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This paper sought to accomplish three goals. First, it provided a systematic, comparative review of several intelligent tutoring systems (ITS). Second, it summarized problems and solutions presented and solved by developers of ITS by consolidating the knowledge of the field into a single review. Third, it provided a unified language from which ITS can be reviewed and understood in the same context. The findings of this review centered on the 5-Component Framework. The first component, the domain model, showed that most ITS are focused on science, technology, and mathematics. Within these fields, ITS generally have mastery learning as the desired level of understanding. The second component, the tutor model, showed that constructivism is the theoretical strategy that informs most ITS. The tutoring tactics employed in the ITS stem from this paradigm. The third component, the student model, describes the several ways ITS infer what a student knows. It described the variety of data that is collected by an ITS and how it is used to build the student model. The fourth component, the interface, revealed that most ITS are now web-based, but vary in their capacity to interact with students. It also showed that user experience is underreported and ought to be included more in the research. Finally, the fifth component, learning gains, demonstrated that ITS are capable of producing learning gains equivalent to a human tutor. However, reporting learning gains does not seem to be a focus of the literature.

Hao, Jianye. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 216-228). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

<p>In this work new artificial learning and innate control mechanisms are proposed for application</p><p>in autonomous behavioral systems for mobile robots. An autonomous system (for mobile robots)</p><p>existent in the literature is enhanced with respect to its capacity of exploring the environment and</p><p>avoiding risky configurations (that lead to collisions with obstacles even after learning). The</p><p>particular autonomous system is based on modular hierarchical neural networks. Initially,the</p><p>autonomous system does not have any knowledge suitable for exploring the environment (and</p><p>capture targets œ foraging). After a period of learning,the system generates efficientobstacle</p><p>avoid ance and target seeking behaviors. Two particular deficiencies of the forme rautonomous</p><p>system (tendency to generate unsuitable cyclic trajectories and ineffectiveness in risky</p><p>configurations) are discussed and the new learning and controltechniques (applied to the</p><p>autonomous system) are verified through simulations. It is shown the effectiveness of the</p><p>proposals: theautonomous system is able to detect unsuitable behaviors (cyclic trajectories) and</p><p>decrease their probability of appearance in the future and the number of collisions in risky</p><p>situations is significantly decreased. Experiments also consider maze environments (with targets</p><p>distant from each other) and dynamic environments (with moving objects).</p>

With the help of the internet, teaching is not constrained in the traditional classroom pedagogy; the instructors can put the course material on the website and allow the students go on to the course webpage as an alternative way to learn the domain knowledge. The problem here is how to design a web-based system that is intelligent and adaptive enough to teach the students domain knowledge in Programmable Logic Controller (PLC). In my research, I proposed a system architecture which combines the pre-test, cased-based reasoning (i.e., heuristic functions), tutorials and tests of the domain concepts, and post-test (i.e., including pre-exam and post-exam) to customize students’ needs according to their knowledge levels and help them learn the PLC concepts effectively. I have developed an intelligent tutoring system which is mainly based on the feedback and learning preference of the users’ questionnaires. It includes many pictures, colorful diagrams, and interesting animations (i.e., switch control of the user’s rung configuration) to attract the users’ attention. From the model simulation results, a knowledge proficiency effect occurs on problem-solving time. If the students are more knowledgeable about PLC concepts, they will take less time to complete problems than those who are not as proficient. Additionally, from the system experiments, the results indicate that the learning algorithm in this system is robust enough to pinpoint the most accurate error pattern (i.e., almost 90 percent accuracy of mapping to the most similar error pattern), and the adaptive system will have a higher accuracy of discerning the error patterns which are close to the answers of the PLC problems when the databases have more built-in error patterns. The participant evaluation indicates that after using this system, the users will learn how to solve the problems and have a much better performance than before. After evaluating the tutoring system, we also ask the participants to submit the survey (feedback), which will be taken into serious consideration in our future work.

Mixed Reality is the combination of the real world with a virtual one. In robotics thisopens many opportunities to improve the existing ways of development and testing. Thetools that Mixed Reality gives us, can speed up the development process and increasesafety during the testing stages. They can make prototyping faster and cheaper, and canboost the development and debugging process thanks to visualization and new opportunitiesfor automated testing.In this thesis the steps to build a working prototype demonstrator of a Mixed Realitysystem are covered. From selecting the required components, over integrating them intofunctional subsystems, to building a fully working demonstration system.The demonstrator uses optical tracking to gather information about the real world environment.It incorporates this data into a virtual representation of the world. This allowsthe simulation to let virtual and physical objects interact with each other. The results ofthe simulation are then visualized back into the real world.The presented system has been implemented and successfully tested at the HalmstadUniversity.

In this work new artificial learning and innate control mechanisms are proposed for application in autonomous behavioral systems for mobile robots. An autonomous system (for mobile robots) existent in the literature is enhanced with respect to its capacity of exploring the environment and avoiding risky configurations (that lead to collisions with obstacles even after learning). The particular autonomous system is based on modular hierarchical neural networks. Initially,the autonomous system does not have any knowledge suitable for exploring the environment (and capture targets œ foraging). After a period of learning,the system generates efficientobstacle avoid ance and target seeking behaviors. Two particular deficiencies of the forme rautonomous system (tendency to generate unsuitable cyclic trajectories and ineffectiveness in risky configurations) are discussed and the new learning and controltechniques (applied to the autonomous system) are verified through simulations. It is shown the effectiveness of the proposals: theautonomous system is able to detect unsuitable behaviors (cyclic trajectories) and decrease their probability of appearance in the future and the number of collisions in risky situations is significantly decreased. Experiments also consider maze environments (with targets distant from each other) and dynamic environments (with moving objects).

In the thesis, we propose an intelligent metamaterial to reduce the specific absorption rate (SAR) of cellular phone to phantom. We call our design intelligent metamaterial because it will not affect the antenna performance greatly. When the antenna is close to the phantom, the metamaterial acts like a stopband filter, thus reducing the SAR. We design a small metamaterial cell resonating at GSM 900 band, having 2 cm x 2cm x 0.4 cm in size. We use three cells to shield the PIFA antenna and the SAR is reduced by 29.12 % at a distance of 15 mm away from the phantom. Then we design a metamaterial cell having 1 cm x 1.95 cm x 0.4 cm in size,operating in GSM 1800 band. We use four cells to shield the PIFA antenna and the SAR reduced by 40.2 % at a distance of 15 mm away from the phantom. We also propose a dualband (GSM 900/1800) metamaterial having 2 cm x 4 cm x 0.8 cm in size. We use nine metamaterial cells to shield the dualband antenna and the ground¡Athe SAR reduced by 25 % at 900 MHz and 32.6 % at 1800 MHz at a distance of 15 mm away from the phantom.