To start with learning analytics you first need to have some recourses to begin with. First thing you need to have some data. After having a dataset at hand, you need get some information out of the data and transform it into knowledge. However, processing raw data without any easy-to-use tools can be a difficult and very time-consuming task. Therefore, we have identified and gathered both datasets and tools for learning analytics as recources that you could start experimenting with.
It is our vision to collect more datasets and tools like these in this initial collection, and connecting new research outcomes to them.
Datasets
The collection of datasets is a selection distilled from the content of the AFEL Data Catalogue (http://data.afel-project.eu/catalogue/), and the Linked-Up catalogue (https://linkededucation.wordpress.com/).
- The AFEL Data Catalogue is a compilation of data resources from various origins especially focusing on online, social and informal learning, that can be used in learning analytics research. As such, it includes mostly two types of datasets; metadata of online resources used for learning, and traces of learners’ activities online in different environments. The first public release of static snapshot datasets was obtained from crawling repositories of resources (such as LRMI, Web of Know How, DBLP, etc.), as well as from extracting historic data from dynamic sources at a given time point (AFEL Deliverable D2.2).
- The LinkedUp Catalogue of Web datasets for education is a meta-dataset dedicated to supporting people and applications in discovering, exploring and using Web data for the purpose of innovative, educational services. It is also an evolving dataset, with most of its content being contributed by automatically extracting relevant information from external descriptions and the included datasets themselves. More detailed information about the LinkedUp Catalogue can be found in the paper Mathieu d’Aquin et al., (2014), www.semantic-web-journal.net/system/files/swj860.pdf
The goal of the “Datasets” section is to collect selected Learning Analytics datasets related to the field of education and make them available for teachers and researchers to get to a more open access data-driven research community within learning analytics. The page provides the links to the corresponding snapshots as of November 2017.
The datasets in this collection can be downloaded individually as dumps in RDF format. The collection of selected learning analytics datasets can be filtered according to specific categories which might address the interest of different types of users.
Tools and Pointers
There are various tools on the market that can help visualizing and analyzing data collected from students learning activities. Many of them provide multiple functionalities, which often are not all needed in the end. Some of these software products for learning analytics also require paying license fees. Therefore, these solutions might not even be an option for many universities, especially for the smaller ones with less available data and resources. However, applying learning analytics only for some specific purposes, instead of buying a complete solution is also possible without buying these complete solutions.
In this page we have gathered the source for some tools and pointers that could be good options try out, even when the digital data from students and available resources to apply learning analytics are limited. The provided links direct you to websites where you can find more information, and register as a user or download the tools. With learning analytics it is first good to start experimenting with some simple solutions. When you see the value it can bring for your purposes, then you can start implementing more and more complex solutions.