Essay on Automated Essay Grader

Writing is recognized as a critical skill in business, education and other layers of social engagement which not only describes the subject matter; but also increases the ways of writing components. At the time of thinking professor grading papers, teachers can imagine a dark room illuminated by a single fluorescent lamp that’s been pushed back to the farthest corner of a desk by an expanding clutter of papers. This is somewhat a mixed-up of papers that is used to be reviewed for assessment purposes (Shermis, Mark D., Sue Lottridge, and Elijah Mayfield, 2015). This may just be an image developed by movies, wherein it is believed that grading a massive stack of essays would be rather stressful and overwhelming. Thus, because of this aspect people are constantly striving to find easier ways of doing things. Hence, in many cases, automated essay graders have been adopted because it is a helpful tool for teachers to find out the efficiency level of essay writing. Further, it is also unbelievable that professors, at a college level, should use these grade systems when giving a final grade on a student’s paper, but rather, the tool can be useful during the writing process for the students and as an added tool when grading papers (Powers, Donald E., David S. Escoffery, and Matthew P. Duchnowski, 2015).

Automated essay graders are unable to grade based on ideas, and this restrains the professor from being able to understand what their students' thought processes are like and what they need help with. Although AES should not be depended on when giving a final grade, AES should be used as a tool during the grading process. Automated essay scoring can save a professor time when grading a large amount of papers, and can allow a professor to focus on grading based on the student's “voice” rather than their grammar and sentence structure. Finding reliable and efficient ways to assess writing highly increases the standard of test writing components and it also generates new tools for computer formats (Ng, Sing Yii, et al, 2015). The software uses algorithms for the purpose of measuring more than 500 text-level variables which also yield scores and feedback regarding the writing quality. Using such tools can assist the teacher in diagnosing the information on each writer give them more time to address problems and assist students in comprehending things that can be managed without machines such as content, reasoning and writing.

The method of assessment should always be judged on the basis of validity, fairness and reliability. Therefore, any instrument can be termed as valid if it actually measures the trait that is significant to measure. It has been observed that teachers are turning to essay grading software to critique student writing; however, at the same time, it also aids them in critiquing serious flaws in the technology (McNamara, Danielle S., et al, 2015). Although automated essay grading is a useful tool for both the professor and the student during the process of writing. However, at the time of perfecting an essay, the professor should give the final grade on a paper after they personally evaluate the student’s work. The AES system has shown to be in the early stages of its grading abilities focusing primarily on grammar, sentence structure and style, and word count. Because of its lack of algorithms composed to create this tool, automatic essay graders lack the ability to grade based on the student's thought processes and logic behind the ideas that they portray in their work.

It has also been analysed that the AES program instantly produces a high-scoring grade. While writing an essay, it is essential for the writer to hold the importance of meaningful sentences so that the writing can be evaluated accordingly (Hoang, Giang Thi Linh, and Antony John Kunnan, 2016). This sentence needs to use proper grammar and structure and it should also hold appropriate meaning. Hence, with the help of a grading system, teachers can look into all these matters so as to evaluate the capability of students. Therefore, the instructor of the class should still be required to evaluate the student's work when using an automated essay grader. It is also explored that those who use standard feedback methods without automated scoring spend more time in discussing spelling, punctuation, grammar and capitalization. Several researchers have established that computer models are highly predictive and that gives an idea about the capability of humans to score good marks in writing (Cummins, Ronan, Meng Zhang, and Ted Briscoe, 2016).

In addition to this, it has also been analysed that the benefits of automation are great when considered from an administrative viewpoint. If computer models provide acceptable evaluation and feedback, they help in reducing the amount of needed training for human scorers. Another reason for which the AES programs are used is that in this tool, the instructor can understand their student’s thought processes. If the professor of an English course does not take the time to read any of their student's work and only knows the grade that the AES program spits out, how will they know what their students need help understanding? Although some students will talk aloud in class and present their ideas, allowing the professor to assume where they stand in the class and their progression throughout the course (Buzick, Heather, et al, 2016). The AES program is not able to inform the professor what their students’ ideas are, the professor should find that out through evaluating the student’s work. The automated assessment helps the teachers in providing valuable feedback to the students and through this, they can adopt new measures for improvement. Further, students can also reinforce and demonstrate the principles and rules of writing. This is highly essential for developing the writing skills of a writer and at the same time, the efforts of teachers can be reduced due to automated assessment methods. Valuable feedback can also help the students to become more competent (Barrett and Catherine, 2015).

A benefit of using this tool is the instant results that the students can receive from the teachers. Rather than waiting to receive feedback roughly a week later when the class has moved on and the student’s ideas are not fresh in their head. This allows the students to write more frequent practice essays while still being able to track their progress. It can be difficult for an instructor to assign essays as frequently as one to two a week because of the strenuous grading. With the AES tool, students can practice writing properly structured essays without having to focus on only writing a few essays (Zhang, Mo, Jing Chen, and Chunyi Ruan, 2015). The system is also accurate in predicting human scores by applying a fairly simple scoring method; hence this could be deceived by students who get higher grades in longer essays. Automated essay scoring is highly useful for teachers because, through this, they can thoroughly analyze the content of the essay and at the same time, they can also organize their own schedule. This is also regarded as the best method of applying thorough understanding in essay writing.

Henceforth, the method is greatly recommended to English teachers because, through this, systematic use of quotations and punctuation can be identified. Moreover, it can also amend the practicality in analysing the large-scale assessments of writing ability. However, on the other hand, employing a human rater could be an expensive method in terms of time and resources. Thus, it is vital to include more than one rater in large-scale writing assessments. This can also reduce bias in individual scorers (Wilson, Joshua, and Amanda Czik, 2016). Automated ratings would surpass the accuracy of the usual two judges. The same tool has many weaknesses as well such as it highly stresses the lack of human interaction as well as the sense of the writer while writing the essay. Another criticism is based on objections; hence that is the major reason computer count variables are considered less important.

References

• Barrett, Catherine M. "Automated essay evaluation and the computational paradigm: Machine scoring enters the classroom." (2015).
• Buzick, Heather, et al. "Comparing Human and Automated Essay Scoring for Prospective Graduate Students with Learning Disabilities and/or ADHD."Applied Measurement in Education 29.3 (2016): 161-172.
• Cummins, Ronan, Meng Zhang, and Ted Briscoe. "Constrained Multi-Task Learning for Automated Essay Scoring." Association for Computational Linguistics, 2016.
• Hoang, Giang Thi Linh, and Antony John Kunnan. "Automated Essay Evaluation for English Language Learners: A Case Study of MY Access."Language Assessment Quarterly (2016): 1-18.
• McNamara, Danielle S., et al. "A hierarchical classification approach to automated essay scoring." Assessing Writing 23 (2015): 35-59.
• Ng, Sing Yii, et al. "Automated Essay Scoring Feedback (AESF): An Innovative Writing Solution to the Malaysian University English Test (MUET)." (2015).
• Powers, Donald E., David S. Escoffery, and Matthew P. Duchnowski. "Validating Automated Essay Scoring: A (Modest) Refinement of the “Gold Standard”." Applied Measurement in Education 28.2 (2015): 130-142.
• Shermis, Mark D., Sue Lottridge, and Elijah Mayfield. "The Impact of Anonymization for Automated Essay Scoring." Journal of Educational Measurement 52.4 (2015): 419-436.
• Wilson, Joshua, and Amanda Czik. "Automated essay evaluation software in English Language Arts classrooms: Effects on teacher feedback, student motivation, and writing quality." Computers & Education 100 (2016): 94-109.
• Zhang, Mo, Jing Chen, and Chunyi Ruan. "Evaluating the Detection of Aberrant Responses in Automated Essay Scoring." Quantitative Psychology Research. Springer International Publishing, 2015. 191-208.

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