In programming education, the instructor tries to find out the learners who needs help by grasping the learners' development of understanding using tests that require knowledge.However, in reality, not many learners will acquire the skill of writing source codes.This kind of current situation implies that programming ability of learners cannot be measured by tests that require knowledge.This paper focuses on not only the knowledge items required for programming but also the programming thinking (computational thinking), which is the ability to combine the constituent elements of the program.In this paper, we propose a method to estimate the learner's understanding from the learner's process to solve the code puzzles that require programming thinking as well as knowledge.We developed the interface to realize the proposed method.The experimental result with the interface showed that the proposed method could estimate with the accuracy of 80% or more.

The improvement of the efficiency in teaching requires knowing the understanding level of each student.However, it is difficult due to limited time in a class.We propose a Virtual Reality (VR) space imposing assignments on students, to know their understanding level from their behavior which comes from cognitive loads during their answering.The VR space presents a student an assignment and a working space to answer it.In general, students solve assignments, using elements on their short term memory.When students solve same kind of assignments many times, they build generalized solution methods in their long term memory.When they engage in such assignments, their cognitive load is low enough to make them watch only the working spaces, keeping their hands working.On the other hand, when students have no solution pattern, their short term memory works hard.Their high cognitive load often stop their hands, because of confusion.They also look assignments and the working space many times, to reconsider solutions.Since answering behavior of students exposes their cognitive load, a VR space is ideal to estimate cognitive load.We conducted an experiment to evaluate the ability of the method to estimate the cognitive load.We examined the movement of the hand and the edit distance of student's answer from the correct sentence during their answering.We confirmed a fair correlation of the hands' stagnation with the confidence in students of good scores.We also found a relationship of eye movement with the change of the edit distance.The experiment result implies the possibility to estimate the cognitive load.The estimation would enable teachers to know students' understanding faults, which leads to education according to the understanding level.

When smart phone users browse web news articles, they encounter attractive phrases by chance. At that time, they try to obtain information on the smart phones. In order to search the information of the attractive phrases on web pages, they have to manipulate the smart phones to search on the small screen. It causes stresses because of situations such as manipulation errors. Such stresses could be eliminated if the attractive phrases can be identified and be input automatically in order to recommend the web pages with the information of the attractive phrases. Because of the small screens of smart phones, users move the news article area displayed on the screens with touch gestures such as swipe. The history of touch gestures during browsing an article implies the position and the timing users have focused on in the article. This paper proposes a method to identify the areas where attractive phrases have appeared on news articles, in order to enable automatic identification of attractive phrases. We have achieved real-time identification by utilizing the history of touch gestures during a web news browsing. The proposed method shows the history of touch gestures by a gesture trail. It is a graph showing the time series of the vertical coordinate of the displayed article area. When users encounter attractive phrases, they take certain patterns of touch gestures to confirm or read carefully the neighborhood of the attractive phrases. Thus, in the proposed method, the news article area including an attractive phrase is detected by matching the gesture trail in a sliding time window with a pattern obtained by pre-training. We use slow-down and resting patterns approximated by quadratic functions with the parameters defined for individual users. Experiments to identify time windows of attractive phrases on gesture trails has revealed that the highest and the lowest precision ratios are 0.579 and 0.278, respectively.

With the continuous advances in mobile technology, numerous applications are being developed to empower the mobile users. Mobile commerce (m-commerce) is starting to make a mark following the success of the internet and e-commerce. With this, application development aims to optimize the performance of the mobile environment such as PDA and cellular phones. Mobile advertisement is one example of mobile applications that provide a lot of potentials. In this paper, we introduce a new method of personalizing mobile advertisement by considering not only the user’s location but also his/her interest. A prototype system called ‘Concierge’ has been developed and tested on a shopping environment. The result of the experiment shows good potential for this kind of service.

This paper proposes the example expansion which supports control system development. In the example expansion, real-time system engineers familiar with programming for real-time computing develop a small example for maintaining the timing consistency. Since the example is small, its development is easy. The example is expanded according to requirements specified by control engineers who are unfamiliar with real-time computing but have expertise in the regulation of a specific plant. Since formal rules and tools expand the example, a mechanism for maintaining the timing consistency is correctly transferred to a target system. The example expansion allows the two kinds of engineers to concentrate on their own work. A control system for a steel mill plant has been developed using this method, and the system has been developed 2.7 times faster than the time taken with a conventional method.

Data sampled from plants are registered as temporal data, combined with time stamps. We developed a real-time data server which periodically acquires temporal data and transmits them to clients for graphic presentation. The real-time data server consists of multi threads scheduled based on the rate monotonic theory. This paper explains the design of a real-time data server. The prediction for schedulability of it based on the rate monotonic theory has been verified with an experiment on an actual system.>

A practical distributed artificial intelligence (AI) system is proposed for the guidance of plant operations in a steel galvanizing plant. The system includes three autonomous agents for guidance. Each agent records data sampled every moment in an appropriate form for a task assigned to it. The data correspond to states of a monitored entity. Each agent recognizes not only a current state but also a state transition in the course of time to select the best moment for a plant operation. An experiment in a real plant has proved that the plant-operation-supporting system can guide plant operations in much the same way as an experienced operator.>