Effectiveness of ontology-based learning content generation for preschool cognitive skills learning

ABSTRACT

During early childhood, children start developing their cognitive, social, emotional, and behavioural skills, laying the foundation for life-long learning. Cognitive skills are usually taught in traditional classrooms through the use of textbooks and worksheets. The learning content in these textbooks and worksheets is static pre-authored content that is repeatedly used for teaching and learning. This repetition jeopardises the child's learning of individualised and cognitive skills. Preschool cognitive skills learning content comprises facts of everyday life. Similarly, the Semantic Web attempts to model these facts through ontologies. From this, a relationship appears between preschool cognitive skills learning content and the ontologies. The present work focuses on the stated problem and presents the theoretical and development details of a child-friendly tutoring application that dynamically generates cognitive skills learning content using ontologies as domain knowledge. The proposed application was evaluated in a preschool environment for its learning effectiveness and the correctness of the generated content. Three groups of preschool children participated in the study for preschool cognitive skills learning through the use of the proposed application. The first group learned the cognitive skills through the traditional method with textbooks and the teacher's teaching. The second group learned the skills through the proposed application at school in classroom sessions. The third group experienced the proposed application both at school and at home, along with regular classroom sessions. The results show significant gains by the third group over the other two groups, and hence support the use of the proposed application in practice. However, the enhanced learning by the third group disappears if the additional application usage time is removed. Moreover, the results of the expert evaluation show that a great deal of the learning content was correctly generated, thus justifying the true modelling of the domain ontology.

KEYWORDS:

• Applied ontology
• intelligent tutoring system
• semantic web
• ontology

Disclosure Statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Mr. Ghulam Mustafa is a Ph.D. student at the University Institute of Information Technology, Pir Mehr Ali Shah Arid Agriculture University. His research interests include context-aware knowledge extraction and cognitive Skills learning.

Muhammad Azeem Abbas is working as Assistant professor at Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan. He received his PhD(IT) from Universiti Teknology Petronas, Malaysia. His research interest is in intelligent tutoring systems and semantic web applications.

Yaser Hafeez is working as Assistant professor at Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Pakistan. He received his PhD from International Islamic University Islamabad, Pakistan. His research interest is in software engineering and knowledge management.

Sharifullah Khan received his PhD in Computer Science from the University of Leeds, Leeds, UK in 2002. He works in School of Electrical Engineering and Computer Science (SEECS), the National University of Sciences and Technology (NUST), Is-lamabad, Pakistan. Dr. Khan is conducting research activities in the areas of Data Science, Ontology Engineering and, Information Retrieval.

Dr. Gwo-Jen Hwang is a chair professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology. His research interests include mobile learning, digital game-based learning, flipped classroom and AI in education.

ORCID

Muhammad Azeem Abbas http://orcid.org/0000-0001-9536-0065