# Evaluating Learner Engagement with Gamification in Online Courses
## 6 Results  
This section analyses the gamification data collected during the experiment. First, we report on how the individual player profiles changed in the DynamicAG experimental  
Figure 5: Top: _GE Displays_ are collected using clicks on the button _1 want an award_. Bottom left: _GE Clicks_ are monitored using clicks on the GE, while _Evaluations_ refer to the scorings of each displayed game element using stars. Bottom right: _Dashboard Clicks_ refer to those clicks made in the dashboard window. group. Recall that the player profile did not change in the StaticAG control group. We analysed the evolution of the player type, computing the difference between the player profile at the beginning and at the end of the course. We observed that the player profile changed in 40% of the participants (18 out of the total of 44). In fact, these differences were very small. Note that this value is greater than a maximum double-precision error, \(10^{-16}\), with the highest being \(8.27\times 10^{-05}\), but they are relevant enough to change the GE Probabilities associated with each Game Element (see Step 2 in Figure 1). Consequently, these changes had an impact on the selection of Game Elements in the DynamicAG group and thus, the overall experience of the students in this group. Specifically, these dynamic changes in players' profiles occurred in participants with a high number of interactions and a high average time spent with the gamified experience. Figure 6 presents a comparison of the _Dashboard Clicks_ values between the StaticAG (blue bars) and DynamicAG (orange bars) groups. On the left, the histogram shows that the majority of the users in the StaticAG group interacted less with the Dashboard (all the values are between 0 and 10 clicks), while users in DynamicAG were more active in using the dashboard. Indeed, the comparison of the means (right side of the figure) confirms that the difference is significant (Brunner-Munzel test, \(p\)-value = 0.040 \(<\) 0.05; [PERSON]'s d = 0.5821). In relation to the dispersion in _Dashboard Clicks_, we analysed the data thoroughly and realised that it corresponded to students who played games regularly, suggesting that this element may have been familiar to them and that they were therefore more inclined to visit the dashboard. Figure 7 presents a between-group comparison of the _GE Displays_ between groups. The figure shows the same trend as the previous one. Note that the display of the GEs requires the users to claim a reward by selecting the _\"I want an award\"_ button (see on left side of Figure 5). Even though this button was equally available to both groups, the DynamicAG group was more engaged and participants in this group demanded awards more frequently. In fact, a comparison of the means (right side of the figure) shows a significant difference (Brunner-Munzel, \(p\)-value = 0.031749 \(<\) 0.05 ;[PERSON]'s d = 0.7175, between medium and large effect size). Figure 6: Comparison of _Dashboard Clicks_. Left side: histogram. Right side: the mean of the number of clicks and the variance of all students in each group. _\"#_ users” means number of users  
Figure 7: Comparison of _GE Displays_. Left side: histogram. Right side: the mean of the number of the game elements shown and the variance of all students in each group. _\"#_ users” means number of users. Game elements are not only aesthetically appealing but are also interactive since they allow students to get rewards, e.g., the lottery, the gift, or sending a tip to work-mates. Figure 8 presents the average number of users' interactions with game elements during the whole experience (\(GE\)_Clicks_). The distribution of orange bars along the entire \(x\) axis indicates that students in the experimental condition (DynamicAG) interacted more with game elements than those in the control condition (Brunner-Munzel \(p\)-value = 0.011 \(<\) 0.05; Cohen's d = 1.0001 large effect size). However, this metric gives low values in both conditions, which can be explained by the discoverability of the designed elements [49].