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AI-based assessment and grading in schools is a part of the new normal.

Once upon a time, there were real classrooms with teachers strictly evaluating you during your pen and paper examinations. This might be a story that our future kids will listen to if the ‘new normal’ is planning to stay here. The Covid-19 pandemic brought rapid digital transformation and AI-driven automation into all industries. According to IDC, the worldwide revenues for the artificial intelligence market are forecast to grow 16.4% in 2021 to USD 327.5 billion.

The growing significance of AI is also visible in the education sector. The pandemic-induced shift to online classes impacted many conventional methods of educational institutions. Remote learning has increased the accessibility and efficiency of the education systems. The shift towards virtual classrooms demands strong support from disruptive technologies. There have been many reports about the role of AI technologies in remote classes and virtual education systems and the ease it brings to different administrative tasks. Let us focus on one of the aspects where AI has already made its mark but has also raised some concerns, that is AI in exam evaluation.

AI in Evaluating Academic Performance

Recent reports revealed that Delhi’s new state school board, DBSE will be employing AI-based continuous assessment and game-based assessment in their schools. A Hindustan Times report states that AI in the assessment process will provide real-time learning feedback to teachers and students will be given situations or involved in activities to evaluate their skills and understanding through games. Will this mean that AI algorithms will decide the performance based on the skills and strength of the students? Absolutely, and this is not the first-ever approach. Many educational institutions and universities have already employed AI for assessment and automated grading systems. Schools in China had already started experimenting with automated AI grading systems a few years back.

AI-based assessments and marking techniques can minimize human biases and enhance the speed of evaluation. Instant feedback to both students and teachers is another advantage of AI in evaluations. Pearson, the multinational publishing and educational organization boasts having many AI-based assessment systems in ELT, which provides unbiased and accurate results.

AI paper grading softwares is gaining attention since they can quickly grade papers and assignments without any human intervention. Machine learning and data analytics are the pillars behind the technology of automated assessment. AI and Machine learning algorithms learn from existing data and try to replicate human evaluation patterns with precision.

AI-driven online marking and assessment, automated grading, AI-assisted proctoring are redefining the education system, while reducing bias and frauds. The Telangana State Board of Intermediate Education in India had announced the use of AI for accuracy in their exam results considering the discrepancies in evaluation that led to the suicides of many students. According to the Economic Times report, the board happened to find various errors in the assessment of OMR sheets due to flawed technology.

Are the Grades Reliable?

Despite the claims that AI-based assessment and grading is accurate, fair, and bias-free, there have been many instances where it went totally wrong. An article in the Harvard Business Review reveals how AI grading systems by the International Baccalaureate Organization produced varying results from the predicted ones and the students went on a protest. And, the AI system apparently, just predicted grades on the data fed to the algorithm rather than actually evaluating papers. Another article on The Verge says how a virtual learning platform’s AI-based assessment method focused on specific keywords to determine marks. Most of us would have heard how an automated AI algorithm caused havoc in the UK amid the pandemic by providing biased and lowered A-level results to the students.

We can find more such discrepancies if we dig more. Do these incidents indicate that AI-based exam evaluation systems are not an ideal approach after all? Maybe we are still lagging behind in addressing the flaws of AI and other disruptive technologies. While feeding loads of data to these systems, it must be taken care that the data do not represent any errors. The virtual and remote learning scenario is here to stay and AI will have many positive impacts on the education system. The future of AI is intertwined with us and hence, AI in the evaluation of exams will benefit many if incorporated in the right way.

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