ai written essay checker
The Role of AI in Written Essay Checking: Enhancing Accuracy and Efficiency
In order to improve student independent writing abilities and enhance the reliability and objectivity of essay assessment, we adopt computer-aided essay assessment technology that can provide immediate and comprehensive comments on essay writing. The proposed technology is a formative assessment tool used to assist the teacher in evaluating student essays by providing automated support on prescribed features of writing, based on a learning objective specified by the user. The technology enables prompt and thorough feedback to be presented in a manner that is consistent with undergraduate education. The process of using essay checking used in this research is not the same as automated scoring engines that assign permanent scores to texts or suggest inappropriate use in high-stakes contexts, such as the evaluation of Common Core Summative Assessment tests. Our tool has been designed to enable and encourage student self-assessment through process writing against all provided objective tools in order to sensitize students to their writing flaws and to encourage them to submit only polished essays for actual grading in the classroom.
In a modern education setting, teachers are confronted with the task of managing large classes where feedback on student essays is a labor and time-consuming process. To minimize the pressure on teachers and make the education process more effective, many AI systems have been introduced to provide assistance, including assessment of student essays using machine-learning knowledge. The role of AI is non-evaluative, which signifies that student-generated content is never graded by the system itself. Instead, the program simply points out possible problems and suggests material that the student can use to revise their work. It is essential that students grapple with prescribed matter posed for the question under consideration, just as they would in any written examination. Such essays can then be assessed by the teacher or a human counterpart acting as the suturing agreement for the cloud-based e-assessment setting. The current process involves AI performing word-checking features, grammar-checking features, and Field-Specific Word Removal Features using semantic knowledge. The usage of these features enhances the accuracy and efficiency of the solution.
The most significant benefits of using AI-based solutions to check written essays are about enhancing the accuracy and diminishing the limitations related to subjectivity in human grading, providing direct, immediate, and invaluable feedback to writing students, and offering more efficient and less monotonous essay checking to modern educators. This way, the competitiveness in education is increased. The need for teachers, pedagogical support staff, and educated native English volunteers is directly reduced. Abolishing distance-related economic costs, which limit equal opportunity to quality education for all, is achieved, and e-learning delivery of essay checking is enhanced. The education level of both students and teachers can be increased with fewer implementation costs. Furthermore, the AI methodology can guarantee the consistent scoring of lengthy responses. Mean scores related to long narratives are less reliable, but long written essays have more reliability. Thus, via the more reliable increase of the English language examination test length, what is also promoted is the power of the writing construct measured.
In recent years, with the increased use of online software applications in education, the automatic checking of written essays has become more common. Up to now, human teachers and educators have been responsible for essay checking, which is a time-consuming and labor-intensive task. Some of the practical problems, especially related to distance education where the teacher-student ratio is high, are severe and critical. Two high-priority problems are grading fairness (all students submit their assignments electronically in digital form, but some teachers still hold a bias towards students submitting handwritten forms in their grading) and grading efficiency (many of the same tasks are repeated over and over by the teacher). With few exceptions, the answers to these problems lie in the heart of the implementation of artificial intelligence methods for written essay checking, which can offer a variety of attractive solutions.
Furthermore, researchers and developers should not lazily rely on off-the-shelf NLP and AI models, but have the model under audit and improvement at all times based on usage and literature review findings.
Current grammatical error correction models have limitations such as not being able to identify the true spatial boundaries of expressions, analyze the semantics at the sentence level based on words, integrate adjacency information on similar errors, and automatically identify writing issue locations. The analysis of the identified limitations shows that much more future work needs to be dedicated to considering each and every point and segment of the issues that were missed or misdirected during the development of the AI and NLP-supported writing correction model.
The task of checking written essays is challenging, as it requires an understanding of the students’ writings and an awareness of the writing issues assessors pay attention to. Moreover, modern students do not compile essays based on accurate grammar and vocabulary only, but rather carry out research and maneuver between different perspectives, viewpoints, and keywords.
In reality, checking written essays and giving explanations of writing issues are complex tasks, and these tasks demand not just having correct grammatical rules, but also having the use of more sophisticated sentence analysis. In this section, the complexity of the task of checking written essays and the limitations of the current grammatical error correction models in the existing AI and NLP works are discussed.
One of the best practices for instructors or developers of next generation English language learning technology is to educate administrators to improve policies about ethical use of AI, particularly when dealing with issues of student privacy in schools or in social media. Wrap-around of learning can soak up some educational effect that students might not otherwise realize, but posing ethical AI literacy will never produce policy resistance to misuse. Unlike teaching people, good education about educational technologies can even provoke technocratic power and problem-focused leaders into policy adaptation and technical facility for interested epistemic reflection on self and society. Educational written essay-checking AI does not just provide upfront educational benefits. Two educational argumentation essays might generate inherently machine-distorted shareable reflective discussions on argumentation itself. With their own opinion their guiding light, students could define behaviors an AI should abide by, demonstrating computational thinking with respect to their subjective opinions.
Integrating an artificial intelligence essay checker can bring benefits to English language arts teachers and to English as a second/foreign language instructors and their students when such functional AI thoroughly complements human performance deficiency. This chapter lays out implications for LELT product developers to define and enhance strengths, since a given AI system is physically adept to deliver value derived from human experience and discovery. This chapter also explicates LELT system users on helping them understand when an AI system is misapplying or malengineered so that educators can focus on correcting software detector-annotational bias or error.
Future writing AI innovations are also seen in summarizing longer and complex pieces and in generating a more natural and coherent summary with logical progression and bridging of ideas. The future teaching assistant design is likely not to be constrained to Ivy Leagues and will offer services for free. It would bring educational opportunities to everyone, with affordable and accessible tools. Course lectures, presentation slides, and textbooks can be transformed into a valuable package for learners. Researchers aiming to gain knowledge from the technical content of a research article structured in a coherent format would greatly benefit from the involvement of these advanced technologies. With all technological capabilities, researchers from all backgrounds and levels will have easy access to knowledge embedded in specialized technical layers.
The future trends and innovations in AI technology for writing are highly dependent on problem solving. Not limited to being an essay writer, research could lead to the design of ‘the teacher.’ It could also make life easier for scientists. Text or whole essay summarization by different AI tools is one way to help out many people besides language learners. In fact, there will be a significant increase in the number of people using the new summarization tools in the future. Artificial neural networks and deep learning will continue to grow significantly to evolve human language solution. Language learning and communication will be more fun to learn from technology. Learners can communicate easily with an individual, a group, a bot, a teacher, or a system. Synergy and collective intelligence of computer and human can work together, harmoniously and effectively.
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