An open learner model for trainee pilots

Inderdip Gakhal,Susan Bull

doi:10.3402/rlt.v16i2.10891

Abstract

This paper investigates the potential for simple open learner models for highly motivated, independent learners, using the example of trainee pilots. In particular we consider whether such users access their learner model to help them identify their current knowledge level, areas of difficulty and specific misconceptions, to help them plan their immediate learning activities; and whether they find a longer-term planning aid useful. The Flight Club open learner model was deployed in a UK flight school over four weeks. Results suggest that motivated users such as trainee pilots will use a system with a simple open learner model, and are interested in consulting their learner model information both to facilitate planning over time, and to understand their current knowledge state. We discuss the extent to which our findings may be relevant to learners in other contexts. Keywords: Intelligent Tutoring Systems; learner model; open learner model; trainee pilots DOI: 10.1080/09687760802318436

Highlights

Intelligent Tutoring Systems (ITSs) offer individualised learning assistance
There are very many questions remaining to be investigated, relating to a broad range of issues including learning gains, learner model presentation preferences, what students use open learner models (OLMs) for, what information they attend to, how OLMs may support collaborative interaction, why some students do not access their OLM, use of OLMs over time, use of OLMs in different courses and the utility of OLMs for different types of user. (See Bull, Dimitrova, and McCalla (2007) for further discussion of research questions.) Using the ‘Flight Club’ OLM, this paper considers just some of the early questions
We investigate whether previous work on the use of simple OLMs is relevant to motivated, independent learners – i.e. we aim to find out whether this type of OLM approach might be of benefit to the kind of learners who have a high drive to succeed, and who may already have successful learning strategies in place

Summary

Introduction

Intelligent Tutoring Systems (ITSs) offer individualised learning assistance. For example, such assistance may include providing exercises of appropriate difficulty and content, and selecting suitable learning material according to the learner’s current learning needs.Traditionally an ITS contains three models. Intelligent Tutoring Systems (ITSs) offer individualised learning assistance. Such assistance may include providing exercises of appropriate difficulty and content, and selecting suitable learning material according to the learner’s current learning needs. The domain model allows the system to generate and understand the content it is teaching, and evaluate the accuracy of the user’s input. Teaching strategies allow an ITS to individualise its teaching: the system interprets the user’s knowledge from their learner model, comparing this to the domain model, and makes a variety of teaching or guidance decisions such as choice of topic, level of detail of information or explanations to present, method of presentation of information or explanations and generation or selection of appropriate exercises. ITSs are being developed for a range of domains, from mathematics (Melis, Haywood, and Smith 2006) to astronaut training (Dubois, Nkambou, and Hohmeyer 2006) to music (Lahart 2005)

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