[Retracted] Personalized Education Based on Hybrid Intelligent Recommendation System

Abstract

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.

Intelligent Physical Education: Utilizing Artificial Intelligence to Improve Learning Effectiveness

“…Teaching is a generative activity of subject interaction, and the charm of education lies in the teaching behavior and art that teachers emit during the teaching process. Under the influence of digital technology, the lack of interaction between teachers and students has gradually weakened the spiritual collision and emotional fusion that originally belonged to physical education classrooms [5] . For example, AR, VR virtual systems, sports teaching data collection systems, mentor systems represented by ChatGPT, and football virtual teaching scenarios mentioned earlier, it is not difficult to find that although human-machine interaction can simulate the natural response of human emotions through simulation technology in sports teaching applications, it still belongs to the program code of data induction and statistics and the results of intelligent algorithm operation, without self-awareness, motivation and desire, making it impossible to achieve empathy and emotional feedback with individuals.…”

Enhancing Student Engagement: Harnessing “AIED”’s Power in Hybrid Education—A Review Analysis

“…According to Zheng, diverse student preparedness, varied learning styles, and individual interests necessitate an adapted pedagogical approach [9]. A primary rationale for incorporating AI in hybrid education is to provide students with personalized and adaptable learning experiences.…”

Research on Knowledge Graph Multiple Environment-Aware Recommendation Algorithm for Teaching Course Recommendation

“…In early studies, the hybrid teaching mode of traditional classrooms and MOOCs was focused on combining the supervised and personalized characteristics of conventional classrooms and the openness and flexibility advantages of MOOCs to improve teaching efficiency [19][20]. At present, with the development of artificial intelligence technology and its wide application in the field of education, intelligent MOOC teaching mode has been paid attention to, aiming at constructing an all-round user portrait of learners, realizing teaching resource management at the knowledge level, and ultimately providing intelligent guided learning services [21][22]. However, the current intelligent MOOC teaching model is still in the research stage, and a number of key issues still lack feasible solutions [23].…”