Scratch like programs are highly popular among schools due to its graphical programming
styles and open source development.
2. Literature review
The 21st century dawned as the beginning of the Digital Age – a time of unprecedented
growth in technology and its subsequent information explosion. The term “computational
thinking” (CT) has been at the center of recent efforts to describe and promote new ways of
thinking in an increasingly digital age. Computational Thinking provides foundational
knowledge in problem solving and design. Computational thinking is being considered as a
critical skill for students in the 21st century. Computational thinking (CT) was first described
by Papert (1993), and then pioneered by Jeannette Wing. Seymour Papert is seen by many as
the pioneer of computing in schools. Jeannette Wing’s (2006) influential article on
2. 2
computational thinking argued for adding this new competency to every child’s analytical
ability as a vital ingredient of science, technology, engineering, and mathematics (STEM)
learning. Educational robotics and its programming known as a transformational tool for
computational thinking, coding or programming, and engineering, all increasingly being
viewed as critical ingredients of STEM (science, technology, engineering and math) learning
in education (Eguchi, A. 2014). Computational tools have been shown to enable deeper
learning of STEM content areas for students (National Research Council, 2011; Sengupta,
Kinnebrew, Basu, Biswas, & Clark, 2013).
Papert’s (1980) constructionism is rooted in Piaget’s (1954) constructivism – which
conveys the idea that the child actively builds knowledge through experience – and the related
“learn-by-doing” approach to education. While Piaget’s (1954) theory was developed to
explain how knowledge is constructed in an individual’s mind, Papert (1980) expands on it to
focus on the ways that internal constructions are supported by constructions in the world,
including through the use of computers and robotics. A constructionist teaching approach
provides children the freedom to explore their own interests through technologies (Bers,
2008) while investigating domain-specific content learning and also exercising meta-
cognitive, problem-solving, and reasoning skills.
Computational thinking is being considered as a critical skill for students in the 21st
century (2011). Computational thinking facilitates new ways of seeing existing problems,
emphasizes creating knowledge rather than using information, presents possibilities for
creatively solving problems ,and facilitates innovation (Dede, et al. 2013). It involves many
skills, but programming abilities seem to be a core aspect since they foster the development of
a new way of thinking that is the key to the solution of problems that require a combination of
human power and computing power capacity (Ambrosio, et al, 2014). Figure 2.1 shows the
Computational thinking explained by Cury, J. et al. (2010). Embedding CT in STEM
coursework can address the issues of practicality of implementation, especially with teachers’
comfort with the material. (National Research Council, 2011; Sengupta, Kinnebrew, Basu,
Biswas, & Clark, 2013).
On the other hand, Scrath is a popular open source for coding. Scratch is a computer
programming language for children, with a graphical drag-and-drop user interface (Harvey, B.
& Monig, J. 2010). Scratch is a free application, developed by MIT Media Lab, which allows
users to create and share their own interactive stories, animations and games. It is easier to use
rather than traditional programming languages as it consists of graphical blocks which snap
together. Figure 2.2 is the interface of Scratch (Lero, 2012). Table 2.2 is the implementation
of Scratch by Wilson, A., Hainey, T. & Connolly, T.M. (2013).
3. 3
S4A (Scratch for Arduino) is a drag and drop programming environment based on the
MIT creation “Scratch”. It has been modified to connect to an Arduino plugged in via USB,
offering a variety of additional code blocks to implement and create scripts to control the
Arduino and attached components. Arduino is a micro-controller, which is a small computer
that can be use to send and receive messages to and from other electrical components. It used
is similar to a motherboard, inside the computer - and can be connected to various
components to it and build up electrical circuits. Figure 2.3 below is the interface of S4A.
Figure 2.4 is the Arduino Uno micro-controller board.
Teaching robotics to young people frequently implies a constructivist approach which
emphasizes “learning by doing” as the main teaching strategy (Bilotta, D., Gabriele, D.,
Servidio, R. & Tavernise, A., 2009). It involves electric motors, sensors, pieces such as gears,
axles, and beams and tool for programming and control of them. So, by using this learning
method, the student is able to learn how to construct, program and control a robot (Thomaz,
S., Aglae, A., Fernandes, C., Pitta, R., Azevedo, S., Burlamaqui, A., Silva, A. & Goncalves,
L.M.G., 2009). The robotics tools made it possible for the students to practice and learn many
necessary skills, like collaboration, cognitive skills, self-confidence, perception and spatial
understanding, active reasoning and critical thinking, and also enhancing students’ interest
and motivation to address often complex subjects (Eija, K-L., Kaisa, P-B., Erkki, S. & Marjo,
V., 2006). The skills may be related to multiplication and division operations for example in
mathematics subjects.
According to Alimisis (2013), robots are becoming an integral component of our society
and have great potential in being utilized as an educational technology. Robotics has attracted
the interest of teachers and researches as a valuable tool to develop cognitive and social skills
for students from pre-school to high school and to support learning in science, mathematics,
technology, informatics and other school subjects or interdisciplinary learning activities. A
four wheel drive robotic platform was developed Alimisis, D. (2012) and E-puck educational
robot was constructed in Mondada, F. et al. (2009).
4. 4
2. Hardware Development
The robot was constructed on a minimalist concept to reduce production cost and experiments
to evaluate the interest levels towards the robotic programming curricular. The robot kit is non
– assemble type and on the shelf which means that no assembling is required. Table 1 shows
the specification of the robotic Kit.
Table 1 : Specification of Robotic system
Size 20 cm (width) x 20 cm (length) x 10 cm (height)
Weight 2.6 Kg
On Board
Processor
Arduino Uno Microcontroller
Sensor 3 line sensor (Infra Red)
3 Obstacle sensor (Digital type, distance adjustable type)
Approximate
cost
USD 120
Communication
link
Bluetooth
Programming
Language
S4A (Scratch for Arduino)
The robot Kit consist of an Arduino microcontroller that communicates with the laptop via a
USB link using HC 06 bluetooth module. The microcontroller communicates with other
motor (actuator) and sensor via the analogue ports. Figure 2 shows the block diagram shows
communication module. The robot kit is shown in Figure 3 (a) and the scratch GUI is shown
in Figure 3 (b). As shown in figure 3 b), the programming is entirely graphical.
5. 5
Figure 2 :Block diagram of communication and Interfacing
Arduino microcontroller
Laptop
processor
Bluetooth link
Motor controller Obstacle sensor IR line sensor
6. 6
(a) (b)
Figure 3 : a) Shows the hardware of the the Arduino BasedRobot Kit. b) Printscreen of
the S4A program executing a Program
The S4A program does not have function program unlike their text based counterpart.
Hence, the ‘broadcasting’ concept was used to replace the function concept. Five states of
robot movement were introduced that is ‘Move Straight’, ‘Turn Left’, ‘Turn Right’, ‘Veer
Left’ and ‘Veer Right’. The five states are based on the differential speed of the left and right
motor. The speed which ranges (0-255) in which the motor moves. It was tested that any
number specified below 50 was unable to make the motor move. The motor is driven by the 2
A motor driver shield for Arduino. The value for the specified movements were fixed in
which the participants only need to ‘Broadcast’ the states such as ‘Move straight’ Or ‘Veer
Right’ to execute the movements. The values for the movements is shown in Table 3.2.
‘Veer’ refers to the slight steering to the left or right as compared to ‘turn’. ‘Veer’-ing is
normally for performing line tracking which requires a slight turning to move back into the
track. However, in research activity, the veer function is not used and only turning required.
The time of ‘turning’ and ‘straight’ is depending on the delay time applied after specifying the
value on the left and right motor. The pin connected to both the motor is analogue pin 5 and
pin 6. The value given to veer and turn are shown in table 2 in which the participants are
allowed to changed but it was found that eventually all participants used the value as
proposed.
7. 7
Table 2: The States and Speed of Motor
States
Left motor
speed
Right Motor
Speed
Move straight 120 120
Veer Right 80 50
Veer Left 50 80
Turn Right 120 80
Turn Left 80 120
3. Study Design
The study conducted is to study the effects of the low cost robotic kit developed in promoting
the interest towards STEM. Table 3 shows the details and duration of the activities proposed.
The introduction include a small demonstration of line following robot and some videos to
show the full potential and to enable the participants to have an overview and future activities.
The subsequent overall activity for every group is approximately 3 hours but students.
Table 3 : Details and duration of activity
Phase Details Description Duration
1 Introduction to
robot Kit
Demonstration of robot. Include line following
with the robot kit and video explanation
30 minutes
2 Learning
activity
Robotic learning activity given template
coding.
Approximately
3 hours
3 Discussion Discussion on what the students wish to do
with the technology. The participants were also
shown the application of sensors in coding to
encourage them to involve in future activities
5 minutes
The participants aged between 10-11 years old, 61% female students and the rest are male
students. Thirty participants take parts that are divided into 6 small groups. Phase 1 took 30
minutes while phase 2 took 3 hours to complete. Due to the preliminary exposure, the students
are given a set of codes to study and modify before start coding. Four scenarios/case study
are prepared for the students to program the robot.
8. 8
(Activity a) Move straight
(Activity b) Move straight and turn left
(Activity c) Move straight and turn right until reaching a destination
(Activity d) Move straight and U-turn to point of origin
In activity a, the robot will be program by the participants to move straight indicated by
colored cones. Activity b and c are similar in which robot must be program to navigate in a ‘L’
path in which the starting and ending was indicated by the cones. The final activity requires
the participant to navigate the robot straight and perform a U-turn. In all the activities, a
sample code is given to the participants to modify as this was their first exposure to such
activity.
In order to assess learning outcomes after each activity, teachers evaluated the program
made by each groups. In each lesson, students were scored on multiple concepts using the
Likert scale below as attached in appendix. Figure 4 shows the learning environment showing
students participation and involvement. Only 3 students were allowed to participate in a single
group but participant were often seen sharing ideas intergroup. Figure 4 shows the activity d
in which participant are required to perform a U- turn as indicated by the colored cone.
Figure 4: Learning Environment During robotic learning activity
It was observed that most discussions are about the delay time setting. It was observed that at
one instances, a participant noted that the delay time to and from back to the cones are the
same whereas some continue trying indicating varying higher order thing capacity of
participants. This preliminary activity shows that interaction can happen in order to solve a
problem by trial and testing which is the core principle of constructivism leaning
9. 9
4. Result
Pre-interviews analysis revealed that robotics programme introduced as the first robotics
programme they have ever attended. Most of them never participated in such activities before,
and they participated in the programme because of curiosity. Post-interview analysis revealed
that they are very excited to participate in the edu-robot programme. They stated that they
have learned much about technology during the programme and also indicated what they can
do with the technology that they learn. Some participants stated that they wish to use the
technology to create a robot that washes dishes while more observant students realized that
the activities would directly enable them to create a robotic vacuum cleaner. This shows that
participant realized that they can actually innovate based on the technology that they learn.
They enjoyed the most in programming the edu-robot to move around and can compete
with other groups. All of them would like to further continue their participation in robotics
programme. The 5-likert scale post-questionnaires analysis shown that 90% (total-up of agree
and strongly agree frequencies) of the participants would like to participate more in after
school STEM projects and classes. And 90% (total-up of agree and strongly agree
frequencies) of them also have changed their mind about how interesting learning STEM is.
Another 10% which responded on the neutral scale (answered don’t know) were mostly found
not able to catch up in the coding activity. This could be due to the rural demography in
which low exposure to computers causing them to be left out and to familiarize to the learning
environment. Hence, for in the future, instructors need to note these student and possibly
reduce number of participants to 2 person per group. The descriptive statistics is shown in
Appendix B and the Post Activities Interview is shown in Appendix A. The variable 1-4
shows the question number as shown in Appendix A.
It was also observed that the activities proposed was suitable for preliminary
exposure to rural children with minimal exposure to computers. The coding only required
sequential Coding and no decision loops such as ‘if-else’ and ‘while’ decision loops were
required. This research shows that as a preliminary introduction to robotics to cultivate STEM
interest, such navigation based robot activity could be a good starting point to progress into to
learn about robots and STEM in general even though it was noted the participant are from
rural demography.
5. Future Works
This involves only the preliminary study in introducing the children (10-11 years old) in a
rural demography with low exposure to robots. The robot kit development involves only the
basic set for cost reduction and making the activities more available. Further work in
development will include refinement of both activities and the robotic kit itself. The robotic
Kit will only focus only ‘Higher order thinking’ problems to promote computational thinking
that is solving a particular problem through computational means.
10. 10
For future development, the research will focus on using A-D-D-I-E instructional
for designing Instructional activity in promotion of STEM interest and computational thinking
skills.
References
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skills of computational thinking, University of Sussex.
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12. 12
APPENDIX A
Post-robotic survey
SKALA
1 2 3 4 5
Strongly
disagree
Disagree Do not know Agree Strongly agree
Questions Scale
1 2 3 4 5
1 This project made
me want to do more
after school STEM
projects if they are
available.
2 This project
changed my mind
about how
interesting learning
STEM is.
3 This project made
me want to take
more classes in
STEM if they are
available.
4 This project made
me consider career
in STEM path.
13. 13
Post student interview questions
1. What are some things you learned
about being in robotics?
2. What did you enjoy the most about
being in robotics?
3. What would you tell someone about
being in robotics that has never been in
it?
4. Is there anything else you want to
share about being in robotics?
Pre student interview questions
1. What do you think you will learn
from your participation in robotics?
2. What do you know about robot?
3. Why did you choose to participate in
robotics?
4. Is there anything else you would like
to tell me?
14. 14
APPENDIX B
DESCRIPTIVE STATISTIC FOR POST ACTIVITY ANALYSIS
Gender
Frequency Percent
Valid
Percent
Cumulative
Percent
Male 13 43.3 43.3 43.3
Female 17 56.7 56.7 100.0
Total 30 100.0 100.0
VARIABLE 1
Frequency Percent
Valid
Percent
Cumulative
Percent
Do not know 3 10.0 10.0 10.0
Agree 16 53.3 53.3 63.3
Strongly
agree
11 36.7 36.7 100.0
Total 30 100.0 100.0
VARIABLE 2
Frequency Percent
Valid
Percent
Cumulative
Percent
Do not know 3 10.0 10.0 10.0
Agree 15 50.0 50.0 60.0
Strongly
agree
12 40.0 40.0 100.0
Total 30 100.0 100.0
15. 15
VARIABLE 3
Frequency Percent
Valid
Percent
Cumulative
Percent
Do not know 3 10.0 10.0 10.0
Agree 14 46.7 46.7 56.7
Strongly
agree
13 43.3 43.3 100.0
Total 30 100.0 100.0
VARIABLE 4
Frequency Percent
Valid
Percent
Cumulativ
e Percent
Do not
know
3 10.0 10.0 10.0
Agree 14 46.7 46.7 56.7
Strongly
agree
13 43.3 43.3 100.0
Total 30 100.0 100.0