Learning Analytics & Knowledge Conference 2020
About this event
- Conferences & Conventions
- Mar 23, 2020, 9:00:00 AM
- Mar 27, 2020, 5:00:00 PM
- University of Frankfurt, Germany
10th Annual International Conference on Learning Analytics & Knowledge (LAK) - https://lak20.solaresearch.org/
The 2020 edition of The International Conference on Learning Analytics & Knowledge (LAK20) will take place in Frankfurt, Germany. LAK20 is organised by the Society for Learning Analytics Research (SoLAR) and hosted by Frankfurt Goethe-University in Germany with support from many European partners. LAK20 is a collaborative effort by learning analytics researchers and practitioners to celebrate and promote the achievements of the learning analytics community over the past ten years and to look forward to what lies ahead.
The tenth anniversary of the LAK conference celebrates the past successes of the learning analytics community and poses new questions and challenges for the field. The theme for this year is “Shaping the future of the field” and focuses on thinking how we can advance learning analytics and drive its development over the next ten years and beyond.
Some of the topics of interest include, (but are not limited) are:
1. Capturing Learning & Teaching:
- Finding evidence of learning: Studies that identify and explain useful data for analysing, understanding and optimising learning and teaching.
- Assessing student learning: Studies that assess learning progress through the computational analysis of learner actions or artefacts.
- Analytical and methodological approaches: Studies that introduce analytical techniques, methods, and tools for capturing and modelling student learning.
- Technological infrastructures for data storage and sharing: Proposals of technical and methodological procedures to store, share and preserve learning and teaching traces.
2. Understanding Learning & Teaching:
- Data-informed learning theories: Proposals of new learning/teaching theories or revisions/reinterpretations of existing theories based on large-scale data analysis.
- Insights into specific learning processes: Studies to understand particular aspects of a learning/teaching process through the use of data science techniques.
- Learning and teaching modeling: Creating mathematical, statistical or computational models of a learning/teaching process, including its actors and context.
- Systematic reviews: Studies that provide a systematic and methodological synthesis of the available evidence in an area of learning analytics.
3. Impacting Learning & Teaching:
- Providing decision support and feedback: Studies that evaluate the impact of feedback or decision-support systems based on learning analytics (dashboards, early-alert systems, automated messages, etc.).
- Practical evaluations of learning analytics efforts: Empirical evidence about the effectiveness of learning analytics implementations or educational initiatives guided by learning analytics.
- Personalised and adaptive learning: Studies that evaluate the effectiveness and impact of adaptive technologies based on learning analytics.
4. Implementing change in Learning & Teaching:
- Ethical issues around learning analytics: Analysis of issues and approaches to the lawful and ethical capture and use of educational data traces; tackling unintended bias and value judgements in the selection of data and algorithms; perspectives and methods for value-sensitive, participatory design that empowers stakeholders.
- Learning analytics adoption: Discussions and evaluations of strategies to promote and embed learning analytics initiatives in educational institutions and learning organisations.
5. Learning analytics strategies for scalability:
- Discussions and evaluations of strategies to scale the capture and analysis of information at the program, institution or national level; critical reflections on organisational structures that promote analytics innovation and impact in an institution.