Experimenting Statecharts for Multiple Experts Knowledge Elicitation in Agriculture

Léger, Bertrand; Naud, Olivier

doi:10.3182/20070927-4-ro-3905.00144

Cited by 6 publications

(9 citation statements)

References 15 publications

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“…To deal with the above problem, experts use a one-crop/one-pest approach (Léger & Naud, 2009;Túnez et al, 2001) solving each elemental problem (one pest, one crop) independently. When more than one pest affects a plot, they assemble elemental solutions in order to obtain a full solution for PCOP.…”

Section: Pest Control Problemmentioning

confidence: 99%

“…An explicit distinction between information and knowledge is applied; the first is related to observations, whereas the latter is related to the knowledge representation and the decision support tasks for each candidate elemental problem and for the context and assembling decisions. Rules are used as knowledge representation formalism, sometimes called IF-THEN rules, because they describe many aspects of skilled behaviour, are easy to elicit and also because there are many previous pest control models that use such rules (Plant, 1989;Mansingh et al, 2007;Lopez-Morales et al, 2008;Léger & Naud, 2009). Each knowledge base contains structures (i.e.…”

Section: Web-pest Toolmentioning

confidence: 99%

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Decision making models embedded into a web-based tool for assessing pest infestation risk

Cano

Cañadas

Túnez

2015

Biosystems Engineering

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Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers.

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Section: Pest Control Problemmentioning

confidence: 99%

Section: Web-pest Toolmentioning

confidence: 99%

Decision making models embedded into a web-based tool for assessing pest infestation risk

Cano

Cañadas

Túnez

2015

Biosystems Engineering

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“…Furthermore, other notations for describing processes and events-flow-charts, state-transition diagrams, data flow diagrams, Petri nets or statecharts could be translated to nested conceptual graphs [46]. Interestingly enough, statecharts have been experimented as a mediation tool between multiple experts and a knowledge engineer, specifically when expertise is not particularly well defined [47].…”

Section: Knowledge Formalization With Conceptual Graphsmentioning

confidence: 99%

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Kamsu-Foguem

Noyes

2013

Computers in Industry

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“…Researchers have indicated that domain experts are likely to have different expertise or understandings for solving problems in the same domain owing to the working environments in which they have been situated, the cases they have experienced or knowledge they have constructed (Chu & Hwang, 2008;Hwang, Chen, Hwang & Chu, 2006;Léger & Naud, 2009;Panjaburee et al, 2010). That is, different qualities of concept relationships might be provided by different domain experts, which could significantly affect the students' learning diagnosis results.…”

Section: Practitioner Notesmentioning

confidence: 99%

A group decision approach to developing concept–effect models for diagnosing student learning problems in mathematics

Hwang

Panjaburee

Triampo

et al. 2012

Brit J Educational Tech

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Diagnosing student learning barriers has been recognized as the most fundamental and important issue for improving the learning achievements of students. In the past decade, several learning diagnosis approaches have been proposed based on the concept–effect relationship (CER) model. However, past studies have shown that the effectiveness of this model heavily depends on the concept relationship knowledge provided by the domain experts (eg, experienced teachers or educators for a specified subject); ie, the performance of the developed learning diagnosis systems could be significantly affected by subjective opinions, ignorance or insufficient knowledge if those concept relationships are derived from a single domain expert. To cope with this problem, this study proposes a group decision approach for developing the CER model with the cooperation of multiple domain experts. Based on the proposed approach, a testing and diagnostic system has been implemented; moreover, an experiment has been conducted to evaluate the effectiveness of this new approach. The experimental results show that this approach is able to develop quality CER models, and hence the low‐achievement students who received the generated learning suggestions had significantly better learning achievements than those who learned with the previous approach. Practitioner notes What is already known about this topic Diagnosing student learning barriers is a fundamental and important issue for improving the learning achievements of students. Several learning diagnosis approaches have been proposed based on the concept–effect relationship (CER) model. The effectiveness of the learning diagnosis model heavily depends on the concept relationship knowledge provided by the domain experts. What this paper adds A group decision approach for developing the CER model with the cooperation of multiple domain experts is proposed. A testing and diagnostic system was implemented based on the proposed approach. An experiment was conducted to investigating whether the students guided by the proposed approach had better learning achievements than those guided by the original CER model approach. Implications for practice and/or policy The experimental results show that the low‐achievement students who received the learning suggestions generated by the new approach had significantly better learning achievements than those who learned with the previous approach. Further studies of developing more effective tools or leading in other group decision strategies to help domain experts cooperatively determine the prerequisite relationships are needed.

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Experimenting Statecharts for Multiple Experts Knowledge Elicitation in Agriculture

Cited by 6 publications

References 15 publications

Decision making models embedded into a web-based tool for assessing pest infestation risk

Decision making models embedded into a web-based tool for assessing pest infestation risk

Graph-based reasoning in collaborative knowledge management for industrial maintenance

A group decision approach to developing concept–effect models for diagnosing student learning problems in mathematics

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