# Assessment of a Location-Based Mobile Augmented-Reality Game by Adult Users with the ARCS Model
## 3 Results  
The questionnaire was designed with 31 items with an acceptable reliability score of 0.97 (Cronbach alpha). The mean value of participants' responses per question for each one of the A,R,C,S factors was calculated by dividing the sum of the Likert scores (ranging from 1 to 5) for each question by the total number of participants (Table 3 and Figure 1). Figure 1a shows the average mean score (on the Likert scale) and the standard deviation of all participants for the eight questions that belong to the Attention factor, before training (lower row) and after training (upper row) with the diameter of each ball being proportional to the standard deviation. The factor of Attention improved for all the questions after training in the game. Additionally, the standard deviation of the answers is higher after game training, indicating that there was greater heterogeneity and variability in the values of participants' answers after training. These results show that participants were highly satisfied with the training of the game. The largest statistically significant difference observed in the questions contained in the factor of attention was between the age groups 20-35 and 52-60 (the test statistic was \(-2.4879\), with \(p\)-value 0.006306, which was statistically significant (\(p<0.01\))). In questions R1, R2, R3, and R6, answers before and after training are highly similar, while in questions R4, R5, R7, R8, they are less similar (Figure 1b). Considering also that there is no noticeable difference in the standard deviation of the answers before and after the game training, it follows that the training did not affect participants significantly in terms of Relevance of the ARCS model. Further, from the responses to questions C1, C3, C4, and C7, it can be seen (Figure 1c) that there is a great overlap of answers before and after training while in questions C2, C5, C6, C8, there is less overlap of participant answers. Additionally, as the standard deviation of question C5 is smaller there was smaller heterogeneity and variability in the values of participants' answers after the training. These results show that training did not affect participants in terms of the factor of Confidence from the ARCS model. Figure 1d shows the average mean score and the standard deviation of all participants for the seven questions that belong to the category of satisfaction before training (lower row) and after training (upper row). We can see that the factor of satisfaction was improved for all the questions after the game training. Additionally, the standard deviation of the answers is about the same after training of the game. These results indicate participants were highly satisfied with the training of the game pointing to the fact that training improved their \"satisfaction\" in the ARCS model. The largest statistically significant difference observed in the questions contained in the factor of satisfaction was between the age groups 20-35 and 36-51 (test statistic \(-1.90892\), with \(p\)-value = 0.01956, which was statistically significant at the level of statistical significance (\(p<0.05\))). The response from the post-test feedback shows that there were high levels of motivation in terms of Attention (A) with mean score 3.42, Relevance (R) with mean score 3.41, Confidence (C) with mean score 3.52 and Satisfaction (S) with mean score 3.28. Concerning all four factors of the ARCS model, we see that responses to questions A5, R7, C5 and S2 yielded the highest differences before and after game training. An interesting picture is revealed with respect to age differences (Table 4, Figure 1). The scores for the factor of Attention were higher for the age groups 20-35 and 36-51 after the training session, so the participants' Attention (as measured by questions corresponding to the ARCS model) improved after the training.