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The principles on which can be based computer model of process of training are formulated. Are considered: 1) the unicomponent model, which is recognizing that educational information consists of equal elements; 2) the multicomponent model,…

Other Computer Science · Computer Science 2013-12-12 R. V. Mayer

We introduce advocacy learning, a novel supervised training scheme for attention-based classification problems. Advocacy learning relies on a framework consisting of two connected networks: 1) $N$ Advocates (one for each class), each of…

Machine Learning · Computer Science 2019-08-08 Ian Fox , Jenna Wiens

We study a fundamental problem in the evaluation of large language models that we call training on the test task. Unlike wrongful practices like training on the test data, leakage, or data contamination, training on the test task is not a…

Computation and Language · Computer Science 2025-04-22 Ricardo Dominguez-Olmedo , Florian E. Dorner , Moritz Hardt

Knowledge constitutes the accumulated understanding and experience that humans use to gain insight into the world. In deep learning, prior knowledge is essential for mitigating shortcomings of data-driven models, such as data dependence,…

Machine Learning · Computer Science 2023-07-04 Hao Xu , Yuntian Chen , Dongxiao Zhang

Recent advances in big/foundation models reveal a promising path for deep learning, where the roadmap steadily moves from big data to big models to (the newly-introduced) big learning. Specifically, the big learning exhaustively exploits…

Machine Learning · Computer Science 2023-05-23 Yulai Cong , Miaoyun Zhao

Teaching electromagnetism by demonstrating a practical application associated with learning content is an important teaching technique. Demonstrations are often performed through video-assisted procedures, and are usually limited to a…

Physics Education · Physics 2018-11-20 Jiro Kitagawa

Classification is a major tool of statistics and machine learning. A classification method first processes a training set of objects with given classes (labels), with the goal of afterward assigning new objects to one of these classes. When…

Machine Learning · Statistics 2024-07-08 Jakob Raymaekers , Peter J. Rousseeuw , Mia Hubert

In the article, proposed is a new e-learning information technology based on an ontology driven learning engine, which is matched with modern pedagogical technologies. With the help of proposed engine and developed question database we have…

Computers and Society · Computer Science 2017-10-18 Liskin Viacheslav , Syrota Sergiy

In this paper, we will explain a successfully proven lecturing method based entirely on system design. Wireless communications will be used as an example to explain this new teaching philosophy.

Computers and Society · Computer Science 2013-06-10 Yousef R. Shayan , Mouhamed Abdulla

Machine learning is the science of discovering statistical dependencies in data, and the use of those dependencies to perform predictions. During the last decade, machine learning has made spectacular progress, surpassing human performance…

Machine Learning · Statistics 2016-07-13 David Lopez-Paz

Recent research has highlighted the high incidence of errors in spreadsheet models used in industry. In an attempt to reduce the incidence of such errors, a teaching approach has been devised which aids students to reduce their likelihood…

Computers and Society · Computer Science 2024-12-31 David Chadwick , Rodney E. Sue

Estimating heterogeneous treatment effects with machine learning has attracted substantial attention in both academic research and industrial practice. However, the two communities often evaluate models under markedly different conditions.…

Machine Learning · Computer Science 2026-05-26 George Panagopoulos

We know anything because we learn about it, there is anything we ever share about it, but now a lot of media that can represent how it happened as infrastructure of the knowledge sharing. This paper aims to introduce a model for…

Social and Information Networks · Computer Science 2013-01-08 Sufianto Mahfudz , Mahyuddin K. M. Nasution , Sawaluddin Nasution

Evolution is a fundamental process that shapes the biological world we inhabit, and reinforcement learning is a powerful tool used in artificial intelligence to develop intelligent agents that learn from their environment. In recent years,…

Neural and Evolutionary Computing · Computer Science 2023-06-19 Taboubi Ahmed

In most E learning systems educational activities are presented in a static way without bearing in mind the particulars or student levels and skills. Personalization and adaptation of an E learning management system are dependent on the…

Software Engineering · Computer Science 2021-07-13 TahirMohammadAli , Attique Ur Rehman , AliNawaz , Wasi Haider Butt

Sound educational policy recommendations require valid estimates of causal effects, but observational studies in physics education research sometimes have loosely specified causal hypotheses. The connections between the observational data…

Physics Education · Physics 2021-09-22 M. B. Weissman

Pedagogy is a method that handles the ethos and culture of instruction from educators and the learning of learners. Pedagogy of Information and Communications Technology (ICT) refers to the interactions among the teacher, children, and…

Computers and Society · Computer Science 2021-08-30 Al Maruf Hassan , Istiak Ahmed Mondal

Purpose: The teacher role in the classroom can explain important aspects of the student's school experience. The teacher-student relationship, a central dimension of social capital, influences students' engagement, and the teaching style…

The main objective of higher education institutions is to provide quality education to its students. One way to achieve highest level of quality in higher education system is by discovering knowledge for prediction regarding enrolment of…

Information Retrieval · Computer Science 2012-01-18 Brijesh Kumar Baradwaj , Saurabh Pal

For many interesting tasks, such as medical diagnosis and web page classification, a learner only has access to some positively labeled examples and many unlabeled examples. Learning from this type of data requires making assumptions about…

Machine Learning · Computer Science 2018-08-28 Jessa Bekker , Jesse Davis