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Luiz Rodrigues; Guilherme Guerino; Thomaz E. V. Silva; Geiser C. Challco; Lívia Oliveira; Rodolfo S. da Penha; Rafael F. Melo; Thales Vieira; Marcelo Marinho; Valmir Macario; Ig I. Bittencourt; Diego Dermeval; Seiji Isotani – International Journal of Artificial Intelligence in Education, 2025
Intelligent Tutoring Systems (ITS) possess significant potential to enhance learning outcomes. However, deploying ITSs in global south countries presents challenges due to their frequent lack of essential technological resources, such as computers and internet access. The concept of AIED Unplugged has emerged to bridge this digital divide,…
Descriptors: Teacher Attitudes, Intelligent Tutoring Systems, Numeracy, Mathematics Education
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Journal of Information Systems Education, 2023
Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream…
Descriptors: Comparative Analysis, Programming Languages, Probability, Error Patterns
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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
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Peltier, Corey; Peltier, Tiffany K. – Beyond Behavior, 2020
The mathematics performance of students identified with emotional and behavioral disorders (EBD) is poor. Students identified with EBD require individualized instruction aligned with their unique academic and behavioral needs. One way that teachers can efficiently identify core mathematics deficits and provide individualized instruction is through…
Descriptors: Mathematics Instruction, Individualized Instruction, Mathematics Achievement, Emotional Disturbances
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de Mooij, Susanne M. M.; Raijmakers, Maartje E. J.; Dumontheil, Iroise; Kirkham, Natasha Z.; van de Maas, Han L. J. – Journal of Computer Assisted Learning, 2021
While response time and accuracy indicate overall performance, their value in uncovering cognitive processes, underlying learning, is limited. A promising online measure, designed to track decision-making, is computer mouse tracking, where mouse attraction towards different locations may reflect the consideration of alternative response options.…
Descriptors: Error Patterns, Identification, Computer Peripherals, Computer Uses in Education
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
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Donaldson, Maleka – Journal of Educational Research, 2019
Now, more than ever, American students at all grade levels face intense pressure to increase academic performance--including kindergarteners. Given that prior research has well established that mistakes and corrective feedback are key elements of the learning endeavor, it is critical to closely examine teachers' mistake-related experiences within…
Descriptors: Kindergarten, Preschool Teachers, Teacher Attitudes, Teacher Student Relationship
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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
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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
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