https://orcid.org/0000-0002-0407-2381
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Abstract
Public speaking anxiety (PSA) is a common phenomenon for language learners involving both psychological and physiological symptoms. Timely and effective PSA assessment can help diagnose learners’ speaking anxiety, offer learners feedback to alleviate their anxiety, and improve their public speaking competence. However, it is still a challenging issue to achieve accurate automated assessment of learners’ PSA due to the lack of large-scale and open-source multimodal datasets based on real classroom settings. This study collected the public speaking videos of English as a foreign language (EFL) learners in public speaking courses, and constructed a large-scale multimodal dataset named Speaking Anxiety in Real Classrooms (SARC) with three modalities of acoustic, visual, and textual data (including 1,158 manually-annotated speech videos and corresponding speech drafts of 382 participants). A multimodal deep learning model for automated assessment of learners’ speaking anxiety was proposed, and an online formative assessment platform was then developed to realize the automated assessment of PSA for classroom teaching. A pilot survey study involving 78 participants was then conducted to investigate learners’ acceptance of the platform. Experimental results verified the validity of the deep learning model and the consistency between automated assessment and teacher assessment. Learners’ acceptance data further indicated that collaboration between automated and human assessment provided them with the most satisfactory experience of using the platform to improve their English public speaking.
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No potential conflict of interest was reported by the author(s).
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Chunping Zheng
Chunping Zheng is currently a professor and the Deputy Dean in School of Humanities at Beijing University of Posts and Telecommunications. She also serves as the Director of the Center for Research on Technology-Enhanced Language Education. Her research interests are computer-assisted language learning and computer-assisted translation.
Tingting Zhang
Tingting Zhang is currently a PhD candidate in Beijing Key Laboratory of Intelligence Telecommunication Software and Multimedia in School of Computer Science (National Pilot School of Software Engineering) at Beijing University of Posts and Telecommunications. Her research interests include multimodal learning analysis, causal machine learning and computer-assisted language learning.
Xu Chen
Xu Chen is an MA student in School of Humanities at Beijing University of Posts and Telecommunications. His research interests include computer-asisted language learning and applied linguistics.
Huayang Zhang
Huayang Zhang is currently a lecturer in School of Communication at Shenzhen Polytechnic University. His research interests are multimodal learning analytics and Artificial Intelligence in education.
Jiangbo Wan
Jiangbo Wan is currently a professor in College of Foreign Languages and Literature at Fudan University. She also serves as the Director of the Center for English Public Speaking and Debating. Her major research interests are TESOL and bilingual lexicography.
Bin Wu
Bin Wu is a professor and doctoral supervisor at the School of Computer Science (National Pilot School of Software Engineering) at Beijing University of Posts and Telecommunications (BUPT). He also serves as the head of the Big Data Department at BUPT. His research interests are data science and big data technology.