서브메뉴
검색
Addressing Bias through Chatbot-Assisted Dynamic Assessment: Toward a Teacher-AI Collaborative Model for Critical L2 Reading
Addressing Bias through Chatbot-Assisted Dynamic Assessment: Toward a Teacher-AI Collaborative Model for Critical L2 Reading
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202104653
- ISBN
- 9798286428953
- DDC
- 420
- 저자명
- Jeon, Jaeho.
- 서명/저자
- Addressing Bias through Chatbot-Assisted Dynamic Assessment: Toward a Teacher-AI Collaborative Model for Critical L2 Reading
- 발행사항
- [Sl] : Indiana University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 229 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
- 주기사항
- Advisor: Coronel-Molina, Serafin M.
- 학위논문주기
- Thesis (Ph.D.)--Indiana University, 2025.
- 초록/해제
- 요약L2 reading has traditionally relied on summative assessments using existing texts and multiple-choice questions with limited reading guidance. This study explores how Generative AI (GenAI)-powered chatbots can offer alternative assessment tools by automating tasks such as text creation and reading guidance. Meanwhile, research also indicates that GenAI's reliance on statistical patterns often reproduces social biases in its output. Rather than viewing this as a limitation, this study uses GenAI's biased texts to promote literal and critical L2 comprehension. It introduces a Teacher-AI Collaborative Assessment model based on Dynamic Assessment (DA), which integrates instruction and assessment within Vygotsky's Sociocultural Theory.In the proposed model, teachers use AI-generated biased texts produced for educational purposes to support L2 learners' development of literal and critical reading performance. Forty-one elementary L2 learners were assigned to experimental (n = 21) and control (n = 20) groups and the students participated in a sequence of "Chatbot-assisted DA 1-Teacher Enrichment-Chatbot-assisted DA 2", where they engaged in reading comprehension activities mediated by AI in collaboration with a teacher. The two groups followed the same sequence mediated by the same AI, while at the teacher enrichment stage, the experimental group was consistently mediated by the teacher using biased texts, and the control group was taught using a textbook.Five types of scores produced through the two chatbot-assisted DA sessions (unmediated, mediated, gain, learning potential, and transfer scores) were quantitatively analyzed, and this analysis was supplemented with a qualitative analysis of scores from select students. The findings show how chatbot-assisted DA can be used to generate diagnostic information about reading performance. This study also demonstrates the effectiveness of the proposed model on literal and critical reading comprehension, as evidenced by a growth in the two groups' reading scores. The introduction of critical comprehension using AI-produced biased texts was found to better facilitate the experimental group's literal comprehension, demonstrating the utility of employing anti-bias texts as part of chatbot-assisted DA. Last, detailed discussions and implications are provided in relation to the roles of AI and critical thinking in the fields of reading education, educational technology, AI ethics, and language assessment.
- 일반주제명
- Educational technology
- 기타저자
- Indiana University School of Education
- 기본자료저록
- Dissertations Abstracts International. 86-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008260126s2025 us c eng d■001000017358382
■00520260202104653
■006m o d
■007cr#unu||||||||
■020 ▼a9798286428953
■035 ▼a(MiAaPQ)AAI32115526
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a420
■1001 ▼aJeon, Jaeho.▼0(orcid)0000-0002-1161-3676
■24510▼aAddressing Bias through Chatbot-Assisted Dynamic Assessment: Toward a Teacher-AI Collaborative Model for Critical L2 Reading
■260 ▼a[Sl]▼bIndiana University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a229 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: B.
■500 ▼aAdvisor: Coronel-Molina, Serafin M.
■5021 ▼aThesis (Ph.D.)--Indiana University, 2025.
■520 ▼aL2 reading has traditionally relied on summative assessments using existing texts and multiple-choice questions with limited reading guidance. This study explores how Generative AI (GenAI)-powered chatbots can offer alternative assessment tools by automating tasks such as text creation and reading guidance. Meanwhile, research also indicates that GenAI's reliance on statistical patterns often reproduces social biases in its output. Rather than viewing this as a limitation, this study uses GenAI's biased texts to promote literal and critical L2 comprehension. It introduces a Teacher-AI Collaborative Assessment model based on Dynamic Assessment (DA), which integrates instruction and assessment within Vygotsky's Sociocultural Theory.In the proposed model, teachers use AI-generated biased texts produced for educational purposes to support L2 learners' development of literal and critical reading performance. Forty-one elementary L2 learners were assigned to experimental (n = 21) and control (n = 20) groups and the students participated in a sequence of "Chatbot-assisted DA 1-Teacher Enrichment-Chatbot-assisted DA 2", where they engaged in reading comprehension activities mediated by AI in collaboration with a teacher. The two groups followed the same sequence mediated by the same AI, while at the teacher enrichment stage, the experimental group was consistently mediated by the teacher using biased texts, and the control group was taught using a textbook.Five types of scores produced through the two chatbot-assisted DA sessions (unmediated, mediated, gain, learning potential, and transfer scores) were quantitatively analyzed, and this analysis was supplemented with a qualitative analysis of scores from select students. The findings show how chatbot-assisted DA can be used to generate diagnostic information about reading performance. This study also demonstrates the effectiveness of the proposed model on literal and critical reading comprehension, as evidenced by a growth in the two groups' reading scores. The introduction of critical comprehension using AI-produced biased texts was found to better facilitate the experimental group's literal comprehension, demonstrating the utility of employing anti-bias texts as part of chatbot-assisted DA. Last, detailed discussions and implications are provided in relation to the roles of AI and critical thinking in the fields of reading education, educational technology, AI ethics, and language assessment.
■590 ▼aSchool code: 0093.
■650 4▼aEnglish as a second language
■650 4▼aEducational technology
■650 4▼aEducational tests & measurements
■653 ▼aAnti-bias education
■653 ▼aCritical thinking
■653 ▼aCurriculum and assessment innovation
■653 ▼aDynamic Assessment
■653 ▼aReading education
■690 ▼a0441
■690 ▼a0710
■690 ▼a0288
■690 ▼a0800
■71020▼aIndiana University▼bSchool of Education.
■7730 ▼tDissertations Abstracts International▼g86-12B.
■790 ▼a0093
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358382▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
