five

Supporting data for "Designing a 5E flipped teaching approach to enhance elementary schoolers' computational thinking concepts, problem-solving and debugging skills"

收藏
DataCite Commons2022-04-14 更新2025-04-16 收录
下载链接:
https://datahub.hku.hk/articles/dataset/Supporting_data_for_Designing_a_5E_flipped_teaching_approach_to_enhance_elementary_schoolers_computational_thinking_concepts_problem-solving_and_debugging_skills_/19481603
下载链接
链接失效反馈
官方服务:
资源简介:
Study One used a mixed-methods research approach to investigate student performance under different teaching approaches and their perceptions of the 5E-supported flipped classroom approach. Both quantitative and qualitative data were collected and analyzed. The quantitative data (e.g., test scores, project evaluation) can be used to indicate the student differences in learning outcomes between two instructional approaches. The qualitative data (e.g., student interviews, the instructor interview) can be used to explain the results obtained based on the quantitative data by identifying cases that describe the experiences of participants. Similar to the approach adopted in Study One, a mixed-methods research approach was also used in Study Two to examine student performance in program debugging under two different types of instructional approaches and students’ perceptions of the program debugging and the scaffolding tool that shows the systematic debugging process. This means that both quantitative and qualitative data needed to be collected and analyzed. The student performance differences in program debugging and cognitive load between the two flipped debugging training groups (i.e., the flipped debugging training approach combined with the systematic debugging process and the modeling method vs. the unassisted flipped debugging training approach) can be indicated through quantitative data (i.e., test scores in program debugging tasks and rating scores in the cognitive load questionnaire). The cases that described students’ experiences can be obtained through qualitative data (e.g., student interviews).

研究一采用混合研究法(mixed-methods research),旨在探究不同教学模式下的学生学习表现,以及学生对依托5E教学模式(5E Instructional Model)的翻转课堂(flipped classroom)教学模式的认知。研究收集并分析了定量与定性两类数据:定量数据(如测验成绩、项目评价结果)可用于反映两种教学模式下学生学习成果的差异;定性数据(如学生访谈、授课教师访谈)则可通过挖掘描述研究参与者学习经历的案例,对定量分析得到的结果作出解释。与研究一采用的研究方法一致,研究二同样采用混合研究法,考察两种不同教学模式下学生的程序调试学习表现,以及学生对程序调试教学与展示系统化调试流程的支架工具(scaffolding tool)的认知。该研究同样需要收集并分析定量与定性两类数据:两个翻转式调试训练组(即结合系统化调试流程与建模法的翻转调试训练模式,与无辅助的翻转调试训练模式)在程序调试表现与认知负荷(cognitive load)方面的学生差异,可通过定量数据(即程序调试任务测验成绩与认知负荷问卷评分)体现;描述学生学习经历的案例,则可通过定性数据(如学生访谈)获取。
提供机构:
HKU Data Repository
创建时间:
2022-03-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作