## 6 Discussion and Conclusions
### Theoretical Contribution  
The results of this research can be used by many: educational institutes, teachers, publishers, researchers, and students. YouTube is used as a learning tool by many prestigious educational institutes such as MIT and Berkley, which is a wake-up call for other educational institutes. As such, this makes YouTube an established venue. Competition among educational YouTube is the way to perfection, which is reflected in the number of views. Publishers in the future may accompany each published book with a YouTube video, much like PowerPoint slides. Based on the findings of this research, students value the credibility of the source very much. Hence, the publisher's YouTube channels will be more attractive to students than others. Content quality and accuracy are much needed aspects on YouTube, where source credibility is an essential factor. As the number of views on YouTube may work as a source of income, YouTube may pay more attention to their delivery style. Information language (IL) is an important factor. As a result, many may deliver knowledge to knowledge seekers via YouTube. Still, according to this research, such a hypothesis was not supported. In fact, the research indicated, in Table 6, that SC correlated the least with IL, and correlated the highest with AIQ, IQ, and IA. Hence, there is a high correlation between SC, IQ, and IA. On the other hand, the least correlated, according to this research finding, is the credibility with IL. The H1 hypothesis, which reflects the impact of SC positively influencing IU is supported, hence agreeing with the findings of [35] as well as [34; 54; 55; 57]. SC ranked as \"high\" in Table 3.  
The H2 hypothesis, which reflects the impact of information language (IL) positively influencing information usefulness (IU) was not supported, hence disagreeing with the findings of [35; 36; 37; 38; 39]. IL ranked as \"moderate\" in Table 3.  
The H3-H5 hypotheses, which reflect the impact of IIQ, CIQ, and AIQ positively influencing IQ, were supported, hence agreeing with the findings of [34; 35; 40]. AIQ and CIQ ranked as \"very high\", while IIQ ranked as \"high\" according to Table 3.  
The H6 hypothesis, which reflects the impact of information quality (IQ) positively influencing information usefulness (IU), was supported, hence agreeing with the findings of [34; 35; 40]. IQ ranked as \"high\" in Table 3  
The H7 hypothesis, which reflects the impact of information usefulness positively influencing information adoption (IA), was supported, hence agreeing with the findings of [16; 34; 35]. IU ranked as \"very high\" in Table 3.  
The H8 hypothesis, which reflects the impact of information adoption (IA) positively influencing academic achievement (AA), was supported, hence agreeing with the findings of [4; 8; 9; 10; 34; 35; 41; 42]. IA and AA both ranked as \"high\" according to Table 3.  
As for the moderating variables, age, gender, education level, and previous experience, these are shown in hypotheses H9-H12. There is a significant difference in the information adoption (IA) that can be credited to gender, that goes for males more than females. This research used a \(t\)-test in Table 8, and the results, shown in Table 8, agreed with the findings from [47; 48; 49; 50; 53; 64]. There is a significant difference in the information adoption that can be attributed to age. This research used the ANOVA test, shown in Table 9, and multiple comparisons analysis, shown in Table 10; the results agreed with the findings from [47; 50; 51; 52; 53]. There is a significant difference in the information adoption that can be credited to age and education level. This research used multiple comparisons analysis, shown in Table 11, and the results agreed with the findings from [46; 52; 65]. There is a significant difference in the information adoption that can be credited to previous experience. This research used multiple comparisons analysis, shown in Table 12, and the results agreed with the findings from [6].