E ‑learning in Higher Education by Dorota Górska

“…The aim of the article is to present main objectives of the teaching method of e ‑learning, and at the same time, to present the legal status and the rules for the use of e ‑learning in Polish higher education. …”
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Language learning in practical training

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Experiential learning for societal impact by Elizabeth A. McCrea, Dilip Mirchandani

“…It presents a typography organizing experiential learning activities along two dimensions: classroom-based versus community-based experiences and students as investments versus agents of change. …”
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Learning Classic Grounded Theory by Carol Roderick

“…This challenge increases further when graduate students encounter poor advice from dissertation supervisors who are unfamiliar with the methodology, or attempt to incorporate elements from the many alternative and modified versions of grounded theory presented in the literature. This article provides an account of one student’s experience learning CGT to complete her doctoral dissertation. …”
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The Blended Learning Science Training by T P. Pushkaryeva, V. V. Kalitina

“…This allows the student to create their individual trajectory of informatics learning. In order to take into account the peculiarities of perception of information by representatives of the digital generation, the content of the course is presented using traditional methodology and nonlinear technologies of informatics training: concentric, parallel and cognitive; lectures are given as text, presentations and infographics; for each module a mental map is created, allowing to cover the content of the module in its entirety and study it not sequentially, but at its own discretion. …”
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Learning from Literature and Heritage by Aleksandar Staničić, Angeliki Sioli

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The machine learning in the prediction of elections by M.S.C. José A. León-Borges, M.A. Roger-Ismael-Noh-Balam, Lic. Lino Rangel Gómez, Br. Michael Philip Strand

“…This research article, presents an analysis and a comparison of three different algorithms: A.- Grouping method K-means, B.…”
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Enhancing the Learning Experience with AI by Adrian Runceanu, Adrian Balan, Laviniu Gavanescu, Marian-Madalin Neagu, Cosmin Cojocaru, Ilie Borcosi, Aniela Balacescu

“…This study’s purpose is to present and evaluate an intuitive open-source framework that transforms existing courses into interactive, AI-enhanced learning environments. …”
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Primer on Machine Learning in Electrophysiology by Shane E Loeffler, Natalia Trayanova

“…The authors present a primer to provide an overview of common supervised (least squares, support vector machine, neural networks and random forest) and unsupervised (k-means and principal component analysis) machine learning models. …”
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Deep learning for computational biology by Christof Angermueller, Tanel Pärnamaa, Leopold Parts, Oliver Stegle

“…This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. …”
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A unified learning framework for by K. Seetharaman, S. Sathiamoorthy

“…This paper presents a unified learning framework for heterogeneous medical image retrieval based on a Full Range Autoregressive Model (FRAR) with the Bayesian approach (BA). …”
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Examination in Conditions of Distance Learning by Malshakova I.L., Portnov Yu.A.

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Tracheal Allotransplantation–Lessons Learned by Subramania Iyer, Narayana Subramaniam, Sivakumar Vidhyadharan, Krishnakumar Thankappan, Deepak Balasubramanian, Balasubramanian K. R., Arun Nair, Kishore Purushottaman, Janarthanan Ramu, Zachariah Paul

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Learning for Universal Health Coverage by Joël Arthur Kiendrébéogo, Bruno Meessen, EL Houcine Akhnif, Abdelali Belghiti Alaoui, Kefilath Bello, Sanghita Bhattacharyya, Hannah Sarah Faich Dini, Fahdi Dkhimi, Jean-Paul Dossou, Allison Gamble Kelley, Basile Keugoung, Tamba Mina Millimouno, Jérôme Pfaffmann Zambruni, Maxime Rouve, Isidore Sieleunou, Godelieve van Heteren

“…We present some of our experience and draw lessons for countries and international actors interested in strengthening national systemic learning capacities for UHC. …”
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Data normalization in machine learning by V. V. Starovoitov, Yu. I. Golub

“…In machine learning, the input data is often given in different dimensions. …”
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Norepinephrine and Dopamine as Learning Signals by Carolyn W. Harley

“…The present review focuses on the hypothesis that norepinephrine (NE) and dopamine (DA) act as learning signals. …”
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The Conceptual Approach to Lifelong Learning by Larisa ȘAVGA

“…In this sense, capitalizing on the concept of lifelong learning (hereinafter LLL) opens up major opportunities for the development and continuous adjustment of skills to the needs of the labour market. …”
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Portfolio of learning in clinical training by Louis S. Jenkins

“…Workplace-based assessment is increasingly crucial in the postgraduate training of specialists in South Africa, including for family physicians. A portfolio of learning allows a structured, flexible way to present evidence of learning. …”
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Feedback-Based Validation Learning by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…This paper presents Feedback-Based Validation Learning (FBVL), a novel approach that transforms the role of validation datasets in deep learning. …”
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Whether Interleaving or Blocking Is More Effective for Long-Term Learning Depends on One’s Learning Strategy by Jeri L. Little, Jexy A. Nepangue

“…Grouping information into categories enables us to learn, integrate, and apply new information. Presenting items from different categories sequentially (i.e., interleaving) is often more effective than presenting items from a single category sequentially (i.e., blocking), particularly when evaluating learning using memory-based tests. …”
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