Acceptance of personalized e-learning systems: a case study of concept-effect relationship approach on science, technology, and mathematics courses

Panjaburee, Patcharin; Komalawardhana, Narisra; Ingkavara, Thanyaluck

doi:10.1007/s40692-021-00216-6

Cited by 22 publications

(12 citation statements)

References 64 publications

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“…Technologies of digital teaching facilitate the betterment of personalized learning, which is a type of approach in which the instructions and the data required for learning are provided based on a clear understanding of the strengths and needs of each individual [41]. These technologies are extending the learning opportunities, so the learners can gain knowledge easily because the information required for learning is easily accessible and is considered as the major advantage of digital teaching [42].…”

Section: Digital Teachingmentioning

confidence: 99%

Research on Digital Teaching of Creative Writing in the Context of Computer Big Data

Yang¹

2022

Wireless Communications and Mobile Computing

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This paper is aimed at examining the effects of digital teaching on reconstructing creative writing skills and to judge the bettering of creativity and writing skills after accepting digital technology. Based on this paper, creativity and writing skills are the most required elements of creative writing. Fluency, flexibility, originality, and elaboration are the major constructs of creativity. From the contribution of Torrance, we find these constructs of creativity. Narrative and linguistics are the major components in writing skills to evaluate the pupils. Concept and background come under the narrative components as subscales. Likewise, content, the structure of grammar, punctuation, and spelling are considered as subscales in linguistic components. Digital teaching methods and traditional teaching methods are used for this research. We are using a nonequivalent comparison-group design for this research. The rubric is a scoring guide used to evaluate performance. We used this scoring guide to access the improvement of pupils. In total, 58 participants were selected from a primary school. 28 participants were selected from the section A class and 30 pupils from the section B class. In creativity, after the digital teaching, the experimental group is greater than the control group; therefore, the digital teaching method improves the pupils’ creativity level. In writing skill, after digital teaching, the experimental group is better than the control group; therefore, the digital teaching method increases the pupils’ writing skill. We proposed a SVM-based Chaotic Grasshopper Optimization algorithm for digital teaching of creative writing in the context of big data. The comparative analysis result shows that the SVM-Chaotic Grasshopper Optimization method accuracy rate is higher than the other three methods’ accuracy rate. The SVM-CGO method execution time (second) speed is fast when compared with that of the other methods. Thus, we have analyzed the effects of digital teaching and evaluated the improvement in creativity and writing skills after utilizing digital tools.

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Section: Digital Teachingmentioning

confidence: 99%

Research on Digital Teaching of Creative Writing in the Context of Computer Big Data

Yang¹

2022

Wireless Communications and Mobile Computing

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“…Considering the range of decisions is important because it consists of two basic stages (Targeted knowledge and skills). Such an environment enables learners to add, change, or use opportunities according to their needs (Panjaburee et al, 2022).…”

Section: Uses Of Virtual Learning Environmentsmentioning

confidence: 99%

Impact of Teaching a Neuro-Computerized Course Through VLE to Develop Computational Thinking Among Mathematics Pre-service Teachers

Abouelenein

Elmaadaway

2023

Journal of Educational Computing Research

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The current study aims to determine the effect of teaching a mechanic neuro-computerized course through virtual learning environments (VLE) to develop computational thinking among mathematics pre-service teachers. The neuro-computerized virtual learning environments (NCVLE) model was designed to be used to teach the mechanics course to third-year students of the mathematics department. To achieve the targeted learning outcomes, the study recruited (102) third-year students of the Faculty of Education and classified them into a control group of (50) students and an experimental group of (52) students. The experiment lasted for 14 weeks during one semester of the 2021-2022 academic year. The results agreed with most of what has been found from relevant literature and studies. Also, the results indicated that the NCVLE model played a vital role in the purposeful teaching, learning, and assessment processes and enhanced the learning of computational thinking.

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“…This is achieved using an AIbased engine, which computes personalized recommendations based upon a learner's assessment and usage data. These recommendations should be continuously updated in order to improve a learner's experience [15].…”

Section: A Requirementsmentioning

confidence: 99%

“…It requires a smooth and capable mechanism exist through which learners can be continuously assessed and proper level of comprehension can be determined. Machine Learning (ML) and Deep Learning (DL) based models may be utilized to determine and match the appropriate level of content for the learner [15].…”

Section: Introductionmentioning

confidence: 99%

AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions

et al. 2022

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A personalized e-learning system is effective in imparting enhanced learning to its users. As compared to a conventional e-learning system, which provides similar contents to each learner, a personalized learning system provides specific learning contents and assessments to the learners. Personalization is based on Artificial Intelligence (AI) based techniques in which appropriate contents for each learner are determined using the level of comprehension of the learner and the preferred modes of learning. This paper presents requirements and challenges for a personalized e-learning system. The paper is focused in elaborating four research questions, which are related to identifying key factors of personalized education, elaborating on state of the art research in the domain, utilizing benefits of AI in personalized education, and determining future research directions. The paper utilizes an extensive survey of current research papers in answering these questions. It provides a comprehensive review of existing solutions in offering personalized e-learning solutions. It also elaborates on different learning models and learning theories, which are significant in providing personalized education. It proposes an efficient framework, which can offer personalized elearning to each learner and identifies significant directions for future research. The paper is beneficial for academicians and researchers in understanding the requirements of such a system, comprehending its methodologies, and identifying challenges which are needed to be addressed.

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Acceptance of personalized e-learning systems: a case study of concept-effect relationship approach on science, technology, and mathematics courses

Cited by 22 publications

References 64 publications

Research on Digital Teaching of Creative Writing in the Context of Computer Big Data

Research on Digital Teaching of Creative Writing in the Context of Computer Big Data

Impact of Teaching a Neuro-Computerized Course Through VLE to Develop Computational Thinking Among Mathematics Pre-service Teachers

AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions

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