AI-based evaluation and grading in schools are part of the new normal.
At one time, there were real classes where teachers were evaluating you hard in your pen and paper exams. If ‘New Normal’ is planned to stay here, this is the story that our future children will hear. The Covid-19 epidemic brought rapid digital transformation and AI-powered automation across all industries. According to IDC, global revenue for the artificial intelligence market is forecast to rise by 16.4% to $327.5 billion in 2021.
The growing importance of AI is also seen in the education sector. Epidemic-induced change in online classes affected many traditional educational institutions. Distance education has increased the reach and efficiency of the education system. The shifting of virtual classrooms demands strong support from destructive technologies. There have been numerous reports about the role of AI technologies in remote classes and virtual education systems and how it can easily bring them to various administrative functions. AI has already scored its mark, but we need to keep in mind some of the factors that are AI in the test evaluation.
AI to evaluate academic performance
Recent reports have revealed that the new State School Board, Delhi, DBSE will use AI-based continuous evaluation and sports-based evaluation in its schools. In the evaluation process, AI provides teachers with real-time learning response and students engage in situations or activities to evaluate their skills and understanding through the game, reports the Hindustan Times. Does this mean AI algorithms determine performance based on student’s skills and abilities? Of course, and this is not the first method. A few years ago, Chinese schools started experiments with automated AI grading systems.
AI-based evaluation and marking techniques can reduce human bias and speed up evaluation. There is another advantage of AI in immediate feedback evaluation for both students and teachers. Pearson, a multinational publishing and educational institution, ELT has several AI-based evaluation systems that provide non-biased and accurate results.
AI paper grading software is attracting attention because it can quickly grade paper and assignment without any human intervention. Machine learning and data analysis are the pillars of the technology of automated evaluation. AI and machine learning algorithms learn from existing data and try to copy human evaluation models with accuracy.
AI-powered people redefine the education system while reducing online scores and evaluation, automatic grading, AI-assisted proxy bias and fraud. The Telangana State Education Board announced that it would use AI for accuracy in its examination results, which led to the suicides of many students. According to the Economic Times report, the board has found many errors due to faulty technology in the evaluation of OMR sheets.
Are grades reliable?
Despite these claims that AI-based assessment and grading are accurate, fair and non-biased, there are many instances where it has been completely wrong. An article in the Harvard Business Review shows how the AI grading systems of the International Backup Organization were predicted and students produce results different from the protest. And, the AI system predicts grades on data rather than just an algorithm, rather than evaluating papers. Another article on Verge describes how the AI-based evaluation method of the virtual learning platform focuses on specific keywords to determine points. We hear many people how an automated AI algorithm caused a disaster in the UK amid epidemics.
If we dig more, we will find more such a discrete ness. Do these events indicate that the AI-based test evaluation system is not an ideal method? Perhaps we are still lagging behind plugging AI and other destructive technologies. While feeding data loads of these systems, it should be noted that the data does not represent any errors. The virtual and remote learning landscape will have many positive effects on staying here and on the AI education system. The future of AI is related to us and therefore, ai can have many benefits if properly applied in test evaluation.