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 knowledge's. This paper presents the Adaptive Smart Student Assessment (ASSA) model. With ASSA instructors worldwide can define their tests, and their students can take these tests on-line. ASSA determines the students' abilities, skills and preferable Learning Style (LS) 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 student's profile for later use in the learning process to adapt course material content appropriately according to individual student abilities.
Aljohany, D. A., Salama, R. M., & Saleh, M. (2018). ASSA: Adaptive E-Learning smart students assessment model. International Journal of Advanced Computer Science and Applications, 9(7), 128–136. https://doi.org/10.14569/IJACSA.2018.090718