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Enda Ridge - One of the best experts on this subject based on the ideXlab platform.

  • guerrilla Analytics challenges and risks
    Guerrilla Analytics#R##N#A Practical Approach to Working with Data, 2015
    Co-Authors: Enda Ridge
    Abstract:

    In this chapter, we describe Guerrilla Analytics Projects in more detail. We will discuss the typical workflow and challenges encountered in Guerrilla Analytics Projects. These challenges bring risks. We will discuss the risks inherent in a Guerrilla Analytics Project and the effects and consequences of not managing these risks.

  • guerrilla Analytics principles
    Guerrilla Analytics#R##N#A Practical Approach to Working with Data, 2015
    Co-Authors: Enda Ridge
    Abstract:

    This chapter describes the Guerrilla Analytics Principles. These are a small number of guiding rules to address the challenges and risks of a Guerrilla Analytics Project as introduced in the previous chapter. After describing each of the principles, we then look at the type of management framework within which these principles can be applied to real-world Analytics Projects.

  • introducing guerrilla Analytics
    Guerrilla Analytics#R##N#A Practical Approach to Working with Data, 2015
    Co-Authors: Enda Ridge
    Abstract:

    In this chapter, we begin by discussing the very broad field of data Analytics and what it means to do data Analytics. To help us frame the subject of this book and escape any marketing and hype terminology, we will define what “data Analytics” means for us . We will then look at the various types of Projects in which data Analytics is performed. This will give us an understanding of the entire spectrum of data Analytics Projects. We describe the particular type of Analytics Project that are the subject of this book. Specifically, these Projects are defined by being very dynamic and having many disruptions while also being subject to several constraints. These are “Guerrilla Analytics” Projects.

  • Chapter 17 – Process
    Guerrilla Analytics, 2015
    Co-Authors: Enda Ridge
    Abstract:

    On many occasions throughout this book you have learned about the dynamics and disruptions in a Guerrilla Analytics Project environment. In a team of anything more than three people, this complexity can quickly become overwhelming. Managers become swamped with reviews and cannot take a forward-looking view on the Project’s direction to identify new opportunities. Workflow management is the software and technique for tracking the various activities of a team and the current state those activities are in. This chapter will describe the workflows that are useful in Guerrilla Analytics Projects. The information about work products that needs to be captured is described. The factors that influence a decision on using workflow management in a Guerrilla Analytics Project are laid out.

  • emerging principles for guerrilla Analytics development research in progress
    2012
    Co-Authors: Enda Ridge, Edward Curry
    Abstract:

    Analytics Projects come in many forms, from large-scale multi-year Projects to Projects with small teams lasting just a few weeks. There is a particular type of Analytics Project identified by some unique challenges. A team is assembled for the purposes of the Project and so team members have not worked together before. The Project is short term so there is little opportunity to build capability. Work is often done on client systems requiring the use of limited and perhaps unfamiliar tools. Deadlines are daily or weekly and the requirements can shift repeatedly. Outputs produced in these circumstances will be subject to audit and an expectation of full reproducibility. These are 'guerrilla Analytics' Projects. They necessitate a versatile and fast moving Analytics team that can achieve quick Analytics wins against a large data challenge using lightweight processes and tools. The unique challenges of guerrilla Analytics necessitate a particular type of data Analytics development process. This paper presents research in progress towards identifying a set of development principles for fast paced guerrilla Analytics Project environments. The paper’s principles cover 4 areas. Data Manipulation principles describe the environment and common services needed by a guerrilla Analytics team. Data Provenance principles describe how data should be logged, separated and version controlled. Coding and Testing principles describe how code should be structured and outputs tested. All these principles focus on lightweight processes for overcoming the challenges of a guerrilla Analytics Project environment while meeting the guerrilla Analytics requirement of auditability and reproducibility.

Leire Nuere - One of the best experts on this subject based on the ideXlab platform.

  • Exploring Student Activity with Learning Analytics in the Digital Environments of the Nebrija University
    Technology Knowledge and Learning, 2019
    Co-Authors: Patricia Ibanez, Cristina Villalonga, Leire Nuere
    Abstract:

    The main objective of educational institutions is to achieve the integral development of their students in their learning and knowledge construction process. One way to achieve these objectives is the accompaniment and continuous monitoring of students in this process, adapting the methods to their training needs. In online and mixed teaching modalities (eLearning methodology), this monitoring is carried out through the digital platforms in which it is carried out in the academic activity, such as the learning management system platforms. These virtual teaching and learning environments (EVA) allow access to learners’ fingerprints, generating a large volume of data, that analysis allows a deep way of their behavior in those policies. This article collects the results of the exploration of student activity in the virtual campus (Blackboard Learn), which is in the first phase of Learning Analytics Project carried out by the Nebrija University and discusses its implications for educational institutions. The data extracted correspond to the 2016–2017 course and have been analyzed around four blocks of information: user behavior, user activity, activity in the content areas and activity in the forums.

Patricia Ibanez - One of the best experts on this subject based on the ideXlab platform.

  • Exploring Student Activity with Learning Analytics in the Digital Environments of the Nebrija University
    Technology Knowledge and Learning, 2019
    Co-Authors: Patricia Ibanez, Cristina Villalonga, Leire Nuere
    Abstract:

    The main objective of educational institutions is to achieve the integral development of their students in their learning and knowledge construction process. One way to achieve these objectives is the accompaniment and continuous monitoring of students in this process, adapting the methods to their training needs. In online and mixed teaching modalities (eLearning methodology), this monitoring is carried out through the digital platforms in which it is carried out in the academic activity, such as the learning management system platforms. These virtual teaching and learning environments (EVA) allow access to learners’ fingerprints, generating a large volume of data, that analysis allows a deep way of their behavior in those policies. This article collects the results of the exploration of student activity in the virtual campus (Blackboard Learn), which is in the first phase of Learning Analytics Project carried out by the Nebrija University and discusses its implications for educational institutions. The data extracted correspond to the 2016–2017 course and have been analyzed around four blocks of information: user behavior, user activity, activity in the content areas and activity in the forums.

Alberto E. Tozzi - One of the best experts on this subject based on the ideXlab platform.

  • The use of web Analytics combined with other data streams for tailoring online vaccine safety information at global level: The Vaccine Safety Net’s web Analytics Project
    Vaccine, 2020
    Co-Authors: Francesco Gesualdo, Francesco Marino, Jas Mantero, Andrea Spadoni, Luigi Sambucini, Giammarco Quaglia, Caterina Rizzo, Isabelle Sahinovic, Patrick L.f. Zuber, Alberto E. Tozzi
    Abstract:

    The Vaccine Safety Net's Web Analytics Project (VSN-WAP) was launched in October 2017 to monitor the behavior of users visiting websites belonging to the VSN, a global network of websites providing science-based information on vaccine safety. Participating websites could provide web metrics in two ways: through a Google Analytics (GA) script, which automatically forwarded metrics to a central account and through manual input (MI) of a reduced subset of metrics (Sessions, Page Views, New Users, Bounce Rate, Views/Session and Average Session Duration), which were pooled with the metrics obtained through GA. Additional metrics were obtained from websites providing data through Google Analytics (Country, Age, Sex, Device). We report results from February 2018 to March 2019. In March 2019, 32 websites were participating in the Project (21 through GA, 11 through MI). From February 2018 to March 2019 we recorded 22,471,535 sessions, with 38,307,349 page views. Sessions, New Users and Page views progressively increased, Views/Session, Bounce Rate and Average Session Duration remained stable. Most users were female (68%) and belonged to the 25-34 age range (37%), followed by 35-44 (22%) and 18-24 (19%). Fifty-four percent of users connected from a mobile device, 42% from a desktop and 4% from a tablet. Digital media monitoring techniques can provide insights on the characteristics of users with a specific interest in vaccines. These data can be exploited to improve the performance of websites providing information on vaccines to the general public.

Cristina Villalonga - One of the best experts on this subject based on the ideXlab platform.

  • Exploring Student Activity with Learning Analytics in the Digital Environments of the Nebrija University
    Technology Knowledge and Learning, 2019
    Co-Authors: Patricia Ibanez, Cristina Villalonga, Leire Nuere
    Abstract:

    The main objective of educational institutions is to achieve the integral development of their students in their learning and knowledge construction process. One way to achieve these objectives is the accompaniment and continuous monitoring of students in this process, adapting the methods to their training needs. In online and mixed teaching modalities (eLearning methodology), this monitoring is carried out through the digital platforms in which it is carried out in the academic activity, such as the learning management system platforms. These virtual teaching and learning environments (EVA) allow access to learners’ fingerprints, generating a large volume of data, that analysis allows a deep way of their behavior in those policies. This article collects the results of the exploration of student activity in the virtual campus (Blackboard Learn), which is in the first phase of Learning Analytics Project carried out by the Nebrija University and discusses its implications for educational institutions. The data extracted correspond to the 2016–2017 course and have been analyzed around four blocks of information: user behavior, user activity, activity in the content areas and activity in the forums.