Learning analytics : measurement innovations to support employee development /
| Main Author: | |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
London ; Philadelphia, PA :
Kogan Page,
2016.
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| Edition: | 1st edition. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Machine generated contents note: Foreword 01 Why now? The occasion for learning analytics?
- Data availability
- Changing the way talent analytics work gets done
- Providing unique insight into employee behaviour
- The learning analytics opportunity
- Endnotes 02 What is learning analytics?
- What is learning analytics?
- Learning analytics today: measure for measure, what should be measured?
- Why measure learning?
- Most organizations start with the simple: measure training adoption and satisfaction
- Efficiency, effectiveness, and business outcomes: closing the learning measurement gap
- The journey to learning analytics
- The Four Levels of Evaluation
- The return on investment training methodology
- Impact Measurement Framework
- Success Case Method
- Performance-based evaluation
- Conclusion
- Endnotes 03 Technology's role in learning measurement
- What should technology do?
- Benefits and costs of learning technologies
- What are the requirements for any new technology system in the business intelligence space?
- What is the ROI of technology systems?
- Applying principles of business intelligence systems to learning and development
- Conclusion
- Endnotes 04 Linking learning to business impact
- What works?
- Why does it work?
- Experimental designs
- Alternatives to experimental designs
- Alternative designs
- The end of the null hypothesis
- almost
- Conclusion
- Endnotes 05 Scrap learning: the new leading indicator of success
- Your training programmes are not as good as you think they are
- Running L & D like a business
- Reporting on scrap learning
- How can scrap be reduced?
- Scrap and manager engagement
- Conclusion
- Endnotes 06 Aligning L & D to business goals through needs assessment
- Measure twice, cut once
- How is alignment achieved?
- The ADDIE model: linear vs. cyclical business alignment
- Unpacking the 'Analyse' stage of business alignment
- How can evaluation results inform the Analyse phase?
- What about tests?
- Needs assessment in action
- Using competency assessments to find skill gaps
- Conclusion
- Endnotes 07 Benchmarks
- A journey of a thousand miles begins with one step
- Benchmarking improves maturity
- Why are benchmarks valuable in the L & D space?
- What benchmarks are available?
- Benchmarks and statistical significance
- What does MTM bring to the market beyond benchmarks?
- How do clients use benchmarks to support decision making?
- Conclusion
- Endnotes 08 Optimizing investments in learning
- Learning and development groups struggle to create value
- Developing a framework
- Reporting measures to the business
- Working with business leaders
- Continuous improvement and management approaches
- Principles
- Less is more
- Assumptions
- Conclusion
- Endnotes 09 Beyond learning analytics to talent management analytics
- The future is for those who can predict it
- Defining what to measure in talent management
- Understanding the employee lifecycle
- Integrating data
- Research on talent analytics
- It's not the analytics that matter: it's how they are applied
- Managing data in the analytics process
- Improving analytic impact
- How companies are addressing the challenge of talent analytics impact
- Analytics across the talent lifecycle
- Conclusion
- Endnotes Index.