In [141] the authors attempt to create a virtual laboratory using the non-declarative modelling language Modelica [142]. The paper proposes a standard modelling methodology through Modelica and demonstrates it by building a virtual laboratory called “VirtualLabBuilder”. The VirtualLabBuilder was used to connect graphical elements to model a water tank. The parameters considered in the laboratory are the pump voltage, gravitational acceleration and an outlet hole.
Exploratory learning has also been shown to be effective in simulating high-performance processors, a system component many students struggle to understand. A user can access the simulator using a web browser and the results are shown visually. The user can construct a processor by supplying a configuration file with the modules listed and their specified interconnections. This extensibility is a very useful feature that allows the tool to be continually updated by anyone. To keep the presentation of information to the user simple, the internal state is hidden but can be shown in a separate frame by clicking on the register/memory location. An example screenshot is provided in Figure 13. The user can monitor these values as they are updated on a cyclic basis as the simulation proceeds. A further example of this can be seen in DLSim 3 which is a multi-level logic simulator demonstrated in [143].
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Figure 13: Screenshot of a simulator to enable students to learn how a CPU works
A web-based pico-controller [144] training simulator has been designed at the National University of Science and Technology (NUST) in Zimbabwe. The students scored the tool highly. The results were 4.44/5.00 for the simulator’s usefulness, 4.74/5.00 for relevance and 4.96/5.00 for ease of use. The evaluation provided adds weight to the idea of a simulator embedded into a web page, allowing students to “rapidly evaluate functions and interfaces of the electronic device, thereby giving them confidence in approaching the real hardware”. Cryptography has also seen an exploratory learning approach [145-146].
The use of graphical representations has been proven to improve users learning over the traditional approach of text [147-149]. The field of using computers for learning resources is expanding with new journals being created and the current Journal on Educational Resources in Computing undergoing a revival. The IEEE now issues a journal named Transactions on Learning Technologies.
3.19.1
PLATO
Computers have been used to provide a Virtual Learning Environment (VLE) for many years. A VLE is a system that facilitates learning in a certain field through specially configured environments. An early and robust VLE for learning is PLATO (Programmed Logic for Automated Teaching Operations) [150] which was developed at the University of Illinois in the early 1960s. This is one of the earliest computer-based VLE and was used to teach students in five key areas at the university (accounting, biology, chemistry, English and mathematics). The system saw continuous development and redesign. A report was published detailing its progress, evaluation and analysis techniques [151]. Subsequent versions of PLATO were designed to cope with 5,000 students using the machine at various distances
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from the framework. A series of lessons were created using the TUTOR [152] language in each of the targeted subjects. PLATO usage increased across all subjects as more lessons were created.
A thorough analysis of PLATO is provided in [151]. Firstly, treatment classes were divided into those where the PLATO system was employed and those where it was not. Keystrokes and measurements of time usage were also collected from the main system. This typifies the passive approach taken here by the evaluators, as they wanted a responsive and non-reactive method of analysis. The evaluation was designed so that the curriculum of each subject was collected, lessons on sections were agreed, then pre-tests and post-tests were constructed. The statistical analysis showed no overall improvement in student performance. There were many possible contributing factors to a lack of improvement such as the ability of the instructors and validity of the pre/post-testing. An encouraging result was the improvement of student attitude towards the topic and system. 70 - 90% continued using the system after class, citing they liked being able to make a mistake without feeling embarrassed and found comments from PLATO useful. 97% of instructors found the system to be moderately or very helpful and 80 - 83% judged PLATO to have a positive impact on student attitude and achievement in the topic area. In the final semester, the schools continued to work together on the PLATO system, assigning new courses and lessons. At the end of the evaluation and initial funded, period the school continued to provide funding.
3.19.2
Grid Architectures for E-Learning
The grid provides a system for linking existing Service Oriented Architectures together with the maintenance of state in a users’ session. This section will discuss the example usage of the GRID as an e-learning platform and the relevant frameworks and tools used.
SELF
SELF is a Semantic grid-based E-Learning Framework [153] for a comprehensive E-Learning environment that will provide full control over class scheduling, courseware maintenance, user collaboration etc. The approach taken by SELF is not to rewrite every level but rather to tie together existing tools. The authors state that a solution cannot be achieved with a new implementation of every level of the architecture, as this may result in a wasteful rework. Equally, a solution cannot be found with loose integration of existing components as this would lead to an unrealistic and non-scalable framework. As such, they propose that a good understanding of the related works and a good mapping between the two can grow a better architecture.
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Figure 14: Structure of SELF [153]
Figure 14 shows that SELF attempts a modular approach with existing technologies to provide collaborative tools.
The SELF components include Chandler [154] which is released under the Apache License. Version 2.0 can be used for note taking, email, calendar and tasks. The software is written in Python and has yet to reach 1.0 status. The advantages are a cross-platform, intuitive user interface and a persistent object database. Chandler is also built using defined open standards
CoAKTing
CoAKTinG [155] (Collaborative Advanced Knowledge Technologies in the GRID) started in June 2002. This project aimed to provide technologies to enable enhanced interactions between people. Edinburgh University provided task-oriented messaging, planning and activity management. KMi, the Open University, worked on online presence, availability, real time conversational mappings of meetings and group memory capture using Compendium [156].
Grid-Based SENSASIM VSE Simulator for Sensor Networks
Continuing the work described in section 3.8, SENSASIM has been expanded to enable service oriented access through the grid [157]. The SENSASIM grid-based VSE simulator was deployed in Athens Information Technology and the CyLab in Kobe, Japan. Encouraging results were reported after two test deployments.