Learning Analytics Archives

Dec142022 by Joshua WeidlichNo Comments

New Pub: Causal Inference and Bias in Learning Analytics

Journal, Learning Analytics, Literature review, Open access, Publication, Research Methods

Learning Analytics is an applied field of research with the goal of producing actionable knowledge to improve student learning. This requires knowledge about cause-and-effect. However, randomized experiments, the usual vehicle for causality, are not always feasible nor desirable. Researchers are then left with observational data, from which they are, understandably, hesitant to draw causal inferences. Fortunately, there has been a lot of progress on the topic of causality in the last two decades. One prominent framework uses Directed Acyclic Graphs (DAGs) to graphically reason about cause-and-effect and/or bias. This primer, authored by Joshua Weidlich, Dragan Gasevic, and Hendrik Drachsler, published in the Journal of Learning Analytics, introduces DAGs to Learning Analytics. Using fictitious and published examples, we show how DAGs are a principled approach to a) improve causal inferences for…

Nov82022 by Daniele Di MitriNo Comments

New CfP: CROSSMMLA @ LAK 2023 Workshop

Multimodal Learning Analytics, Workshop

Call for Papers: CROSSMMLA @ LAK 2023 Workshop: Leveraging Multimodal Data for Generating Meaningful Feedback To be held face-to-face on March 13, 2023, in Arlington, Texas, United States, in conjunction with the LAK 2023 conference. The CROSSMMLA workshop series has focused on collecting and analysing multimodal data across the physical and virtual spaces for understanding and optimising learning processes. (more…)

Oct132021 by Prof. Dr. Hendrik DrachslerNo Comments

ALICE project workshop

Learning Analytics, Learning Design, School, Workshop

On 12/13 of October the EduTec Team finally hit the road again and met with the ALICE Project partners in Kiel at the IPN for the first post-pandemic f2f Workshop. Wuhuuuuuuuu! The purpose of the 2-day workshop was to work on an instructional model for designing and implementing instructional units in four domains – biology, chemistry, mathematics, and physics – and tracking students learning progression with learning analytics during these units. The units will be hybrid in that they will take place in regular classrooms but will involve students working through instructional activities involving digital media. Instruction will be led by a regular teacher but will have students continuously interact with a (tablet) computer. In order to be able to analyze students learning progression using learning analytics across the four…

May32021 by Prof. Dr. Hendrik DrachslerNo Comments

New Pub: Towards Automatic Collaboration Analytics for Group Speech Data Using Multimodal Learning Analytics

General education, Journal, Multimodal Learning Analytics, Open access, Publication

Collaboration is an important 21st Century skill. Co-located (or face-to-face) collaboration (CC) analytics gained momentum with the advent of sensor technology. Most of these works have used the audio modality to detect the quality of CC. The CC quality can be detected from simple indicators of collaboration such as total speaking time or complex indicators like synchrony in the rise and fall of the average pitch. Most studies in the past focused on “how group members talk” (i.e., spectral, temporal features of audio like pitch) and not “what they talk”. The “what” of the conversations is more overt contrary to the “how” of the conversations. Very few studies studied “what” group members talk about, and these studies were lab based showing a representative overview of specific words as topic clusters…