Technology plays a crucial role in fully understanding all aspects of language and uncovering the hidden patterns, such as sense and emotion density in texts. Yet, it seems that remarkable attention has not been paid to the sensory and emotional loads of learning texts as them primary source of learning. This study attempts to present an objective way of analyzing English learning texts from both emotional and sensory perspectives to provide material developers to measure the emotional and sensory loads of the texts. For this purpose, a new kind of software was developed using two datasets; Sensicon and EmoLex. Then as an example, an English course book series, Interchange (5th ed.), was analyzed by this software to determine any probable pattern(s) concerning sensory and emotional loads. The results showed that the dominant sense in these books is hearing at all levels of language proficiency. In the emotion analysis part, the eight basic emotions were categorized as positive and negative emotions, and the results showed a higher frequency of positive emotions. It was also found that the frequency of negative emotions increases at higher levels, resulting in more authenticity

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