Application of data mining techniques to identify the main factors affecting the digital divide among students in Colombia
DOI:
https://doi.org/10.26507/paper.4580Keywords:
Brecha digital, Minería de datos, Competencias digitales, Análisis de datos, Factores determinantes, Modelo descriptivos y predictivosAbstract
The digital divide or digital gap is defined as the inequality in access, capacity, and the necessary skills to effectively use information and communication technologies (ICT). Although traditionally this divide has been measured by internet access, the current challenge lies in the fact that many people, despite having access to technology, lack the necessary skills to make the most of it. In the Colombian educational context, this issue is reflected in the limitations faced by students to develop their digital skills, which negatively impacts their ability to make the most of the available technological resources. Since 2022, we have been working on a project to identify the main factors influencing the digital divide among students in Colombia, using advanced data mining techniques.
There are multiple factors that can contribute to this divide and accurately identifying them is key to improving educational quality and fostering the appropriate use of ICT among students. Therefore, this study proposes the application of data mining techniques to analyze large volumes of information and uncover hidden patterns that allow us to better understand the factors affecting students' digital capabilities. One of the major challenges in this process is data cleaning, as some participants do not provide all the requested information, either because they do not understand the data collection tools or due to the difficulties inherent in the digital divide itself. Therefore, it is necessary to explore various data cleaning techniques, exploratory analysis, and predictive modeling to understand the processes that generate the digital divide and design effective strategies to address it.
In terms of methodology, we have designed a hierarchical matrix that facilitates mapping the factors of the digital divide. This methodology is based not only on bibliographic review but also on fieldwork carried out in Colombian schools, where relevant data has been collected through surveys and other reliable sources. This data includes information on internet access, availability of technological devices, school infrastructure, socioeconomic level, geographic location, and academic performance in technological activities, which are essential for assessing students' digital competencies.
Through this fieldwork, we have identified that the factors determining the digital divide are clearly established and can be classified into different categories. In particular, the research conducted by Constanza Alvarado from Universidad ECCI and Philippe Aniorte from Indicatic Panama has been fundamental in deepening the definition and measurement approaches of the digital divide. Moreover, the methodologies employed in these studies have served as the foundation for the development of the hierarchical matrix and for the association of key factors.
Finally, the potential of predictive models is highlighted, as they can, based on the analysis of the collected data, anticipate the impact of interventions such as investments in technological infrastructure or digital training programs. These models can be very useful in designing more inclusive and efficient educational policies aimed at closing the digital divide in Colombian schools. In this regard, the creation of a digital divide observatory would significantly contribute to monitoring and improving students' technological and educational conditions, facilitating informed, data-driven decision-making.
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