The effects of video-annotated learning and reviewing system with vocabulary learning mechanism on English listening comprehension and technology acceptance

Abstract

This study is aimed to design a novel vocabulary learning mechanism (VLM) in the previously developed video-annotated learning and reviewing system (VALRS) that allows learners to identify unfamiliar or unknown words when listening to the video and generate personalized input enhancement from English subtitles for vocabulary learning. It is expected that the VALRS with VLM (VALRS-VLM) can help learners improve their English listening comprehension in the recognition of speech sounds of individual vocabulary words and meaning understanding of vocabulary words and oral sentences. To investigate the learning effectiveness and learners’ experiences of the newly developed VLM, this study compared the outcomes of English listening comprehension performance and technology acceptance between the experimental group using the VALRS-VLM and the control group using the VALRS without the VLM (VALRS-NVLM). Analytical results show that the learners using the VALRS-VLM achieved remarkably better in both English listening learning outcomes and learning retention for vocabulary learning and overall English listening comprehension performance than those who used the VALRS-NVLM. Besides, according to the results of the questionnaire surveyed after the experiment, both the VALRS-VLM and VALRS-NVLM groups showed good technology acceptance. This study confirms that the proposed VALRS-VLM could effectively facilitate learners’ English listening learning as well as provide them with a positive learning experience.

Keywords:

• English listening comprehension
• English listening learning
• Input enhancement
• Video-annotated learning and reviewing system with vocabulary learning mechanism (VALRS-VLM)
• Vocabulary learning

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Chih-Ming Chen

Chih-Ming Chen is currently a professor in the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. He received B.Sc. and M.Sc. degree from the Department of Industrial Education at National Taiwan Normal University in 1992 and 1997, and received Ph.D. degree from the Department of Electronic Engineering at National Taiwan University of Science and Technology in 2002. His research interests include computer assisted language learning, e-learning, digital library, data mining, machine learning and intelligent agents on the web.

Ming-Chaun Li

Ming-Chaun Li is currently a postdoctoral researcher in the Graduate Institute of Library, Information and Archival Studies at National Chengchi University, Taipei, Taiwan. He received M.Sc. degree from the Department of Child and Family Studies in University of Wisconsin-Madison in 1999, and received Ph.D. degree from the Graduate Institute of Applied Science and Technology in National Taiwan University of Science and Technology in 2017. His research interests include game-based learning, problem solving, and mini-flipped game-based learning.

Mei-Feng Lin

Mei-Feng Lin is currently a master student in the E-learning Master Program of Library and Information Studies at National Chengchi University, Taipei, Taiwan. Her research interests include computer assisted language learning and e-learning.