Artificial intelligence(AI) has started to penetrate into almost all fields and it is playing a dynamic role in the education sector too.
The role of AI in education is significantly increasing and nowadays it is mainly talked about in assessing the students’ performance in multifarious aspects with greater precision.
AI-based technologies are mainly used in teaching and in evaluation /assessment. AI has always been a technology-based promoter in bringing transformation for the education sector. As per many research studies in this specific area, it is found that AI decreases the cost up to
33% of what actually cost traditionally by providing a cost-effective and fraud-free environment.
AI could solve complex problems and voluminous computations with ease. Designing reasonable and robust AI-based assessments systems is gaining acceptance. AI technologies could contribute to a fairer assessment of students’ performance at all levels of the education system to deliver accurate and transparent results. In general assessment in higher education scenarios are of two types namely summative and formative.
The power of AI could be leveraged for both types of assessments of students in higher education – Summative and Formative Assessments.
In the Indian context, equal importance is given for both types of assessment. In common for the assessment activity, the formative assessment occurs as part of the continuous assessment during the execution of a course to verify the students’ learning progress by the teacher or by the students themselves. The summative assessment occurs at the end of the specific course to determine the learning outcomes (Harlen and James 1997). The integration of AI in assessment has created a positive effect on students’ performance and mental well-being.
In formative assessments, teachers check student understanding, accumulate valuable data on student learning, and then use that data to modify course delivery and this happens as a cyclic activity. There are formative assessment apps for everything from discussion forums to quizzing, polling, and student responses to interactive lessons and videos. AI, again is mainly used in the process of formative evaluation and also for the automatic grading of students. AI-based assessments help to provide personalised feedback on students’ performance. Novel forms of assessment that AI-driven systems can facilitate also improve students’ learning and subject knowledge.
Artificial intelligence-based tools when used in summative assessment shortens the time duration and improve the manual correction activities. Various studies in this aspect have recorded several projected educational benefits. The time taken to evaluate an assignment, on average, reduced from approximately 148 s to 85 s, i.e., a 43% reduction. In a similar case for the normalised time, the reduction was marginally less (i.e., 33%). When looked at from the student’s perspective these tools include the ability to support their understanding of the subject, interpret and apply the concepts and theories appropriately. AI in educational assessment allows measuring of performance through score constructed responses, so teachers no longer have to spend time on time-consuming hand scoring. Instead, they can analyse large pools of student individual learning progressions, customizing learning paths per student need. Hence it is very evident that efficiency and accuracy are at the forefront of measuring assessment through AI-based technologies. These technologies also allow students to experience more real-life scenarios and provide equal opportunity in terms of education for all.
The traditional grading system in blended environments is going to be challenging and tedious as in the case of MOOC courses. The teacher would be functioning on tight schedules and there are chances of errors in the grading process. Providing individual and specific remarks to each and every student with precision is a huge challenge. In this context, the use of artificial intelligence can be useful to address these issues. Moving towards an automated grading process will reduce the complexity and also prove to be more effective.
Blending AI into the Assessment Process
Student assessment in specific is over arduous and time-consuming task and takes a huge quantum of teachers’ schedules. AI-based automated assessment systems could free up teacher’s time thereby facilitating them to focus on better classroom engagement with students and foster the classroom community.
AI-driven assessment software can provide insight into students’ learning processes. The in-build data mining algorithms can handle the 4 v’s in students’ log data, namely volume, veracity, velocity, and variability. These algorithms can be used to assess students in a real-time environment so as to provide constructive and progressive feedback, at scale, and to drive scaffolds to students while they learn, blending assessment and learning without using the critical instructional time for assessment. AI-based assessment helps the teachers to get a more detailed and accurate picture of students’ performance. AI-assessment systems are likely to bring important changes to the exam culture at schools and universities and might initiate a fundamental transformation of the current assessment methods.
Again various studies reveal that predictive analytics might play a central role in the classroom of the future to help teachers take pre-emptive measures before individual students can fall behind. Predictive analytics (PLA) is a group of techniques used to make inferences about uncertain future events.
AI-driven assessment and feedback systems enable students to receive more detailed feedback than teachers can provide with the current teacher to student ratio. “This pays off particularly in large classes”, and for student work that is time-consuming to grade and give good feedback on, examples of the latter being complex capabilities such as producing high-quality academic writing, and face-to-face teamwork.”
Designing valid, reliable assessments is an established discipline, and AI should be held to the same standards. Some AI tutors are validated assessment tools, predictive of student performance in established exams. Technology allows testing to be more timely, accessible and reliable. In addition, advancements in AI and ML can expose students to a wider range of information, experience, and technical approaches than traditional assessment mechanisms.
We need strategy and investment to ensure that AI shapes education in the most productive directions in developing future citizens. The question starts right here: What kind of learners does society need to provide solutions to intractable challenges? In general, the options that AI offers to the higher education system are enormous especially for tutoring, continuous assessment and personalization of education, and many more. We must encourage the collaboration between education experts and AI experts, as we cannot understand the educational potential of technologies if we do not understand the educational context, the characteristics of educational interaction and the real users’ needs. Technology and Pedagogy must be considered as two sides of a coin and a simultaneous focus on both is absolutely required to face the new challenges and then to arrive at optimized solutions.
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