Self-instructive spreadsheets: an environment for automatic knowledge acquisition and tutor generation

Lentini, Massimo; Nardi, Daniele; Simonetta, Alessandro

doi:10.1006/ijhc.1999.0363

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…Domeinu-modulua sortzea zaila bada, are zailagoa da domeinu-modulua era automatikoan edo erdiautomatikoan erauztea, dokumentu elektronikoetatik edo corpusetatik abiatuta. Egiteko horren inguruan argitaratu diren lanak, gainera, domeinu-modulu elebakarretara mugatuta daude [8,9,10,11,12,13]. Euskararen kasuan, DOM-Sortze inguruneak ahalbidetzen du Testuliburuetatik domeinu-modulu eleaniztunak eraikitzen domeinu-moduluak sortzea.…”

Section: Sarreraunclassified

Testuliburuetatik domeinu-modulu eleaniztunak eraikitzen

Conde

Arruarte

Larrañaga

et al. 2017

EKAIA

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Laburpena: Lan honetan LiDom Builder tresnaren analisia, diseinua eta ebaluazioa aurkezten dira. Domeinu Modulu Eleaniztunak testuliburu elektronikoetatik era automatikoan erauztea ahalbidetzen du LiDom Builderek. Ezagutza eskuratzeko, Hizkuntzaren Prozesamendurako eta Ikaste Automatikorako teknikekin batera, zenbait baliabide eleaniztun erabiltzen ditu, besteak beste, Wikipedia eta WordNet.Hitz gakoak: Teknologian oinarritutako hezkuntzarako tresnak, domeinu-modulu eleaniztuna, sorkuntza automatikoa.Abstract: This paper presents the analysis, design and validation of LiDom Builder, a framework for the automatic generation of Multilingual Domain Modules from electronic documents. LiDom Builder uses Natural Language Processing and Machine Learning techniques, along with multilingual resources such as Wikipedia and W ordNet to fulfil its work.

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Section: Sarreraunclassified

Testuliburuetatik domeinu-modulu eleaniztunak eraikitzen

Conde

Arruarte

Larrañaga

et al. 2017

EKAIA

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“…Spreadsheets are often ineffectively and inefficiently designed due to a multitude of reasons such as, social, cultural and cognitive reasons (Bhavnani, Peck, & Reif, 2008). Accordingly, significant research effort has been expended in studying spreadsheet error correction (Bishop & McDaid, 2011;Burnett, Sheretov, Ren, & Rothermel, 2002;Chadwick, Knight, & Rajalingham, 2001;Chan, Ying, & Peh, 2000;Clermont, 2003;Davis, 1996;Hendry & Green, 1993;Igarashi, Mackinlay, Chang, & Zellweger, 1998;Lentini, Nardi, & Simonetta, 2000;Rajalingham, Chadwick, Knight, & Edwards, 2000;Sajaniemi, 2000).…”

Section: Introductionmentioning

confidence: 99%

An Alternative Fit through Problem Representation in Cognitive Fit Theory

Chan

Goswami

Kim

2012

Journal of Database Management

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This paper uses cognitive fit theory to analyze the problem solving process in spreadsheet analyses. Cognitive fit theory proposes the formation of mental representation as a part of the problem solving process. However, there is little research examining mental representation, which is a key concept in cognitive fit theory. This study examines the formation of mental representation and proposes an alternative mechanism of cognitive fit between different problem representations and their corresponding mental representations when the task is invariant, but the problem representation changes. Mental representation is then empirically assessed based on the application of Hick’s law, which states that the response time of users making a choice varies with the logarithm of the number of possible choices. Therefore, this study contributes to research on cognitive fit theory by proposing an alternative fit and by demonstrating a feasible approach for identifying mental representations. It contributes to spreadsheet research by showing how problem representations affect task performance in the case of spreadsheet error correction.

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“…Researchers have often advocated the use of visualization support or visualization tools to prevent spreadsheet errors as well as aid in their identification and correction (Chadwick et al, 2001;Chan et al, 2000;Clermont, 2003;Davis, 1996;Igarashi et al, 1998;Lentini et al, 2000;Rajalingham et al, 2000;Sajaniemi, 2000). As such, existing spreadsheet research is often based on a software engineering perspective, with the primary objective of designing and developing tools that can help prevent errors during spreadsheet development or make them easier to identify for correction later on (e.g., Burnett et al, 2002;Chadwick et al, 2001;Hendry and Green, 1993).…”

Section: Introductionmentioning

confidence: 99%

The Role of Visualization Tools in Spreadsheet Error Correction from a Cognitive Fit Perspective

Goswami

Chan

Kim

2008

JAIS

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Errors in spreadsheets pose a serious problem for organizations and academics. This has resulted in ongoing efforts to devise measures for reducing errors or efficient ways of correcting them. Visualization tools are often advertised as means for improving spreadsheet error correction performance. This study investigates the role of visualization tools in spreadsheet error correction. For this purpose, this study proposes a framework for classifying activities associated with spreadsheet error correction. The framework is to highlight the activities that are important for correcting different types of spreadsheet errors, and to show how different visualization tools can aid error correction by effectively supporting these activities. By identifying "chaining" as one of the most important activities from the framework, this study uses cognitive fit theory to examine the effects of a visualization tool that supports chaining on spreadsheet error correction performance. Experimental methodology is used to test the outcome of cognitive fit between the error correction task and the visualization tool. The results of the experiment highlight the importance of cognitive fit between the type of task and the visualization tool for attaining better performance. This study also provides guidelines for designing and developing tools for spreadsheet error correction.

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Self-instructive spreadsheets: an environment for automatic knowledge acquisition and tutor generation

Cited by 6 publications

References 30 publications

Testuliburuetatik domeinu-modulu eleaniztunak eraikitzen

Testuliburuetatik domeinu-modulu eleaniztunak eraikitzen

An Alternative Fit through Problem Representation in Cognitive Fit Theory

The Role of Visualization Tools in Spreadsheet Error Correction from a Cognitive Fit Perspective

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