Genetic Algorithm-based Curriculum Sequencing Model For Personalised E-Learning System

Abstract

Abstract-Personalised learning is a way of organising the learning content and to be accessed by the individual learner in a manner that is suitable to learner's requirements. There are existing related works on personalised e-learning systems that focused on learner's preference without considering the difficulty level and the relationship degree that exists between various course concepts. Hence, these affect the learning ability and the overall performance of learners. This research paper presents a genetic algorithm-based curriculum sequencing model in a personalised e-learning environment. It helps learners to identify the difficulty level of each of the curriculum or course concepts and the relationship degree that exists between the course concepts in order to provide an optimal personalised learning pattern to learners based on curriculum sequencing to improve the learning performance of the learners. The result of the implementation showed that the genetic algorithm is suitable to generate the optimal learning path using the values of difficulty level and relationship degree of course concepts. Furthermore, the system classified the learners into three different understanding levels of the course concepts such as partially, moderately and highly successful.

Sequence generation for learning: a transformation from past to future

“…The first iteration involves using the past learner’s data and also expert rules. C. Agbonifo and A. Obolo (2018) used a genetic algorithm to generate learning paths using the difficulty level of concepts and relationship degree of concepts, but no learner characteristics were considered.…”

Personalisation methods in e‐learning‐A literature review

“…Genetic algorithms are an evolutionary computation technique that mimics a gene's evolution to solve problems [5]. It is one of the main techniques for constructing a learning path for each student that can be found in many early articles [5,10,77,135].…”

“…Genetic algorithms are an evolutionary computation technique that mimics a gene's evolution to solve problems [5]. It is one of the main techniques for constructing a learning path for each student that can be found in many early articles [5,10,77,135]. The specific form of this algorithm is the memetic algorithm, which applies a separate local search process to refine individuals [95,192,246].…”

Sequenciamento de Ações Pedagógicas baseadas na Taxonomia de Bloom usando Planejamento Automatizado apoiado por Algoritmo Genético

“…Os problemas de otimização abordados no cenário de aprendizagem são diversos, dentre os quais podemos destacar: i) A busca pela rota de aprendizagem ideal, de acordo com o perfil do estudante, observada em (Rastegarmoghadam & Ziarati, 2017), (Hssina, 2019) e (Vanitha, Krishnan, & Elakkiya, 2019); ii) o desempenho do estudante e o tempo de aprendizagem, abordados em (Lin, Chang, & Chu, 2016); iii) o sequenciamento curricular, como visto em (Agbonifo & Olanrewaju, 2018); iv) a satisfação do estudante, além da minimização e equalização no tempo de trabalho entre os participantes de um grupo são tratados em (de Miranda, et al, 2019).…”