Introducing NEURONE

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.

  • Search Engine Simulation

    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.

  • Interactions and data capturing

    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.

  • Distributed design

    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).

  • Custom flow and stages

    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 purpose

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.

Stages & Flows

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.

Currently available stages are:


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.

Critical Evaluation:

Users can rate web pages (e.g., credibility, relevance) and justify their ratings.


Users can write a brief text report of their findings.

Meet the Contributors

  • Roberto González-Ibáñez, PhD

    Researcher | UdeSantiago
  • Carita Kiili, PhD

    Researcher | U. Oslo
  • Eero Sormunen, PhD

    Researcher | U. Tampere
  • Daniel Gacitúa

    Software Engineer | UdeSantiago
  • Tuulikki Alamettälä

    Research Assistant | U. Tampere
  • Teemu Mikkonen

    Research Assistant | U. Tampere
  • María Teresa Escobar

    Research Assistant | UdeSantiago
  • Gonzalo Martínez

    Research Assistant | UdeSantiago
  • Polett Pizarro

    Software Developer | UdeSantiago
  • Javier Pinto

    Software Developer | UdeSantiago
  • Bastián Santana

    Software Developer | UdeSantiago
  • Álvaro Montecinos

    Software Developer | UdeSantiago


NEURONE's distribution packages, source code and manuals can be found below.

  • Node.js Package

    Ready to use package for Node.js environments

  • Docker Image

    Docker Image for production environments

  • Source Code

    Source Code for development

  • Experimenter's Manual

    The Experimenter's Manual includes general instructions for use in experiments and asset development

  • Sysadmin's Manual

    The Sysadmin's Manual includes the proper installation procedure of the NEURONE in development, staging and production environments

  • Developer's Manual

    The Developer's Manual includes general guidelines and tech specs to be considered while developing directly with the NEURONE API and the source code

The NEURONE Ecosystem

The NEURONE platform can be extended through modules. These modules interact with the NEURONE Core Module in order to implement new functionalities.


Some NEURONE stages can be seen below



Theses and Dissertations

  • Pizarro, P. (2019). Desarrollo de servicios de evaluación y recomendaciones de contenido web para asegurar la compatibilidad con lectores de pantalla. Undergraduate Thesis. Supervised by González-Ibáñez, R. Departamento de Ingenieria Informatica, Universidad de Santiago de Chile.


Short papers, Posters and Integrated Demos

  • Gacitúa, D., Martínez, G., González-Ibáñez, R. (2018). NEURONE-AM: Active monitoring platform for online inquiry skills evaluation. Presented at Congreso Internacional de Innovación e Investigación en Tecnología Educativa (ITIE 2018), Santiago, Chile, Nov. 26 - Nov. 28.


Conference Papers

  • Sormunen, E., González-Ibáñez, R., Kiili, C., Leppanen, P.H.T., Mikkila-Erdmann, M., Erdmann, N. & Escobar-Macaya, M. (2017). A Performance-based Test for Assessing Students Online Inquiry Competences in Schools. To be included in Proceedings of the Fifth European Conference on Information Literacy (ECIL), 18-21 September 2017, Saint-Malo, France. 10 pages.

Short papers, Posters and Integrated Demos

  • González-Ibáñez, R., Gacitúa, D., Sormunen, E., Kiili, C. (2017). NEURONE: oNlinE inqUiRy experimentatiON systEm. To be included in Proceedings of the 80th Annual Meeting of the Association for Information Science and Technology (ASIS&T 2017), Washington D.C., USA, Oct. 27 - Nov. 1.
  • Mikkila-Erdmann, M., Sormunen, E., Mikkonen, T., Erdmann, N., Kiili, C., Quintanilla, M., González-Ibáñez, R., Leppanen, P. & Vauras, M. (2017). A comparative study on learning and teaching online inquiry skills in Finland and Chile. To be presented at EARLI 2017, Tampere, Finland, Aug 29th - Sep 2nd.

Theses and Dissertations

  • Escobar-Macaya, M. (2017). Predicting and Clasifying Students Search Performance in Online Inquiry. Master Thesis. Supervised by González-Ibáñez, R. Departamento de Ingenieria Informatica, Universidad de Santiago de Chile.
  • Martínez, G. (2017). Exploiting Behavioral Data for Active Monitoring of Students' Search Process During Formal Training of Online Inquiry Skills. Master Thesis. Supervised by González-Ibáñez, R. Departamento de Ingenieria Informatica, Universidad de Santiago de Chile.


Theses and Dissertations

  • Gacitúa, D. (2016). NEURONE: oNlinE inqUiry expeRimentatiON systEm. Undergraduate Thesis. Supervised by González-Ibáñez, R. Departamento de Ingenieria Informatica, Universidad de Santiago de Chile.

Participating Institutions





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