Data-mining techniques in detecting factors linked to academic achievement

Martínez‐Abad, Fernando; López, Alicia Alelí Chaparro Caso

doi:10.1080/09243453.2016.1235591

Cited by 48 publications

(30 citation statements)

References 42 publications

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“…Furthermore, their results identified statistically significant factors influencing academic performance. The studies of Alivernini (2013), Abad and Lopez (2017), and İdil, Narlı, and Aksoy (2016) also dealt with decision trees for constructing student-based models that would ensure accurate classifications and predictions, but respectively used the different algorithms of CART, J48 and C5.0. Kotsiantis, Pierrakeas, and Pintelas (2010) investigated the prediction performance of six different machine-learning methods/algorithms (decision tree/C4.5, neural networks/ back propagation, Bayesian network/naive Bayes, instance-based learning/k-nearest neighbor, logistic regression/maximum likelihood, and support vector machines/ sequential minimal optimization).…”

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confidence: 99%

Identifying the Classification Performances of Educational Data Mining Methods: A Case Study for TIMSS

2017

EDUC SCI-THEOR PRACT

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Educational data mining (EDM) is a rapidly growing research area, and the outputs obtained from EDM shed light on educators' and education planners' efforts to make efficient decisions concerning educational strategies. However, a lack of work still exists on using EDM methods for international assessment studies such as the International Association for the Evaluation of Educational Achievement' s Trends in International Mathematics and Science Study (IEA' s TIMSS). This study aims to fill the gap in the current literature on the latest-released TIMSS 2011 data by applying a decision tree, a Bayesian network, a logistic regression, and neural networks. The best performing algorithm in classification based on several performance measures has been found for eighth-grade Turkish students' mathematics data. During the construction of models, 11 student-based factors have been taken into account. The results show that logistic regression outperforms other algorithms in terms of measuring classification performance. The factor of student confidence has also been found as the most effective factor on eighth-grade students' mathematics achievement.

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confidence: 99%

Identifying the Classification Performances of Educational Data Mining Methods: A Case Study for TIMSS

2017

EDUC SCI-THEOR PRACT

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“…Given the results shown in the state of play, we decided to use the C4.5 algorithm in the construction of the models. This algorithm is an extension of ID3 (Quinlan, 1986, 1992), and its use is widespread in EDM to model student performance (Martínez-Abad and Chaparro-Caso-López, 2017; Rodrigues et al, 2018). The fit of this algorithm allowed the use of variables of all types (categorical and scale), and uses the information gain ratio for their selection.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, these techniques are applied with minimal intervention by researchers, which, together with the aforementioned, represent a great advantage for the identification of valuable information in massive databases (Xu, 2005). More specifically, the algorithm proposed in this study is the decision tree (classification algorithm), since it simplifies the analysis and interpretation of the predictor variables and their relationships (Martínez-Abad and Chaparro-Caso-López, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The current calculation capacity of computers allows the development and application of appropriate statistical techniques for the analysis of massive data. In this regard, data mining emerges as a set of techniques that add value to large-scale data analysis (Martínez-Abad and Chaparro-Caso-López, 2017). These techniques enable the identification of patterns in the data without proposing previous assumptions or starting models, and with minimal intervention by the researcher (Xu, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Identification of Factors Associated With School Effectiveness With Data Mining Techniques: Testing a New Approach

Martínez‐Abad

2019

Front. Psychol.

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The study of school effectiveness and the identification of factors associated with it are growing fields of research in the education sciences. Moreover, from the perspective of data mining, great progress has been made in the development of algorithms for the modeling and identification of non-trivial information from massive databases. This work, which falls within this context, proposes an innovative approach for the identification and characterization of educational and organizational factors associated with high school effectiveness. Under a perspective of basic research, our aim is to study the suitability of decision trees, techniques inherent to data mining, to establish predictive models for school effectiveness. Based on the available Spanish sample of the PISA 2015 assessment, an indicator of the school effectiveness was obtained from the application of multilevel models with predictor variables of a contextual nature. After selecting high- and low-effectiveness schools in this first phase, the second phase of the study was carried out and consisted of the application of decision trees to identify school, teacher, and student factors associated with high and low effectiveness. The C4.5 algorithm was calculated and, as a result, we obtained 120 different decision trees based on five determining factors (database used; stratification in the initial selection of schools; significance of the predictor variables of the models; use of items and/or scales; and use of the training or validated samples). The results show that the use of this kind of technique could be appropriate if mainly used with correctly pre-processed data that include the combined information available from all educational agents. This study represents a major breakthrough in the study of the factors associated with school effectiveness from a quantitative approach, since it proposes and provides a simple and appropriate procedure for modeling and establishing patterns. In doing so, it contributes to the development of knowledge in the field of school effectiveness that can help in educational decision-making.

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“…The economy, social and cultural status (ESCS) of the family influenced academic results (Karakolidis et al, 2016). Academic performance was unfavorable in families with a low socioeconomic level (Gamazo et al, 2017;Karakolidis et al, 2016;Martínez et al, 2017;Martinez-Abad & Chaparro-Caso, 2017;Murillo, Martínez-Garrido & Hidalgo, 2014;Özdemir, 2016;Perry, 2017;Salgado, Marchione & Gilbert, 2014;Sulis & Porcu, 2014;Troncoso et al, 2016;Tsai, Smith & Hauser, 2017;Van Hek, Kraaykamp & Pelzer, 2018;Valenzuela, Bellei & Allende, 2016). The influence may vary depending on cultural mechanisms given the greater influence of the number of books in some Western countries than in others in the East (Tsai et al, 2017).…”

Section: Contextual Factors Associated With School Effectivenessmentioning

confidence: 99%

What is Published in Impact Journals on School Effectiveness? A Systematic Review of Research Results and Methods

García-Jiménez

Gordillo

Rodríguez-Santero

2020

PED

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A systematic review of 45 articles on school effectiveness (SE) indexed in SJR and JCR (2014–2018) has been conducted. The results obtained show that the quantitative methodology catalyses the greatest number of researches. The articles are mainly published in Q1-Q2 journals with impact factor. The content of the articles reviewed found that, although exist contextual factors that affect the SE, the variables at the school level also have an impact.

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Data-mining techniques in detecting factors linked to academic achievement

Cited by 48 publications

References 42 publications

Identifying the Classification Performances of Educational Data Mining Methods: A Case Study for TIMSS

Identifying the Classification Performances of Educational Data Mining Methods: A Case Study for TIMSS

Identification of Factors Associated With School Effectiveness With Data Mining Techniques: Testing a New Approach

What is Published in Impact Journals on School Effectiveness? A Systematic Review of Research Results and Methods

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