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Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
Garcia, Léo Manoel Lopes da Silva; Lara, Daiany Francisca; Gomes, Raquel Salcedo; Cazella, Silvio Cézar – Turkish Online Journal of Educational Technology - TOJET, 2022
In educational data mining (EDM), preprocessing is an arduous and complex task and must promote an appropriate treatment of data to solve each specific educational problem. In the same way, the parameters used in the evaluation of postprocessing results are decisive in the interpretation of the results and decision-making in the future. These two…
Descriptors: Educational Research, Information Retrieval, Data Processing, Mathematics
Nyland, Rob – Journal of Educational Technology Systems, 2018
The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose…
Descriptors: Formative Evaluation, Data Collection, Data Processing, Data Analysis
Villanueva Manjarres, Andrés; Moreno Sandoval, Luis Gabriel; Salinas Suárez, Martha Janneth – Digital Education Review, 2018
Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…
Descriptors: Information Retrieval, Data Analysis, Educational Environment, Research Methodology
Schwendimann, Beat A.; Rodriguez-Triana, Maria Jesus; Vozniuk, Andrii; Prieto, Luis P.; Boroujeni, Mina Shirvani; Holzer, Adrian; Gillet, Denis; Dillenbourg, Pierre – IEEE Transactions on Learning Technologies, 2017
This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning…
Descriptors: Literature Reviews, Educational Research, Data Analysis, Data Processing
Yin, Chengjiu; Hirokawa, Sachio; Yau, Jane Yin-Kim; Hashimoto, Kiyota; Tabata, Yoshiyuki; Nakatoh, Tetsuya – International Journal of Distance Education Technologies, 2013
To help researchers in building a knowledge foundation of their research fields which could be a time-consuming process, the authors have developed a Cross Tabulation Search Engine (CTSE). Its purpose is to assist researchers in 1) conducting research surveys, 2) efficiently and effectively retrieving information (such as important researchers,…
Descriptors: Search Engines, Online Searching, Surveys, Research

Berghel, H. L. – Information Processing and Management, 1987
Proposes a method for correcting spelling errors found in electronic documents which is derived from a logical analysis of the problem. Similarity relations and character string matching are discussed, the use of PROLOG is described, suggestions for further research are made, and a literature review is included. (47 references) (Author/LRW)
Descriptors: Data Processing, Literature Reviews, Logic, Research Needs

Shaffer, Clifford A. – Annual Review of Information Science and Technology (ARIST), 1992
Surveys the field and literature of geographic information systems (GIS) and spatial data representation as it relates to GIS. Highlights include GIS terms, data types, and operations; vector representations and raster, or grid, representations; spatial indexing; elevation data representations; large spatial databases; and problem areas and future…
Descriptors: Data Analysis, Data Processing, Databases, Futures (of Society)