Monique Grandbastien

Modeling Tutoring Knowledge

This chapter introduces Part II on modeling tutoring knowledge in ITS research. Starting with its origin and with a characterization of tutoring, it proposes a general definition of tutoring, and a description of tutoring functions, variables, and interactions. The Interaction Hypothesis is presented and discussed, followed by the development of the tutorial component of ITSs, and their evaluation. New challenges are described, such as integrating the emotional states of the learner. Perspectives of opening the Tutoring Model and of equipping it with social intelligence are also presented.

Computer Science Education in French Secondary Schools: Historical and Didactical Perspectives

Computer science as a school subject in France is characterized by a succession of promising starts that have not yet been transformed into perennial solutions. The main goal of this article is to analyze this complex situation from a historical perspective, and describe the current rebirth of an optional Computer Science course in the last year of secondary education, together with other initiatives that might contribute to introducing Computer Science as a school subject. We also aim at discussing some perspectives for the future to support a better informatics education for all students. The sources we have used are mainly historical and administrative, however we have also drawn on empirical research and surveys conducted since the seventies. This article therefore takes both retrospective and perspective viewpoints.

Preface to the IJAIED 25th Anniversary Issue

It is our great pleasure, as guest editors, to present an issue with invited articles by authors of high-impact articles from the journal’s past. By the end of 2015, the International Journal of Artificial Intelligence in Education completed its 25th volume and its 25th year of operation. This milestone called for a celebration of a scholarly kind. The current issue is part of that celebration. Although several landmark publications in the field appeared long before the journal’s first year of publication (1989), the journal’s early years coincided with the coalescing of the research community in Artificial Intelligence and Education (AIED). The same period saw the start of two relevant conferences, the International Conference on AI in Education (first held in 1987) and Intelligent Tutoring Systems (first held in 1988), although there had been two AI and Education conferences in the UK prior to Int J Artif Intell Educ (2016) 26:1–3 DOI 10.1007/s40593-015-0092-6

Two Recommending Strategies to Enhance Online Presence in Personal Learning Environments

Aiming to facilitate and support online learning practices, TEL researchers and practitioners have been increasingly focused on the design and use of Web-based Personal Learning Environments (PLE). A PLE is a set of services selected and customized by students. Among these services, resource (either digital or human) recommendation is a crucial one. Accordingly, this chapter describes a novel approach to supporting PLEs through recommendation services. The proposed approach makes extensive use of ontologies to formally represent learning context that, among other components, includes students’ presence in the online world, i.e., their online presence. This approach has been implemented in and evaluated with the OP4L (Online Presence for Learning) prototype. In this chapter, we expose recommendation strategies devised for OP4L. One is already implemented in OP4L, it is based on the well-known Analytical Hierarchical Process (AHP) method. The other one which has been tested on data coming from the prototype is based on the active user’s navigation stream and used a Kalman filter approach.

From learner information packages to student models: which continuum?

User adaptation has been a major issue of ITS research since the beginning. At first knowledge about individual learners was used to produce adaptive educational hypermedia. Then, the deployment of web based learning management systems put the need to exchange learner data between systems in the forefront. Nowadays, specifications for describing learner information in a standardized way are being developed. So far most existing systems have processed learner data. Yet the processed data are neither the same nor are they used for the same purposes, even if they are data about the learners. We argue that it is time to bridge the gap between the many sets of data about a learner processed within different learning environments. We propose a set of categories for describing learner information that goes beyond IMS LIP and could bring a link with ITS learner models.

Experimenting Features from Distinct Software Components on a Single Platform

This paper addresses the issue of building research scenarios with existing or forthcoming research prototypes for educational purposes. It defines an Experimentation Space allowing the cooperation of several software components. First it presents the general architecture and the properties which are required from each component to run on the experimentation platform. Then a case study showing several existing prototypes in Geometry cooperating on the platform is described. Lastly implementation problems and choices are discussed.

Teaching Expertise and Learning Environments

To design efficient, flexible and user-adaptable learning environments, we need to embed a great deal of knowledge into them. In the field of ITS, people often classify this knowledge into four categories: domain, tutoring, student and interface, based on the ITS architecture popular in the eighties. This talk emphasizes the teacher’s knowledge, which encompasses all the expertise of the teacher or of the trainer. Thus it is broader than that which is usually called tutoring knowledge.

The e-Fran Program: A Nation-Wide Initiative Supporting Research Projects to Foster Learning and Teaching Through Digital Technologies

This paper presents e-Fran, an on-going French initiative for linking academics from various disciplines and practitioners to design and test innovative ways of using digital technologies to improve learning outcomes. It is a research policy paper as first research results are not yet available. e-Fran is a nation-wide research program deployed in France from October 2016 over four years. The national context, the objectives, the project selection process and the funded projects are described as well as the follow-up actions.

Can Learning Object Metadata stand as Learning Resource Models for iLMS

In this paper, we present the work done for a small company who launched a reengineering process on an existing LMS called SERPOLET in order to allow flexibility in design and interoperability with other LMS. This paper proposes a set of metadata for describing learning resources. For that purpose, we analyse the many data which are processed both by humans and machines about a digital learning resource and to use existing models from the learning sciences field to organise these data from an education perspective as well as from a technical perspective.