Faaizah Shahbodin
Universiti Teknikal Malaysia Melaka

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Developing Computational Thinking Ability in Early Childhood Education: The Influence of Programming-toy on Parent-Children Engagement Cucuk Wawan Budiyanto; Faaizah Shahbodin; Muhammad Ulin Khoirul Umam; Ratih Isnaini; Anayanti Rahmawati; Indah Widiastuti
International Journal of Pedagogy and Teacher Education Vol 5, No 1 (2021): International Journal of Pedagogy and Teacher Education
Publisher : The Faculty of Teacher Training and Education (FKIP), Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijpte.v5i1.44397

Abstract

Technology and smart devices have become ubiquitous staples in every aspect of human life. Given the rise of computation in everyday life, introducing technology to early childhood students requires exposure to logical thinking and problem-solving skills through programming approaches or computational thinking. This research addresses an inquiry into a comprehensive elaboration of the development of early childhood computational thinking. A novel programming toy was introduced as an educational tool based on designated themes in accordance with early childhood education curricula. Five stages were conducted to reveal parental and child engagement in robotics activities and later, interviews were conducted on children’s cognitive development from the parent's perspective. Children were observed exploring in various ways by concentrating and paying attention, doing the given activities and expressing their excitement and happiness. The notion that children learn from their social network environment was highlighted by the way in which the children involved in the KARIN programming toy’s hands-on activities were driven to be more actively engaged in the exercise. In addition to parent-student engagement, the use of the KARIN programming toy helps to shed light on how students in early childhood learn while away from their social relations during a pandemic.
Biomarkers of attention bias during public speaking anxiety Akmal Razak; Farah Shahnaz Feroz; Siva Kumar Subramaniam; Faaizah Shahbodin; Sujatha Rajkumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp140-147

Abstract

The analysis of brain signals and their properties yields significant insights into the fundamental neural impairments associated with attention bias in individuals suffering from public speaking anxiety (PSA). This study aims to identify electroencephalogram (EEG) and performance biomarkers of attention bias in individuals with public speaking anxiety using the ex-Gaussian modeling technique, frontal alpha asymmetry (FAA) and delta-beta correlation (DBC). 12 subjects with high (H) PSA and 12 subjects with low (L) PSA performed the modified emotional stroop task. EEG data were captured using the low-cost 14-channel emotiv Epoc+. Results showed that the ex-Gaussian sigma was higher in the emotional condition in the high public speaking anxiety (HPSA) group, indicating attention bias. The study also found higher right FAA in HPSA compared to LPSA group. There was a negative correlation between σ and alpha power in the left region of the brain in the HPSA group, potentially related to attentional bias. Moreover, there was a notable trend towards significantly heightened DBC in the frontal and central regions of the brain among HPSA subjects. In conclusion, in biomedical engineering, the ex-Gaussian model, FAA and DBC are useful because they can identify EEG and performance biomarkers of attention bias in people with PSA.