Citation

Shakil, Md. Shahid Ahammed and Al Farid, Fahmid and Podder, Nitun Kumar and Iqbal, S. M. Hasan Sazzad and Miah, Abu Saleh Musa and Rahim, Md Abdur and Abdul Karim, Hezerul (2025) Bangla Speech Emotion Recognition Using Deep Learning-Based Ensemble Learning and Feature Fusion. Journal of Imaging, 11 (8). p. 273. ISSN 2313-433X

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Abstract

Education has been steadily incorporating technology to support and enhance teaching and learning practices. One illustrative example is the use of augmented reality (AR), which seamlessly merges virtual elements with the physical world. Children are acquainted with emerging technology as they are the new generation who have been exposed to smart phones and tablets. They belong to a new generation profoundly influenced by these devices. In this research, an AR-based edutainment mobile application with digital visual elements and sound, namely ARKiD, is developed as an alternative to traditional educational mechanisms. It aims to enhance the learning experience for preschool children. This research investigates teachers’ and preschoolers’ perceptions and behavioral patterns in using ARKiD. A mixed method approach was used to collect data from 12 teachers and 65 preschoolers aged 4–5. During data collection, both qualitative and quantitative methods are used. Qualitative methods include observation based on psychomotor aspects, for example, controlling, turning, inspecting, and interview while quantitative refers to the use of questionnaires. The questionnaire was designed based on the technology acceptance model (TAM) which consisted of four antecedents, namely perceived usefulness (PU), perceived ease of use (PEOU), attitude (A) and behavioral intention (BI). This research revealed that the teachers and preschoolers enjoyed using ARKiD despite some concerns regarding AR technology. Overall, preschoolers can operate the ARKiD independently and it shows the learning effectiveness. This research has presented a new type of educational technology to bridge the gap in the field.

Item Type:	Article
Uncontrolled Keywords:	Deep learning
Subjects:	L Education > L Education (General) Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 Sep 2025 01:15
Last Modified:	05 Oct 2025 05:10
URII:	http://shdl.mmu.edu.my/id/eprint/14528

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