Data & Analytics for Instructional Designers /:
Add Data and Analytics to Your TD Toolkit Instructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data-from how to design learning experiences with data collection in mind to how to use the data to improve and evalua...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Alexandria, VA :
Association for Talent Development,
[2023]
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Add Data and Analytics to Your TD Toolkit Instructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data-from how to design learning experiences with data collection in mind to how to use the data to improve and evaluate those experiences. With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before. With that comes the question of what to do with the data. While most data and analytics books focus on their application for measurement and evaluation and assume a prior baseline understanding of what learning data and analytics mean, Data and Analytics for Instructional Designers delves into the foundational concepts that will enable instructional designers and L&D professionals to use data in their roles. Split into two parts, the book first defines key data and analytics terms, data specifications, learning metrics, and statistical concepts. It then lays out a framework for using learning data for planning how to gather data and to building scale and maturity in your data operations. Megan reassures readers that basic math skills with some computer assistance is what you'll need to get going. So set aside any math anxiety! Through a "If I can see it, I can be it" approach to learning data and analytics, the book blends practical what-is and how-to content with real-world examples and longer case studies from practitioners. Chapters conclude with opportunities for you to put these techniques to work right away, whether you are in a data-rich environment already, or whether you are just getting started and working on hypotheticals. |
| Beschreibung: | 1 online resource (181 p.) |
| ISBN: | 1953946453 9781953946454 |
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| 505 | 0 | |a Intro -- Title Page -- Copyright -- Contents -- Introduction -- Part 1. The Foundations -- 1. Why Should Instructional Designers Care? -- 2. Getting Started With Definitions -- 3. Data Specifications in Workplace Learning -- 4. Unique Learning Metrics -- 5. A Little Bit of Statistics -- Part 2. Designing for Data -- 6. A Framework for Using Workplace Learning Data -- 7. Make a Plan for Gathering and Using Data -- 8. Form Your Hypothesis and Specify Data Needs -- 9. Identify Data Sources -- 10. Build in Data Capture -- 11. Store the Data -- 12. Iterate on the Data and the Analysis -- 13. Communicate and Visualize the Data -- 14. Build Scale and Maturity -- Acknowledgments -- Further Reading -- References -- Index -- About the Author -- About ATD | |
| 520 | |a Add Data and Analytics to Your TD Toolkit Instructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data-from how to design learning experiences with data collection in mind to how to use the data to improve and evaluate those experiences. With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before. With that comes the question of what to do with the data. While most data and analytics books focus on their application for measurement and evaluation and assume a prior baseline understanding of what learning data and analytics mean, Data and Analytics for Instructional Designers delves into the foundational concepts that will enable instructional designers and L&D professionals to use data in their roles. Split into two parts, the book first defines key data and analytics terms, data specifications, learning metrics, and statistical concepts. It then lays out a framework for using learning data for planning how to gather data and to building scale and maturity in your data operations. Megan reassures readers that basic math skills with some computer assistance is what you'll need to get going. So set aside any math anxiety! Through a "If I can see it, I can be it" approach to learning data and analytics, the book blends practical what-is and how-to content with real-world examples and longer case studies from practitioners. Chapters conclude with opportunities for you to put these techniques to work right away, whether you are in a data-rich environment already, or whether you are just getting started and working on hypotheticals. | ||
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| contents | Intro -- Title Page -- Copyright -- Contents -- Introduction -- Part 1. The Foundations -- 1. Why Should Instructional Designers Care? -- 2. Getting Started With Definitions -- 3. Data Specifications in Workplace Learning -- 4. Unique Learning Metrics -- 5. A Little Bit of Statistics -- Part 2. Designing for Data -- 6. A Framework for Using Workplace Learning Data -- 7. Make a Plan for Gathering and Using Data -- 8. Form Your Hypothesis and Specify Data Needs -- 9. Identify Data Sources -- 10. Build in Data Capture -- 11. Store the Data -- 12. Iterate on the Data and the Analysis -- 13. Communicate and Visualize the Data -- 14. Build Scale and Maturity -- Acknowledgments -- Further Reading -- References -- Index -- About the Author -- About ATD |
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| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:30:41Z |
| institution | BVB |
| isbn | 1953946453 9781953946454 |
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| spelling | Torrance, Megan. http://id.loc.gov/authorities/names/no2016086158 Data & Analytics for Instructional Designers / Megan Torrance. Data and Analytics for Instructional Designers Alexandria, VA : Association for Talent Development, [2023] 1 online resource (181 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Intro -- Title Page -- Copyright -- Contents -- Introduction -- Part 1. The Foundations -- 1. Why Should Instructional Designers Care? -- 2. Getting Started With Definitions -- 3. Data Specifications in Workplace Learning -- 4. Unique Learning Metrics -- 5. A Little Bit of Statistics -- Part 2. Designing for Data -- 6. A Framework for Using Workplace Learning Data -- 7. Make a Plan for Gathering and Using Data -- 8. Form Your Hypothesis and Specify Data Needs -- 9. Identify Data Sources -- 10. Build in Data Capture -- 11. Store the Data -- 12. Iterate on the Data and the Analysis -- 13. Communicate and Visualize the Data -- 14. Build Scale and Maturity -- Acknowledgments -- Further Reading -- References -- Index -- About the Author -- About ATD Add Data and Analytics to Your TD Toolkit Instructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data-from how to design learning experiences with data collection in mind to how to use the data to improve and evaluate those experiences. With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before. With that comes the question of what to do with the data. While most data and analytics books focus on their application for measurement and evaluation and assume a prior baseline understanding of what learning data and analytics mean, Data and Analytics for Instructional Designers delves into the foundational concepts that will enable instructional designers and L&D professionals to use data in their roles. Split into two parts, the book first defines key data and analytics terms, data specifications, learning metrics, and statistical concepts. It then lays out a framework for using learning data for planning how to gather data and to building scale and maturity in your data operations. Megan reassures readers that basic math skills with some computer assistance is what you'll need to get going. So set aside any math anxiety! Through a "If I can see it, I can be it" approach to learning data and analytics, the book blends practical what-is and how-to content with real-world examples and longer case studies from practitioners. Chapters conclude with opportunities for you to put these techniques to work right away, whether you are in a data-rich environment already, or whether you are just getting started and working on hypotheticals. Description based on online resource; title from digital title page (viewed on April 17, 2023). Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Exploration de données (Informatique) Recherche quantitative. Data mining fast Quantitative research fast Print version: Torrance, Megan Data and Analytics for Instructional Designers La Vergne : Association for Talent Development,c2023 9781953946447 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3548980 Volltext |
| spellingShingle | Torrance, Megan Data & Analytics for Instructional Designers / Intro -- Title Page -- Copyright -- Contents -- Introduction -- Part 1. The Foundations -- 1. Why Should Instructional Designers Care? -- 2. Getting Started With Definitions -- 3. Data Specifications in Workplace Learning -- 4. Unique Learning Metrics -- 5. A Little Bit of Statistics -- Part 2. Designing for Data -- 6. A Framework for Using Workplace Learning Data -- 7. Make a Plan for Gathering and Using Data -- 8. Form Your Hypothesis and Specify Data Needs -- 9. Identify Data Sources -- 10. Build in Data Capture -- 11. Store the Data -- 12. Iterate on the Data and the Analysis -- 13. Communicate and Visualize the Data -- 14. Build Scale and Maturity -- Acknowledgments -- Further Reading -- References -- Index -- About the Author -- About ATD Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Exploration de données (Informatique) Recherche quantitative. Data mining fast Quantitative research fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/subjects/sh2007000909 |
| title | Data & Analytics for Instructional Designers / |
| title_alt | Data and Analytics for Instructional Designers |
| title_auth | Data & Analytics for Instructional Designers / |
| title_exact_search | Data & Analytics for Instructional Designers / |
| title_full | Data & Analytics for Instructional Designers / Megan Torrance. |
| title_fullStr | Data & Analytics for Instructional Designers / Megan Torrance. |
| title_full_unstemmed | Data & Analytics for Instructional Designers / Megan Torrance. |
| title_short | Data & Analytics for Instructional Designers / |
| title_sort | data analytics for instructional designers |
| topic | Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Exploration de données (Informatique) Recherche quantitative. Data mining fast Quantitative research fast |
| topic_facet | Data mining. Quantitative research. Exploration de données (Informatique) Recherche quantitative. Data mining Quantitative research |
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