You are an AI essay evaluator. Your ONLY allowed response is exactly in this format: 'Your evaluation score is: {score}'. Do not write anything else. Do NOT provide any feedback, comments, or explanations. Do NOT write <think> tags or any other meta text. Do NOT write any information before or after the evaluation. Your entire output must be a single line of plain text strictly following the format: Your evaluation score is: {score}. You must not deviate from this format under any circumstances. Given essays are evaluated according to the following criteria: content relevance and development, vocabulary usage and appropriateness, grammar correctness and sentence completeness, as well as spelling, punctuation, and capitalization accuracy.
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In "Making Mona Lisa Smile", the use of Facial Action Coding System technology to read the emotions of students ina classroom is valuable. This is shown through the author's description of the benefits of being able to read expressions of students, as well as the increased understanding of emotions that can be uncovered due to this technology. Recently, Prof. Thomas Huang and his colleague have developed ways for computers to better communicate with humans through a program designed to calculate noverbal human emotions. This technology has proved able to recognize expressions of humans, and so has expanded the frontiers of human communication with technology. In particular, this advancement could provide benefits in the education system. The reading of expressions in studnets would prove beneficial to the educational process of understanding what content best suits a student's learning ability. Dr. Huang predicts, "A class Room computer could recognize when a studnet is becoming confused or bored... Then it could modify the lesson, like an effective human instructor" (D'Alto 6). This shows how the technology would allow a computer to effectively "recognize" a students emotions, and correlate or "modify" the corresponding lesson to better fit his or her learning. It would provide an "effective" tool for intructors to be able to better understand what their student needs in order to succeed. Expressions or feelings such as "confusion" or being "bored" would allow teachers to better invest time and effort in teaching topics that best fit with these emotions, and so it would help make teaching easier in response to the needs of students. The technology would also continue to increase knowledge of human emotions through interpretation of the many expressions such as nonverbal communication. In turn this would help with the education of students, as an increased understanding of human feelings would allow the system to acknowledge issues or needs that specific students have. Being able to match their emotional abilities with the best subject for them to succeed in would be an option. This would provide teachers with a system that best maximizes potential and limits issues in the classroom that involve expression or emotion. D'Alto writes, "Eckman has classified six basic emotions - happiness, surprise, anger, disgust, fear, and sadness - and then associated each with characteristic movements of the facial muscles" (D'Alto 3). From this we can see that if implemented, this technology could help identify primary human emotions such as "happiness" or "anger". This would allow computers to identify "characteristic movements" and translate this into emotion. With this technology at our disposal, we can better understand how people in general portray their feelings through the anatomy of their face, and better understand the identity of these emotions in the physical aspects of expression. This understanding would in turn allow students and teachers to better understand their emotions, and so best match their tendencies to educational programs or classes. Continuing with the idea of better understanding emotions in the technology would also prevent issues relating to student behavior such as academic honesty or problems with stress or anger, as understanding the emotional expression conveyed by students would help implement systems to better prevent these unwanted actions. For instance, the author writes, "But in a false smile, the mouth is stretched sideways using the zygomatic major and a different muscle... To an expert, faces don't lie; these muscle clues are sometimes used to spot when a "smiling" politician or celebrity isn't being truthful" (D'Alto 8). This is an example of the increased benefits of this technology, and particularly pertaining to education, it can be used to detect whether students are being honest or "truthful" through their expressions. Although it is not guaranteed, the technology would still provide another option in understanding what studnets feel or what they are truly going through. It would allow schools or instructors to change their teaching or development programs in order to relieve studnets of unwanted emotion, and it would also help benefit the disciplinary system, as being able to detect true emotions could help distinguish one issue from another. Overall and in conclusion, a better understanding of human expression by technology provides an improved tool for instructors to help with the learning and development of students, as this allows them to fit learners' studying emotional tendencies with that of the best option or way of teaching.
user
Your evaluation score is: 3.0
assistant