NEURONE is a software platform oriented to provide a research and data capture environment for information literacy studies. NEURONE is designed to be efficient, distributed and customizable. NEURONE is powered by Meteor, Node.js, MongoDB and Solr.
NEURONE's main component is a search engine simulation in a isolated environment, where users can browse in a limited (and predetermined) web document set, in order to test their online inquiry skills.
NEURONE captures usage information from the user in every simulation run. Some relevant data being captured are visited links, bookmarks, text snippets, formulated queries, mouse movements, mouse clicks and keystrokes.
NEURONE is designed using the client-server distributed model. This means that a single server instance (connected to the Internet) could serve user simulations in almost any user computer around the world (through a web browser).
NEURONE uses a linear flow of stages in order to build a experiment. These flows and stages can be customized and new HTML assets can be added. NEURONE also has i18n support.
NEURONE is an effort to build a complete data capuring tool for online inquiry studies being easy to deploy and simple to customize. NEURONE allows the application of experiments remotely requiring only a computer with internet connection. NEURONE's isolated environment ensures experimental control over the study.
NEURONE was originally designed to support data capturing of iFuCo Project and other related research instances. In order to allow the replication of these experiments and encourage information literacy and online inquiry studies, NEURONE is released as open source software.
NEURONE offers a linear flow experience for users running the tests. Flows are formed by stages in any established order and they could have time limit or not. These stages can be customized using HTML assets or directly on the source code.
Multiple choice, single line text, paragraph text and star rating questions are available.
Provides a search engine simulation, where users can bookmark their relevant pages.
Users can select text snippets from bookmarked pages.
Users can rate web pages (e.g., credibility, relevance) and justify their ratings.
Users can write a brief text report of their findings.
Roberto González-Ibáñez, PhD
Researcher | UdeSantiagoCarita Kiili, PhD
Researcher | U. OsloEero Sormunen, PhD
Researcher | U. TampereDaniel Gacitúa
Software Engineer | UdeSantiagoTuulikki Alamettälä
Research Assistant | U. TampereTeemu Mikkonen
Research Assistant | U. TampereMaría Teresa Escobar
Research Assistant | UdeSantiagoGonzalo Martínez
Research Assistant | UdeSantiagoPolett Pizarro
Software Developer | UdeSantiagoJavier Pinto
Software Developer | UdeSantiagoBastián Santana
Software Developer | UdeSantiagoÁlvaro Montecinos
Software Developer | UdeSantiagoNEURONE's distribution packages, source code and manuals can be found below.
The NEURONE platform can be extended through modules. These modules interact with the NEURONE Core Module in order to implement new functionalities.
This module is designed to support users with vision impairment, users with dyslexia and web designers to know the compatibility degree of a web site with screen readers (whether they are software or hardware). NEURONE-SC can determine the degree of compatibility of a web site (based on its URL) with screen readers and identify non-compatible code sections. NEURONE-SC can be used either as a standalone module or integrated with NEURONE.
Developed by: Polett Pizarro Source code: (coming soon)
NEURONE-Store is a standalone module that complements the original NEURONE Admin Panel in order to create assets and experimental flows for NEURONE. This module is built thinking in simplicity and user experience in order to ease the generation of content for NEURONE by researchers and teachers. NEURONE-Store also allows sharing assets between users in a same instance and all generated flows can be packaged for use in NEURONE.
Developed by: Bastián Santana Source code: (coming soon)
This module takes advantage of the rich interaction logging features of NEURONE by adding a monitor to data registered in NEURONE and parsing this data into machine learning algorithms in order to get accurate and real time performance metrics of NEURONE users. This module is intended to be a companion for information literacy lecturing for researchers and teachers.
Developed by: Javier Pinto Source code: (coming soon)This module allows the use of multimedia elements (like images, videos and maps) while searching in NEURONE. Originally, NEURONE only allowed text documents as part of the indexing and search process. NEURONE-MS takes advantage of Solr multimedia features in order to make a richer (and more realistic) search experience for NEURONE users.
Developed by: Álvaro Montecinos Source code: (coming soon)Some NEURONE stages can be seen below
