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Signal to Noise: Intra-active Entanglements in an Interdisciplinary Course on Data and Storytelling
Signal to Noise: Intra-active Entanglements in an Interdisciplinary Course on Data and Storytelling
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151949
- ISBN
- 9798382826639
- DDC
- 370
- 서명/저자
- Signal to Noise: Intra-active Entanglements in an Interdisciplinary Course on Data and Storytelling
- 발행사항
- [Sl] : Michigan State University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 232 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-12, Section: A.
- 주기사항
- Advisor: Herbel-Eisenmann, Beth.
- 학위논문주기
- Thesis (Ph.D.)--Michigan State University, 2024.
- 초록/해제
- 요약In this dissertation, I engage in three analytic cuts to think about/with a relational ontological orientation to data and data literacies/science education. The analysis focuses on the following question: What possibilities for teaching and learning about data are made possible when we attune to the relational, noisy, liminal, and material dimensions of data and the connections between data and broader issues of power and ethics? This study is situated in an interdisciplinary course on data and data storytelling at a large public university in the U.S. Midwest that I and another colleague designed and taught in the 2022-2023 academic school year. I organize my findings and discussions along three chapters in this dissertation. Chapter 2 is a theoretical examination of norms and values about data suggested in certain data science education reform efforts in the U.S. and a reconsideration of new possibilities for teaching and learning about data informed by relational ontologies and philosophical theories about signal and noise. Chapter 3 is an empirical piece that shares vignettes of two students' engagements with data physicalizations as part of a data postcard activity and year-long survey-based research project. Chapter 4 examines how opportunities for critical, creative, and interdisciplinary engagements with data throughout the data storytelling course shaped how students made sense of data and processes of data generation, analysis, and communication. I co-authored the piece alongside my co-instructor and five of the students from the data storytelling course. Overall, this dissertation offers a unique approach of attuning to and elevating the concept of noise as a potentially generative concept for data literacies/science education. It raises important questions about the role of material agency, ethics and response-ability, ambiguity and improvisation, storytelling, and interdisciplinarity in connection with efforts to teach and learn about data in critical, creative, and relational ways.
- 일반주제명
- Education
- 일반주제명
- Mathematics education
- 일반주제명
- Pedagogy
- 일반주제명
- Ethics
- 일반주제명
- Educational philosophy
- 키워드
- Data literacy
- 키워드
- Data science
- 기타저자
- Michigan State University Curriculum Instruction and Teacher Education - Doctor of Philosophy
- 기본자료저록
- Dissertations Abstracts International. 85-12A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211151949
■006m o d
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■020 ▼a9798382826639
■035 ▼a(MiAaPQ)AAI31328170
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a370
■1001 ▼aPeralta, Lee Melvin M.▼0(orcid)0000-0002-2980-4390
■24510▼aSignal to Noise: Intra-active Entanglements in an Interdisciplinary Course on Data and Storytelling
■260 ▼a[Sl]▼bMichigan State University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a232 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-12, Section: A.
■500 ▼aAdvisor: Herbel-Eisenmann, Beth.
■5021 ▼aThesis (Ph.D.)--Michigan State University, 2024.
■520 ▼aIn this dissertation, I engage in three analytic cuts to think about/with a relational ontological orientation to data and data literacies/science education. The analysis focuses on the following question: What possibilities for teaching and learning about data are made possible when we attune to the relational, noisy, liminal, and material dimensions of data and the connections between data and broader issues of power and ethics? This study is situated in an interdisciplinary course on data and data storytelling at a large public university in the U.S. Midwest that I and another colleague designed and taught in the 2022-2023 academic school year. I organize my findings and discussions along three chapters in this dissertation. Chapter 2 is a theoretical examination of norms and values about data suggested in certain data science education reform efforts in the U.S. and a reconsideration of new possibilities for teaching and learning about data informed by relational ontologies and philosophical theories about signal and noise. Chapter 3 is an empirical piece that shares vignettes of two students' engagements with data physicalizations as part of a data postcard activity and year-long survey-based research project. Chapter 4 examines how opportunities for critical, creative, and interdisciplinary engagements with data throughout the data storytelling course shaped how students made sense of data and processes of data generation, analysis, and communication. I co-authored the piece alongside my co-instructor and five of the students from the data storytelling course. Overall, this dissertation offers a unique approach of attuning to and elevating the concept of noise as a potentially generative concept for data literacies/science education. It raises important questions about the role of material agency, ethics and response-ability, ambiguity and improvisation, storytelling, and interdisciplinarity in connection with efforts to teach and learn about data in critical, creative, and relational ways.
■590 ▼aSchool code: 0128.
■650 4▼aEducation
■650 4▼aMathematics education
■650 4▼aPedagogy
■650 4▼aEthics
■650 4▼aEducational philosophy
■653 ▼aData literacy
■653 ▼aData science
■653 ▼aData storytelling
■653 ▼aInterdisciplinarity
■653 ▼aRelational ontology
■653 ▼aTeaching and learning
■690 ▼a0515
■690 ▼a0280
■690 ▼a0456
■690 ▼a0998
■690 ▼a0394
■71020▼aMichigan State University▼bCurriculum, Instruction, and Teacher Education - Doctor of Philosophy.
■7730 ▼tDissertations Abstracts International▼g85-12A.
■790 ▼a0128
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17162239▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
