Kirjojen hintavertailu. Mukana 12 595 353 kirjaa ja 12 kauppaa.

Kirjailija

Hendrik Drachsler

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuosilta 2012-2020, suosituimpien joukossa Recommender Systems for Learning. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

2 kirjaa

Kirjojen julkaisuhaarukka 2012-2020.

Learning Analytics Cookbook

Learning Analytics Cookbook

Roope Jaakonmäki; Jan vom Brocke; Stefan Dietze; Hendrik Drachsler; Albrecht Fortenbacher; René Helbig; Michael Kickmeier-Rust; Ivana Marenzi; Angel Suarez; Haeseon Yun

Springer Nature Switzerland AG
2020
nidottu
This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels. While the majority of existing literature on the subject focuses on its application at large corporations, this book develops and showcases approaches that bring LA closer to smaller organizations, and to educational institutions that lack sufficient resources to implement a full-fledged LA infrastructure. In closing, the book introduces a set of software tools for data analytics and visualization, and explains how they can be employed in several LA scenarios.
Recommender Systems for Learning

Recommender Systems for Learning

Nikos Manouselis; Hendrik Drachsler; Katrien Verbert; Erik Duval

Springer-Verlag New York Inc.
2012
nidottu
Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.