A Hybrid Adaptive Educational eLearning Project based on Ontologies Matching and Recommendation System

Each individual diversifies in the population with certain characteristics. Thus, diversity is a scientifically proven and widely accepted phenomenon when the human being is a concern. One of the areas where the diversity of human beings is mostly paid attention to is called the learning process, since different forms of responses could be observed. For example, each student perceives, assimilates, and uniquely processes the information when being transmitted to him, which confirms the inherited diversity. In this regard, educational systems are required to deal effectively with students and to apply the principles of personalized learning, which is pertinent to learning processes that meet the individual needs and interests of learners. By doing so, taking into account their unique characteristics, talents, skills, inclinations, and desires are satisfied. This manuscript presents an innovative model to classify college students’ skills. A hybrid artificial intelligence (AI) system that fully automates the process of personalized training is proposed based on individual skills by taking into account the priority of personalized and fully customized learning systems. The process specifically utilizes the Rasch statistical analysis model and an innovative fuzzy Bayesian network. Higher-level reasoning is generated for the automated and personalized learning process in which college students are automatically classified into a certain category based on their skills.

“…e following criteria were used to evaluate the performance of the hybrid AI system [40][41][42][43]:…”

Section: Resultsmentioning

confidence: 99%

[Retracted] Classification and Analysis of College Students’ Skills Using Hybrid AI Models

Tang¹,

Wei²

2022

“…Finally, Demertzi and Demertzis [18] proposed the Adaptive Educational eLearning System (AEeLS), which can acquire and analyze data from learning repositories and modify it to the educational curriculum based on the student's skills and experience. It is a new hybrid machine learning system that combines a Semisupervised Classification method for ontology matching with a Recommendation Mechanism that employs a hybrid method trying to combine neighborhood-based collaborative and contentbased filtering techniques to provide each student with a personalized educational environment.…”

Section: Related Literaturementioning

confidence: 99%

[Retracted] An Artificial Intelligent Virtual Reality Interactive Model for Distance Education

Yin¹

2022

Information and communication technologies play an important role in education. This fact was emphasized even more due to the significant upheavals, globally, caused by the pandemic of COVID-19 and because distance education uses tools of modern technology that prove to be significantly important. Particularly, virtual reality immersion systems, which may include 3D spatial representations, multisensory interaction channels, and real-time intuitive physical interaction, can extend the learning process by providing learners with stimuli that represent a real advanced training environment. In the present work, based on the most modern technologies of computational intelligence, virtual and augmented reality, wireless communications, and space-sensitive positioning applications, an Artificial Intelligent Virtual Reality (AI-VR) interactive model for distance education is presented. This is a case study of escape-room-type educational application, wherewith appropriate practices and methodologies promote individual and collective participation, enhance the active role of the learner, personalize the educational experience, and upgrade the process of participation in distance education, strengthening and assisting role of the educator. Specifically, a Newton polynomial is used for max-polynomials arising from the stereoscopic problem of augmented reality used to indirectly indicate the number of linear regions in order to optimize the problem. The proposed application is related to the training course of agricultural education and methods of modernization of crops, including additional sound, 3D graphics, and short film projection. The history-space-objects relationship takes and evolves with various versions such as the parts of the story to be unlocked as the trainee moves from one tool to the next or the story to guide the trainee to explore the space-time continuum, giving a new dimension to the technological development of agricultural education and the methods of modernization of crops. This finding shows that they learn best when they receive information in a style that incorporates visual, auditory, and kinetic stimuli so that learning improves when learners can examine an idea or concept using a multidimensional approach.

“…A typical example of the implementation of pedagogical strategies that are adapted to the real individual skills of students is the adaptive educational systems (AES) that adapt their teaching content to the educational needs and skills of students. Demertzi et al [7] proposed a new adaptive educational e-learning system (AEeLS) that can collect and analyze data from learning repositories and adapt it to the curriculum according to students' skills and experience. It is a new hybrid machine learning system that combines a semisupervised classification method for matching educational ontologies and a recommendation mechanism that uses a hybrid method of content-based filtering techniques to provide a personalized learning environment for each student.…”

Section: Related Literaturementioning

confidence: 99%

“…To determine whether the topic area of a lesson plan is relevant to the topic set by the teacher, lexical analysis is performed based on the keywords related to the topic area in question. For this reason, intelligent natural language processing techniques are used [7]. A key feature of complexity in the process of converting words into concepts is related to the required rearrangements of the words in the original sentence to create the conceptual expression.…”

Section: Proposed Systemmentioning

confidence: 99%

[Retracted] Personalized Education Based on Hybrid Intelligent Recommendation System

Zheng

2022

Differentiated pedagogy is a flexible and organized adaptation of teaching and learning as it argues that students, even those of the same age, have differences in learning readiness, interests, learning style, experiences, and living circumstances. These differences are important in the determination of requirements of their learning and the way of effective learning. In addition, the foundation for effective learning is the sense of community within the classroom, the authentic learning opportunities of using educational equipment, and the connection of the lesson with the experiences and interests of the students. In essence, the support of a teacher guides the pupils to learn to work on their own during a declining guidance policy, to improve their abilities and skills. Thus, the teachers are asked to modify their teaching methods instead of applying a similar way of teaching for all students. The modified teaching style should meet the different levels of readiness of students, the different ways they learn, and their different interests. In support of this specific task for teachers, the current work presents a personalized education system based on hybrid intelligent recommendations. Specifically, a hybrid framework of artificial intelligence is proposed, which focuses on the way to provide targeted recommendations for the implementation of integrated standard lesson plans, which will be the main tool for creating flexible differentiated pedagogical programs that will perfectly meet the personal needs and particularities of each student.