ArticleMultimedia tools and applications2022
Using refined kano model and decision trees to discover learners' needs for teaching videos.
Article in Multimedia tools and applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A study of family care needs after pediatric congenital heart disease interventions based on the KANO model.BMC cardiovascular disorders · 2025Article
- Demand analysis of telenursing among empty-nest elderly individuals with chronic diseases based on the Kano model.Frontiers in public health · 2022Article
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Authors and funding
4 authors.
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Abstract
With the advancement of technology and the spread of the COVID19 epidemic, learning can no longer only be done through face-to-face teaching. Numerous digital learning materials have appeared in large numbers, changing people's learning mode. In the era of information explosion, how to capture the learners' attention to teaching videos and improve learning effectiveness is the common goal of every designer of e-leaning teaching content. Previous researches focused on the analysis of learning effectiveness and satisfaction. Instructional designers only provided design elements with high learning effectiveness or high satisfaction, and lacked in-depth analysis of the learners' perspectives. The opinions of these e-learning users are often the key to the success of online teaching videos. Therefore, this study aims at the design elements that will be used in the teaching film. The operation mode of the piano mechanism will be employed as the content of the teaching film. Based on eight elements including arrow cueing, dynamic arrow cueing, spreading-color cueing, contrary to cueing, font style, color application, anthropomorphic, and audiovisual complementarity, we use Refined Kano Model to analyze learners' needs of categorization of each element, and discover learners' expectations for teaching videos. In addition, this study also conducts in-depth data analysis through decision trees algorithm, and stratification analyses using different variables (such as design expertise, using frequency, and usage experience, etc.) to find out the key design factors that affect learners' learning. Depending on the learner's background, the use of e-learning experience, using frequency, and the length of the learning video, our results could provide for reference when designing teaching videos. Instructional designers can better understand how to effectively use design elements, so that the teaching videos can achieve the best learning effect.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.