Multi-Source Educational Analytics Dataset for Student Performance and Contextual Analysis

This dataset is a unified analytical dataset containing 32,593 records, each representing a student’s participation in a specific course presentation. It is constructed by integrating multiple data sources, including internal academic activity data from the Open University Learning Analytics Dataset (OULAD), regional broadband speed statistics from Ofcom, and unemployment rates from the UK Office for National Statistics (ONS). The integration results in a comprehensive dataset that combines educational, behavioral, and socioeconomic perspectives into a single analytical structure .

The dataset represents the final Gold layer in a Medallion data architecture and is organized as a structured tabular dataset with 20 features. These features include a mix of numerical and categorical data types, capturing diverse aspects of student profiles. Each record contains demographic attributes such as gender, age group, education level, and region, alongside academic information including course module, year, term, number of previous attempts, and credits studied. Behavioral data is represented through interaction metrics within the Virtual Learning Environment (VLE), such as total clicks and accessed learning materials, as well as engagement indicators like submitted assessments.

In addition to internal academic data, the dataset incorporates external contextual variables, including regional unemployment rates and average broadband speeds. This enrichment enables the dataset to reflect not only individual academic behavior but also the broader environmental conditions that may influence student performance. Academic outcomes are represented through a binary variable indicating whether a student successfully completed the course or faced failure or withdrawal.

The dataset is provided in CSV format, ensuring compatibility with common data analysis environments such as Python, SQL-based systems, and standard machine learning frameworks. All data sources are publicly available and fully anonymized. Personal identifiers are not included, and external indicators are aggregated at the regional level, ensuring that individual privacy is preserved.

This integrated dataset supports comprehensive analysis of student engagement, performance, and contextual influences, making it suitable for educational analytics, data mining, and institutional research applications.