**5. Using MALESAassessment in a test**

The second algorithm – MALESAassessment - is to test students' performance after MALESAbrain's learning discussion. In this section, we use an example to explain how learners apply MALESAassessment for answering the testing problem.

After completing learning discussion, the educator will re-assign suitable keywords to each AK-cell according to his/her own understanding and viewpoint. This operation causes knowledge base reconstruction and turns it into a CBR expert system - called MALESAassessment. According to the matching of the reassigned-keywords, similar cases would be retrieved whenever users enter their inquiry. The similar cases retrieved are the AK-cells with attached knowledge-weight as the users' reference.

After set up CBR expert system, the educator will explain important cases to the learners with MALESAassessment. In the discussion the educator gives learners an understanding of what kind of cases that s/he considers good discussion-issues. It then gives a demonstration of how to use MALESAassessment to answer the questions in the assessment test.

After the demonstration, the educator will give learners a practical test to assess their understanding when handling a testing problem. For example, the educator can take off some memory from a motherboard and then run a heavy memory consuming game in a computer laboratory. S/he would ask the learners to make their own troubleshooting-plans and then to fix the problem. To make a troubleshooting plan the learners can seek advice from MALESAassessment. They can get the consultation cases from the original discussions, this helps them understand and cope with the testing problem. Their answers

knowledge (AK-cell *K2.1* ), which provides a quantitative measure of the synergic viewpoint

Then any AK-cell weights higher than 2 point will be qualified to join the competition for promotion (see Definition 1-5). This means that the moment the knowledge-weights "3.1" of *K1* and "2.9" *K2* are greater than *K2.1* "2.1" (see Fig. 12); otherwise the system will swap the positions of the lower-weighted AK-cell with the higher-weighted AK-cell. Furthermore, the

weight *wi,j* = *w2.1,2* = 1.4, therefore the learning system does not agree the solution *s2.1,2* is able

The second algorithm – MALESAassessment - is to test students' performance after MALESAbrain's learning discussion. In this section, we use an example to explain how

After completing learning discussion, the educator will re-assign suitable keywords to each AK-cell according to his/her own understanding and viewpoint. This operation causes knowledge base reconstruction and turns it into a CBR expert system - called MALESAassessment. According to the matching of the reassigned-keywords, similar cases would be retrieved whenever users enter their inquiry. The similar cases retrieved are the

After set up CBR expert system, the educator will explain important cases to the learners with MALESAassessment. In the discussion the educator gives learners an understanding of what kind of cases that s/he considers good discussion-issues. It then gives a demonstration

After the demonstration, the educator will give learners a practical test to assess their understanding when handling a testing problem. For example, the educator can take off some memory from a motherboard and then run a heavy memory consuming game in a computer laboratory. S/he would ask the learners to make their own troubleshooting-plans and then to fix the problem. To make a troubleshooting plan the learners can seek advice from MALESAassessment. They can get the consultation cases from the original discussions, this helps them understand and cope with the testing problem. Their answers

of how to use MALESAassessment to answer the questions in the assessment test.

learners apply MALESAassessment for answering the testing problem.

AK-cells with attached knowledge-weight as the users' reference.

solution-weight *w2.1,1* = 0.7, therefore the solution *s2.1,1* will not be deleted by the system. There is one definition worth to memtion here, the growth-factor, in definition 1-6, is introduced to convert the linear structure into a hierarchical structure of discussion-issues posted on the forum. The hierarchical structure helps our learners decide on different important positions, the learning-issues posted on the forum must not appear as a linear structure on the separate pages on the web site, but as hierarchical on demand. The growth factor normally is set up before discussion; however, it can also be changed after discussion if the educator wants to view the forum from a different angle. If the growth-factor has been set to 3 then the decision tree will be turned into three AK-cells on the top level and become a three-branch tree; if it has been switched to 5 then the decision tree will be turned into five best AK-cells on the top level for the learning decision and become a five-branch tree; if set up as one AK-cell then there is only one best decision to be made and become a linear-tree.

*2.1* obtained from the discussion and it forms the basis for MALESAbrain's knowledge

*kq* is set to "2" (see Fig. 3).

*sm* is set up as "4.2" and the solution-

*sd* is set up as "-3" and the

*kr* is set up as "-3.2" and the knowledge-weight *w2.1*=2.1, therefore

*2.1*) in the

This value of 2.1 represents the weight (*w2.1*) of the knowledge-content (

judgment capability. In the example the qualification threshold

**5. Using MALESAassessment in a test** 

*K2.1* will not be deleted. The *solution maturity threshold*

to solve the problem *p2.1*. The *solution disagreement threshold* 

on 

*AK-cell rejection threshold*

(troubleshooting plan) and thinking processes (log file) will also be recorded in the system to help educator in marking.

Fig. 13 shows the assessment interfaces in MALESAassessment. The CBR expert system consults the learners when making their troubleshooting-plans for answering the test. There are four screens or interfaces for consulting the learners to arrange their troubleshooting plans. First, the "*Inquiry"* screen can enter clients' query problem. Secondly, the "*consultation"* screen will offer the advice. Thirdly, the "*attention"* screen can help clients pay attention to their chosen cases/AK-cells. And the last/forth "*plan"* screen will help the learners make their problem-solving plan.

Fig. 13. The interfaces of assessment model in MALESAassessment.
