Abstract
This paper proposes a traces model in the form of an object or class model (in the UML sense) which allows the automatic calculation of indicators of various kinds and independently of the computer environment for human learning (CEHL). The model is based on the establishment of a trace-based system that encompasses all the logic of traces collecting and indicators calculation. It is im-plemented in the form of a trace database. It is an important contribution in the field of the exploitation of the traces of apprenticeship in a CEHL because it pro-vides a general formalism for modeling the traces and allowing the calculation of several indicators at the same time. Also, with the inclusion of calculated indica-tors as potential learning traces, our model provides a formalism for classifying the various indicators in the form of inheritance relationships, which promotes the reuse of indicators already calculated. Economically, the model can allow organi-zations with different learning platforms to invest only in one traces Management System. At the social level, it can allow a better sharing of trace databases be-tween the various research institutions in the field of CEHL.
Highlights
A digital trace of interaction is a temporally located series of observations [1] [4] which is either an interaction between humans, mediated in various ways by computer, or a series of actions and reactions between a human and a computer
We rely on the process of calculating indicators from a trace model to build our trace model
We have presented a theoretical and practical framework for automatically calculating different types of indicators in a Computer Environment for Human Learning (CEHL) context
Summary
A digital trace of interaction is a temporally located series of observations [1] [4] which is either an interaction between humans, mediated in various ways by computer, or a series of actions and reactions between a human and a computer. There are several types of traces (computer data, screenshots, audio, videos). They are categorized according to the tools that are used for capturing and collecting the observed interactions. In a computer environment for human learning (CEHL), there are three facets of use of traces of interactions, namely: empirical studies on the characteristics of human interactions, reengineering of CEHLs and adaptation of interactions in real time. The appropriate modeling of interaction traces allows teachers to design and automate the calculation of indicators, which in turn will help them understand, assess, monitor and support ongoing learning.
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