Development and preliminary investigations of a language-specific trisyllabic word set for assessing speech recognition threshold in school-aged children

Nikolaos Trimmis, Fotini Feida, Angelos Papadopoulos, Panagiotis Plotas — Mon, 28 Sep 2026 00:00:00 +0800

The purpose of this study was to develop a set of three-syllable words suitable for assessing the Speech Recognition Threshold (SRT) in school-aged children (6 to 12 years old), as there is a gap in the Greek population. Word selection was based on four key criteria: syllabic structure (trisyllabics), age-appropriate vocabulary familiarity, phonemic differentiation, and homogeneity in relation to audibility. Words were recorded and processed in accordance with the International Organization for Standardization (ISO) 8253-3:2022 for speech audiometry. A total of 20 children participated in the word homogeneity evaluation. For each word, the presentation level required to achieve 50% correct recognition was determined. Next, recognition rates were measured across a range of intensities to determine recognition from 20% to 80%, during which the steepest rise in the Performance-Intensity (PI) function occurred. Findings indicated that all words that are homogeneous in terms of recognition rate are not homogeneous in terms of recognition threshold, and vice versa. Therefore, to optimise homogeneity, only words falling within a range of +1 Standard Deviation (SD) in both recognition rate and recognition threshold were selected. Results are consistent with previous studies in other languages that developed trisyllabic material for the SRT test. In conclusion, a list of 40 trisyllabic words was developed that will increase the reliability of audiological pediatric testing and can serve as a foundation for further research and clinical application across Greek-speaking populations.

Neuroscience for all: empowering memory and learning among orang asli students through STEM@USM program

Thu, 17 Sep 2026 00:00:00 +0800

The STEM@USM program is a neuroscience-driven university-community engagement initiative conducted by the Department of Neurosciences, USM at SK Sungai Rual, Jeli, Kelantan. The school serves Orang Asli communities, Malaysia’s indigenous population, and is the only school of its kind in the district. Grounded in neuroscience in education, the program was designed to enhance memory formation, learning processes, motivation, and student engagement through experiential learning and multisensory approaches. Implemented from June 2024 to July 2025, the initiative comprised three phases: experiential exposure to neuroscience and medical sciences, creative integration of STEM concepts through digital art and NFT-based learning, and impact evaluation. Based on the assessment, the program improved students’ scientific understanding, learning motivation, and classroom engagement, consistent with stronger memory retention through hands-on and visual learning strategies. By combining neuroscience concepts with digital innovation, the initiative reinforced the role of active learning environments in supporting cognitive engagement and sustained interest in STEM subjects, particularly among underserved learners. Overall, STEM@USM illustrates how neuroscience-informed pedagogy can bridge the STEM gap for indigenous education while providing a versatile platform for community empowerment. Beyond its local impact, the initiative offers a scalable, adaptable framework that integrates cognitive science, digital technology, and community engagement. Future directions include extending the program to other underserved schools, strengthening longitudinal evaluation of educational and cognitive outcomes, and positioning neuroscience-based experiential learning as a strategic approach for advancing equitable STEM development.

Neuroscience Research Notes

Development and preliminary investigations of a language-specific trisyllabic word set for assessing speech recognition threshold in school-aged children

Neuroscience for all: empowering memory and learning among orang asli students through STEM@USM program