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Understanding and Addressing Misconceptions in Introductory Programming: A Data-Driven Approach
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Understanding and Addressing Misconceptions in Introductory Programming: A Data-Driven Approach. |
| 개인저자 | Qian, Yizhou. |
| 단체저자명 | Purdue University. Curriculum and Instruction. |
| 발행사항 | [S.l.]: Purdue University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 116 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-10A(E). Dissertation Abstract International |
| ISBN | 9780438017993 |
| 학위논문주기 | Thesis (Ph.D.)--Purdue University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: A.
Adviser: James D. Lehman. |
| 요약 | With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. This explorat |
| 요약 | Using students' erroneous solutions, 55 distinct compilation errors were identified, and 15 of them were categorized as common ones. The 15 common compilation errors accounted for 92% of all compilation errors. Based on the 15 common compilation |
| 요약 | Both quantitative and qualitative data analysis were conducted to see whether and how the targeted feedback affected students' solutions. Quantitative analysis indicated that targeted feedback messages enhanced students' rates of improving erron |
| 요약 | The results of this study suggest that a data-driven approach to understanding and addressing student misconceptions, which is using student data in automated assessment systems, has the potential to improve students' learning of programming and |
| 일반주제명 | Educational technology. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
