Learning Model of Intelligent Sign Language Online

Abstract

Background and Aims: Learning smart sign language online is particularly interesting nowadays due to various technologies and platforms that facilitate learning and communication in this domain. Therefore, research on intelligent online learning formats for sign language is of great interest across multiple dimensions. This research aims to: 1) Develop intelligent online learning formats for sign language; 2) Evaluate these intelligent online learning formats.

Methodology: The study includes two groups: 9 experts involved in analyzing and designing intelligent sign language learning formats, and 9 qualified evaluators using purposive sampling. Research tools consist of structured deep interviews and format evaluation questionnaires. Statistical methods include basic statistics such as mean and standard deviation, and quality statistics of research tools like question validity and confidence intervals.

Results: The findings reveal: (1) Intelligent online sign language learning formats consist of six components: principles of 21st-century learning, teaching sign language learning skills, intelligent sign language learning environments, knowledge round-based sign language learning activities, and learning format assessment. And (2) Evaluation results from qualified evaluators show overall high levels of feasibility, accuracy, appropriateness in learning format management, and usefulness in learning management formats.

Conclusion: The results demonstrate that six essential components of intelligent online sign language learning formats are in line with 21st-century educational ideas. According to evaluations, these formats are very accurate, suitable, workable, and practical for efficient learning management.