# An e-Learning Toolbox Based on Rule-Based Fuzzy Approaches
## 4 Results and Discussion
### Introductory Course
#### 4.2.5 Using the Toolbox in the Next Course  
The models developed and validated for the introductory course using data from students who had taken the course in previous editions, were analyzed, and used by five teachers in the new edition of the same course.  
As in the previously analyzed course, the Time 1 model, due to the fact that the course has just started, does not provide useful knowledge for the teachers who are carrying out the new edition of the course. However, Time 2 model is very useful for teachers. Firstly, analyzing the rules, it is concluded that it is possible to predict quite accurately (MSE of 0.15) the final grade of the student using only homework 2 (H2), independently of the grade the student had obtained in homework H1. The five teachers involved in the course were very surprised about this. They considered the H1 assignment to be important in the learning process and decided that they would study how to make it more relevant, both in content and in its role in the final grade formula. Secondly, they decided to send an e-mail to the cluster of fail students, offering them a review and questions class regarding the H2 task. It is important that students understand very well the concepts associated to H2 in order that they can consolidate the knowledge of the rest of the course, since in Time 3 model H2 feature still is a key factor of students' learning behavior. Notice that in model 3, the mark of the co-evaluation (COEV) plays also an important role. Teachers, at this point in time (third month from the beginning of the course),  
\begin{table}
\begin{tabular}{l l l l} \hline \hline \multicolumn{4}{l}{**Analysis of the course evaluation process (ACEP)**} \\ Relative Relevance of the FIR model features: COEV = 0.55; FRDP = 0.45 & \\
**Understanding students’ learning behavior (USLB)** & & \\ Rules & Sens. & Spec. & Acc. \\ _if_ FRDP is low _then_ MARK _is_ Fail & 1 & 1 & 1 \\ _if_ FRDP is high _then_ MARK is Excellent & & 0.94 & 0.79 & 0.87 \\ _if_ COEV is high _and_ FRDP _is_ medium _then_ MARK _is_ Excellent & & 0.40 & 0.96 & 0.90 \\ _otherwise_ MARK _is_ Pass & & 0.40 & 0.96 & 0.90 \\
**Macro-average precision:** 0.78; **Micro-average precision:** 0.86 & & & \\ \hline \hline \multicolumn{4}{l}{**Assessment of Students’ Learning Performance (ASLP) and Grouping of Students’ Learning Behavior (GSLB)**} \\ Mean Square Error: 0.025 & Clustering: Fail 9/9; Pass 2/5; Excellent 15/16 & & \\ \hline \hline \end{tabular}
\end{table}
Table 10: ACEP, USLB, ASLP, and GSLB toolbox results for the model 4 of the introductory course. The MARK variable was discretized into three classes: fail (from 0–60), pass (from 61–80), and excellent (from 81–100). COEV was discretized into three classes: low (from 0–6), medium (from 6.1–8.9), and high (from 9–10). FRDP was discretized into three classes: low (from 0–20), medium (from 21–30), and high (from 31–40). Spec., Sen., and Acc. stand for specificity, sensitivity, and accuracy, respectively.  
decided to give a stricter follow-up to students who obtained low evaluation in the H2 homework. A weekly message is sent to the students asking them to report the work done that week. The rules model at Time 4 tells us that if students do a good job in the final report of the didactic problem (FRDP) they will pass the course. Therefore, the objective of teachers is to try to ensure that students carry out a continuous and quality work in the rest of the tasks that remain to finish the course, and for that reason they propose a more personalized follow-up measure to this cluster of students.  
Finally, the five teachers of the current course analyzed the fact that homework 3 (H3) was not relevant in the prediction model. They considered that this task was just as important, from the point of view of knowledge acquisition, as H2, and that, therefore, they should study how to give it greater weight in the final grade. Notice that at any time students can consult the prediction of their final grade, in order to be aware of their learning behavior.