Abstract
This research is to investigate the impact of massive open online course (MOOC) learning platforms on teacher development, promote the development and innovation of online learning models under the “Double First-Rate,” and especially expand the application of the MOOC platforms combining language learning with professional development paths. The MOOC online learning platform has a problem of a high abandonment rate. This paper first proposes a MOOC learning recommendation algorithm based on the learning sequence and similarity distance analysis as well as evaluates its accuracy. Then, the reliability test and the MOOC learning recommendation algorithm are used to evaluate the quality evaluation system of English teaching in the MOOC utilizing the structural equation model. Finally, the strengths, weaknesses, opportunities, and threats (SWOT) are determined to analyze the impact of the MOOC regarding the English teaching platform on teachers' comprehensive development. The results show that the MOOC platform-based learning recommendation algorithm has higher recommendation accuracy and efficiency, improving the learning effect with the utilization of the MOOC. Also, it can effectively reduce the abandonment rate and has a positive effect of resolving the interaction problem pertinent to characteristic differences and sequences in the learning recommendation. The quality evaluation system of online English teaching in the MOOC has higher reliability and convergent validity, which shows better stability and consistency in all dimensions. If teachers can actively learn from the resources of the MOOC platform, then they continuously update teaching concepts, improve online teaching, give full play to their language advantages, accurately locate student needs, and develop unique courses. Therefore, it will promote the overall development of their careers and improve innovation.
Highlights
Massive open online courses (MOOCs) were originally proposed based on innovative teaching practices of online courses in Canada
A similar system is called “muke” in China that has open-access online courses and large-scale participation. e so-called “massive” means that there are many learners who have registered and participated in the teaching and learning activities. e online learning platform is not limited by space, and information resources can be shared in the Internet environment. e MOOC combines information with network technology to provide high-quality and free learning resources while providing a complete learning experience in the framework of higher education that is developed based on traditional classroom settings [1,2]
Since China has been under a comprehensive process of transformation in higher education for three decades, one of the implemented actions is called “Double First-Rate.” us, one of the implementations that China plans to conduct to move towards a new era of higher education is based on implementing the concept of “Double First-Rate.”. We investigate this approach concerning the MOOC platform
Summary
Massive open online courses (MOOCs) were originally proposed based on innovative teaching practices of online courses in Canada. Is paper takes the impact of the MOOC’s online learning platform on the development of college teachers as the starting point and employs the MOOC English teaching in a college in Hunan Province as the research object as a problem. Is paper proposes the MOOC learning recommendation algorithm based on learning sequence and similarity distance analysis since the MOOC platform has a high abandonment rate and a low completion rate When it is combined with the reliability assessment method, the quality evaluation system of online English teaching in the MOOC platform is tested.
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