Fuzzy cognitive map modelling educational software adoption

Hossain, Sarmin; Brooks, Laurence

doi:10.1016/j.compedu.2008.03.002

Cited by 62 publications

(32 citation statements)

References 17 publications

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“…FCMs have been used to study and analyze foreign policy, stock-investment, software adoption, modeling IT project management, designing and improving information system evaluation (ISE), product planning, manufacturing problems, fault detection and troubleshooting for electronic circuits, supervisory system control analysis, web data mining, socio-economic modeling, ecosystem and water quality issues, emigration issues, drug control, child labor issues, and community mobilization against the AIDS epidemic [21,42,[47][48][49][50][51][52][53][54][55][56].…”

Section: Fuzzy Cognitive Map-based Scenariosmentioning

confidence: 99%

Application of Fuzzy Cognitive Map for the Development of Scenarios: A Case Study of Wind Energy Deployment

Daim

Jetter

2013

Research and Technology Management in the Electricity Industry

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In the present era characterized by uncertainty, innovation and change, scenario planning is an increasingly popular way to look at future environments because of its usefulness in times of uncertainty and complexity. Scenario planning outlines the possible futures, stimulates strategic thinking about the future and helps to overcome thinking limitations by presenting multiple futures. Developing Fuzzy Cognitive Map (FCM)-based scenarios is a very new approach. FCM is based on causal cognitive map which is an accepted intuitive method. This approach combines the benefits of both qualitative and quantitative analysis. In this study FCM-based scenarios are developed for the deployment of wind energy in a developing country to illustrate the usefulness of this approach. This study also describes the utilization of various tools proposed in the scenario planning literature to select and validate FCM-based raw scenarios. Moreover, a comparison of FCM-based scenario development approach with other prominent quantitative scenario development techniques is also presented in this chapter.

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Section: Fuzzy Cognitive Map-based Scenariosmentioning

confidence: 99%

Application of Fuzzy Cognitive Map for the Development of Scenarios: A Case Study of Wind Energy Deployment

Daim

Jetter

2013

Research and Technology Management in the Electricity Industry

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“…Thus, it can be concluded that using this model in the final stage of SSM can facilitate choosing comprehensive solution to improve the current condition of problems. Table 1 summarizes the When the manger faces a massive amount of information, cognitive map can magnify the preferences and key factors (Siau and Tan 2005) Fuzzy cognitive map specifies the information defects, weak reasoning, and helps to find out the areas needing information gathering (Siau and Tan, 2005) Meaningful definitions and models proposed under a particular view (Lane and Oliva 1998;Rodr'iguez-Ulloa and Paucar-Caceres 2005) Fuzzy cognitive map can show the expert's knowledge in group decision making (it has the potential to be used as a group tool) (Khan and Quaddus 2004) The effectiveness of systems thinking in SSM depends on individual's knowledge, wisdom, expertise, and attitude (Yinghong 2007) Fuzzy cognitive map makes it possible to combine the experts' views.So, it can give more accurate results and reduce the ambiguity (Kosko 1987(Kosko , 1992Banini and Bearman 1998;Kardaras and Karakostas 1999;Khan and Quaddus 2004;Hossain and Brooks 2008) Not revising the coordination and conflicts between the proposed changes (Checkland and Scholes 1990;Lane and Oliva 1998) Fuzzy cognitive map provides the feasibility for static and dynamic analysis of different scenarios (Khan et al 2001;Irani et al 2002) Lack of precise and normative tools for ensuring the effectiveness of changes and conformity among them (Avison and Fitzgerald 2003) Not prioritizing and offering optimum solution for improving system (Flood and Jackson, 1991;Lane and Oliva 1998) Syst Pract Action Res (2011) 24:325-354 327 limitations of SSM and advantages of using FCM for improving the recommended methodology. This article is organized in seven sections; after the introduction, the second section briefly addresses SSM methodology and the stages where FCM is applied in it.…”

Section: Introductionmentioning

confidence: 97%

The Application of Fuzzy Cognitive Map in Soft System Methodology

Hanafizadeh

Aliehyaei

2011

Syst Pract Action Res

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Facing the issues of structural complexity, on which stakeholders have different views, has increasingly led to the use of Soft Systems Methodology (SSM) in solving managerial problems. Moreover, the weaknesses of this methodology in considering all point of views and ensuring the effectiveness of the proposed changes have provided the motivation for applying Fuzzy Cognitive Map (FCM) in SSM. Using FCM as a modeling tool makes it possible to combine the views of different experts and form group FCM (GFCM). GFCM has the potential to be applied as a useful decision support tool in the stage of offering recommendations and changes. The methodology proposed in this article is applied to ticketing system of Raja passenger train company. This system, influenced by various policies and views, is analyzed with the recommended methodology and then the solutions for developing the system are suggested in a prioritized manner.

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“…These domains include software project management [21], software quality risk analysis [22], software education [23] and agile software development [24].…”

Section: Preliminariesmentioning

confidence: 99%

An FCM-based Personalized Affective Model for Agile Software Development

He¹,

Lin

et al. 2016

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Developers' emotional stability in agile software development (ASD) teams is an important factor affecting the success of a project. Traditional Happiness Chart depends on people's self-report and is unable to produce predictive analysis to facilitate decision-making. In this paper, we proposed a Fuzzy Cognitive Map (FCM) based method for analyzing ASD developers' emotional stability. We designed an easy-touse survey questionnaire which can help establish the values of the causal relationship weights to support personalization of the proposed FCM model. The FCM affective model produces two metrics for assessing a given user's emotional stability: 1) the stable state mood value, and 2) the number of iteration steps for the FCM model to reach equilibrium. The two metrics are evaluated through a real-world experiment involving 20 undergraduate students. The results show that they are strong explanation factors for a user's emotional stability with 99% confidence. A regression model based on the user study has also been presented in the paper to help researchers study the relationships between the two metrics and a person's emotional stability computationally in the future.

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Fuzzy cognitive map modelling educational software adoption

Cited by 62 publications

References 17 publications

Application of Fuzzy Cognitive Map for the Development of Scenarios: A Case Study of Wind Energy Deployment

Application of Fuzzy Cognitive Map for the Development of Scenarios: A Case Study of Wind Energy Deployment

The Application of Fuzzy Cognitive Map in Soft System Methodology

An FCM-based Personalized Affective Model for Agile Software Development

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