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E-learning environment

21 January, 2016 - 14:46

We defined and implemented a Java framework for designing and implementing intelligent and practical e-learning tools, to be used by both the students and the teaching staff in a context of open learning. This framework provides the infrastructure for preparing e-learning scenarios based on practice and real world experiences, as practice is essential in learning activities. Our e-learning scenarios promote active learning, forcing the students to take part in real world activities simulated on computer. Also, we designed e-learning tools based on bootstrapping methods (which are quite valuable for reasoning in uncertain conditions), with the purpose to simulate laboratory experiments in both didactic and research activities.

An e-learning scenario is in fact like a traditional lesson, and the ideal solution is to simulate a teaching-learning relation with a virtual teacher able to interact with the learners and to instruct them (Prodan et al., 2008). A good traditional teacher learns all the time from previous didactic experiences. Based on this historical feedback, the teacher exploits prior specific successful episodes, and avoids prior failures. We introduce a similar feedback mechanism in our technology of elaborating e-learning scenarios (Figure 3.1). The feedback information, collected from learners’ remarks and from prior results and successes, is stored in case bases. The relevant cases are retrieved and adapted to fit new situations from new e-learning scenarios, or to improve the previous ones. In addition, our approach in creating an e-learning scenario relies upon a special sort of goal oriented intelligent agents

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Figure 3.1 The generation of the e-learning scenarios 
 

(Nwana, 1996), able to incorporate knowledge, teaching methods and pedagogical characteristics into e-courses (Kanuka 2008). We intend to implement a simulation of some intelligence based actions and initiatives, that are to be incorporated into e-learning scenarios, with the purpose to map, to plan and to monitor the pace and the progress of a learning process. Following the traditional model, the cases of positive experiences from previous e-learning scenarios are stored into case bases created with XML and CBR (Case Based Reasoning) technologies (Leake, 1996).

An e-course consists of a set of e-learning scenarios, each e-learning scenario being generated by virtue of some well-defined learning objectives. To generate intelligent and practical e-learning scenarios for a particular e-course, we created first a particular infrastructure containing the knowledge from particular domains of the target e-course. For this purpose, we generated consistent Java and XML based knowledge bases, containing integrated knowledge of the best teachers. In addition, we implemented in Java a set of simulation algorithms describing real world phenomena, processes and activities we have to include in e-courses. When generating a new e-learning scenario, we use a feedback mechanism based on our historical experience from previous e-learning scenarios (Figure 3.1). Also, we use Java technologies to generate intelligent and practical e-learning scenarios, based on new AI (Artificial Intelligence) paradigms, such as Case-Based Reasoning, Bayesian Inference and Intelligent Agents (Prodan et al., 2006, 2008, 2010). A learner can access the e-course and launch an e-learning scenario either locally, or via WWW in a context of distance learning.

When generating an e-learning scenario, we focus on pedagogical context and have all the time in mind the following pedagogical characteristics:

  • Friendly interface – When the learners have the initiative to enter the e-course, a teaching-learning relation is initiated through the user interface. Hence, it follows that if our purpose is to facilitate the learners’ access to knowledge, our system provides a friendly, easy to learn, efficient and agreeable graphical user interface.
  • General information – When a learner enters for the first time into an e-course, we have to visualize some general information about that e-course, the objectives of the e-course, specific information about e-learning scenarios and how to use them.
  • Objectives – Each e-learning scenario is generated by virtue of some well defined learning objectives. When a learner launches a particular e-learning scenario, it is necessary to visualize the objectives corresponding to that scenario. By doing so, we help the learners to see what it is expected to be able to do after they will traverse the respective e-learning scenario.
  • Orientation facilities – When the learners use e-learning scenarios to navigate in an ocean of information and knowledge, browsing through XML based knowledge bases and hyperdocuments, they want to know at any time their position. We implement in elearning scenarios many techniques to facilitate the navigation, such as maps, marked routes, bookmarks, diagrams, queries, etc.
  • Layered structure – An e-course has a layered structure from simple to complex, allowing each learner to access an optimum layer, depending on his purpose and previous knowledge.
  • Customization – The functionality of an e-learning scenario is adapted to ability and purpose of each learner. Customization can be either static or dynamic. Static customization is an easy task, being carried out by a set of parameters before run time. Dynamic customization is more difficult, because it is necessary to collect information about learner during e-learning scenario execution.
  • Global and local coherency – To improve global coherency of an e-learning scenario, we implement adequate visualization and orientation techniques. As concerning local coherency, each link must have a well-defined destination and it is necessary to minimize the fragmentation, to avoid the confusion and getting lost.
  • Learning by doing – We think that practice is essential in learning activities, because learning by doing increases substantially the effectiveness of learning processes. We elaborate practical e-learning tools, allowing the learners to work on experiments with real world items.
  • Active learning – The experienced learners can take part in activities of design and elaboration of some particular e-learning scenarios for beginners.
  • Homework assignments – Previous studies show that most traditional learners appreciate the homework assignments. However, in traditional teaching-learning relations, the teachers do not have the means to react properly to the individual problems the learners have when working out the assignments. This problem is overcome in case of a simulated teaching-learning relation, because the virtual teacher is always present in a running e-learning scenario.
  • Virtual teacher evaluates the solution – Before the final solution is sent to the virtual teacher, each learner can obtain some hints and suggestions to handle the problem. After the final solution is sent, the learner gets the outcome for self-evaluation.