“…ReactiVision and Processing processed the scanned fiducial marks. The system is acceptable for teaching programming and there is an option for improvement [45]. Motoyoshi et al from Toyama Prefectural University developed Pro-Tan to improve TUI accessibility, as well.…”
Section: Tui For Programming and Controlling A Robotmentioning
confidence: 99%
“…ReactiVision and Processing processed the scanned fiducial marks. The system is acceptable for teaching programming and there is an option for improvement [ 45 ].…”
Section: Tui Application Areasmentioning
confidence: 99%
“…Some works used fiducial markers from the library of computer vision approaches (ARtag, ARToolkit). They were black/white markers in a square [ 5 , 10 , 14 , 16 , 23 , 28 , 45 , 51 , 54 , 55 , 64 ].…”
“…For image capturing situations, webcams [ 16 , 23 , 28 , 29 , 31 , 45 ] were used in the work of [ 28 ], specifically, the Logitech Webcam Pro 9000, USB cameras with a resolution of 640 × 480 were used in [ 67 ], in [ 74 ], specifically, the Point Grey Firefly MV was used, infrared cameras in [ 9 , 26 , 54 ], and in the work by [ 75 ], specifically the Wiimote infrared camera with a resolution of 1024 × 628. In the work of [ 55 ], a Sony PS3 Eye camera was used without an infrared filter and an infrared light pass filter 850nm was added.…”
“…ReacTIVision is an open-source platform for computer vision. It is used for the fast and robust tracking of fiducial markers placed on tangible objects and their identification in real-time [ 9 , 23 , 25 , 26 , 45 , 51 , 55 , 66 ]. The principle of the software is the binarization of the input images with an adaptive thresholding algorithm.…”
A tangible user interface or TUI connects physical objects and digital interfaces. It is more interactive and interesting for users than a classic graphic user interface. This article presents a descriptive overview of TUI’s real-world applications sorted into ten main application areas—teaching of traditional subjects, medicine and psychology, programming, database development, music and arts, modeling of 3D objects, modeling in architecture, literature and storytelling, adjustable TUI solutions, and commercial TUI smart toys. The paper focuses on TUI’s technical solutions and a description of technical constructions that influences the applicability of TUIs in the real world. Based on the review, the technical concept was divided into two main approaches: the sensory technical concept and technology based on a computer vision algorithm. The sensory technical concept is processed to use wireless technology, sensors, and feedback possibilities in TUI applications. The image processing approach is processed to a marker and markerless approach for object recognition, the use of cameras, and the use of computer vision platforms for TUI applications.
“…ReactiVision and Processing processed the scanned fiducial marks. The system is acceptable for teaching programming and there is an option for improvement [45]. Motoyoshi et al from Toyama Prefectural University developed Pro-Tan to improve TUI accessibility, as well.…”
Section: Tui For Programming and Controlling A Robotmentioning
confidence: 99%
“…ReactiVision and Processing processed the scanned fiducial marks. The system is acceptable for teaching programming and there is an option for improvement [ 45 ].…”
Section: Tui Application Areasmentioning
confidence: 99%
“…Some works used fiducial markers from the library of computer vision approaches (ARtag, ARToolkit). They were black/white markers in a square [ 5 , 10 , 14 , 16 , 23 , 28 , 45 , 51 , 54 , 55 , 64 ].…”
“…For image capturing situations, webcams [ 16 , 23 , 28 , 29 , 31 , 45 ] were used in the work of [ 28 ], specifically, the Logitech Webcam Pro 9000, USB cameras with a resolution of 640 × 480 were used in [ 67 ], in [ 74 ], specifically, the Point Grey Firefly MV was used, infrared cameras in [ 9 , 26 , 54 ], and in the work by [ 75 ], specifically the Wiimote infrared camera with a resolution of 1024 × 628. In the work of [ 55 ], a Sony PS3 Eye camera was used without an infrared filter and an infrared light pass filter 850nm was added.…”
“…ReacTIVision is an open-source platform for computer vision. It is used for the fast and robust tracking of fiducial markers placed on tangible objects and their identification in real-time [ 9 , 23 , 25 , 26 , 45 , 51 , 55 , 66 ]. The principle of the software is the binarization of the input images with an adaptive thresholding algorithm.…”
A tangible user interface or TUI connects physical objects and digital interfaces. It is more interactive and interesting for users than a classic graphic user interface. This article presents a descriptive overview of TUI’s real-world applications sorted into ten main application areas—teaching of traditional subjects, medicine and psychology, programming, database development, music and arts, modeling of 3D objects, modeling in architecture, literature and storytelling, adjustable TUI solutions, and commercial TUI smart toys. The paper focuses on TUI’s technical solutions and a description of technical constructions that influences the applicability of TUIs in the real world. Based on the review, the technical concept was divided into two main approaches: the sensory technical concept and technology based on a computer vision algorithm. The sensory technical concept is processed to use wireless technology, sensors, and feedback possibilities in TUI applications. The image processing approach is processed to a marker and markerless approach for object recognition, the use of cameras, and the use of computer vision platforms for TUI applications.
Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners’ behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents a systematic review of 36 papers to understand, compare, and reflect on recent attempts to utilize chatbots in education using seven dimensions: educational field, platform, design principles, the role of chatbots, interaction styles, evidence, and limitations. The results show that the chatbots were mainly designed on a web platform to teach computer science, language, general education, and a few other fields such as engineering and mathematics. Further, more than half of the chatbots were used as teaching agents, while more than a third were peer agents. Most of the chatbots used a predetermined conversational path, and more than a quarter utilized a personalized learning approach that catered to students’ learning needs, while other chatbots used experiential and collaborative learning besides other design principles. Moreover, more than a third of the chatbots were evaluated with experiments, and the results primarily point to improved learning and subjective satisfaction. Challenges and limitations include inadequate or insufficient dataset training and a lack of reliance on usability heuristics. Future studies should explore the effect of chatbot personality and localization on subjective satisfaction and learning effectiveness.
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