• The Art of Art with Dr. R – Ch. 3 – Pt. 2 – Research Data, Data Collection, Data Analysis

  • 2024/01/04
  • 再生時間: 5 分
  • ポッドキャスト

The Art of Art with Dr. R – Ch. 3 – Pt. 2 – Research Data, Data Collection, Data Analysis

  • サマリー

  • S2E5

    The Art of Art with Dr. R – Ch. 3 – Pt. 2 – Research Data, Data Collection, Data Analysis

    This is the link to my entire dissertation if you have access. Otherwise, please stay tuned, and I will share the chapters here:

    https://scholarworks.lib.csusb.edu/etd/1422/

    EPISODE DESCRIPTION

    For the Research Data part of my research, I structured the autoethnography study by outlining students' projects, reflecting on instances of self-efficacy and divergent thinking. I shared personal experiences in response to research questions about cultivating self-efficacy and divergent thinking attributes through art education with creative learning principles. The class organization, classroom management, and structure are discussed, emphasizing their impact on students' self-efficacy and divergent thinking. Data collection involved rich descriptions, field notes, memos, and personal experiences are coded to identify patterns and themes. Thematic analysis that included deductive and inductive coding was used to capture anticipated and unanticipated themes. Semiotic analysis focused on visual and linguistic signs, tracking students' use of these signs to understand their development of self-efficacy. Strategies such as crystallization, thick descriptions, and peer review were employed to enhance the study's trustworthiness, and member checking allowed participants to verify information. Prolonged engagement and a subjectivity statement aimed to establish rapport and transparency. Validity was further supported through triangulation, an audit trail, and peer review. Chapter four will present the data and findings of this comprehensive autoethnographic study.

    SHOW DESCRIPTION

    This show will explore how education and innovation used to occur through art. The show also describes how art was always interdisciplinary and tied to science, technology, engineering, and mathematics. However, somewhere along the way, our culture changed how we viewed art and artists. I take a deep dive into how important art is for education, innovation, and for future careers. I start with the chapters from my dissertation, but I will later go into other topics, including the perceptions, politics, and solutions created by art. Support this podcast:

    https://anchor.fm/julian-rubalcaba

    Listen to this podcast on your favorite app:

    Spotify

    https://open.spotify.com/show/0gy8zjzCxBWT7lmN35njW2

    Apple Podcast

    https://podcasts.apple.com/us/podcast/the-art-of-art/id1636606373

    Substack

    https://drjfr.substack.com

    Amazon Music

    https://music.amazon.com/podcasts/d798618b-f358-49a4-8b96-13956f62049d/the-art-of-art

    Audible

    https://www.audible.com/pd/ITEM_NAME-Podcast/B0B7QG7KF1?action_code=ASSGB149080119000H&share_location=pdp&shareTest=TestShare

    Stitcher

    https://www.stitcher.com/podcast/the-art-of-art

    Google Podcasts

    Overcast

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あらすじ・解説

S2E5

The Art of Art with Dr. R – Ch. 3 – Pt. 2 – Research Data, Data Collection, Data Analysis

This is the link to my entire dissertation if you have access. Otherwise, please stay tuned, and I will share the chapters here:

https://scholarworks.lib.csusb.edu/etd/1422/

EPISODE DESCRIPTION

For the Research Data part of my research, I structured the autoethnography study by outlining students' projects, reflecting on instances of self-efficacy and divergent thinking. I shared personal experiences in response to research questions about cultivating self-efficacy and divergent thinking attributes through art education with creative learning principles. The class organization, classroom management, and structure are discussed, emphasizing their impact on students' self-efficacy and divergent thinking. Data collection involved rich descriptions, field notes, memos, and personal experiences are coded to identify patterns and themes. Thematic analysis that included deductive and inductive coding was used to capture anticipated and unanticipated themes. Semiotic analysis focused on visual and linguistic signs, tracking students' use of these signs to understand their development of self-efficacy. Strategies such as crystallization, thick descriptions, and peer review were employed to enhance the study's trustworthiness, and member checking allowed participants to verify information. Prolonged engagement and a subjectivity statement aimed to establish rapport and transparency. Validity was further supported through triangulation, an audit trail, and peer review. Chapter four will present the data and findings of this comprehensive autoethnographic study.

SHOW DESCRIPTION

This show will explore how education and innovation used to occur through art. The show also describes how art was always interdisciplinary and tied to science, technology, engineering, and mathematics. However, somewhere along the way, our culture changed how we viewed art and artists. I take a deep dive into how important art is for education, innovation, and for future careers. I start with the chapters from my dissertation, but I will later go into other topics, including the perceptions, politics, and solutions created by art. Support this podcast:

https://anchor.fm/julian-rubalcaba

Listen to this podcast on your favorite app:

Spotify

https://open.spotify.com/show/0gy8zjzCxBWT7lmN35njW2

Apple Podcast

https://podcasts.apple.com/us/podcast/the-art-of-art/id1636606373

Substack

https://drjfr.substack.com

Amazon Music

https://music.amazon.com/podcasts/d798618b-f358-49a4-8b96-13956f62049d/the-art-of-art

Audible

https://www.audible.com/pd/ITEM_NAME-Podcast/B0B7QG7KF1?action_code=ASSGB149080119000H&share_location=pdp&shareTest=TestShare

Stitcher

https://www.stitcher.com/podcast/the-art-of-art

Google Podcasts

Overcast

The Art of Art with Dr. R – Ch. 3 – Pt. 2 – Research Data, Data Collection, Data Analysisに寄せられたリスナーの声

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