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Lesson Plan EDRS 9100

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Lesson Plan: EDRS 9100Advanced Qualitative Research Methods

10/10/2019

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Introduction

The clip below describes the main features of the IRML:

This lesson plan has been co-developed between the Interactive Research Methods Lab's team, and Dr. Iván Jorrín (Professor of Educational Research at Kennesaw State University). The aim of the lesson plan is to help graduate students to collaboratively develop a a visual representation of the key elements of their qualitative research designs. EDRS 9100 is a doctoral seminar that helps doctoral candidates in conceptualizing, identifying the components of, and articulating the emerging conceptual framework of their dissertation.

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This lesson plan will help students taking EDRS 9100, a course on Advanced Qualitative Research Designs, to work in “A.8-Design your Study,” an assignment in which students are asked to generate a visual representation of the key elements of their qualitative research designs.

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1. This activity will help graduate students develop their research skills.These include logic, and problem-solving skills (Bauer & Bennett, 2003) and experimental skills like design, data collection, data analysis, understanding of limitations, and research ethics (John & Creighton, 2012; Russell, Hancock, & McCullough, 2007). 2. It will also help students develop their communication skills by improving students' oral, written, and visual communication skills (Bauer & Bennett, 2003). 3. The proposed activity will promote students’ critical thinking. 4. Finally, this lesson plan will help graduate students to reflect upon the key elements of the qualitative research designs for their dissertation studies.

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Step 0: Prior to the face-to-face session in the IRML, students will receive this lesson plan so they can be aware of the activity to be conducted.Step 1: The IRML and Hopscotch will be presented to the students (see: http://irml.kennesaw.edu) (see: https://youtu.be/HW7fz_ZmSiM) (see: http://hopscotchmodel.com) (10’) Step 2: A.8-Design your Study (30’). This part of the session will be devoted to the generation of a visual representation of the key elements of students' qualitative research designs. To do so, students will have to select the research tradition that best fits their research problem, and generate a visual representation of its main components. Use the templates provided in Appendix A, as well as the digital resources listed below: Template to generate a visual representation of a/an: - Narrative Research Study - Phenomenological study - Phenomenographic Study - Ethnographic Study - Grounded Theory Study - Case Study - Action Research Study During the process of elaborating the visual, and with the aim of refreshing ideas behind the different components of your research design, you will be able to interact with the augmented reality contents of the Interactive Research Methods Lab.

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Step 3: Students will present/share with the rest of the group the visual representation of their studies (40’) (3+2 minutes each) Step 4: The Anticipated data reduction strategy will be presented to the students (20’)(see Appendix B) Download template

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Interactive Research Methods Lab Website

Hopscotch Model

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The outcome of this session will be a visual representation of a conceptual framework visual representation of students's research designs supporting their dissertation study.

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APPENDIX A: Templates to generate the visual representation of your study

APPENDIX B: Anticipated Data Reduction Template

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APPENDIX A: Templates to generate the visual representation of your study

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Tool to generate a visual representation of a/an: - Narrative Research Study - Phenomenological Study - Phenomenographic Study - Ethnographic Study - Grounded Theory Study - Case Study - Action Research Study

Download templates

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APPENDIX B: Anticipated Data Reduction Template

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Download Anticipated Data Reduction template

Contact Information

Interactive Research Methods Lab

Bagwell College of Education 580 Parliament Garden Way Room BEB 403 Kennesaw, 30144

irml@kennesaw.edu

https://irml.kennesaw.edu