Yu, Brown and Billett (2005: 7) concluded more than a decade ago that “Computer-based virtual learning environment is a relatively new technology in education and training. Studies to date have shown VLEs potentially benefits both educators and students, particularly in higher education and in the delivery of complex scientific concepts and principles. It eliminates time and geographical constraints. At the moment, such applications would not replace real world laboratory exercises. Students, however, could augment their real life laboratory experience. They can explore the virtual laboratory experiments in a relaxed and flexible environment at their own speed and need. They can use it at revision time, when access to the real laboratory may be prohibited in an unsupervised way, due to the expensive or dangerous nature of the laboratory exercises. Educators can add to their battery of course materials to promote more effective understanding of curricula, and more easily accessible course resource.”
About ‘virtual tutoring agents’ Yu, Brown and Billett (2005: 7) elaborate on the “development of a set of intelligent tutoring agents” to ‘scaffold’ virtual laboratory experiential learning for students. They explain an ‘intelligent agent’ as “a section of computer programme that simulates a human relationship by doing something that another person could do” and name three types:
1. Deductive tutor provides assistance to students in the course of their deduction with scientific problem solving, which is required to accomplish their tutorial. For example, if students add a certain liquid to a tube, but instead they select a wrong tube, the deductive tutor will display a warning message and play an audio track to the students.
2. Rule-based tutor provides assistance to students by:
- Encoding a set of rules of an experiment.
- Monitoring a student's action and looking for one of these rules to be "broken".
- "Visiting" students to present expert advice.
For example, there are dilution rules: (1) the amylase in tube 1 should be diluted from the Amylase bottle (the first bottle from left in Figure 2) and (2) the amylase in tubes 2 to 6 should be diluted from the tube to the left of the current one. If the students break one of the dilution rules, the rule-based tutor will remind them. It also tells students where to find a relevant case-based virtual tutor for demonstration.
3. Case-based tutor provides assistance to students by presenting an example of closest relevant experience. For example, a video for each experimental procedure is embedded in the virtual step in the Help system.
The deductive and rule-based tutoring agents are embedded in the 3D virtual environment to monitor
student's actions and record the status of the objects in the learning process to ensure the learning tasks tackled. A virtual agent provides the students with advice once the students make a mistake, overlook an object or break a rule, which result in the experimental progress toward successful completion impasse.
The advice is designed in both text and voice message formats for greater accessibility.
The case-based virtual agents are embedded in the Help system in order to reduce the working load of the 3D virtual laboratory. The case-based virtual agents play a video stream to demonstrate a procedure of the experiment once a request is explicitly made.
Yu, J.Q.; Brown, D.J. & Billett, E. (2005). Development of a Virtual Laboratory Experiment for Biology. European Journal of Open, Distance and E-Learning, 8(2). Electronically accessible from http://www.eurodl.org/materials/contrib/2005/Jian_Quing_Yu.pdf
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