Improving Examination Checking Process using Artificial Intelligence

AI in Educational Sector:

How AI can be Used in Examination Checking and Grading Process

The evaluation of written examinations, particularly essay-based exams, poses a significant challenge for institutions of higher education such as universities like my own, Asia Pacific University due to the large student body and limited manual checking labour. This makes the review and checking of these exams a long and very time-consuming process. Implementation of artificial intelligence in the grading process of exams can streamline and speed up the process benefitting all the parties involved. 

AI systems have demonstrated remarkable proficiency in reading and analysing human language through the use of machine learning and natural language processing. These AI algorithms can be used to check and evaluate the exam scripts and generate corresponding replies and reviews rapidly, identify key ideas, and provide accurate scores reflecting the performance of the students. This approach would deliver students a more timely feedback and reduce the strain for lecturers and examiners.

Moreover, AI grading systems could potentially mitigate inherent biases and inconsistencies that may arise from human graders. Factors such as fatigue, subjectivity, and varying interpretations of rubrics can inadvertently influence the evaluation process. Well-trained AI models, on the other hand, can apply grading criteria uniformly across all submissions, promoting fairness and objectivity in the assessment experience.

However, the implementation of AI in exam grading is not without its challenges. One significant obstacle lies in the complexity of natural language and the nuances of human expression. AI systems may struggle to interpret contextual cues, recognize subtle nuances, or appreciate creative or unconventional approaches to responding. Additionally, ensuring the diversity and representativeness of the training data used to develop the AI models is crucial to avoid perpetuating biases or failing to accurately assess responses that deviate from expected patterns. 

Furthermore, concerns regarding the transparency and accountability of AI grading systems must be addressed. Stakeholders, including students and educators, may require an understanding of the decision-making process and the ability to challenge or appeal the AI's evaluation if discrepancies arise. Robust validation mechanisms and human oversight could help build trust and acceptance of this technology within academic institutions.

Despite these challenges, the potential benefits of implementing AI for checking exam papers are significant. By carefully addressing the limitations, incorporating human oversight, and continuously improving the underlying algorithms and training data, AI could become a powerful tool to streamline the grading process, enhance consistency, and ultimately improve the overall quality and efficiency of written assessments in higher education.