Metric based efficiency analysis of educational ERP system usability-using fuzzy model

Kumar, Anil; Tadayoni, Reza; Sørensen, Lene Tolstrup

doi:10.1109/iciip.2015.7414801

Cited by 10 publications

(13 citation statements)

References 3 publications

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“…We chose to utilize Learnability, Presentation, Errors, and Navigation in this research as well since they have been successfully used in several separate studies of usability (Kumar et al, 2015;Scholtz et al, 2013;Singh & Wesson, 2009;Yusuf et al, 2014). Learnability and usability are closely connected (Arning et al, 2016;Seffah et al, 2006).…”

Section: Research Modelmentioning

confidence: 99%

“…2 Research Model (Pirhonen, 2005;Zali & Fadzlah, 2016), and how they can finish a task easily when using the system for the first time (Lin, 2013). There are several research that study the relationships between learnability and usability (Alves & Nunes, 2016;Abran et al, 2003;Kumar et al, 2015;Weichbroth, 2020;Alotaibi, 2017;Tesavrita et al, 2016;Kabir et al, 2018). It was proven that learnability is positively correlated with usability (Alves & Nunes, 2016).…”

Section: Research Modelmentioning

confidence: 99%

“…Rafla et al (2007) revealed that in the Human-Computer Interaction (HCI) community, the presentation of information is the primary concern of software usability. Presentation is about the user interface's layout (Rafla et al, 2007;Kumar et al, 2015). The presentation gives a context about where usability is taken into account (Rosenbaum, 1989).…”

Section: Research Modelmentioning

confidence: 99%

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The effect of usability on the intention to use the e-learning system in a sustainable way: A case study at Universitas Indonesia

et al. 2021

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E-Learning has been massively used in higher education, one of which is in Universitas Indonesia. The e-learning system in Universitas Indonesia is called Student Centered E-Learning Environment Universitas Indonesia (SCELE UI). This research determines the effect of usability on the intention to use SCELE UI in a sustainable way. The Expectation Confirmation Model (ECM) is used as a basis of the research model. Perceived Usability, Learnability, Presentation, Navigation and Error variables are added to the model. The Partial Least Square is used to analyze and test the model. Of the 12 proposed hypotheses, 10 hypotheses were accepted and 2 hypotheses were rejected. This research gives theoretical and practical contributions. On the theoretical side, this research successfully proposes and examines the integration of usability and ECM in the context of sustain e-learning usage intention. This research reveals the indirect effect of Perceived Usability on continued usage intention of the e-learning system. On the practical side, this research also provides insights for developers and universities that can help them to effectively foster the improvement of their system that can ensure sustained usage by their students.

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Section: Research Modelmentioning

confidence: 99%

Section: Research Modelmentioning

confidence: 99%

Section: Research Modelmentioning

confidence: 99%

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The effect of usability on the intention to use the e-learning system in a sustainable way: A case study at Universitas Indonesia

et al. 2021

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“…Chang and Dillon (2006) evalu ated their FIS in several d ifferent u ser interfaces [29]. Ku m ar, Tad ayoni, & Sorensen (2015) d efined five fu zzy u sability attribu tes as navigation, presentation, learnability, cu s tom izing, and task su p port [31]. H u d d y et al (2019) su ggest a consolid ated , hierarchical u sability m od el w ith a d etailed taxonom y for specifying and id entifying the qu ality com ponents and m easu ring u sability [32].…”

Section: Related Workmentioning

confidence: 99%

“…They have prop osed FISs for a d ynam ic u sability evalu ation. This FIS is provid ed for ge neral evalu ation [29]; [30]; [32] or a specific application [31]. In these stu d ies, the evalu ation m etrics are the inpu t of FIS, and the ou tpu t is the score of u sability.…”

Section: Related Workmentioning

confidence: 99%

An Integrated Model for Evaluation of Big Data Interactive Systems Under Uncertainty

Asemi

2021

Preprint

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The study aimed to propose a judgment-based evaluation model for usability evaluating of big data interactive system s. Human judgment is associated with uncertainty and gray information. We used the fuzzy technique for integration, summarization, and distance calculation of quality value judgment. The proposed model is an integrated fuzzy Multi Factors Evaluation (MFE) model based on experts’ judgments in HCI, ISPD, and AMLMs. We provided a Fuzzy Inference System (FIS) for scoring usability evaluation metrics in different big data interactive system s. A multi-model big data interactive system is implemented for experimental testing of the model. The achieved results from the proposed model and experimental tests are compared using statistical correlation tests. The results show the ability of the proposed model for usability evaluation of big data interactive systems without the need for conducting empirical tests. It is concluded that applying a dataset in a neuro-FIS and training system cause to produce more than a hundred effective rules. The findings indicate that the proposed model can be applied for big data interactive system evaluation, informative evaluation, and complex empirical tests. Future studies may improve the FIS with the integration of artificial neural networks.

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Online Attendre Tracking System

Suguna¹,

Prakash

Shobana³

2019

Sustainable Communication Networks and Application

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Metric based efficiency analysis of educational ERP system usability-using fuzzy model

Cited by 10 publications

References 3 publications

The effect of usability on the intention to use the e-learning system in a sustainable way: A case study at Universitas Indonesia

The effect of usability on the intention to use the e-learning system in a sustainable way: A case study at Universitas Indonesia

An Integrated Model for Evaluation of Big Data Interactive Systems Under Uncertainty

Online Attendre Tracking System

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