基于PBL的线上线下混合教学法在营养与食品卫生学课程教学中的应用研究
Application Research of PBL-Based Online-Offline Blended Teaching Method in Nutrition and Food Hygiene Courses
陈芳 1潘瑶 1徐群英 1张中伟 1胡敏 1冯花1
作者信息
- 1. 南昌大学公共卫生学院,江西南昌 330000
- 折叠
摘要
目的:探讨基于PBL的线上线下混合教学法在营养与食品卫生学课程中应用的教学效果.方法:选取我校预防医学专业大四的本科生为研究对象.2015级学生(93人)为对照组,按照传统教学方法授课;2017级学生(97人)为试验组,按照基于PBL的线上线下混合教学方法授课.两组学生课程设置、教学大纲和学时数相同.比较分析两组学生的成绩,并对试验组进行教学效果的满意度调查.结果:试验组的学生平时成绩、期末成绩、总评成绩均优于对照组(P＜0.05),大部分学生(88.66％)希望在今后的教学中继续使用该教学方法.结论:在营养与食品卫生学教学中应用基于PBL的线上线下混合教学法,有利于激发学生学习兴趣、提高分析和解决问题能力.
Abstract
Objective:To explore the teaching effect of the PBL-based online-offline blended teaching method in nutrition and food hygiene courses.Methods:The study selected fourth-year undergraduate students majoring in preventive medicine as research subjects.Students from the 2015 cohort(93 students)were assigned to the control group and taught using traditional methods,while students from the 2017 cohort(97 students)were assigned to the experimental group and taught using the PBL-based online-offline blended teaching method.Both groups had the same course setup,syllabus,and class hours.Students'performance was compared between the two groups,and a satisfaction survey on the teaching effectiveness was conducted for the experimental group.Results:The experimental group students achieved higher average grades,final grades,and overall grades compared to the control group(P＜0.05).Most students(88.66％)expressed a desire to continue using this teaching method in the future.Conclusion:Applying the PBL-based online-offline blended teaching method in nutrition and food hygiene courses is beneficial for stimulating students'interest in learning and improving their problem analysis and solving abilities.
关键词
PBL教学方法/线上线下混合/营养与食品卫生学Key words
PBL teaching method/online-offline blended/nutrition and food hygiene引用本文复制引用
基金项目
南昌大学教学改革项目(NCUJGLX-19-103)
江西省教学改革研究课题重点项目(JXIG-21-1-3)
江西省高等学校教学改革研究重点项目(JXIG-21-1-3)
南昌大学本科教学改革项目(NCUJGLX-2021-167-98)
南昌大学创新创业教育类教改项目(NCUSCJG-2022N54)
教育部产学合作协同育人项目(230809434407236)
出版年
2024
NETL
NSTL
万方数据