on-line learning environment for multilevel modelling fiona steele and sacha brostoff centre for...

On-line Learning Environment for Multilevel Modelling

Fiona Steele and Sacha BrostoffCentre for Multilevel Modelling

University of Bristol

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The LEMMA Project

A node of the ESRC-funded National Centre for Research Methods

LEMMA – Learning Environment for Multilevel Methodology and Applications

– www.cmm.bris.ac.uk

Research and training components

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LEMMA Training

Capacity building in the analysis of data with complex structure

– Ultimate goal is to move learners to “take-off”, i.e. conducting and publishing multilevel analyses

Different modes of delivery– Face-to-face workshops (3-day + 5-day with time allocated to

analysis of participants’ data)– Face-to-face workshop followed by on-line mentoring– Training for established networks (e.g. university departments)– Web-based materials in a virtual learning environment

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Lessons Learnt

Participants need to be motivated and have time to learn

– Best motivated are those with data and research questions that can be addressed through MLM

Experience of on-line follow-up and targeting established groups disappointing

Participants often do not possess pre-requisites for MLM (good understanding of multiple regression)

In practical sessions, tendency to focus on mechanics of using software rather than interpretation

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Basic Principles

Accessible to anyone with basic statistics training (up to simple regression)

Modules to have 2 integrated components: concepts and practice

Facility for learner’s self-evaluation

– Pre-requisite quiz, and regular quizzes throughout materials

Collect data to evaluate materials and inform future training initiatives

– Basic user profile information collected on registration

– Quiz responses, webstats on patterns of use

Design materials so they can be easily modified by other trainers

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Types of Material

5-minute video giving overview of content

Prerequisites with links to other online resources

2 linked documents: (i) Concepts and methods, and (ii) practice (MLwiN instructions with interpretation of output)

Quiz questions

Further reading (published research and other online resources)

Glossary

For each module:

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Structure of Linked Documents

Concepts – 30-40 pages, split into lessons– Illustrative examples from mix of disciplines– Draw links between fitted model equations, graphs of

predictions and verbal interpretation – No reference to software– Expect other trainers to use with little change

Practice– Each Concepts lesson followed by exercises in MLwiN– Thorough analysis and interpretation of one dataset– Trainers can rewrite for other datasets and software

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Core Materials

1. Types of variable2. Introduction to statistical modelling3. Multiple regression (single-level)4. Data structures5. Multilevel modelling of continuous data6. Logistic regression (single-level)7. Multilevel logistic regression

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Future Materials

Substantive examples linked to core materials

Models for other types of outcome

– Nominal, ordinal, counts, duration

Models for non-hierarchical structures

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The LEMMA VLE

Moodle Open source, widely used

– Open University is involved in it’s development

Has a good licensing model– Avoids annual fees– No restrictions on how many users– Sustainable

Does everything we need

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Demonstrating the prototype

Encouraging engagement– Video overviews– Quizzes– Straw polls– ML Driver’s Licence

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Further work

Improving navigation Pilot testing Link in to the follow up to Athens Link administration with MLwiN UK free

version More question types Certainty based marking