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The purpose of this study was to investigate the effect of self-regulated programming learning on undergraduate students’ academic performance and motivation compared to traditional methods.

This study was conducted with an explanatory sequential mixed method. Participants consist of 31 undergraduate students studying in the department of computer and instructional technologies education. The students were separated into two groups as experimental (n = 15) and control (n = 16) in the robotic programming course. Academic performance tests, programming motivation scale and interview form were used as data collection tools. After collecting quantitative data, interviews were conducted with the students regarding their academic performance and motivation.

The results indicated that the self-regulated programming learning process can contribute positively to students’ academic performance and motivation compared to traditional methods. Students stated that self-regulated learning strategies can positively affect their academic performance and motivation.

In this study, a self-regulated learning support system was designed to encourage students to use self-regulated learning strategies. This study has the potential to contribute to the gap in the literature, especially as a study of adapting the phased model of self-regulated learning to programming teaching. Instructors can use the self-regulating programming learning framework by adapting it to different disciplines.

This paper aims to present the critical issues and methodologies to improve robotic machining performance with flexile industrial robots.

A complete solution using active force control is introduced to address various issues during the robotic machining process.

Programming complex couture parts without a CAD model is made easy by using force control functions such as lead‐through and path‐learning. The problem of process control is treated with a novel methodology that consists of stiffness modeling, real‐time deformation compensation for quality and controlled material removal rate for process efficiency.

Experimental results showed that higher productivity as well as better surface quality can be achieved, indicating a promising and practical use of industrial robots for machining applications that is not available at present.

The purpose of this paper is to examine the ability of high-functioning autistic (HFA) children to programme robotic behaviour and sought to elucidate how they describe and construct a robot’s behaviour using iconic programming software.

The robotic learning environment is based on the iPad, an iconic programming app (KinderBot), and EV3. Two case studies, of A. and N., both HFA children of average age 10.5, are the focus of this research.

The research revealed how the participants succeeded in programming the behaviour of an “other” at different programming complexity levels (from simple action to combinations of states of two binary sensors and rule with subroutine). A transformation from procedural to declarative description was also found.

This research on the ability of HFA children to programme robotic behaviour yielded results that can be implemented in K-12 education. Furthermore, learning to programme robots and understand how robotic technologies work may help HFA children to better understand other technology in their environment.

In this research, the authors present an innovative approach that for the first time enables HFA children to “design” the behaviour of smart artefacts to use their sensors to adapt in accordance with the environment. For most HFA children, this would be the first opportunity to “design” the behaviour of the other, as opposed to oneself, since in most of their experience they have been largely controlled by another person.

Advancements in technology require that everyone is skilled with computational thinking (CT), problem-solving and computer programming skills. This study aims to examine the development of CT in problem-solving skills (PSS) and programming learning attitude by integrating LEGO robotics kits in a project-based learning course.

This study examines the development of CT in PSS and programming learning attitude by integrating LEGO robotics kits in a project-based learning course. This study consists of a single group pre-post-test research design with 32 freshmen university students. Quantitative and qualitative data were collected by pre-post-tests and recording of classroom discussions, respectively.

Therefore, this finding implies that robotics can be used to develop CT in university students; however, there is a need for designing curricula with advanced robotic kits as artificial intelligence (AI) has become more prevalent. Hence, programming knowledge learned will help students to understand the application of robots in AI.

The study creates educators' awareness that CT skills might be developed in freshmen university students through robotics. However, many still consider them toys rather than learning aids.

This chapter explores how to introduce young children to coding as a literacy using mobile devices. Learning how to code is changing what it means to be literate in the twenty-first century and, increasingly, early years educators are expected to teach young children how to code. The idea that coding is a literacy practice is relatively new, and this chapter first presents strategies for introducing coding without technology. It then explores how to scaffold young children’s coding literacy proficiencies through programming and coding robotic toys. When young children have become familiar with coding and solving challenges using concrete materials and robotic toys, it is possible to introduce mobile devices, apps and humanoid robots in playful ways. This chapter explores how this can be done.

The purpose of this paper is to examine how robotics program developers perceived the role of emulation of human ethics when programming robots for use in educational settings. A purposive sampling of online robotics program developer professional sites which focused on the role of emulation of human ethics used when programming robots for use in educational settings was included in the study. Content related to robotics program developers’ perceptions on educational uses of robots and ethics were analyzed.

The design for this study was a qualitative summative content analysis. The researchers analyzed keywords related to a phenomenon. The phenomenon was the emulation of human ethics programmed in robots. Articles selected to be analyzed in this study were published by robotics program developers who focused on robots and ethics in the education. All articles analyzed in this study were posted online, and the public has complete access to the studies.

Robotics program developers viewed the importance of situational human ethics interpretations and implementations. To facilitate flexibility, robotics program developers programmed robots to search computer-based ethics related research, frameworks and case studies. Robotics program developers acknowledged the importance of human ethics, but they felt more flexibility was needed in the role of how classroom human ethical models were created, developed and used. Some robotic program developers expressed questions and concerns about the implementations of flexible robot ethical accountability levels and behaviors in the educational setting. Robotics program developers argued that educational robots were not designed or programmed to emulate human ethics.

One limitation of the study was 32 online, public articles written by robotics program designers analyzed through qualitative content analysis to find themes and patterns. In qualitative content analysis studies, findings may not be as generalizable as in quantitative studies. Another limitation was only a limited number of articles written by robotics programs existed which addressed robotics and emulation of human ethics in the educational setting.

The significance of this study is the need for a renewed global initiative in education to promote debates, research and on-going collaboration with scientific leaders on ethics and programming robots. The implication for education leaders is to provide ongoing professional development on the role of ethics in education and to create best practices for using robots in education to promote increased student learning and enhance the teaching process.

The implications of this study are global. All cultures will be affected by the robotics’ shift in how students are taught ethical decision making in the educational setting. Robotics program developers will create computational educational moral models which will replace archetypal educational ethics frameworks. Because robotics program developers do not classify robots as human, educators, parents and communities will continue to question the use of robots in educational settings, and they will challenge robotics ethical dilemmas, moral standards and computational findings. The examination of robotics program developers’ perspectives through different lens may help close the gap and establish a new understanding among all stakeholders.

Four university doctoral faculty members conducted this content analysis study. After discussions on robotics and educational ethics, the researchers discovered a gap in the literature on the use of robots in the educational setting and the emulation of human ethics in robots. Therefore, to explore the implications for educators, the researchers formed a group to research the topic to learn more about the topic. No personal gains resulted from the study. All research was original. All cultures will be affected by the robotics’ shift in how students are taught ethical decision making in the educational setting. Robotics program developers will create computational educational moral models which will replace archetypal educational ethics frameworks. Because robotics program developers do not classify robots as human, educators, parents and communities will continue to question the use of robots in educational settings, and they will challenge robotics ethical dilemmas, moral standards, and computational findings. The examination of robotics program developers’ perspectives through different lens may help close the gap and establish a new understanding among all stakeholders.

Most industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. This is a tedious and time‐consuming task that requires some technical expertise, and hence new approaches to robot programming are required. The purpose of this paper is to present a robotic system that allows users to instruct and program a robot with a high‐level of abstraction from the robot language.

The paper presents in detail a robotic system that allows users, especially non‐expert programmers, to instruct and program a robot just showing it what it should do, in an intuitive way. This is done using the two most natural human interfaces (gestures and speech), a force control system and several code generation techniques. Special attention will be given to the recognition of gestures, where the data extracted from a motion sensor (three‐axis accelerometer) embedded in the Wii remote controller was used to capture human hand behaviours. Gestures (dynamic hand positions) as well as manual postures (static hand positions) are recognized using a statistical approach and artificial neural networks.

It is shown that the robotic system presented is suitable to enable users without programming expertise to rapidly create robot programs. The experimental tests showed that the developed system can be customized for different users and robotic platforms.

The proposed system is tested on two different robotic platforms. Since the options adopted are mainly based on standards, it can be implemented with other robot controllers without significant changes. Future work will focus on improving the recognition rate of gestures and continuous gesture recognition.

The key contribution of this paper is that it offers a practical method to program robots by means of gestures and speech, improving work efficiency and saving time.

This paper presents an alternative to the typical robot teaching process, extending the concept of human‐robot interaction and co‐worker scenario. Since most companies do not have engineering resources to make changes or add new functionalities to their robotic manufacturing systems, this system constitutes a major advantage for small‐ to medium‐sized enterprises.

This chapter examines the existing work on tangible user interfaces (TUIs) and focuses on tangible programming with the scope to enlighten the opportunities for innovation and entrepreneurship in this particular domain.

In the first section, we start by presenting in short the history of TUIs and then focus on tangible programming presenting the different design approaches. Then we present the opportunities for innovation and guidelines for future products.

In the second section, we review the entrepreneurial activities that combine educational toys and TUIs.

The main finding of this chapter is that although TUI design and research are still in its infancy and more design guidelines and research are required to further bridge the digital and the physical world, the first signs of entrepreneurship promise a bright future.

Limitations arise from the fact that many companies keep many of their financial data confidential. Thus, it was impossible to include and validate all the information that we intended to present.

Initially, this chapter motivates and challenges scientist to find novel innovative solutions in the field. Then, reveals the entrepreneurial opportunities and potential customers. Finally, shows the funding sources and how tangible products are offered in the market.

We propose a new kind of toys that might alter and expand science, technology, engineering, and mathematics (STEM) in education.

This chapter appears to be unique in the sense that is the first that reports simultaneously on TUIs, entrepreneurship, and innovation.

This paper describes a two-month summer intensive course designed to introduce participants with a hands-on technical craft on robotics and to acquire experience in the low-level details of embedded systems. Attendants started this course with a brief introduction to robotics; learned to draw, design and create a personalized 3D structure for their mobile robotic platform and developed skills in embedded systems. They were familiarize with the practices used in robotics, learning to connect all sensors and actuator, developing a typical application on differential kinematic using Arduino, exploring ROS features under Raspberry Pi environment and Arduino – Raspberry Pi communication. Different paradigms and some real applications and programming were addressed on the topic of Artificial Intelligence. Throughout the course, participants were introduced to programming languages (including Python and C++), advanced programming concepts such as ROS, basic API development, system concepts such as I2C and UART serial interfaces, PWM motor control and sensor fusion to improve robotic navigation and localization. This paper describes not just the concept, layout and methodology used on RobotCraft 2017 but also presents the participants knowledge background and their overall opinions, leading to focus on lessons learned and suggestions for future editions.

The purpose of this paper is to present a case‐based system for offline automatic programming in robotic assembly production. This system can reuse past learned robot programs to generate programs for new assembly tasks.

The approach used in this paper is case‐based reasoning. The assembly knowledge acquired from the robot program for an assembly task is retained in a case, which is composed of the primitive task description and the corresponding robot program schema. The retained cases are retrieved by matching features of their primitive task descriptions, and are reused to automatically program for new tasks by instantiating their robot program schemata.

A case not only can be reused as a whole, but also can be reused partly by synthesizing different parts of several cases to generate a program for a new task in a variant environment.

The teaching time of robots can be greatly reduced. This helps to introduce robots into small and medium enterprises.

This paper proposes a novel system that can automatically program for assembly tasks in various environments by flexibly reusing past robot programs.