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Abbas, Safia; Sawamura, Hajime – International Working Group on Educational Data Mining, 2009
This paper presents an agent-based educational environment to teach argument analysis (ALES). The idea is based on the Argumentation Interchange Format Ontology (AIF)using "Walton Theory". ALES uses different mining techniques to manage a highly structured arguments repertoire. This repertoire was designed, developed and implemented by us. Our aim…
Descriptors: Data Analysis, Persuasive Discourse, Intelligent Tutoring Systems, Models
Nagata, Ryo; Takeda, Keigo; Suda, Koji; Kakegawa, Junichi; Morihiro, Koichiro – International Working Group on Educational Data Mining, 2009
This paper proposes a novel method for recommending books to pupils based on a framework called Edu-mining. One of the properties of the proposed method is that it uses only loan histories (pupil ID, book ID, date of loan) whereas the conventional methods require additional information such as taste information from a great number of users which…
Descriptors: Data Analysis, Books, Automation, Library Services
Ritter, Steven; Harris, Thomas K.; Nixon, Tristan; Dickison, Daniel; Murray, R. Charles; Towle, Brendon – International Working Group on Educational Data Mining, 2009
In Cognitive Tutors, student skill is represented by estimates of student knowledge on various knowledge components. The estimate for each knowledge component is based on a four-parameter model developed by Corbett and Anderson [Nb]. In this paper, we investigate the nature of the parameter space defined by these four parameters by modeling data…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Knowledge Level, Skills
Ayers, Elizabeth; Nugent, Rebecca; Dean, Nema – International Working Group on Educational Data Mining, 2009
A fundamental goal of educational research is identifying students' current stage of skill mastery (complete/partial/none). In recent years a number of cognitive diagnosis models have become a popular means of estimating student skill knowledge. However, these models become difficult to estimate as the number of students, items, and skills grows.…
Descriptors: Data Analysis, Skills, Knowledge Level, Students
Vialardi, Cesar; Bravo, Javier; Shafti, Leila; Ortigosa, Alvaro – International Working Group on Educational Data Mining, 2009
One of the main problems faced by university students is to take the right decision in relation to their academic itinerary based on available information (for example courses, schedules, sections, classrooms and professors). In this context, this work proposes the use of a recommendation system based on data mining techniques to help students to…
Descriptors: Data Analysis, Higher Education, Course Selection (Students), Enrollment
Pechenizkiy, Mykola; Trcka, Nikola; Vasilyeva, Ekaterina; van der Aalst, Wil; De Bra, Paul – International Working Group on Educational Data Mining, 2009
Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated through the use of different information systems. The results of data mining can be used for getting a better understanding of the underlying educational processes, for…
Descriptors: Data Analysis, Methods, Computer Software, Computer Assisted Testing
Feng, Mingyu; Beck, Joseph – International Working Group on Educational Data Mining, 2009
Representing domain knowledge is important for constructing educational software, and automated approaches have been proposed to construct and refine such models. In this paper, instead of applying automated and computationally intensive approaches, we simply start with existing hand-constructed transfer models at various levels of granularity and…
Descriptors: Data Analysis, Models, Transfer of Training, Intelligent Tutoring Systems
Madhyastha, Tara M.; Tanimoto, Steven – International Working Group on Educational Data Mining, 2009
Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…
Descriptors: Web Based Instruction, Computer Assisted Testing, Computer Software, Computer Science Education