# The LAVA Model: Learning Analytics Meets Visual Analytics

**Authors:** Mohamed Amine Chatti, Arham Muslim, Manpriya Guliani, Mouadh Guesmi  
**arXiv:** [2303.12392](https://arxiv.org/abs/2303.12392)  
**Date:** 2023-03-22  
**Summary page:** https://www.summarizepaper.com/en/paper/2303.12392v1/

## Key points

- The paper explores the benefits of incorporating visual analytics into learning analytics
- Human-centered learning analytics (HCLA) is important and involves users in all stages of design, analysis, and evaluation
- The Learning Analytics and Visual Analytics (LAVA) model is proposed as an enhancement to the learning analytics process with humans in the loop
- The LAVA model is applied in the Open Learning Analytics Platform (OpenLAP) to support human-centered indicator design
- Blending learning analytics and visual analytics can enhance acceptance and adoption based on the technology acceptance model (TAM)
- Visual analytics can foster acceptance of learning analytics through a multidisciplinary data science research field that follows a human-centered approach
- Incorporating visual analytics concepts into learning analytics can increase value and drive forward acceptance and adoption while meeting user needs through HCLA principles.

## Summary

The paper titled "The LAVA Model: Learning Analytics Meets Visual Analytics" explores the potential benefits of incorporating visual analytics concepts into the learning analytics process. The authors emphasize the importance of human-centered learning analytics (HCLA) that truly meets user needs and involves users in all stages of design, analysis, and evaluation. They propose the Learning Analytics and Visual Analytics (LAVA) model as an enhancement to the learning analytics process with humans in the loop. The LAVA model is applied in the Open Learning Analytics Platform (OpenLAP) to support human-centered indicator design. The authors evaluate how blending learning analytics and visual analytics can enhance acceptance and adoption based on the technology acceptance model (TAM). This paper aims to fill a gap by exploring how visual analytics can foster acceptance of learning analytics through a multidisciplinary data science research field that follows a human-centered approach. It highlights how incorporating visual analytics concepts into learning analytics can increase value and drive forward acceptance and adoption while meeting user needs through HCLA principles.