“…That stereotype therefore provides probable tags for the KUs which have not yet been observed in sufficient quantity in the user's performance. We are currently undertaking our own exploration of the typical linguistic structure acquisition order for our user population to determine placement of KUs into Easy, Medium and Hard; for a detailed discussion of our methodology, see (Michaud and McCoy, 2004). In this earlier work we have concentrated on the errors occurring in writing samples we have collected to represent our user population.…”
Section: A Model Of Grammar Proficiencymentioning
confidence: 99%
“…Structures at a given layer, regardless of hierarchy, are typically learned before structures at a layer 'above' that layer. For more detailed information on the structure of the model, please see (Michaud and McCoy, 2004). Using this SLALOM model, we can define three different stereotypes of users as depicted in Figure 1: Low, Middle, and High.…”
Section: A Model Of Grammar Proficiencymentioning
confidence: 99%
“…16 Our judges were a panel of four instructors trained in the evaluation of writing by second language learners. The judging is discussed in (Michaud and McCoy, 2004). sentences that clearly exhibit structures expected primarily of a High-level learner, the new stage to which our user had progressed.…”
Section: Updating the Stereotype Assignmentmentioning
confidence: 99%
“…The name ICICLE represents 'Interactive Computer Identification and Correction of Language Errors' and is the name of an intelligent tutoring system currently under development , 2003, 2004. The system's primary long-term goal is to employ natural language processing and generation to tutor deaf students on grammatical components of their written English.…”
Section: Introduction: the Icicle Systemmentioning
User Modeling and User-Adapted Interaction (2005) 15: 55-84Abstract. This paper discusses the design and evaluation of an implemented user model in ICICLE, an instruction system for users writing in a second language. We show that in the task of disambiguating natural language parses, a blended model combining overlay techniques with user stereotyping representing typical linguistic acquisition sequences captures user individuality while supplementing incomplete information with stereotypic reasoning.
“…That stereotype therefore provides probable tags for the KUs which have not yet been observed in sufficient quantity in the user's performance. We are currently undertaking our own exploration of the typical linguistic structure acquisition order for our user population to determine placement of KUs into Easy, Medium and Hard; for a detailed discussion of our methodology, see (Michaud and McCoy, 2004). In this earlier work we have concentrated on the errors occurring in writing samples we have collected to represent our user population.…”
Section: A Model Of Grammar Proficiencymentioning
confidence: 99%
“…Structures at a given layer, regardless of hierarchy, are typically learned before structures at a layer 'above' that layer. For more detailed information on the structure of the model, please see (Michaud and McCoy, 2004). Using this SLALOM model, we can define three different stereotypes of users as depicted in Figure 1: Low, Middle, and High.…”
Section: A Model Of Grammar Proficiencymentioning
confidence: 99%
“…16 Our judges were a panel of four instructors trained in the evaluation of writing by second language learners. The judging is discussed in (Michaud and McCoy, 2004). sentences that clearly exhibit structures expected primarily of a High-level learner, the new stage to which our user had progressed.…”
Section: Updating the Stereotype Assignmentmentioning
confidence: 99%
“…The name ICICLE represents 'Interactive Computer Identification and Correction of Language Errors' and is the name of an intelligent tutoring system currently under development , 2003, 2004. The system's primary long-term goal is to employ natural language processing and generation to tutor deaf students on grammatical components of their written English.…”
Section: Introduction: the Icicle Systemmentioning
User Modeling and User-Adapted Interaction (2005) 15: 55-84Abstract. This paper discusses the design and evaluation of an implemented user model in ICICLE, an instruction system for users writing in a second language. We show that in the task of disambiguating natural language parses, a blended model combining overlay techniques with user stereotyping representing typical linguistic acquisition sequences captures user individuality while supplementing incomplete information with stereotypic reasoning.
“…A framework for the development of adaptive systems taking into consideration context and user models was proposed by Zimmermann et al [92]; they focused on the relation-120 ship between user and context modelling. Michaud and McCoy [64] proposed a methodology for acquiring stereotypes to be used in the modelling process.…”
Section: Adaptive Learning Systems Methodologiesmentioning
Learner models are built to offer personalised solutions related to learning. They are often developed in parallel to the development of adaptive learning systems and thus, linked to the system's development.The adaptive learning systems literature reports numerous accounts of learner model development, but there are no reports on the methodological aspects of developing learner models and the relation between the development of the learner model component and the rest of the system. This paper presents the Participatory Learner Modelling Design methodology, which outlines the steps for learner model development and their relation to the development of the system. The methodology is illustrated with a case study of an adaptive educational system.
In computer‐assisted language learning (CALL), a student model is a computational data structure that contains information about individual students and thus facilitates individualized instruction through the adaptation of a language learning system to the learner.
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