ECSR-Net: An Efficient Classroom Speech Recognition Network Based on Convolutional Neural Networks with Mixup Attention

Опубликована: Янв. 10, 2025

Язык: Английский

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Values and valuing pedagogies in affect-focused mathematics teaching

Social Sciences & Humanities Open, Год журнала: 2024, Номер 10, С. 101050 - 101050

Опубликована: Янв. 1, 2024

Affect-focused mathematics teaching (featuring the mathematics-grounding activity [MGA] was developed by Shi-Da Institute for Mathematics Education in Taiwan. In this study, values and valuing pedagogies (VPs) associated with approach were identified. Qualitative analysis of lesson videos interview transcripts found that students value MGA because gamification experiences, embodiment understanding, peer interaction. Teachers its invite students' active autonomous learning (by increasing motivations), logical thinking (toward understanding), meaningful (for an inclusive community). These VPs can be grouped into affective, cognitive, social VPs, cultural issues emerging regarding gap between traditional approaches. The identification student teacher values, pedagogies, contributes to a deeper understanding affect education, related practice.

Язык: Английский

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Transforming Pedagogical Assessment: AI and Computer Vision-Enhanced Classroom Observations for Experiment-Centric Learning Environments

Опубликована: Авг. 4, 2024

Abstract This paper presents an innovative approach to revolutionizing STEM education by seamlessly integrating artificial intelligence (AI) into the assessment of experiment-centric pedagogy. Our research spans diverse disciplines, including biology, chemistry, physics, civil engineering, transportation mathematics, and computer science. We've transitioned from traditional teaching methods immersive approach, embedding experiments core curriculum modules convey essential concepts effectively. Initially, this study employed Laboratory Observation Protocol for Undergraduate (LOPUS) later Classroom (COPUS), relying on manual observations. Dedicated spaces sheets were marked at two-minute intervals record student instructor activities. proposes a transformative leap forward, introducing AI-based model automate observation process. primary goal is develop sophisticated deep learning capable autonomously tracking documenting wide range activities performed students instructors in classroom. will recognize, document 26 distinct activity constructs evenly distributed between instructors, encompassing questioning frequency, lecturing intervals, student-led discussions. Leveraging state-of-the-art AI technologies, we aim enhance efficiency, precision, scalability pedagogical assessment, providing educators with invaluable insights dynamics environment. extends beyond measure engagement within classes, frequency questions, their predictive abilities concerning experimental outcomes, participation In conclusion, our drives shift education, offering novel framework precise personalization, instructional enhancement. advancement empowers refine strategies, enhancing engagement, creating dynamic Furthermore, complements existing protocols, like COPUS, potentially serving as valuable control assessing classroom

Язык: Английский

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Towards a Multimodal Approach for Assessing ADHD Hyperactivity Behaviors

Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 3 - 14

Опубликована: Янв. 1, 2024

Язык: Английский

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