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This study focused on the effects of an early math online professional learning course offered to preschool teachers. The course was designed to inform participants' knowledge of developmental progressions and promote daily mathematics instruction that ...

One of the enduring challenges for the Machine Learning community is developing models that can process and learn from very long data sequences. Transformer-based models and Recurrent Neural Networks (RNNs) have excelled in processing long ...

As massive medical data become available with an increasing number of scans, expanding classes, and varying sources, prevalent training paradigms—where AI is trained with multiple passes over fixed, finite datasets—face significant challenges. ...

Likert-type items or scales, as well as open-ended questions, are frequently used in the collection of student feedback. While the analysis of numeric feedback includes many established statistical techniques, systematic analyses of answers to ...

Modeling spatiotemporal interactions in multivariate time series is key to their effective processing, but challenging because of their irregular and often unknown structure. Statistical properties of the data provide useful biases to model ...

Online learning (OL) is a new platform, which is used as a supplementary resource to improve the teaching and learning process in university education. The open educational resources provide supplementary resources for strengthening online learning ...

Revamped IPE confronts static material constraints and outdated pedagogy, warranting integration of web resources and big data analytics for instructional innovation. Digital IPE adoption in vocational education optimizes online resource use, enhancing ...

Scholars have long delved into the realm of MOOCs. However, with the proliferation of diverse platforms hosting course videos, it was realized that learning experiences may vary across these platforms. Hence, this research explores the forums within two ...

The COVID-19 pandemic has affected individuals across various sectors, including university students. As a result, online learning emerged as the primary mode of education worldwide, including in the Philippines. However, the abrupt shift to online ...

The rapid expansion of online education has highlighted the critical need for a reliable and efficient learning evaluation framework. To address this challenge, we propose a blockchain-powered framework for assessing educational behavior ...

The knowledge concept recommendation aims to identify and suggest specific knowledge concepts that a student needs to master on Massive Open Online Courses (MOOCs) platforms, addressing the information overload issue and offering a tailored ...$\underset{}{}\underset{}{}\underset{}{}\underset{}{}$

Electroencephalography (EEG) based Brain Computer Interface (BCI) systems play a significant role in facilitating how individuals with neurological impairments effectively interact with their environment. In real world applications of BCI system ...

In the information age, with the explosive growth of data volume, big data analysis and prediction have become central to ensuring stable operations across various industries. As hardware computing power increases and data volume continues to grow, the ...

This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an “interest” parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. ...

Self-directed learning and the ability to self-regulate are crucial for success in online studies. This study focuses on the development and evaluation of digital nudges in learning management systems (LMS) to strengthen these key competencies in ...

Persuasive messages and communications are powerful tools for influencing individuals’ behaviours in a specific manner. A range of persuasive strategies are employed to construct persuasive messages to make them more effective. In this research, ...

This research aims to analyze the influence of perceived enjoyment, perceived ease of use, perceived usefulness, and social influence on online learning intentions among RPL students at universities in Indonesia, especially in Surabaya. RPL students are ...

We study the problem of regret minimization for a single bidder in a sequence of first-price auctions where the bidder discovers the item’s value only if the auction is won. Our main contribution is a complete characterization, up to logarithmic factors, ...

Bilateral trade models the problem of intermediating between two rational agents — a seller and a buyer — both characterized by a private valuation for an item they want to trade. We study the online learning version of the problem, in which at each time ...

Hybridizing learning and optimization often improves existing algorithms in single-objective optimization. Indeed, high-quality solutions often contain relevant knowledge that can be used to guide the heuristic towards promising areas. Learning ...