引用本文:贺雨真1 徐阳婷2 毛雨灏3 郑思颖4 暨明5 罗自强5.《生理学》线上学习中学习投入、互动行为和学习动机对学习效果的影响分析[J].中华医学教育探索杂志,2022,(3):288~292
《生理学》线上学习中学习投入、互动行为和学习动机对学习效果的影响分析
Analysis of the influence of learning engagement, interactive behavior and learning motivation on learning effect on online learning of Physiology course
DOI:
中文关键词:  在线学习  学习投入  互动学习行为  学习动机  慕课
英文关键词:Online learning  Learning engagement  Interactive learning behavior  Learning motivation  Massive open online course
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作者单位
贺雨真1 徐阳婷2 毛雨灏3 郑思颖4 暨明5 罗自强5 1中南大学湘雅医学院五年制临床医学专业长沙 4100132中南大学湘雅医学院五年制麻醉医学专业长沙 4100133中南大学计算机学院计算机科学与技术专业长沙410024中南大学法学院法学卓越人才培养长沙 4100125中南大学基础医学院生理学系长沙 410013 
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中文摘要:
      目的 分析不同教学模式下和有不同学习动机的学生的线上学习行为与学习效果,为优化线上教学提供参考。方法 选择2019和2020年参与中南大学生理学小规模限制性在线课程(small private online course,SPOC)和同年参与大规模在线开放课程(massive open online courses,MOOC)的学生,探讨不同教学模式下的线上学习行为和不同学习动机的学生的学习效果。从学习投入、互动行为和学习动机3方面分析学生的线上学习行为。采用SPSS 25.0软件,用函数计算、频率统计、回归分析、秩和检验、相关性检验、卡方检验等统计学方法进行数据分析。结果 2020年SPOC学习者的学习参与度(z=14.36,P<0.001)和人机、人际互动学习水平(z=-11.70、-16.18,P均<0.001)均高于2019年。2019年、2020年的学生整体互动行为与成绩呈中等相关(r=0.42、0.52,P均<0.001),且人际互动行为相关更强(r=0.60、0.55,P均<0.001)。2019年SPOC和MOOC学习者的成绩构成不同(?字2=857.45,P<0.001)。外部动机的SPOC学习者学习效果优于内部动机的MOOC学习者(z=-28.42,P<0.001)。结论 学校所采用的教学模式通过学生的在线学习投入和互动学习行为影响学习效果,学生自身的学习动机也对其在线学习效果起到关键作用。
英文摘要:
      Objective To analyze the online learning behaviors and learning results of students under different teaching modes with different learning motivations, and to provide a reference for optimizing the development of online teaching. Methods Samples of students taking the physiology small private online course (SPOC) in 2019 and 2020, and students taking the massive open online courses (MOOC) in the same year were selected in the study to discuss the differences in learning behaviors of students under different teaching modes and learning effects on students with different learning motivations. The online learning behaviors of students were analyzed based on their learning engagement, interactive behavior and learning motivation. SPSS 25.0 was used to analyze the data with statistical methods such as function calculation, frequency statistics, regression analysis, rank sum test, correlation test and chi-square test. Results The learning participation level (z=14.36, P<0.001), and the human-machine and interpersonal learning interaction level (z=-11.70,-16.18, both P<0.001) of SPOC learners in 2020 were higher than those in 2019. The overall interactive level was moderately correlated with performances of students (r=0.42, 0.52, both P<0.001), and the correlation between interpersonal behavior and grades was much more stronger (r=0.60, 0.55, both P<0.001). The performance composition of SPOC and MOOC learners in 2019 was completely different ( ?字2=857.45, P<0.001). The learning effect of externally motivated students was significantly better than that of internally motivated students (z=-28.42, P<0.001). Conclusion The teaching mode adopted by the school can affect the learning effect by influencing the students' online learning engagement and interactive behavior. Besides, students' own learning motivation also plays a key role in their academic performance.
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