Mapping Learning Analytics initiatives in Latin America

Cechinel, Cristian; Ochôa, Xavier; Santos, Henrique Lemos dos; Nunes, João Batista Carvalho; Rodés, Virgínia; Queiroga, Emanuel Marques

doi:10.1111/bjet.12941

Cited by 33 publications

(32 citation statements)

References 14 publications

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“…Previous studies also described how learning analytics developed in specific world regions. For instance, Cechinel et al (2020) and Pontual Falcão et al (2020) list several research initiatives and practical applications of learning analytics in Latin America. Similarly, Ferguson et al (2015) described the perspectives of the adoption of learning analytics in Europe.…”

Section: Learning Analyticsmentioning

confidence: 99%

“…Therefore, this review starts by highlighting the educational motivation and problems that lead to the adoption of learning analytics in high schools. More specifically, we evaluated a subset of the categories proposed in previous works ( Moissa et al, 2015 ; Viberg et al, 2018 ; Cechinel et al, 2020 ), such as predicting and enhancing students learning outcomes, analyzing students’ learning processes, supporting teachers’ decisions and reflection, and support writing activities. Subsequently, as the application of learning analytics in general means using data analysis, we intended to analyze the data processing approaches used in the learning analytics adoption process.…”

Section: Research Questionsmentioning

confidence: 99%

“…Learning analytics has been widely researched and used in higher education institutions, especially due to the maturity level of adopting data analysis tools in these institutions ( Leitner et al, 2017 ; Waheed et al, 2018 ; Charitopoulos et al, 2020 ). However, despite some promising results, learning analytics does not have the same level of adoption in other educational contexts, such as high schools ( Cechinel et al, 2020 ; Ifenthaler, 2021 ). That is a limitation, as the adoption of educational technology in these levels of education has created environments where rich information could be extracted from the generated data ( Schmid and Petko, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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Applications of Learning Analytics in High Schools: A Systematic Literature Review

Sousa

Alexandre

Mello

et al. 2021

Front. Artif. Intell.

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Learning analytics aims to analyze data from students and learning environments to support learning at different levels. Although learning analytics is a recent field, it reached a high level of maturity, especially in its applications for higher education. However, little of the research in learning analytics targets other educational levels, such as high school. This paper reports the results of a systematic literature review (SLR) focused on the adoption of learning analytics in high schools. More specifically, the SLR followed four steps: the search, selection of relevant studies, critical assessment, and the extraction of the relevant field, which included the main goals, approaches, techniques, and challenges of adopting learning analytics in high school. The results show that, in this context, learning analytics applications are focused on small-scale initiatives rather than institutional adoption. Based on the findings of this study, in combination with the literature, this paper proposes future directions of research and development in order to scale up learning analytics applications in high schools.

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Section: Learning Analyticsmentioning

confidence: 99%

Section: Research Questionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Applications of Learning Analytics in High Schools: A Systematic Literature Review

Sousa

Alexandre

Mello

et al. 2021

Front. Artif. Intell.

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“…Even though Latin America already has a number of initiatives in the field of LA ( dos Santos et al., 2017 ), they are also mainly concentrated on the use of data coming from the tertiary level ( Cechinel et al., 2020 ; Hilliger et al., 2020 ). Works that include data from primary and secondary level are very few in Latin America, as well as the works including the integration of different granularities of data sources coming from different institutions.…”

Section: Literature Reviewmentioning

confidence: 99%

Unveiling educational patterns at a regional level in Colombia: data from elementary and public high school institutions

Hernandez-Leal

Méndez

Cechinel

2021

Heliyon

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Even though the field of Learning Analytics (LA) has experienced an expressive growth in the last few years. The vast majority of the works found in literature are usually focusing on experimentation of techniques and methods over datasets restricted to a given discipline, course, or institution and are still few works manipulating region and countrywide datasets. This may be since the implementation of LA in national or regional scope and using data from governments and institutions poses many challenges that may threaten the success of such initiatives, including the same availability of data. The present article describes the experience of LA in Latin America using governmental data from Elementary and Middle Schools of the State of Norte de Santander - Colombia. This study is focusing on students' performance. Data from 2013 to 2018 was collected, containing information related to 1) students’ enrollment in school disciplines provided by Regional Education Secretary, 2) students qualifications provided by educational institutions, and 3) students qualifications provided by the national agency for education evaluation. The methodology followed includes a process of cleaning and integration of the data, subsequently a descriptive and visualization analysis is made and some educational data mining techniques are used (decision trees and clustering) for the modeling and extraction of some educational patterns. A total of eight patterns of interest are extracted. In addition to the decision trees, a feature ranking analysis was performed using xgboost and to facilitate the visual representation of the clusters, t-SNE and self-organized maps (SOM) were applied as result projection techniques. Finally, this paper compares the main challenges mentioned by the literature according to the Colombian experience and proposes an up-to-date list of challenges and solutions that can be used as a baseline for future works in this area and aligned with the Latin American context and reality.

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“…In an academic environment, the identification of such attributes is relevant to get some insights and information about students’ knowledge, misconceptions, and problem-solving when learning new concepts [ 10 ], and to give feedback to them. Feedback is essential for students to achieve their goals [ 11 ], and its role in the learning process is to confirm or propose changes in their knowledge [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

A Learning Analytics Framework to Analyze Corporal Postures in Students Presentations

Vieira

Cechinel

Ramos

et al. 2021

Sensors

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Communicating in social and public environments are considered professional skills that can strongly influence career development. Therefore, it is important to proper train and evaluate students in this kind of abilities so that they can better interact in their professional relationships, during the resolution of problems, negotiations and conflict management. This is a complex problem as it involves corporal analysis and the assessment of aspects that until recently were almost impossible to quantitatively measure. Nowadays, a number of new technologies and sensors have being developed for the capture of different kinds of contextual and personal information, but these technologies were not yet fully integrated inside learning settings. In this context, this paper presents a framework to facilitate the analysis and detection of patterns of students in oral presentations. Four steps are proposed for the given framework: Data collection, Statistical Analysis, Clustering, and Sequential Pattern Mining. Data Collection step is responsible for the collection of students interactions during presentations and the arrangement of data for further analysis. Statistical Analysis provides a general understanding of the data collected by showing the differences and similarities of the presentations along the semester. The Clustering stage segments students into groups according to well-defined attributes helping to observe different corporal patterns of the students. Finally, Sequential Pattern Mining step complements the previous stages allowing the identification of sequential patterns of postures in the different groups. The framework was tested in a case study with data collected from 222 freshman students of Computer Engineering (CE) course at three different times during two different years. The analysis made it possible to segment the presenters into three distinct groups according to their corporal postures. The statistical analysis helped to assess how the postures of the students evolved throughout each year. The sequential pattern mining provided a complementary perspective for data evaluation and helped to observe the most frequent postural sequences of the students. Results show the framework could be used as a guidance to provide students automated feedback throughout their presentations and can serve as background information for future comparisons of students presentations from different undergraduate courses.

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Mapping Learning Analytics initiatives in Latin America

Cited by 33 publications

References 14 publications

Applications of Learning Analytics in High Schools: A Systematic Literature Review

Applications of Learning Analytics in High Schools: A Systematic Literature Review

Unveiling educational patterns at a regional level in Colombia: data from elementary and public high school institutions

A Learning Analytics Framework to Analyze Corporal Postures in Students Presentations

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