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Debugging and Help-Seeking With Chatbots in CS1
Debugging and Help-Seeking With Chatbots in CS1
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103548
- ISBN
- 9798280719569
- DDC
- 370
- 저자명
- Yang, Stephanie.
- 서명/저자
- Debugging and Help-Seeking With Chatbots in CS1
- 발행사항
- [Sl] : Harvard University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 164 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
- 주기사항
- Advisor: Schneider, Bertrand.
- 학위논문주기
- Thesis (Ph.D.)--Harvard University, 2025.
- 초록/해제
- 요약For many beginner programmers, encountering errors in code can be frustrating and disheartening-leading some to questions their belonging in computer science (CS). In these moments, timely debugging help is essential to sustain motivation and foster learning. While students have traditionally turned to peers or teaching assistants for guidance, many now seek debugging support from conversational Large Language Models (LLMs). These chatbots offer promise in providing immediate help, but their ability to generate full-code solutions raises concerns about learning and over-reliance. As these tools become more prevalent, it is important to understand how they can be used to support student's in their debugging and how students seek-help with chatbots. This dissertation explores how students interact with chatbots in introductory computer science courses (CS1) and opportunities to support debugging. The research is presented in a three-paper format. The first paper examines past debugging interventions before the rise of LLMs, identifying gaps that these tools could potentially address. The second paper presents findings from student interviews about their experiences using a course-integrated chatbot, highlighting how they engage with the debugging assistance throughout the semester and their evolving beliefs about appropriate chatbot use. The third study analyzes naturalistic chat data and survey responses in another CS1 course to investigate how students' goal-orientation and beliefs associate with their help-seeking behaviors. The findings from this dissertation offer insights into designing course chatbots and instructional framing around chatbot use to support students' debugging and learning.
- 일반주제명
- Education
- 일반주제명
- Computer science
- 일반주제명
- Information technology
- 키워드
- Chatbots
- 키워드
- Debugging
- 기타저자
- Harvard University Education
- 기본자료저록
- Dissertations Abstracts International. 86-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798280719569
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a370
■1001 ▼aYang, Stephanie.▼0(orcid)0009-0006-7737-6729
■24510▼aDebugging and Help-Seeking With Chatbots in CS1
■260 ▼a[Sl]▼bHarvard University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a164 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: B.
■500 ▼aAdvisor: Schneider, Bertrand.
■5021 ▼aThesis (Ph.D.)--Harvard University, 2025.
■520 ▼aFor many beginner programmers, encountering errors in code can be frustrating and disheartening-leading some to questions their belonging in computer science (CS). In these moments, timely debugging help is essential to sustain motivation and foster learning. While students have traditionally turned to peers or teaching assistants for guidance, many now seek debugging support from conversational Large Language Models (LLMs). These chatbots offer promise in providing immediate help, but their ability to generate full-code solutions raises concerns about learning and over-reliance. As these tools become more prevalent, it is important to understand how they can be used to support student's in their debugging and how students seek-help with chatbots. This dissertation explores how students interact with chatbots in introductory computer science courses (CS1) and opportunities to support debugging. The research is presented in a three-paper format. The first paper examines past debugging interventions before the rise of LLMs, identifying gaps that these tools could potentially address. The second paper presents findings from student interviews about their experiences using a course-integrated chatbot, highlighting how they engage with the debugging assistance throughout the semester and their evolving beliefs about appropriate chatbot use. The third study analyzes naturalistic chat data and survey responses in another CS1 course to investigate how students' goal-orientation and beliefs associate with their help-seeking behaviors. The findings from this dissertation offer insights into designing course chatbots and instructional framing around chatbot use to support students' debugging and learning.
■590 ▼aSchool code: 0084.
■650 4▼aEducation
■650 4▼aComputer science
■650 4▼aInformation technology
■653 ▼aChatbots
■653 ▼aComputing education
■653 ▼aDebugging
■653 ▼aLarge Language Models
■653 ▼aComputer science courses
■690 ▼a0515
■690 ▼a0489
■690 ▼a0984
■690 ▼a0800
■71020▼aHarvard University▼bEducation.
■7730 ▼tDissertations Abstracts International▼g86-12B.
■790 ▼a0084
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357698▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
