I-OnAR: a rule-based machine learning approach for intelligent assessment in an online learning environment

Abstract

Intelligent systems are created to automate decision making process that is similar to human intelligence. Incorporating intelligent component has achieved promising results in many applications, including in education. Intelligence modules in a tutoring system would bring the application and its capability closer to a human's ability to serve its human users and to solve problems. However, the majority of the online learning provided in the literature review especially in Malaysia, normally only provide the lecture notes, assignments and tests and rarely suggest or give feedbacks on what the students should study or do next in order to fully understand the subjects. Hence, the researchers propose an online learning environment called Intelligent Online Assessment and Revision (I-OnAR). It facilitates the learning process at multiple learning phases such as test creation, materials revision, feedback for improvement and performance analysis. These components are incorporated into the tutoring system to assist self-pace learning at anytime and anywhere. The intelligent agent uses a Rule-based Machine Learning method for the adaptive capabilities such as automated test creation and feedbacks for improvement. The system has been tested on a group of students and found to be useful to support learning process. The results have shown that 60% of the subjects’ performance have improved with the help of the system. The students were given feedbacks on the topic they did poorly as well as how to improve their performance. This proves that the Intelligent Online Assessment and revision (I-OnAR) can be a useful tool to help online students intelligently, systematically and efficiently. For the future works, the researchers would like to apply the usage of other techniques such as Fuzzy Logic to strengthen the analysis and decision of the current system.

Building skills for the future of work: Students’ perspectives on emerging jobs in the Data and AI Cluster through artificial intelligence in education

“…AI and big data support personalized learning [13] . The research by Rodzman et al [12] developed a personalized learning system (intelligent online assessment and revision) applying rulebased machine learning methods to improve the learner's performance in Malaysia. They reported 60% improvement in the learners' performance due to using the designed system.…”

“…They can explore concepts on their own time without relying solely on a tutor. Additionally, students have access to high-quality courses and learning materials from around the world, all from the comfort of their own homes [12,48] . Chincholi [47] emphasizes that the education landscape is rapidly changing with the influence of technology.…”

“…Extrapolating from this AI makes it possible to devise a tailored or individualized learning pathway for each student, which is specific to them and designed to accommodate their strengths, weaknesses, talents, and challenges [9,11] . Learning with artificial intelligence, in other words, incorporates artificial intelligence technologies into the classroom to improve student learning and teaching [12] . Although AI tools and technologies are being developed primarily for business and industry, many AI tools are already available to educators who want to use AI to improve student learning [13] .…”

Utilizing the ATM technology in e-distance learning

“…An online learning environment called Intelligent Online Assessment and Revision (I-OnAR) has been proposed in [16]. The presented system provides an e-learning system with several phases as exam creation, revision and feedback analysis.…”