SeisTutor: A Custom-Tailored Intelligent Tutoring System and Sustainable Education

Ninni Singh, Vinit Kumar Gunjan, Amit Kumar Mishra, Ram Krishn Mishra and Nishad Nawaz
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Ninni Singh: Department of Computer Science and Engineering, CMR Institute of Technology Kandlakoya, Hyderabad 501401, Telangana, India
Vinit Kumar Gunjan: Department of Computer Science and Engineering, CMR Institute of Technology Kandlakoya, Hyderabad 501401, Telangana, India
Amit Kumar Mishra: School of Computing, DIT University, Dehradun 248009, Uttarakhand, India
Ram Krishn Mishra: Department of Computer Science, BITS Pilani, Dubai Campus, Dubai P.O. Box 345055, United Arab Emirates
Nishad Nawaz: Department of Business Management, College of Business Administration, Kingdom University, Riffa 3903, Bahrain

Sustainability, 2022, vol. 14, issue 7, 1-24

Abstract: Education is the cornerstone of improving people’s lives and achieving global sustainability. Intelligent systems assist sustainable education with various benefits, including recommending a personalized learning environment to learners. The classroom learning environment facilitates human tutors to interact with every learner and obtain the opportunity to understand the learner’s psychology and then provide learning material (access learner previous knowledge and well-align the learning material as per learner requirement) to them accordingly. Implementing this cognitive intelligence in Intelligent Tutoring System is quite tricky. This research focused on mimicking human tutor cognitive intelligence in the computer-aided system of offering an exclusive curriculum or quality education for sustainable learners. The prime focus of this research article was to evaluate the proposed SeisTutor using Kirkpatrick four-phase evaluation model. The experimental results depict the enhanced learning gained through intelligence incorporated SeisTutor against the intelligence absence, as demonstrated.

Keywords: sustainable education; curriculum recommendation; intelligent tutoring system; adaptive; bug model; prior-knowledge level; learning style; tutoring strategy; artificial intelligence (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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