Reducing the Burden of Essay Grading
Concerns and Challenges of AI in Grading
Future Prospects of AI in Grading

Education is not an exception to the transformation of various industries by Artificial Intelligence (AI). Automated essay evaluation has emerged as a focal point among the numerous applications of AI in the classroom. Educators worldwide are utilizing AI-powered assessment tools to improve efficiency, streamline the evaluation of student assignments, and provide detailed feedback. Nevertheless, despite the potential advantages of AI, there are ongoing apprehensions regarding its accuracy, bias, and over-reliance on technology. The utilization of AI in the grading of students has gained momentum as a result of its capacity to analyze large volumes of student work in a timely and consistent manner, thereby alleviating the burden on instructors who frequently encounter difficulty in keeping up with the grading demands.

Reducing the Burden of Essay Grading

Grading essays is a labor-intensive task, particularly for middle and high school instructors who are responsible for managing large class sizes. Traditionally, the number of writing duties that teachers can assign is restricted by the hours they spend evaluating assignments. Educators are currently utilizing AI tools, including ChatGPT and other generative AI models, to assist in the grading of essays, thereby reducing their burden and allowing them to offer students additional writing opportunities. Heather Van Otterloo, an English instructor at South Middle School in Joplin, Missouri, has incorporated AI into her grading procedure. She claims that AI enables her to reduce the time required for grading by half, while also assigning writing assignments more frequently and offering students additional revision opportunities. This efficiency allows educators to concentrate on interactive learning rather than becoming inundated by grading. AI has been found to increase the capacity of teachers to provide constructive feedback to students, thereby enabling them to gradually improve their writing.

Brisk, a Chrome extension that is specifically designed to assist teachers in the grading of essays, is one AI tool that is gathering traction in educational settings. Brisk provides four distinct types of feedback: targeted feedback that emphasizes specific areas of strength and improvement, glow & grow assessments that balance praise with areas for improvement, rubric criteria that align feedback with grading standards, and next steps suggestions that assist students in refining their writing skills. Brisk is a convenient tool for educators due to its seamless integration with existing platforms and its capacity to generate feedback in over 20 languages. Teachers can provide personalized feedback while maintaining consistency and efficiency by employing AI-powered evaluators such as Brisk. Furthermore, this instrument facilitates targeted interventions by enabling educators to monitor student progress and identify recurring writing challenges.

There are numerous benefits to incorporating AI into the evaluation process. AI has the ability to rapidly process and analyze large volumes of assignments, thereby reducing turnover time and facilitating the provision of timely feedback. It guarantees the consistent application of grading criteria by eliminating human bias and subjectivity. AI tools have the ability to customize feedback for individual students, thereby facilitating their comprehension of their strengths and weaknesses. Additionally, teachers can delegate repetitive grading duties to AI, thereby enabling them to allocate more time to lesson planning and student engagement. By generating structured feedback that is congruent with grading rubrics, AI guarantees that students receive objective evaluations, thereby improving their learning experience.

Concerns and Challenges of AI in Grading

AI-assisted grading has provoked substantial apprehensions, despite its benefits. AI models are trained on extensive datasets, which may contain biases that compromise the impartiality of assessments. Research suggests that AI occasionally prioritizes specific writing styles that are associated with specific racial or socioeconomic groups, which could result in discrimination. Numerous artificial intelligence systems operate in intricate manners that are challenging to comprehend. Teachers may experience difficulty in elucidating the process by which the AI determined the score when students challenge their grades, which may raise concerns about transparency. AI is incapable of comprehending the subtleties of unconventional, persuasive, or inventive writing styles, which may result in inaccurate evaluations. The quality of human engagement in education may deteriorate if instructors and students become overly reliant on AI-generated feedback. In addition, students may employ artificial intelligence (AI) to generate entire essays, rather than cultivating their own writing abilities. The necessity of responsible AI usage and appropriate oversight to prevent unintended negative consequences is underscored by these challenges.

AI assessment has been the subject of a variety of opinions from educators and experts. AI is perceived by certain educators as a beneficial assistant that enables them to more effectively manage their workloads and provide more effective feedback. For example, Diane Gayeski, a professor at Ithaca College, employs AI to evaluate student essays and facilitate discussions regarding AI-generated feedback. She emphasizes that AI should be regarded as a teaching assistant rather than a substitute for human assessment. In contrast, there are educators who are skeptic. Concerns regarding the oversimplification of writing assessment by AI were raised in a Reddit thread. Teachers noted that AI tools may not be able to assess the more complex aspects of writing, such as critical thinking and argumentation. Others expressed concern that the student-teacher relationship would be diminished by AI-generated feedback, which lacks the personal touch of a human educator. Dorothy Leidner, a professor at the University of Virginia, is among the experts who contend that AI should be employed with caution. She suggests that AI is most appropriate for large classes in which the grading process emphasizes declarative knowledge with unambiguous right and wrong answers. Nevertheless, human evaluation is still indispensable for smaller classes or assignments that necessitate creative and analytical thinking. The ongoing debate regarding the impact of AI grading on the integrity of education is underscored by these discussions.

Schools and universities must establish explicit policies regarding the use of AI as it becomes more prevalent in the classroom. Although numerous institutions have policies that govern the use of AI by students, there are significantly fewer that regulate its function in grading. Alan Reid, a researcher at Johns Hopkins University, is currently engaged in the development of AI policies for educators. He underscores the significance of transparency, ensuring that students are aware of the instances in which AI is employed to evaluate their work. Additionally, educators should evaluate the ethical implications of intellectual property and data privacy. Student submissions are processed by AI tools. In the absence of rigorous privacy protocols, student work may be stored or utilized to train AI models without their assent. Institutions should obtain student consent prior to uploading their work to AI platforms, according to experts. Institutions can guarantee that AI is employed ethically and responsibly in grading by establishing explicit guidelines.

Future Prospects of AI in Grading

AI in education is anticipated to develop and enhance, despite the apprehensions. Tamara Tate, a researcher at the University of California, Irvine, is investigating the effects of AI grading on student learning. Tate's research revealed that ChatGPT's grading is consistent with human evaluators in certain instances, with an accuracy rate of 89%. She emphasizes, however, that AI grading is still not sufficiently dependable for high-stakes assessments and should be reserved for low-stakes feedback. Grading accuracy and impartiality may be enhanced by future developments in AI. Teacher-calibrated scoring may be incorporated into emerging AI grading models, in which educators train AI with a limited number of sample essays to ensure that it is in accordance with their grading standards. Furthermore, AI tools may enhance their mechanisms for elucidating their classification decisions, thereby addressing concerns regarding the black box effect. It will be essential to maintain ongoing research and development in AI evaluation to guarantee that these systems are beneficial to educators rather than a hindrance.

The integration of AI in grading is revolutionizing education by reducing the workload of instructors and enhancing efficiency. Nevertheless, it is imperative to resolve ethical concerns regarding transparency, bias, and over-reliance. AI grading tools, such as Brisk, offer vital support; however, they should be used in conjunction with human evaluations rather than as a complete replacement. In order to establish ethical AI frameworks that strike a balance between technological efficiency and human supervision, educators, policymakers, and AI developers must work together. The ultimate objective should be to utilize AI as an instrument for improvement, thereby guaranteeing fairness, transparency, and meaningful student learning experiences. AI evaluation can be a valuable asset in modern education by ensuring that student learning remains the central focus, while also maintaining a balance between technological innovation and human judgment.