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Affective states, a dimension of attitude, have a critical role in the learning process. In the educational setting, affective states are commonly captured by self-report tools or based on sentiment analysis on asynchronous textual chats, discussions, or students’ journals.
Drawbacks of such tools include: distracting the learning process, demandin...
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... resulted in 28 datasets to feed into the text mining and sentiment analysis algorithms. This process is illustrated in Figure 1. ...
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... identify the correlation between neutral sentiments and performance we applied the VADER tool to extract neutral sentiments (cv =0). The regression plot of the frequency of neutral sentiments vs performance is presented in Figure 14. In this figure, the horizontal axis is the frequency of the neutral sentiments, and the vertical axis is the performance. ...
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... subjectivity level vs. performance score is plotted in Figure 15, where the vertical axis is the performance score, and the horizontal axis is the subjectivity score. ...
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... scatter plot of the frequency of the unigrams in the negative sentiment vectors (cv<0) (Figure 16) shows the most frequent token in negative sentiments is the word "wrong". And finally, it is worth mentioning that we did not find a statistically significant correlation between vectors with cv <0 and the performance score in this study. ...
