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No Child Left Behind Act 20011
Showing 1 to 15 of 39 results Save | Export
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Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
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Nathan Jones; Lindsey Kaler; Jessica Markham; Josefina Senese; Marcus A. Winters – Educational Researcher, 2025
Students with and without disabilities may be educated across various service delivery models (SDMs): general education, cotaught, pull-out, and self-contained. Still, evidence for their relative effectiveness at scale remains limited. Using longitudinal administrative data from Indiana, we measured the effect of different SDMs on test scores,…
Descriptors: Students with Disabilities, Teaching Methods, Students, Instructional Effectiveness
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Hongyan Xi; Dongyan Sang – International Journal of Information and Communication Technology Education, 2024
By using modern data analysis techniques, this study aims to construct an innovative university English teaching effectiveness evaluation model based on particle swarm algorithm and support vector machine. The model is designed to improve assessment accuracy and personalization. The research process includes the methodology of data collection,…
Descriptors: Foreign Countries, English (Second Language), Second Language Instruction, Higher Education
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Danial Hooshyar; Nour El Mawas; Yeongwook Yang – Knowledge Management & E-Learning, 2024
The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…
Descriptors: Artificial Intelligence, Course Content, Tests, Scores
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Thontirawong, Pipat; Chinchanachokchai, Sydney – Marketing Education Review, 2021
In the age of big data and analytics, it is important that students learn about artificial intelligence (AI) and machine learning (ML). Machine learning is a discipline that focuses on building a computer system that can improve itself using experience. ML models can be used to detect patterns from data and recommend strategic marketing actions.…
Descriptors: Marketing, Artificial Languages, Career Development, Time Management
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Dæhli, Olav; Kristoffersen, Bjørn; Lauvås, Per, Jr.; Sandnes, Tomas – Electronic Journal of e-Learning, 2021
Data modeling is an essential part of IT studies. Learning how to design and structure a database is important when storing data in a relational database and is common practice in the IT industry. Most students need much practice and tutoring to master the skill of data modeling and database design. When a student is in a learning process,…
Descriptors: Game Based Learning, Educational Games, Computer Games, Information Technology
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Ambrosetti, Angelina; Dekkers, John; Knight, Bruce Allen – Mentoring & Tutoring: Partnership in Learning, 2017
Within many preservice teacher education programs in Australia, mentoring is used as the overarching methodology for the professional placement. The professional placement is considered to be a key component of learning to teach, and typically a dyad mentoring model is utilized. However, it is reported that many preservice teachers experience a…
Descriptors: Mentors, Models, Preservice Teacher Education, Preservice Teachers
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Olney, Andrew M.; Donnelly, Patrick J.; Samei, Borhan; D'Mello, Sidney K. – International Educational Data Mining Society, 2017
Automatic assessment of dialogic properties of classroom discourse would benefit several widespread classroom observation protocols. However, in classrooms with low incidences of dialogic discourse, assessment can be highly biased against detecting dialogic properties. In this paper, we present an approach to addressing this imbalanced class…
Descriptors: Models, Classroom Communication, Audio Equipment, Discourse Analysis
Norton, Jill; Goodson, Barbara; Checkoway, Amy; Velez, Melissa – Abt Associates, 2017
Increasingly, early education, regardless of setting type, is considered to be an educational intervention that sets the stage for children's long-term school success. Accordingly, policymakers are focused on how to develop and support educators who have the skills and capacity to deliver high-quality programming to children. A pressing question…
Descriptors: Coaching (Performance), Early Childhood Education, Capacity Building, Elementary School Teachers
Rollinson, Joseph; Brunskill, Emma – International Educational Data Mining Society, 2015
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Descriptors: Prediction, Models, Educational Policy, Intelligent Tutoring Systems
Huang, Yun; González-Brenes, José P.; Kumar, Rohit; Brusilovsky, Peter – International Educational Data Mining Society, 2015
Latent variable models, such as the popular Knowledge Tracing method, are often used to enable adaptive tutoring systems to personalize education. However, finding optimal model parameters is usually a difficult non-convex optimization problem when considering latent variable models. Prior work has reported that latent variable models obtained…
Descriptors: Guidelines, Models, Prediction, Evaluation Methods
Nye, Benjamin D.; Morrison, Donald M.; Samei, Borhan – International Educational Data Mining Society, 2015
Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…
Descriptors: Tutoring, Instructional Effectiveness, Tutors, Models
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Izadi, Dina; Ley, César Eduardo Mora; Díaz, Mario Humberto Ramírez – Physics Education, 2017
Succeeding theories and empirical investigations have often been built over conceptual understanding to develop talent education. Opportunities provided by society are crucial at every point in the talent-development process. Abilities differ and can vary among boys and girls. Although they have some responsibility for their own growth and…
Descriptors: Foreign Countries, Science Education, Student Motivation, Student Attitudes
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Mohamed-Salah, Boukhechem; Alain, Dumon – Chemistry Education Research and Practice, 2016
This study aims to assess whether the handling of concrete ball-and-stick molecular models promotes translation between diagrammatic representations and a concrete model (or vice versa) and the coordination of the different types of structural representations of a given molecular structure. Forty-one Algerian undergraduate students were requested…
Descriptors: Foreign Countries, Undergraduate Students, Molecular Structure, Models
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Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao – Interactive Learning Environments, 2016
To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…
Descriptors: Reading Strategies, Prediction, Models, Quasiexperimental Design
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