## 6 Discussion
### RQ2: What Is Its Influence in the Students' Self-Perception of Their Knowledge Acquisition? To answer this research question, we evaluated the subjects' answers to questions P2.1 to P2.4. As it can be seen in Table 3, in general, the subjects using the novelette show a better self-perception of their knowledge acquisition than the Eg, or there is no statistical significance between the results of the two groups. Analyzing the differences between the two groups globally (i.e., applying no filter), the novelette tends to be graded better overall. More specifically, the differences in P2.2 (\"I know what kind of tools I should use to start exploring a system.\") and P2.3 (\"I know what kind of tools I should use to protect my systems.\") can be considered as statistically significant. Regarding P2.2, the Eg has a significantly lower mean and higher variance than the Ng (Eg: mean = 3.80, std = 0.79; Ng: mean = 4.08, std = 0.61). These differences are even more remarkable in the category of subjects older than 40 (Eg: mean = 3.58, std = 0.77; Ng: mean = 4.04, std = 0.47). Regarding P2.3, globally, the Ng subjects show a greater self-perceived knowledge on protection tools than the Eg (Eg: mean = 3.43, std = 0.87; Ng: mean = 3.90, std = 0.74). Differences are also particularly meaningful in the category of subjects younger than 30 (Eg: mean = 3.00, std = 1.00; Ng: mean = 4.00, std = 0.89) and the ones older than 40 (Eg: mean = 3.42, std = 0.77; Ng: mean = 3.91, std = 0.67). It is also noteworthy to see that approaching basic cybersecurity topics in a narrative manner is more effective for inexperienced students than for experienced ones. We can observe significant statistical differences between subjects without previous cybersecurity knowledge; meanwhile, the differences between the Eg and the Ng are not relevant for those that already know the theoretical basis on the area. The differences can be seen for those without previous knowledge in P2.2 (Eg: mean = 3.71, std = 0.80; Ng: mean = 4.11, std = 0.57), P2.3 (Eg: mean = 3.47, std = 0.80; Ng: mean = 3.93, std = 0.71) and P2.4 (\"I would be able to put into practice what I have learned.\") (Eg: mean = 3.53, std = 0.80; Ng: mean = 3.85, std = 0.92). Hence, the self-perception of knowledge acquisition is similar between the two groups. Nonetheless, the results show that the novelette can be a better tool as a starting point in the cybersecurity area. In this regard, the subjects without previous knowledge from the Ng sample answer more positively about being able to put into practice the learned concepts and their understanding on the tools described in the learning resources. This is particularly interesting considering that both learning resources (i.e., the novelette and the conventional expository learning resource) are written focusing on inexperienced technical readers, the general public, and also taking into account that cybersecurity is an eminently practical subject and the CompSec course is mainly taught and graded through practical assignments. From this point of view, storytelling can be considered a better approach to start studying this subject. Again, the conclusions of this research question can be considered aligned with the previous literature, further justifying the introduction of fiction as study materials, when the educational design is sound. Many studies consider that a study of the motivational aspect also requires an assessment of student perception of acquired knowledge. Nevertheless, some of them stop at the attitudinal aspect, or just treat self-perception in very broad terms, such as \"prompting critical reflection\" (e.g., [31]). Even when this aspect is taken into account, it must be reminded that only a few make extra effort to compare it with classic learning methods, and qualitative results are seldom fine-grained or grounded on asking about very specific key topics in the curriculum, such as in our case. They mostly rely on a single generic question of the style \"Do you think the fiction helped you learn?\".