LA – Learning Analytics

LA@IV2024 – 8th  International Symposium Learning Analytics

Worldwide, the use of technology in all fields of education is at a historical high. The pandemic situation boosted the growth of education in the online context: online learning is becoming an essential part of the educational landscape.

Learning Analytics has always been a measurement of data about learners and their contexts for understanding and optimizing learning and the environments in which it occurs. It is a combination of educational research, assessment sciences, statistics, visualization, data sciences, artificial intelligence, and socio-technical system thinking for human-centered design.

Educational concepts and practices can be enhanced and put on trial by means of theories and techniques of Learning Analytics. Learning Analytics can support educational practices to reach better results in any learning context, from traditional learning in less technological areas to personalized and adaptive e-learning, extending its usefulness to social-wide learning-on-demand applications.

In order to perform and develop Learning Analytics, current data science and intelligent systems should be introduced in addition to the conventional instruction/learning systems, theories, and practices.

At this stage of its evolution, Learning Analytics requires transparency and an “easy to grasp” feeling, such as the visualization process of the educational data can produce.

The interaction between Learning Analytics and Information Visualization may produce a new concept of educational innovation.

The Learning Analytics Symposium within the Information Visualization Conference LA@IV2024 aims to bring together researchers from a number of disciplines (e.g., Education, Computer Science, and Artificial Intelligence in particular, Management, Psychology, Economics, CyberSecurity, and Data Governance), practitioners, students, policymakers and companies to share and discuss the latest research insights related to Learning Analytics and its interaction with Information Visualization.

Therefore, we welcome submissions from both research and practice, encompassing different theoretical, methodological, empirical, and technical contributions to the Learning Analytics field. Academics and practitioners who are interested in such topics should consider submitting their research work and attending this event.

The topics of interest include but are not limited to:

Learning Analytics and AI

• AI for Education [Learning, Teaching, Intelligent Assessment and Feedback]
• AI-supported educational resources
• AI virtual personal assistants

Learning & Teaching Tracking

• Temporal Analysis of Learning Data
• Tools for quality assurance and quality improvement
• Tools for Boosting Retention Rate
• Tools for adaptive learning
• Tools to improve teaching quality
• Emotional and expression for cognitive condition learning
• Learning activity and eye movements
• Learning activity and behavioural / bio signals

Learning Analytics for Education

• Data Science for Education: open data, big data
• Machine and Deep Learning for Education
• Educational Data Mining
• Platforms and Tools for Educational Data
• Analytics for Teaching and learning methodologies supporting departments and schools  for education

Learning strategies

• Self-regulated learning
• Instructional designs
• Peer support & assessment
• Collaborative learning
• Team-based learning
• Generic skills / Key competence
• Literacy development/assessment
• Cultural difference

Evaluation theories and techniques

• Test theory
• Item Response Theory
• Learning activities
• Performance assessment
• Essay document text analysis
• Motivation assessment
• Self Efficacy
• Conceptual mapping
• Portfolio
• Educational indicators
• Game-Based Learning / Gamification

Technical infrastructures and platforms for Learning Analytics

• E-Learning
• M-Learning
• Platforms for MOOC management
• Personalised and Adaptive Learning systems
• Learning analytics warehouse
• Data Science Platforms for Learning Analytics

Issues in Data-Driven Educational Theories and Models

• Automate assessment
• Automate Essay / Report assessment
• Prediction of learning performance and engagement
• Educational Database / Datashare
• Ethics and privacy in learning analytics