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- 1. Systematic reviews/insight reports
A qualitative and quantitative literature review with the aim of answering a particular question.
Example: an organisation may wish to determine whether early intervention maths programmes improve attainment in at-risk pupils. The student would compile a systematic literature review of the existing evidence and apply relevant meta-analytic methods to answer this question.
- 2. Analysis of existing data
An independent analysis of existing data provided by the research partner that addresses a novel question and leverages the analytic skills of the UCL student.
Example: a market research company wants to know how memorable television adverts are, and has data on consumers’ emotional engagement with these ads. The student would apply existing psychological theories and models, combined with Big Data analytic techniques, to determine whether emotional engagement predicts memory for adverts and to what extent.
- 3. Novel data collection
A new study is designed, conducted and analysed to address a specific research question.
Example: An insurance company wants to know whether the price of a mobile phone affects a customer’s willingness-to-pay for insurance. They collaborate with the student to design an experiment to answer this question. The student collects and analyses the data, and evaluates the results.
Where appropriate, BIX projects can involve more than one student. In cases such as this, our industry partner will be presented with a single report at the end of the project.
We cannot offer BIX projects with the NHS that require clinical research. However, other NHS projects may be suitable.
Finally, these projects provide access to UCL expertise and resources in the form of more extensive research partnerships such as funded PhD studentships (e.g. CASE, Impact, and others), consulting opportunities for academics (UCLC), clinical trials, and via research projects. In other words, the BIX project is an easy method to develop a broader operational and/or strategic partnership with UCL.
