Fundamentals of the design and the operation of an intelligent tutoring system for the learning of the arithmetical and algebraic way of solving word problems

Arnau, David; Arevalillo‐Herráez, Miguel; Puig, Luis; González‐Calero, José Antonio

doi:10.1016/j.compedu.2012.11.020

Cited by 38 publications

(17 citation statements)

References 8 publications

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“…Table 4 shows participants, data collecting tools, and examined variables of reviewed studies. Some of the studies (Arnau et al, 2013;Chen, 2008;Cuendet et al, 2013;Curilem et al, 2007;Dangsaart et al, 2008;He et al, 2009;Jaques & Vicari, 2007;Latham et al, 2014;Mitrovic et al, 2013;Moundridou & Virvou, 2003;Nussbaum et al, 2001;Pavlekovic et al, 2009;Sayed et al, 2011;Stankov et al, 2008;Vega-Gorgojo et al, 2010;Virvou & Alepis, 2005;Waalkens et al, 2013;Wu, Lee, Chang & Liang, 2013) included in the review and presented their findings in other sub-problems were not examined in Table 4, as they do not include any implementations and are only intended for software promotion or potential of softwares as a teaching/learning tool.…”

Section: Results Of the Fourth Sub Problemmentioning

confidence: 99%

Web 3.0 in Learning Environments: A Systematic Review

Firat¹,

Firat²

2020

Turkish Online Journal of Distance Education

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Web 3.0 technologies have inevitably affected educational research. Many studies have been conducted on the use of Web 3.0 tools in learning environments. The synthesis and summarization of the results of these studies with a systematic review is considered important in terms of being the source of future research and helping to spread the use of these technologies in education. Hence the purpose of this systematic review is to obtain a better understanding of how Web 3.0 technologies can be used to enhance quality of educational settings. The systematic analysis was conducted by 81 papers from 2005 to 2020. The PRISMA Statement was used in the research and report generation process. Papers related to semantic, augmented reality, intelligent tutoring system, 3d visual environments, 3d games and ontologies is included in the study. The results show that in 2008 and 2013 there was an increase in the number of studies. In addition, most experimental studies have been conducted in this literature and the studies in the discipline of science education are more than other disciplines. When the data collection tools used in the studies were examined, it was found that the majority of the studies were quantitative and most benefited from surveys, questionnaires and observational information in the data collection process. In addition, the majority of studies focus on the learning usefulness and learning outcomes of the software used in the research. Furthermore, suggestions for future researches were made in line with the limitations and results of the study.

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Section: Results Of the Fourth Sub Problemmentioning

confidence: 99%

Web 3.0 in Learning Environments: A Systematic Review

Firat¹,

Firat²

2020

Turkish Online Journal of Distance Education

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“…Several approaches can be used to solve an algebraic word problem by transforming it into a mediated structure (trees, graphs, etc. ;Arnau, Arevalillo-Herráez, Puig, & González-Calero, 2013;Bakman, 2007;Ding, Cong, Lin, & Zhu, 2008;Jaques et al, 2013;Liguda & Pfeiffer, 2012;Shi, Wang, Lin, Liu, & Rui, 2015), whereas the present work solves the problem from unstructured data.…”

Section: Related Workmentioning

confidence: 96%

Automatically solving two‐variable linear algebraic word problems using text mining

et al. 2018

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The teaching and learning of algebraic word problems is a basic component of elementary education. Recently, to facilitate its learning, a few approaches for automatically solving algebraic and arithmetic word problems have been proposed. These systems generally use either natural language processing (NLP) or a combination of NLP and machine learning. However, they have low accuracy due to their large feature sets, extracted using limited preprocessing techniques. In this research work, we propose a template‐based approach that was developed by following a two‐step process. In the first step, we predict an equation template from a training dataset using NLP and a classification mechanism. The next step is to instantiate the predicted template with nouns and numbers through reasoning. To validate the proposed methodology, a prototype system was implemented. We then compared the proposed system with the existing systems using their respective datasets and the proposed dataset. The experimental results show improvement in accuracy, with an average precision of 80.6% and average recall of 83.5%.

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“…CBR has been applied in various areas including emergency response [21], the Remanufacturing Process [22] and Cost Estimation [23]. The CBR algorithm has also contributed to the development of various ITS including UZWEBMAT [10], CBRPROMATH [17], MACBR [24], Domus [25], PLS-ML [26] and STIMTutor [27]. The CBR works in four main phases, which are (i) retrieve, (ii) revise, (iii) reuse and (iv) retain [28].…”

Section: Methodsmentioning

confidence: 99%

Learning material recommendation based on case-based reasoning similarity scores

Masood

Mokmin

2017

AIP Conference Proceedings

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Abstract.A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

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Fundamentals of the design and the operation of an intelligent tutoring system for the learning of the arithmetical and algebraic way of solving word problems

Cited by 38 publications

References 8 publications

Web 3.0 in Learning Environments: A Systematic Review

Web 3.0 in Learning Environments: A Systematic Review

Automatically solving two‐variable linear algebraic word problems using text mining

Learning material recommendation based on case-based reasoning similarity scores

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