Learning Analytics / Data-Driven Learning Design

Learning Analytics

Data-Driven Learning Design

Start

ContenT

Introduction to the Trend

3 Phase Cycle

Rationale and Application

Trend Use

Trend Information

References

Data Points

Impact on Digital Learning

Introduction to the trend

Learning Analytics

Data-Driven Learning Design

Learning Analytics is the measurement, collection, analysis and reporting of learning data to understand learners, learning and the learning environment.

Data-Driven Learning Design is the use of the learning data to design courses and optimise learning and the learning environment.

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Trend use

While these are two separate elements of EdTech: Learning Analytics in Technology and Data-Driven Learning Design in Design - they are complimentary in their use in Digital Learning Design by interpreting and transforming the data into meaningful action that will improve learning and the overall success of the course.

Corporate organisations have been using analytics for many years to better understand their customers, products and improve performance. Learning Analytics can be used in similar ways in Digital Learning to give valuable insights into learner experience, learners and courses overall. Sales and Marketing techniques such as Digital Body Language can provide target data for learners that allow Digital Learning Designers to be responsive and adaptive to learners behaviours resulting in a positive learning experience.

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Trend information

Types of Learning Analytics

There is a vast amount of data that is readily available through an LMS or dedicated Learning Analytics software and platforms.

Diagnostic Analytics

Descriptive Analytics

Prescriptive Analytics

Predictive Analytics

Why something happened

Insights into past performance

Understanding the future

Likely to happen in the future

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Data points for digital learning

Learner Experience Analytics

Digital Body Language

Program Analytics

Learner Analytics

Online habits Learner behaviours

Usage patterns Learning activity

Specific person Specific group Cohort

Overall effectiveness of the program Strategic impact

impact on digital learning

When the learning data has been collected, measured and analysed it can be utilised for Data-Driven Learning Design.

DDLD

The data can be used to:

• Leverage decision making

• Design and diagnose learning needs

• Improve learner interactions and success

• Identify and resolve performance gaps

• Personalise learner pathways

• Optimise learning and the learning environment

• Enhance engagement and course impact

• Respond and adapt to learner behaviours

• Create a positive learner experience

Data-Driven Learning Design

DDLD 3 Phase Cycle

Uncover Insights (Learner Habits)

3 Phase Continuous Cycle

Proposed by Lori Niles-Hoffman (Data-Driven Learning Strategist)

Respond (Build Solutions)

Monitor (What Worked)

Rationale

I have chosen this complimentary technology and design trend because data analytics has featured heavily as a trend in my CIPD Learning and Development studies. I am conscious of having access to a vast amount of data and I am invested in learning how to fully utilise it to improve our processes and design impactful and engaging learning materials.

My Rationale

My working roles are part teaching and part library resource development. These involve design, creation and delivery of learning content and the development and re-design of resources with a current project on developing a digital induction course. Utilising the learning analytics available through the library database, current induction booking system and various staff and student surveys we have carried out, can help us to diagnose and design our new induction course. We could use the 3 phase model set out by Lori Niles-Hoffman to continuously learn about our students behaviours, respond to students needs and evaluate our programme.

Application to Practice

I can utilise the data available in our LMS Blackboard Ultra to understand more about my learners engagement and activity. I currently use Blackboard for assessment data and an overview of completed course work and performance. There is more data available that can provide insights into access, usage, content preference and time spent on activities. This will allow me to critically reflect on my approach and adapt resources to better meet the needs of my learners.

references

Omer, A. H., PhD. (2021, May 12). The Importance Of Learning Analytics In Learning And Development. eLearning Industry. https://elearningindustry.com/learning-analytics-benefits-ld

Finch, S. (2021, December 7). What is digital body language in learning and development? Thinqi. https://thinqi.com/resources/blogs/behind-the-screen-interpreting-digital-body-language-in-ld

What is Learning Analytics? (2021, March 24). Society for Learning Analytics Research (SoLAR). https://www.solaresearch.org/about/what-is-learning-analytics/

Niles, L. (2020, July 6). Continue your journey with data-driven learning - Data-Driven Learning Design. LinkedIn. https://www.linkedin.com/learning/data-driven-learning-design/continue-your-journey-with-data-driven-learning?autoplay=true&resume=false&u=42491124

Sampson, D. G. (2021, May 12). Learning Analytics: Analyze Your Lesson To Discover More About Your Students. eLearning Industry. https://elearningindustry.com/learning-analytics-analyze-lesson

Learning analytics in a nutshell. (2019, August 28). [Video]. YouTube. https://www.youtube.com/watch?v=XscUZ8dIa-8

Learning analytics in higher education. (2016, April 19). Jisc. https://www.jisc.ac.uk/reports/learning-analytics-in-higher-education