大學生運算思維與程式設計學習成就研究
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2018
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Abstract
本研究發展一門運算思維與程式設計通識課程,欲探究大學生之學習成就差異。在一學期課程後,分析不同背景學生之運算思維能力、程式設計實作與專題表現,並針對表現不理想的學生進一步討論其學習困難。本研究之對象為選修此通識課程之大學生共計348人,課程共18週,包含運算思維初探3週,程式設計概念培養8週,專題創作5週以及期中測驗2週。資料分析以期中測驗成績、專題成績與問卷為量化資料,課堂觀察與補救教學問答為質性資料。
研究結果發現,期中測驗一的成績對於期中測驗二有極高的預測力,表示課程內容安排合宜且具連貫性。針對學生的表現差異,未曾學習過程式設計相關課程的學生在基礎程式設計概念的表現與有學習經驗的學生並駕齊驅,然而在「重複結構」、「列表應用」及「列表綜合應用」的表現仍較差。理學院和科技與工程學院也在「重複結構」、「列表應用」及「列表綜合應用」表現優於教育學院和文學院。整體而言,學習表現較差的學生皆在學習「重複結構」時遇到困難,連帶影響以「重複結構」為基礎的「列表」及「綜合應用」的表現。
本研究針對程式設計通識課程提出建議,增加基礎「重複結構」的教學時數,以確保學生能在熟悉迴圈運用的情況下,有效學習更進階的內容。另由於部分學院修課人數未達十人,因此難以歸納其學院學生的特性與需求,未來可考慮開設單一學院或科系之專班,以期在通識教育的一般性之下,有更多符合個別差異的空間。
This study developed a course in computational thinking (CT) and programming to explore the differences in learning performance among college students. After an one-semester course, we analyze the performance of students from different backgrounds, and further discuss their learning difficulties for students with poor performance. There are 348 students enrolled in this course. The course consisted of 18 weeks, including 3 weeks of CT exploring, 8 weeks of programming concepts constructing, 5 weeks of project creating and 2 weeks of mid-term testing. The data analysis is based on the programming test grade and questionnaires as quantitative data, and the classroom observation and interviews are qualitative data. The results show that students with poor performance have encountered difficulties in learning the "repetition structure", which is the basis of "list" and "comprehensive application". Moreover, students major in Science or Technology and Engineering have better learning performance than students major in Education or Liberal Arts. We suggest to increase learning hours of the "repetition structure" to ensure that students can effectively learn advanced content while understanding the use of loops.
This study developed a course in computational thinking (CT) and programming to explore the differences in learning performance among college students. After an one-semester course, we analyze the performance of students from different backgrounds, and further discuss their learning difficulties for students with poor performance. There are 348 students enrolled in this course. The course consisted of 18 weeks, including 3 weeks of CT exploring, 8 weeks of programming concepts constructing, 5 weeks of project creating and 2 weeks of mid-term testing. The data analysis is based on the programming test grade and questionnaires as quantitative data, and the classroom observation and interviews are qualitative data. The results show that students with poor performance have encountered difficulties in learning the "repetition structure", which is the basis of "list" and "comprehensive application". Moreover, students major in Science or Technology and Engineering have better learning performance than students major in Education or Liberal Arts. We suggest to increase learning hours of the "repetition structure" to ensure that students can effectively learn advanced content while understanding the use of loops.
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運算思維, 程式設計學習, computational thinking, programming learning