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Rodríguez-Martínez, José Antonio; González-Calero, José Antonio; Olmo-Muñoz, Javier; Arnau, David; Tirado-Olivares, Sergio – British Journal of Educational Technology, 2023
This study analyses the potential of a learning analytics (LA) based formative assessment to construct personalised teaching sequences in Mathematics for 5th-grade primary school students. A total of 127 students from Spanish public schools participated in the study. The quasi-experimental study was conducted over the course of six sessions, in…
Descriptors: Foreign Countries, Elementary School Students, Grade 5, Mathematics Instruction
Rebecca Smith – ProQuest LLC, 2019
In recent years, computer science has become a cornerstone of modern society. As a result, enrollment in undergraduate computer science programs has expanded rapidly. While the influx of talent into the field will undoubtedly lead to countless technological developments, this growth also brings new pedagogical challenges. Educational resources,…
Descriptors: Computer Science Education, Individualized Instruction, Interaction, Learning Experience
Hofman, Abe D.; Brinkhuis, Matthieu J. S.; Bolsinova, Maria; Klaiber, Jonathan; Maris, Gunter; van der Maas, Han L. J. – Journal of Intelligence, 2020
One of the highest ambitions in educational technology is the move towards personalized learning. To this end, computerized adaptive learning (CAL) systems are developed. A popular method to track the development of student ability and item difficulty, in CAL systems, is the Elo Rating System (ERS). The ERS allows for dynamic model parameters by…
Descriptors: Teaching Methods, Computer Assisted Instruction, Difficulty Level, Individualized Instruction
Dube, France; Bessette, Lyne; Dorval, Catherine – Online Submission, 2011
This collaborative research was carried out among 197 elementary school students, in the context of a rural Canadian school of the Quebec province. Several students of the school presented learning difficulties, mostly in writing. The teachers and the learning specialist decided to differentiate the groups in special subgroups of needs that met…
Descriptors: Elementary School Students, Learning Problems, Learning Disabilities, Foreign Countries
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals

Fowler, Mary Anne – Arithmetic Teacher, 1980
Diagnostic teaching is described and discussed. Different types of errors are explained and examples of errors and their possible diagnoses are given. (MK)
Descriptors: Educational Diagnosis, Elementary Education, Elementary School Mathematics, Error Patterns
Rivers, Wilga M. – 1972
Research into the psychology of perception can uncover important discoveries for more efficient learning. There must be increased understanding of the processing of input and the pre-processing of output for improved language instruction. Educators must at the present time be extremely wary of basing what they do in the foreign-language classroom…
Descriptors: Auditory Perception, Child Language, Cognitive Processes, Deep Structure
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