A Phenomenographic Analysis of College Students' Conceptions of and Approaches to Programming Learning: Insights From a Comparison of Computer Science and Non-Computer Science Contexts

被引:8
|
作者
Chou, Te-Lien [1 ]
Tang, Kai-Yu [2 ]
Tsai, Chin-Chung [3 ,4 ]
机构
[1] Natl Taiwan Normal Univ, Grad Inst Informat & Comp Educ, Taipei, Taiwan
[2] Ming Chuan Univ, Dept Int Business, 250 Zhong Shan N Rd Sec 5, Taipei 111, Taiwan
[3] Natl Taiwan Normal Univ, Program Learning Sci, Taipei, Taiwan
[4] Natl Taiwan Normal Univ, Inst Res Excellent Learning Sci, Taipei, Taiwan
关键词
conceptions of programming learning (CoPL); approaches to programming learning (APL); phenomenographic analysis; computer science (CS); non-computer science (non-CS);
D O I
10.1177/0735633121995950
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Programming learning has become an essential literacy for computer science (CS) and non-CS students in the digital age. Researchers have addressed that students' conceptions of learning influence their approaches to learning, and thus impact their learning outcomes. Therefore, we aimed to uncover students' conceptions of programming learning (CoPL) and approaches to programming learning (APL), and analyzed the differences between CS and non-CS students. Phenomenographic analysis was adopted to analyze 31 college students (20 CS-related, and 11 not) from northern Taiwan. Results revealed six categories of CoPL hierarchically: 1. memorizing concepts, logic, and syntax, 2. computing and practicing programming writing, 3. expressing programmers' ideas and relieving pressure, 4. applying and understanding, 5. increasing one's knowledge and improving one's competence, and 6. seeing in a new way. Four categories of APL were also found, namely: 1. copying from the textbook, teachers, or others, 2. rote memory, 3. multiple exploration attempts, and 4. online or offline community interactions. Furthermore, we found that most CS students held higher level CoPL (e.g., seeing in a new way) than non-CS students. However, compared with non-CS students, CS students adopted more surface approaches to learning programming, such as copying and rote memory. Implications are discussed.
引用
收藏
页码:1370 / 1400
页数:31
相关论文
共 50 条
  • [1] College Students' Conceptions of Learning of and Approaches to Learning Computer Science
    Umapathy, Karthikeyan
    Ritzhaupt, Albert D.
    Xu, Zhen
    JOURNAL OF EDUCATIONAL COMPUTING RESEARCH, 2020, 58 (03) : 662 - 686
  • [2] The Assessment of Taiwanese College Students' Conceptions of and Approaches to Learning Computer Science and Their Relationships
    Liang, Jyh-Chong
    Su, Yi-Ching
    Tsai, Chin-Chung
    ASIA-PACIFIC EDUCATION RESEARCHER, 2015, 24 (04): : 557 - 567
  • [3] The Assessment of Taiwanese College Students’ Conceptions of and Approaches to Learning Computer Science and Their Relationships
    Jyh-Chong Liang
    Yi-Ching Su
    Chin-Chung Tsai
    The Asia-Pacific Education Researcher, 2015, 24 : 557 - 567
  • [4] Non-Computer Science Majored Women Students Perspective on a Pictorial Programming Environment
    Sillessi, Shannon
    Varol, Cihan
    Varol, Hacer
    INTERNATIONAL JOURNAL OF EDUCATION AND INFORMATION TECHNOLOGIES, 2013, 7 (02): : 44 - 51
  • [5] Experiences of Assessment in Introductory Programming From the Perspective of Non-Computer Science Majors
    Riese, Emma
    Stenbom, Stefan
    2020 IEEE FRONTIERS IN EDUCATION CONFERENCE (FIE 2020), 2020,
  • [6] Effects of Question Types on Engagement and Performance of Programming Learning for Non-Computer Science Majors
    Arunoprayoch, Nuttaphat
    Lai, Chih-Hung
    Pham-Duc Tho
    Liang, Jing-SAn
    Yang, Jie-Chi
    2018 7TH INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS (IIAI-AAI 2018), 2018, : 306 - 311
  • [7] Computer science and non-computer science faculty members’ perception on teaching data science via an experiential learning platform
    Huan Chen
    Ye Wang
    You Li
    Yugyung Lee
    Alexis Petri
    Teryn Cha
    Education and Information Technologies, 2023, 28 : 4093 - 4108
  • [8] Computer science and non-computer science faculty members' perception on teaching data science via an experiential learning platform
    Chen, Huan
    Wang, Ye
    Li, You
    Lee, Yugyung
    Petri, Alexis
    Cha, Teryn
    EDUCATION AND INFORMATION TECHNOLOGIES, 2023, 28 (04) : 4093 - 4108
  • [9] Analysis on the Learning Burnout of College Students of Computer Science in Chongqing
    Tian, Linfeng
    3RD INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE AND MECHANICAL ENGINEERING, (ICMSME 2016), 2016, : 193 - 195
  • [10] Designing a Data Science Course for Non-Computer Science Students: Practical Considerations and Findings
    Velaj, Yllka
    Dolezal, Dominik
    Ambros, Roland
    Plant, Claudia
    Motschnig, Renate
    2022 IEEE FRONTIERS IN EDUCATION CONFERENCE, FIE, 2022,