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6 Potential Usage of Proposed System

For each course in a specific teaching environment, it is necessary to identify which types of augmented contents are required by end-users, i.e. educators and learners. Therefore, we conduct surveys to evaluate the practical need for our system in enhancing the enthusiasm and attractiveness for learners, including high school students and undergraduate students.

In the meeting with high school teachers and students in enhancing learning experience in Chemistry, we identify the first two main requirements for our system. The first is 3D visualization of chemical elements, substances, atoms, molecules, and stoichiometry. The second is to assist teachers in the visualization and simulation for chemical reactions. Although no activities have been set up for students, it is a new teaching activity with the assistance of our smart educational environment via AR.

In the meeting with instructors of the two courses on Introduction to Information Technology 1 and 2, we identify more interesting augmented contents including multimedia/social media data and augmented activities that can be established via our system. These two courses aim to provide the overview on different aspects in Information Technology for freshmen as a preparation and guidance for students following the teaching strategy of Conceive Design Implementation Operation (CDIO). With the assistance of our system, we can deploy the trial teaching environment for freshmen volunteers to join the active learning activities with AR interactions. The volunteers use the proposed system in the two courses. Students are assigned to read printed materials with AR media, to discuss and do exercises with others via our system. We collect useful feedbacks from participants to evaluate the usefulness and convenience of our system as well as the satisfaction of volunteers with the system and favorite functions. Based on the qualitative interviews in this study, most students find that our system can provide a more interesting and attractive way to study than traditional approaches do. Moreover, the features of collaboration in our system successfully attract students interest and trigger their motivation in reading documents.

7 Conclusion and Future Work

The authors propose a new method for organizing a collaborative class using AR and interaction. Via our proposed system, learners and educators can actively interact with others. Learners can do exercises embedded virtually as augmented contents linked to a printed lecture note. They can add a new virtual note or comment to a specific part of a printed lecture and share with others as well. Besides, educators get feedbacks from learners on the content and activities designed and linked to a specific page in a lecture note or textbook to improve the quality of lecture designs. Educators can also keep track of the learning progress of each individual or each group of learners.

In our proposed system, we focus on providing the natural means of interactions for users. The system can recognize the context, i.e. which section of a page in a lecture note or a textbook is being read, by natural images, not artificial markers. Users can also interact with related augmented contents with their bare hands.

We also propose a new method based on saliency metric to quickly eliminate irrelevant regions in a page of a book or printed material to enhance the accuracy and performance of the context aware process on mobile devices or AR glasses. Furthermore, our method works independently of the training and detecting stage. It is compatible to most well-known local features. Therefore, this stage can be incorporated into any existed system for printed material detection and recognition.

There are more saliency metrics for implementation in our visual search engine, thus requires further experiments. In addition, the authors are interested in applying psychology and neuroscience knowledge of human vision in further research. To enhance the system, we are doing classification by Neuron network algorithm to analysis the profiles and learn their behaviors in order to utilize better.

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