Research Article
Semantic Web-Based Education with AI in Basic Education with Values and Morals
Manavapati Venkateswarlu*
,
Mohammed Nazeer Hussain
Issue:
Volume 15, Issue 5, October 2026
Pages:
186-199
Received:
22 June 2026
Accepted:
27 August 2026
Published:
4 September 2026
Abstract: The present education is concerned with the formation of the whole person child, rather than on just learning academic skills. In addition to academic achievement and subject knowledge, students' overall development is enhanced through their qualities of integrity, empathy, responsible behavior, ethical thinking and active participation. But, in many current education systems, measurable academic results are more significant and resources are less available for the identification and development of those personal and moral abilities. To fill this gap and meet the need of learning recommendations for individual students, this study proposes an intelligent education model based on the Semantic Web and Artificial Intelligence (AI) technologies. The proposed framework is a semantic based framework of RDF, RDFS, and OWL, to present student-related information in a structured and meaningful way. Relationships between various aspects of a learner's academic and behavioral data are established through ontologies and knowledge graph. These learner characteristics are then analyzed using AI and machine learning techniques to derive relevant learning recommendations. An implementation was built using Python, Flask, Scikit-learn, Joblib and RDFLib. It takes into account academic performance along with factors like honesty, empathy and participation in the classroom in order to predict the learning outcomes and create meaningful semantic profiles for students. The proposed system shows that the use of semantic knowledge representation along with AI can facilitate more relevant recommendations and meet individual learners' needs. The method can also help teachers make decision making by offering a wider perspective of the students' growth rather than relying on their academic performance. Furthermore, including aspects related to values in the learner profile provides opportunities to promote values awareness and responsible attitudes. The proposed framework illustrates the potential of the Semantic Web and AI technologies to assist a learning environment that preserves academic outcomes by considering personal, social, and ethical growth.
Abstract: The present education is concerned with the formation of the whole person child, rather than on just learning academic skills. In addition to academic achievement and subject knowledge, students' overall development is enhanced through their qualities of integrity, empathy, responsible behavior, ethical thinking and active participation. But, in ma...
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Research Article
From Tool-Centric to Cognitive Collaboration: Reconfiguring Generative AI in Education from a Cognitive Deficits Perspective
Kaidan Deng*,
Yantian Xu
Issue:
Volume 15, Issue 5, October 2026
Pages:
200-208
Received:
14 August 2026
Accepted:
26 August 2026
Published:
18 September 2026
DOI:
10.11648/j.edu.20261505.12
Downloads:
Views:
Abstract: Generative Artificial Intelligence (AIGC) is driving widespread transformation in the field of education. However, current applications largely remain at the superficial level of "mechanical adoption of technology," failing to address the core educational objectives of cultivating students' deeper cognitive abilities, such as critical thinking and metacognition. This phenomenon reveals that the educational application of AIGC is facing a profound predicament, rooted in the field's widespread neglect of AIGC's fundamental cognitive deficiencies in causal reasoning, contextual understanding, and symbolic grounding, which has led to a structural contradiction between technological application and educational objectives. To resolve this predicament, this study combines critical analysis with theoretical construction. It first systematically analyzes the educational implications of AIGC's cognitive deficiencies and then proposes a systematic path for reconfiguration. At the theoretical level, this study constructs a "Human-Centered Three-Tiered Collaborative Cognitive Development Framework for AIGC." Through the interplay of metacognitive design, cognitive collaboration, and continuous reflection, it redefines AIGC as "a controlled collaborator under the guidance of educational objectives." At the technical level, addressing the three major cognitive deficiencies, this study proposes a dual-track evolutionary approach that combines "innovations in educational methodology" with "advancements in algorithmic frameworks" aiming to drive AIGC's evolution toward an "educational world model" that embodies educational logic. This study aims to transcend the limitations of instrumental rationality and provide a systematic solution—combining theoretical foresight with practical guidance—for constructing a new paradigm of intelligent education that prioritizes human development and leverages technology appropriately. Future research will validate the effectiveness of this approach through practical application and continue to focus on the dynamic adaptation between technological evolution and the essence of education.
Abstract: Generative Artificial Intelligence (AIGC) is driving widespread transformation in the field of education. However, current applications largely remain at the superficial level of "mechanical adoption of technology," failing to address the core educational objectives of cultivating students' deeper cognitive abilities, such as critical thinking and ...
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