Document Details

Document Type : Thesis 
Document Title :
ADAPTIVE SMART STUDENT ASSESSMENT (ASSA) MODEL IN E-LEARNING
نموذج تقييم طلاب ذكي ومتكيف في التعليم الإلكتروني
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : Adaptive e-learning can be improved through measured e-assessments that can provide accurate feedback to instructors. E-assessments can not only provide the basis for evaluation of the different pedagogical methods used in teaching and learning but they also can be used to determine the most suitable delivered materials to students according to their skills, abilities, and prior knowledges. Discovering and evaluating the prior knowledges and skills of students need smart e-assessment model. Smart Assessment Model (SAM) can facilitate the evaluation process and measure the students proficiency with more accuracy. This research presents the Adaptive Smart Student Assessment (ASSA) model. ASSA determines the students abilities, skills and preferable learning style with more accuracy and then generates the appropriate questions in an adaptive way, then presents them in a preferable learning style of student. It facilitates the evaluation process and measures the students knowledge level with more accuracy and then store it in the students profile for later use in the learning process to adapt course material content appropriately according to individual student abilities. We have selected the Felder Silverman model (FSLSM) to identify student learning style. ASSA used Smart Ontology Model (SOM) to direct the assessment process to assess the students knowledge and skills, and it also uses the Revised Bloom Taxonomy (RBT). 
Supervisor : Dr. Reda Mohamed Salama 
Thesis Type : Master Thesis 
Publishing Year : 1439 AH
2018 AD 
Co-Supervisor : Dr. Abdulrahman Altalhi 
Added Date : Monday, July 16, 2018 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
دلال عبدالله الجهنيAl-johany, Dalal AbdullahResearcherMaster 

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