NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20250
Since 20240
Since 2021 (last 5 years)0
Since 2016 (last 10 years)7
Since 2006 (last 20 years)14
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing all 14 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Shilo, Gila; Ragonis, Noa – Journal of Further and Higher Education, 2019
A central issue in the design of curricula for all school levels is the development of the learners' high-order thinking skills and metacognitive skills. Among such required skills is the ability to solve problems. The literature dealing with the development of problem-solving skills is vast and primarily addresses the scientific disciplines, even…
Descriptors: Thinking Skills, Metacognition, Problem Solving, Linguistics
Peer reviewed Peer reviewed
Direct linkDirect link
Hopkins, Sarah; Bayliss, Donna – Mathematical Thinking and Learning: An International Journal, 2017
In this research, we examined how 200 students in seventh grade (around 12 years old) solved simple addition problems. A cluster approach revealed that less than half of the cohort displayed proficiency with simple addition: 35% predominantly used min-counting and were accurate, and 16% frequently made min-counting errors. Students who frequently…
Descriptors: Middle School Students, Grade 7, Problem Solving, Mathematics Skills
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kerr, Deirdre – Journal of Educational Data Mining, 2015
This study uses information about in-game strategy use, identified through cluster analysis of actions in an educational video game, to make data-driven modifications to the game in order to reduce construct-irrelevant behavior. The examination of student strategies identified through cluster analysis indicated that (a) it was common for students…
Descriptors: Information Retrieval, Data Analysis, Video Games, Educational Games
Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2015
This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…
Descriptors: Learning Activities, Learning Processes, Data Collection, Student Behavior
Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman – Online Submission, 2015
The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…
Descriptors: Science Achievement, Mathematics Achievement, Information Retrieval, Data Analysis
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – International Educational Data Mining Society, 2015
The field of EDM has focused more on modeling student knowledge than on investigating what sequences of different activity types achieve good learning outcomes. In this paper we consider three activity types, targeting sense-making, induction and refinement, and fluency building. We investigate what mix of the three types might be most effective…
Descriptors: Information Retrieval, Data Analysis, Learning Activities, Grade 4
Peer reviewed Peer reviewed
Direct linkDirect link
Yeh, Yi-Fen; Hsu, Ying-Shao; Chuang, Fu-Tai; Hwang, Fu-Kwun – Australasian Journal of Educational Technology, 2014
With the near-overload of online information, it is necessary to equip our students with the skills necessary to deal with Information Problem Solving (IPS). This study also intended to help students develop major IPS strategies with the assistance of an instructor's scaffolding in a designed IPS course as well as on an Online Information…
Descriptors: Middle School Students, Educational Technology, Information Literacy, Computer Literacy
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kiray, S. Ahmet; Gok, Bilge; Bozkir, A. Selman – Journal of Education in Science, Environment and Health, 2015
The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…
Descriptors: Science Achievement, Information Retrieval, Data Analysis, Middle School Students
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Gross, Melissa; Latham, Don; Underhill, Jennifer; Bak, Hyerin – School Library Research, 2016
An after-school book club, led by the school librarian, was held to test the efficacy of the peritextual literacy framework (PLF) in teaching skills related to critical thinking, problem solving, information literacy, and media literacy. The PLF is an extension of paratext theory developed by Gérard Genette, which provides a typology of the…
Descriptors: Middle School Students, After School Programs, Youth Clubs, Clubs
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Carmo, Mafalda, Ed. – Online Submission, 2017
This book contains a compilation of papers presented at the International Conference on Education and New Developments (END 2017), organized by the World Institute for Advanced Research and Science (W.I.A.R.S.). Education, in our contemporary world, is a right since we are born. Every experience has a formative effect on the constitution of the…
Descriptors: Educational Quality, Models, Vocational Education, Outcomes of Education
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection