A Study on the Possibility of Automatically Estimating the Confidence Value of Students’Knowledge in Generated Conceptual Models

Abstract

<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; layout-grid-mode: char;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">We propose a new metric to automatically evaluate the confidence that a student knows a certain concept included in his or her conceptual model. The conceptual model is defined as a simplified representation of the concepts and relationships among them that a student keeps in his or her mind about an area of knowledge. Each area of knowledge comprises several topics and each topic several concepts. Each concept can be identified by a term that the students should use. A concept can belong to one topic or to several topics. Terms are automatically extracted from the answers provided to an automatic and adaptive free-text scoring system using Machine Learning techniques. In fact, the conceptual model is fully generated from the answers provided by the students to this system. In the paper, the automatic procedure that makes it possible is reviewed in detail. Finally, concept maps are used to graphically display the conceptual model to teachers and students. In this way, they can instantly see which concepts have already been assimilated and which ones should still be reviewed.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p&gt

Navigation support in complex open learner models: assessing visual design alternatives

“…Examples of more detailed, structured visualizations which use color or size of nodes to represent concepts include concept maps (e.g. Pérez-Marín, Alfonseca, Rodríguez, & Pascual-Neito, 2007), proficiency maps (e.g. Zapata-Rivera, Hansen, Shute, Underwood, & Bauer, 2007) and hierarchical trees (e.g.…”

“…Mazzola & Mazza, 2010;Shi & Cristea, 2016), and concept maps (e.g. Duan et al, 2010;Pérez-Marín et al, 2007). Prototypes were created based on initial thoughts about manageable complexity (e.g., limiting amount of depth shown in the concept maps).…”

SMILI☺: a Framework for Interfaces to Learning Data in Open Learner Models, Learning Analytics and Related Fields

“…This increase in their use has continued both in the more traditional adaptive teaching systems, such as constraint-based tutors (Duan et al 2010) and cognitive tutors (Long and Aleven 2013); and in systems using newer technologies and displays, for example: open social learner models (Brusilovsky et al 2011); using Facebook to discuss learner model contents (Alotaibi and Bull 2012); e-portfolio and independent OLMs (Raybourn and Regan 2011); OLMs in MOOCs (Cook et al 2015); systems taking data for an independent OLM from a variety of applications (Bull et al 2012). In addition to more traditional learner model visualisations such as skill meters (e.g., Corbett and Bhatnagar 1997;Mitrovic and Martin 2007) and concept maps (e.g., Mabbott and Bull 2004;Perez-Marin et al 2007;Rueda et al 2003), innovative visualisation methods have been deployed, such as treemaps (Brusilovsky et al 2011;Johnson et al 2013;Kump et al 2012) and word or tag clouds (Johnson et al 2013;Mathews et al 2012). Therefore, interest in OLMs has been maintained as systems embrace the opportunities that new technologies offer for learning.…”

“…For example, rather than viewing the underlying system rules or complex knowledge representations, users can be presented with views of this learner model data in interfaces that have been designed to support learning. This has been described for learner models inferred using a variety of modelling approaches, e.g., Bayesian networks (Zapata-Rivera and Greer 2004a, b); concept mapping (Perez-Marin et al 2007); constraint-based modelling (Mitrovic and Martin 2007); and simpler weighted algorithms (Johnson et al 2013). In principle, any type of learner model can be opened to users, and the method of presenting the learner model may depend on:…”

Fine-Grained Open Learner Models

“…[26,30]), and concept maps (e.g. [11,24,29]). Although the prototypes were presented as paper mock-ups to subjects, we described them to subjects as functional prototypes with some interactivity features (e.g.…”