TY - GEN
T1 - Extending the AAT tool with a user-friendly and powerful mechanism to retrieve complex information from educational log data
AU - Kladich, Stephen
AU - Ives, Cindy
AU - Parker, Nancy
AU - Graf, Sabine
N1 - Funding Information:
The authors acknowledge the support of Athabasca University and NSERC.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Learning Analytics
KW - Learning Management System
KW - Log Data
UR - http://www.scopus.com/inward/record.url?scp=84879871681&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39146-0_31
DO - 10.1007/978-3-642-39146-0_31
M3 - Published Conference contribution
AN - SCOPUS:84879871681
SN - 9783642391453
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 334
EP - 341
BT - Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data - Third International Workshop, HCI-KDD 2013, Held at SouthCHI 2013, Proceedings
T2 - 3rd International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, HCI-KDD 2013, Held at SouthCHI 2013
Y2 - 1 July 2013 through 3 July 2013
ER -