CONCLUSIONS AND RECOMMENDATIONS
The woods are lovely, dark, and deep,
But I have promises to keep,
And miles to go before I sleep,
And miles to go before I sleep.
One of the goals of the study was to create a programming-free administration and instruction environment to enable teachers to generate low-cost multimedia-based bilingual courseware. Based on that perspective, the approach focused on pragmatic issues rather than on theoretical subjects. With a basic understanding of computer programming, both expert systems techniques and conventional programming were used to construct the system.
TITES, a prototype of an tutorial expert system, was developed earlier by the researcher. The system can be used as a personal research tool; it also offers the researcher a pregnant experimental environment for programming. Some concepts and ideas were implemented in the system, such as course-independent design, the use of graphics to present Chinese characters, combining database management and word processing techniques to create a text file editor, and the use of the hungry-tracing method in the hybrid inference of forward chaining and backward chaining.
During the development process, it was confirmed that developing an expert system without conventional programming was not efficient. Although expert system development shells provide specific techniques for handling knowledge representations and inference mechanisms, its vast memory requirements and complicated inference processes
frequently results in garbage collection that slows down the system’s executing rate. In
other words, the
flexibility of the expert system is obtained at the cost of its
the contrary, conventional programming techniques are more efficient but less flexible.
The study also revealed that developing an expert system requires long-term efforts and a wide variety of background knowledge; hence, it is time-consuming and expensive. Figure 5-1 shows the development time of each implementation item.
Pilot Systems Design
Shell Study & Knowledge Base Design
Text File Editor Design
Auxiliary Programs Design
Testing & Debugging
Total Time Used
Figure 5-1. Development Time in Hours: Where the Time Went.
Tutorial expert systems can be regarded as a combination of art, education, and scientific technologies. As more and more information and technologies become available with the use of computers, the process of learning will change. As people become more knowledgeable, they want to know more and they want more indepth information. Under the influence of the proliferation of microcomputers and the increasing costs of traditional education, using personal computers as auxiliary teaching and learning tools is not only a trend but a fact that educators must recognize. Unless educators keep track of the efforts made by modern scientists and keep abreast of technological change, they will lose the battle as effective instructors.
The design philosophy of TITES is to create an experimental environment for one of the knowledge navigators. Turing (1950) said, "We can see only a short distance ahead, but we can see plenty there that needs to be done" (p. 35). Research is like opening the door; there is always another door inside the open door. Developing TITES not only verified the feasibility of applying expert system techniques in building educational software, it also holds the key to another door for future research.
Recommendations for Future Research
The system described above is intended to be an instructional tool for teaching consultants. It requires consideration of teaching material and student involvement in the form of an experimental tutor and the provision of information. There are still several limitations in the current version of TITES. Some students may prefer a more active learning style and feel excited if they can ask some questions and communicate with the computer in natural language. As current linguistic and AI research have made some breakthrough in natural language understanding, it is believed that intelligent dialogue functions will become possible in the near future.
Another problem stems from the limited feedback available. Although feedback is one of the most important functions in the expert system, the assessment of the student's learning is still the weakness of the study. Unlike a physics or chemical laboratory experiment, it is very difficult for the system to apply quality or quantity analysis of student performance. Individual differences among students, such as learning curves, background knowledge, and personality, make feedback functions more difficult.
Applying a student-learning model to install a more efficient feedback function will be feasible; however, it involves a relatively large student sample. The tutorial system, equipped with a highly flexible teaching model which can survey students' learning curves, their potential and achievement, can provide the right teaching method for each student. From this point of view, machine learning could be the way to a more flexible teaching model.
Another way to make the tutorial system more intelligent is to develop intelligent-design courseware. One of the important responsibilities of the teacher is to orchestrate student learning. Designing courseware is not just to place lessons or tests in files or graphics. The courseware author must set up the objectives for the lessons, write a behavioral objective for each concept to be taught, and decide how to measure whether the objectives have been met. In other words, the author should make a logical analysis of the courseware. This analysis includes applications of different domains: cognitive psychology, subject knowledge, instructional technology, Boolean analysis, syllogisms, and synthesis. Once the courseware has been analyzed precisely and logically, effective feedback can be provided to direct the user toward the correct learning modes.
Applying audio and video techniques to strengthen students' learning will be a valuable experiment for the tutorial system. Sound is the sensation that is produced when auditory nerves are stimulated by vibrating air molecules. It is an analog format signal. To reproduce or simulate a sound effect on a computer, it is necessary to employ digitizing techniques. Digitizing converts a sound from analog to digital format (see Figure 5-2).
Figure 5-2. Digital sound format of a Taiwanese folk song presented in the MacRecorder.
Image processing is another changing technique. The 256 colors available with VGA cards on today's personal computers cannot present high quality graphics. The 32-bit color or "true color" technique can provide 16.7 million colors to display perfect images. The computer, however, requires much more data storage space and takes more time to display. A more practical method of adding video effects to the tutorial system is to design an external video interface for the videodisc player. A Constant Angular Velocity (CAV) videodisc can contain up to 54,000 frames of addressable video images. Using a "search" command, users can move through the video frames sequentially or randomly. By means of programming control, "Play" and multispeed commands display motion sequences at normal (30 frames per second), slow, or fast speed in forward or reverse.
It can be expected that mass storage techniques and graphics coprocessors will be improved in the near future. As a low-cost desktop video production system and the re-writable CD-ROM SCSI disk drive are marketed, it will become possible to integrate more and more multimedia technologies into tutorial expert systems.
Expert systems provide a good experimental environment for intelligent tutorial modules. It is possible to build an intelligent tutorial module based on meta-level knowledge in rule-based systems. Any system that lacks feedback and automatic learning features cannot be a “true intelligent” system. One of the next goals of TITES is to integrate CAI, database, expert system, and multimedia technologies to construct a knowledge base, with the ability to exhibit behavior classified as "an intelligent tutor." The development of TITES is a definite effort in this direction. The final goal of TITES is to be an artificial tutor expert that has the capability to teach, to communicate with the student, to know what to teach, and to be an assistant to the teacher.
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