Extending the AAT tool with a user-friendly and powerful mechanism to retrieve complex information from educational log data

Stephen Kladich, Cindy Ives, Nancy Parker, Sabine Graf

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

6 Citations (Scopus)

Abstract

In online learning, educators and course designers traditionally have difficulty understanding how educational material is being utilized by learners in a learning management system (LMS). However, LMSs collect a great deal of data about how learners interact with the system and with learning materials/activities. Extracting this data manually requires skills that are outside the domain of educators and course designers, hence there is a need for specialized tools which provide easy access to these data. The Academic Analytics Tool (AAT) is designed to allow users to investigate elements of effective course designs and teaching strategies across courses by extracting and analysing data stored in the database of an LMS. In this paper, we present an extension to AAT, namely a user-friendly and powerful mechanism to retrieve complex information without requiring users to have background in computer science. This mechanism allows educators and learning designers to get answers to complex questions in an easy understandable format.

Original languageEnglish
Title of host publicationHuman-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data - Third International Workshop, HCI-KDD 2013, Held at SouthCHI 2013, Proceedings
Pages334-341
Number of pages8
DOIs
Publication statusPublished - 2013
Event3rd International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, HCI-KDD 2013, Held at SouthCHI 2013 - Maribor, Slovenia
Duration: 1 Jul. 20133 Jul. 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7947 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, HCI-KDD 2013, Held at SouthCHI 2013
Country/TerritorySlovenia
CityMaribor
Period1/07/133/07/13

Keywords

  • Learning Analytics
  • Learning Management System
  • Log Data

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