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Improvised progressive model based on automatic calibration of difficulty level: A practical solution of competitive-based examination

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Publicado en:Education and Information Technologies vol. 29, no. 6 (Apr 2024), p. 6909
Autor principal: Shah, Aditya
Otros Autores: Devmane, Ajay, Ranka, Mehul, Churi, Prathamesh
Publicado:
Springer Nature B.V.
Materias:
Tests
Distance learning
Academic Achievement
Student Evaluation
Difficulty Level
Electronic Learning
Acceso en línea:Citation/Abstract
Full Text - PDF
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045 2 |b d20240401  |b d20240430 
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100 1 |a Shah, Aditya  |u NMIMS University, B. Tech- Computer Science and Business Systems (CSBS), Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, Mumbai, India (GRID:grid.444588.1) (ISNI:0000 0004 0635 4408) 
245 1 |a Improvised progressive model based on automatic calibration of difficulty level: A practical solution of competitive-based examination 
260 |b Springer Nature B.V.  |c Apr 2024 
513 |a Journal Article 
520 3 |a Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to improve understanding assessment. The suggested student assessment system paradigm involves determining difficulty, creating the exam, and assessing the student. Based on the previously established relationship between question difficulty and right responses, questions are computed and then divided into difficulty categories. This model improves testing by adapting to the student's ability in real-time. This method ensures that all students are graded uniformly and fairly using pre-determined questions and criteria. The methodology can also cut exam creation and administration time, freeing up teachers and administrators to focus on other assessment tasks. It considers more evidence, learner-centered assessment can help employers evaluate candidates more accurately and meaningfully. It might boost academic productivity by letting assessors quickly write high-quality papers and save up time for deeper investigation and experimentation. This may accelerate scientific progress. Automatic paper generation raises ethical questions about research validity and reliability. 
653 |a Tests 
653 |a Distance learning 
653 |a Academic Achievement 
653 |a Student Evaluation 
653 |a Difficulty Level 
653 |a Electronic Learning 
700 1 |a Devmane, Ajay  |u NMIMS University, B. Tech- Computer Science and Business Systems (CSBS), Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, Mumbai, India (GRID:grid.444588.1) (ISNI:0000 0004 0635 4408) 
700 1 |a Ranka, Mehul  |u NMIMS University, B. Tech- Computer Science and Business Systems (CSBS), Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, Mumbai, India (GRID:grid.444588.1) (ISNI:0000 0004 0635 4408) 
700 1 |a Churi, Prathamesh  |u NMIMS University, B. Tech- Computer Science and Business Systems (CSBS), Computer Engineering Department, Mukesh Patel School of Technology Management & Engineering, Mumbai, India (GRID:grid.444588.1) (ISNI:0000 0004 0635 4408) 
773 0 |t Education and Information Technologies  |g vol. 29, no. 6 (Apr 2024), p. 6909 
786 0 |d ProQuest  |t Education Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3039622293/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3039622293/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch