## 5 Discussion  
This research aims to answer eight research questions (RQs) explained earlier. Regarding RQ1 (Is there any significant difference in terms of the engagement index measured using EEG signals between the non-tailored game mode and the tailored game mode? ), two comparisons were performed to analyze the engagement index in the two game modes: tailored game mode, and non-tailored game mode. In terms of the Unicorn sensor, contrary to expectations, the non-tailored game mode reported the highest mean engagement index (mean = 6.297, standard deviation = 11.274). Additionally, the statistical analysis revealed that there was a significant difference in the engagement index between game modes using the Unicorn sensor to collect the EEG signals (\(p\) value = 0.04054). Conversely, with regard to the Bitalino sensor, the tailored game mode achieved the highest mean engagement index (mean = 3.619, standard deviation = 0.551); nevertheless, the statistical analysis concluded that there was no significant difference in the engagement index between game modes using Bitalino sensor to collect the EEG signals (\(p\) value = 0.3884). Furthermore, both sensors achieved the highest engagement index values in the non-tailored game modes (Unicorn: 57.638; Bitalino: 6.340). Figure 19: Participants’ opinions on game response time to the commands in game modes using the Bitalino sensor. Figure 20: Participants’ opinions on entertainment in game modes using the Bitalino sensor. Focusing on RQ2 (Which game mode is the favorite? ), most participants agreed that the non-tailored game mode was their favorite game mode, irrespective of the EEG sensor used to obtain the engagement index (Unicorn sensor: 57.58% of the participants, Bitalino sensor: 60% of the participants). Furthermore, it is important to remark that a chi-squared test revealed (\(\alpha\) = 0.05) no significant association in terms of \"favorite game mode\" between the EEG sensors used to collect the EEG data to process the engagement (Bitalino, Unicorn) and the game modes (non-tailored, tailored); \(p\) value = 1. With respect to RQ3 (Which game mode is the easiest to play? ), the majority of participants selected the tailored game mode as the easiest game mode to play, irrespective of the EEG sensor used (Unicorn sensor: 60.60% of the participants, Bitalino Sensor: 55% of the participants), i.e., they ranked the tailored game mode with the highest score (a score of 1) in terms of the ease-of-play Likert scale (1: easy, 2, 3, 4, and 5: hard). Additionally, [PERSON]'s exact test (\(\alpha\) = 0.05) revealed a significant association between the game modes (non-tailored, tailored) and the ease-of-play variable in the Likert scale values (1, 2, 3, 4) when the Unicorn sensor was used to collect the EEG data for processing the engagement (\(p\) value = 0.009341). In the case of RQ4 (Which game mode is the least frustrating to play), similarly to RQ3, over half of the participants ranked the tailored game mode with low frustration rates (scores of 0 and 1) on a Likert scale (0: nothing; 1, 2, 3, 4, and 5: high), irrespective of the EEG sensor, i.e., 75.75% of the participants that used the Unicorn sensor (a score of 0: 36.36% of the participants, and a score of 1: 39.39% of the participants) and 55% of the participants that used the Bitalino sensor (a score of 0: 50% of the participants, and a score of 1: 5% of the participants). Moreover, [PERSON]'s exact test (\(\alpha\) = 0.05) revealed a significant association between the game modes (non-tailored, tailored) and the frustration variable in the Likert scale values (0, 1, 2, 3) when the Unicorn sensor was used to collect the EEG data for processing the engagement (\(p\) value = 0.0466). Focusing on RQ5 (Which game mode is the least boring to play?