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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
Haim, Aaron; Gyurcsan, Robert; Baxter, Chris; Shaw, Stacy T.; Heffernan, Neil T. – International Educational Data Mining Society, 2023
Despite increased efforts to assess the adoption rates of open science and robustness of reproducibility in sub-disciplines of education technology, there is a lack of understanding of why some research is not reproducible. Prior work has taken the first step toward assessing reproducibility of research, but has assumed certain constraints which…
Descriptors: Conferences (Gatherings), Educational Research, Replication (Evaluation), Access to Information
Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, 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
Beth Chance; Andrew Kerr; Jett Palmer – Journal of Statistics and Data Science Education, 2024
While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…
Descriptors: Publications, Public Opinion, Surveys, Bias
Luiz Rodrigues; Filipe Dwan Pereira; Marcelo Marinho; Valmir Macario; Ig Ibert Bittencourt; Seiji Isotani; Diego Dermeval; Rafael Mello – Education and Information Technologies, 2024
Intelligent Tutoring Systems (ITS) have been widely used to enhance math learning, wherein teacher's involvement is prominent to achieve their full potential. Usually, ITSs depend on direct interaction between the students and a computer. Recently, researchers started exploring handwritten input (e.g., from paper sheets) aiming to provide…
Descriptors: Intelligent Tutoring Systems, Handwriting, Equal Education, Access to Education
Christine M. White; Stephanie A. Estrera; Christopher Schatschneider; Sara A. Hart – Grantee Submission, 2024
Researchers in the education sciences, like those in other disciplines, are increasingly encountering requirements and incentives to make the data supporting empirical research available to others. However, the process of preparing and sharing research data can be daunting. The present article aims to support researchers who are beginning to think…
Descriptors: Data, Educational Research, Information Dissemination, Incentives
Liu, Min; Pan, Zilong; Li, Chenglu; Han, Songhee; Shi, Yi; Pan, Xin – International Journal on E-Learning, 2021
There has been an increasing interest in learning analytics (LA) research especially in higher education (HE) in recent years. In this study, we conducted a systematic focused review of research, from 2016 to present, on using analytics in HE (specifically system- or user-generated data) to understand in what way such analytics has been…
Descriptors: Learning Analytics, Educational Research, Higher Education, Data Collection
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
Hung, Jui-long – British Journal of Educational Technology, 2012
This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…
Descriptors: Electronic Learning, Medical Education, Social Sciences, Journal Articles
Baker, Ryan S. J. D.; Yacef, Kalina – Journal of Educational Data Mining, 2009
We review the history and current trends in the field of Educational Data Mining (EDM). We consider the methodological profile of research in the early years of EDM, compared to in 2008 and 2009, and discuss trends and shifts in the research conducted by this community. In particular, we discuss the increased emphasis on prediction, the emergence…
Descriptors: Trend Analysis, Educational History, Educational Research, Research Methodology

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