Assessment of Personalized Learning in Immersive and Intelligent Virtual Classroom on Student Engagement

• URL: http://arxiv.org/abs/2501.07883v1
• Date: Tue, 14 Jan 2025 06:49:22 GMT
• Title: Assessment of Personalized Learning in Immersive and Intelligent Virtual Classroom on Student Engagement
• Authors: Ying Weng, Yiming Zhang,
• Abstract summary: The study aims to provide insights into how personalized learning approaches can enhance student participation, motivation, and academic performance. The eye movement paradigm has the potential to assess student engagement and promote better educational outcomes.
• Score: 5.982610439839458
• License:
• Abstract: As trends in education evolve, personalized learning has transformed individuals' engagement with knowledge and skill development. In the digital age, state-of-the-art technologies have been increasingly integrated into classrooms to support intelligent education and foster personalized learning experiences. One promising approach is the use of eye-tracking technology to evaluate student engagement in intelligent virtual classrooms. This paper explores the assessment of personalized learning in the virtual classroom and its impact on student engagement through the eye movement paradigm. The study aims to provide insights into how personalized learning approaches can enhance student participation, motivation, and academic performance in the online learning environment. Through a comprehensive literature review, case study, and data analysis, the paper examines the key elements of personalized learning, the methods of assessment, and the resulting effects on student engagement. The findings suggest that the eye movement paradigm has the potential to assess student engagement and promote better educational outcomes.

Related papers

• Exploring Engagement and Perceived Learning Outcomes in an Immersive Flipped Learning Context [0.195804735329484]
  The aim of this study was to explore the benefits and challenges of the immersive flipped learning approach in relation to students' online engagement and perceived learning outcomes. The study revealed high levels of student engagement and perceived learning outcomes, although it also identified areas needing improvement. The findings of this study can serve as a valuable resource for educators seeking to design engaging and effective remote learning experiences.
  arXiv  Detail & Related papers  (2024-09-19T11:38:48Z)
• The Perceived Learning Behaviors and Assessment Techniques of First-Year Students in Computer Science: An Empirical Study [0.0]
  Students believe that in-person instruction is the most effective way to learn. For evaluation methods, there is a preference for practical and written examinations.
  arXiv  Detail & Related papers  (2024-05-10T08:45:32Z)
• Towards Automated Knowledge Integration From Human-Interpretable Representations [55.2480439325792]
  We introduce and motivate theoretically the principles of informed meta-learning enabling automated and controllable inductive bias selection. We empirically demonstrate the potential benefits and limitations of informed meta-learning in improving data efficiency and generalisation.
  arXiv  Detail & Related papers  (2024-02-25T15:08:37Z)
• Emotion Based Prediction in the Context of Optimized Trajectory Planning for Immersive Learning [0.0]
  In the virtual elements of immersive learning, the use of Google Expedition and touch-screen-based emotion are examined. Pedagogical application, affordances, and cognitive load are the corresponding measures that are involved.
  arXiv  Detail & Related papers  (2023-12-18T09:24:35Z)
• Dynamic Diagnosis of the Progress and Shortcomings of Student Learning using Machine Learning based on Cognitive, Social, and Emotional Features [0.06999740786886534]
  Student diversity can be challenging as it adds variability in the way in which students learn and progress over time. A single teaching approach is likely to be ineffective and result in students not meeting their potential. This paper discusses a novel methodology based on data analytics and Machine Learning to measure and causally diagnose the progress and shortcomings of student learning.
  arXiv  Detail & Related papers  (2022-04-13T21:14:58Z)
• Comparative Study of Learning Outcomes for Online Learning Platforms [47.5164159412965]
  Personalization and active learning are key aspects to successful learning. We run a comparative head-to-head study of learning outcomes for two popular online learning platforms.
  arXiv  Detail & Related papers  (2021-04-15T20:40:24Z)
• Personalized Education in the AI Era: What to Expect Next? [76.37000521334585]
  The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to meet her desired goal. In recent years, the boost of artificial intelligence (AI) and machine learning (ML) has unfolded novel perspectives to enhance personalized education.
  arXiv  Detail & Related papers  (2021-01-19T12:23:32Z)
• Social Engagement versus Learning Engagement -- An Exploratory Study of FutureLearn Learners [61.58283466715385]
  Massive Open Online Courses (MOOCs) continue to see increasing enrolment, but only a small percent of enrolees completes the MOOCs. This study is particularly concerned with how learners interact with peers, along with their study progression in MOOCs. The study was conducted on the less explored FutureLearn platform, which employs a social constructivist approach and promotes collaborative learning.
  arXiv  Detail & Related papers  (2020-08-11T16:09:10Z)
• Dual Policy Distillation [58.43610940026261]
  Policy distillation, which transfers a teacher policy to a student policy, has achieved great success in challenging tasks of deep reinforcement learning. In this work, we introduce dual policy distillation(DPD), a student-student framework in which two learners operate on the same environment to explore different perspectives of the environment. The key challenge in developing this dual learning framework is to identify the beneficial knowledge from the peer learner for contemporary learning-based reinforcement learning algorithms.
  arXiv  Detail & Related papers  (2020-06-07T06:49:47Z)
• The didactic potential of virtual information educational environment as a tool of geography students training [0.0]
  The article determines the didactic potential of the virtual information educational environment for the geography students training. The authors highlighted the advantages of virtual information educational environment implementation. Among the disadvantages the article mentions low level of computerization, insignificant quantity and low quality of software products.
  arXiv  Detail & Related papers  (2020-02-18T10:25:05Z)
• A Review on Intelligent Object Perception Methods Combining Knowledge-based Reasoning and Machine Learning [60.335974351919816]
  Object perception is a fundamental sub-field of Computer Vision. Recent works seek ways to integrate knowledge engineering in order to expand the level of intelligence of the visual interpretation of objects.
  arXiv  Detail & Related papers  (2019-12-26T13:26:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.