Examining Interest and Grades in Computer Science 1

Author:

Zingaro Daniel1

Affiliation:

1. University of Toronto Mississauga, Mathematical and Computational Science, Mississauga, ON, CA

Abstract

Computer Science 1 (CS1), the first course taken by college-level computer science (CS) majors, has traditionally suffered from high failure rates. Efforts to understand this phenomenon have considered a wide range of predictors of CS success, such as prior programming experience, math ability, learning style, and gender, with findings that are suggestive but inconclusive. The current quasiexperimental study extends this research by exploring how the pedagogical approach of the course (traditional lecture vs. Peer Instruction (PI) and clickers) in combination with student achievement goals (mastery goals vs. performance goals) relates to exam grades, interest in the subject matter, and course enjoyment. The research revealed that students with performance goals scored significantly lower on final exams in both the lecture and PI conditions. However, students with performance goals reported higher levels of subject matter interest when taught through PI. Students with mastery goals, in both conditions, scored significantly higher on the final exam, had higher levels of interest, and reported higher levels of course enjoyment than their performance-oriented counterparts. The results suggest that PI may improve the level of subject-matter interest for some students, thereby indicating the importance of studying pedagogical approach as we seek to understand student outcomes in CS1.

Publisher

Association for Computing Machinery (ACM)

Subject

Education,General Computer Science

Cited by 63 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Achievement goal theory in STEM education: A systematic review;Journal of Engineering Education;2024-02-13

2. Online course in web development: the case of Chinese universities;Interactive Learning Environments;2023-02-23

3. A Chatbot to Facilitate Student Learning in a Programming 1 Course;International Journal of Virtual and Personal Learning Environments;2022-09-30

4. Investigating the impact of adopting Python and C languages for introductory engineering programming courses;Computer Applications in Engineering Education;2022-09-21

5. Fostering the Learning Process in a Programming Course With a Chatbot;International Journal of Online Pedagogy and Course Design;2022-08-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3