Attention-based automatic editing of virtual lectures for reduced production labor and effective learning experience

Hwang, Eugene; Lee, Jeongmi

doi:10.1016/j.ijhcs.2023.103161

International Journal of Human-Computer Studies

2024

DOI: 10.1016/j.ijhcs.2023.103161

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Attention-based automatic editing of virtual lectures for reduced production labor and effective learning experience

Eugene Hwang,

Jeongmi Lee

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Cited by 2 publications

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AI Eye-Tracking Technology: A New Era in Managing Cognitive Loads for Online Learners

Šola,

Qureshi,

Khawaja

2024

Education Sciences

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Eye-tracking technology has emerged as a valuable tool for evaluating cognitive load in online learning environments. This study investigates the potential of AI-driven consumer behaviour prediction eye-tracking technology to improve the learning experience by monitoring students’ attention and delivering real-time feedback. In our study, we analysed two online lecture videos used in higher education from two institutions: Oxford Business College and Utrecht University. We conducted this analysis to assess cognitive demands in PowerPoint presentations, as this directly affects the effectiveness of knowledge dissemination and the learning process. We utilised a neuromarketing-research consumer behaviour eye-tracking AI prediction software called ‘Predict’, which employs an algorithm constructed on the largest neuroscience database (comprising previous studies conducted on live participants n = 180,000 with EEG and eye-tracking data). The analysis for this study was carried out using the programming language R, followed by a series of t-tests for each video and Pearson’s correlation tests to examine the relationship between ocus and cognitive demand. The findings suggest that AI-powered eye-tracking systems have the potential to transform online learning by providing educators with valuable insights into students’ cognitive processes and enabling them to optimise instructional materials for improved learning outcomes.

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AI Eye-Tracking Technology: A New Era in Managing Cognitive Loads for Online Learners

Šola,

Qureshi,

Khawaja

2024

Education Sciences

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EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

Zhang,

Ba,

et al. 2024

Sensors

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Traditional broadcasting methods often result in fatigue and decision-making errors when dealing with complex and diverse live content. Current research on intelligent broadcasting primarily relies on preset rules and model-based decisions, which have limited capabilities for understanding emotional dynamics. To address these issues, this study proposed and developed an emotion-driven intelligent broadcasting system, EmotionCast, to enhance the efficiency of camera switching during live broadcasts through decisions based on multimodal emotion recognition technology. Initially, the system employs sensing technologies to collect real-time video and audio data from multiple cameras, utilizing deep learning algorithms to analyze facial expressions and vocal tone cues for emotion detection. Subsequently, the visual, audio, and textual analyses were integrated to generate an emotional score for each camera. Finally, the score for each camera shot at the current time point was calculated by combining the current emotion score with the optimal scores from the preceding time window. This approach ensured optimal camera switching, thereby enabling swift responses to emotional changes. EmotionCast can be applied in various sensing environments such as sports events, concerts, and large-scale performances. The experimental results demonstrate that EmotionCast excels in switching accuracy, emotional resonance, and audience satisfaction, significantly enhancing emotional engagement compared to traditional broadcasting methods.

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Attention-based automatic editing of virtual lectures for reduced production labor and effective learning experience

Cited by 2 publications

References 42 publications

AI Eye-Tracking Technology: A New Era in Managing Cognitive Loads for Online Learners

AI Eye-Tracking Technology: A New Era in Managing Cognitive Loads for Online Learners

EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

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