This applet aims to provide a visual tool for examining different critical valuesand provide insights into the evaluation of a concept map’s quality and itsvisual representation. We focus on salience metrics to assess and help usersenhance the effectiveness of their concept maps with an evaluation of itsquality.

The applet features an Interactive Graph Visualization by leveraging thePython library “dash-interactive-graphviz”, allowing the user to seamlesslyzoom in or out, to check in an easy manner the different graph layouts thatthe user can choose. It also allows the user to click on nodes to get specificmetrics and information of the node. Although two sample concept maps areprovided and the user can explore them, it also allows the user to upload aCSV file to the applet for working with its custom concept maps.Furthermore, the applet has multiple buttons with question marks that whenclicked, displays information about the usage and the shown metrics. By usingBootstrap, the applet has a responsive design and allows using it insmartphones.

Thus, the user can visualize the following metrics for a given concept map:

• Number of nodes and edges.
• Selected node and its descendants.
• Selected GraphViz layout engine (and the ability to change it)
• Number of dummy nodes generated for the visualization.
• Number of Crossings between edges.
• Median of the Manhattan Distance between the related edges.

Concept map, Concept lattice, Application, Feature engineering, Human–Computer Interaction, Measuring students, Mobile learning adoption,technology adoption, Benchmark, Heuristics