Exploring Social Constructivist Practices: Collaborative Learning Challenges and Strategies in TEFL Classrooms at Islamic Boarding Schools by Rizki Azizah, Putri Itsna Ulayya, Endang Fauziati

“…Within these institutions, implementing collaborative learning presents unique challenges due to their emphasis on discipline, religious values, and limited technological access. …”
Get full text

Konstruktivisme Model Pembelajaran Kognitif Moral Melalui Aplikasi “Dimo” Untuk Meningkatkan Kemampuan Moral Decision Siswa Sekolah Dasar by Aiman Faiz, Aris Fadly

“…This study provides recommendations that with active and varied models, students can better understand the context of the learning presented.…”
Get full text

Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors. by Toheeb Salahudeen, Maher Maalouf, Ibrahim Abe M Elfadel, Herbert F Jelinek

“…Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present an avenue for further investigation. This study employed advanced machine learning techniques to classify major depressive disorders based on clinical indicators and mitochondrial oxidative stress markers. …”
Get full text

Identifying Challenges and Opportunities in the Implementation of Mobile Learning in Physical Education: A Literature Review by Raehang, La Ode Adhi Virama, Dewangga Yudhistira

“…The findings indicate that mobile learning presents both challenges and opportunities in physical education. …”
Get full text

Assessing the effectiveness of transfer learning strategies in BLSTM networks for speech denoising by Marvin Coto-Jiménez, Astryd González-Salazar, Michelle Gutiérrez-Muñoz

“…For denoising the speech signals degraded with the many kinds and possibly different levels of noise, several algorithms have been proposed during the past decades, with recent proposals based on deep learning presented as state-of-the-art, in particular those based on Long Short-Term Memory Networks (LSTM and Bidirectional-LSMT). …”
Get full text

Exploring the Impact of Mobile Devices in E-Learning: A case Study Evaluating its Effectiveness by Khalid Ghoulam, Belaid Bouikhalene

“…The integration of mobile devices into educational environments has revolutionized the landscape of e-learning, presenting new opportunities and challenges. This research paper aims to examine the pivotal role of mobile devices in the e-learning environment and assess the effectiveness of mobile learning applications in enhancing the educational experience. …”
Get full text

Dynamic Multi-Level Competition Learning-Based Dual-Task Optimization for High-Dimensional Feature Selection by Weiwei Zhang, Yiwei Zhao, Chunbo Yuan, Xiaolong Chen, Wenzhao Liu, Yingjie Feng, Yongxin Feng, Jinchu Yang, Meng Li

“…Feature selection (FS) is a critical task in data science and machine learning, presenting significant challenges in high-dimensional settings due to the complexity and noise inherent in large feature sets. …”
Get full text

The Taxonomy Mobile Learning Applications in Higher Institutions of Learning in Ugandan Universities: A Case of Kabale University, Uganda. by Muhaise, Hussein, Businge,Phelix Mbabazi, Ssemaluulu, Paul, Muhoza, Gloria

“…As a result, currently, existing models do not specifically address mobile learning, presenting a gap that we aimed to remedy. The study developed a model that estimates usability as a function of aggregated usability influencing factors. …”
Get full text

Educational multimedia design principles affect local and global information processing in functional brain networks by Mohammadhossein Ostadi, Masoumeh Golmohamadian, Alireza Bosaghzadeh, S. Hamid Amiri, Reza Ebrahimpour

“…However, the complex cognitive processes involved in multimedia learning present challenges for understanding its neural mechanisms. …”
Get full text

Developing national frameworks for climate services: Experiences, challenges and learnings from across Europe by Nicola Golding, Keith Lambkin, Louise Wilson, Rozemien De Troch, Andreas Marc Fischer, Hans Olav Hygen, Angela Michiko Hama, Anita Verpe Dyrrdal, Ella Jamsin, Piet Termonia, Christopher Hewitt

“…While this article focuses on the experiences and practical learning within Europe, the benefit of establishing an NFCS is global, and many of the challenges and learnings presented here will be relevant anywhere in the world.It is the experience of this group that peer support has accelerated and enhanced the NFCS implementation process, as well as provided a forum for exchange on how to maintain and evolve an operational NFCS. …”
Get full text

Unlocking the potential of miRNAs in detecting pulmonary tuberculosis: prospects and pitfalls by Rakesh Arya, Surendra Kumar, Joseph M. Vinetz, Jong Joo Kim, Reetika Chaurasia

“…These limitations can be overcome by integrating standard protocols with machine learning, presenting a novel tool for TB diagnostics and therapeutics. …”
Get full text

Non-Invasive Monitoring of Cerebral Edema Using Ultrasonic Echo Signal Features and Machine Learning by Shuang Yang, Yuanbo Yang, Yufeng Zhou

“…The fusion of ultrasound echo features with machine learning presents a promising non-invasive approach for the monitoring of cerebral edema.…”
Get full text

Generative adversarial networks (GANS) for generating face images by Dolly Indra, Muh Wahyu Hidayat, Fitriyani Umar

“…The advancement of artificial intelligence technology, particularly deep learning, presents significant potential in facial image processing. …”
Get full text

Challenging paradigms: integrating Critical Feminist Service-Learning into Higher Education Physical Activity and Sport programs by Nuria Cuenca Soto, María Luisa Santos-Pastor, Oscar Chiva-Bartoll, Luis Fernando Martínez-Muñoz

“…This article aims to define the pedagogical model called Critical Feminist Service-Learning, presenting a series of keys that allow feminist theories to be applied in real-life contexts within the framework of Physical Activity and Sports. …”
Get full text

Digital Media and Foreign Language Learning

“…Dieter Kranz examines blended learning, presenting case studies and reflections on how digital and face-to-face learning complement each other. …”
Get full text

Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…Addressing these risks requires advanced diagnostic and management strategies, and machine learning presents a powerful solution due to its ability to adapt across multiple facets of battery management. …”
Get full text

The effectiveness, equity and explainability of health service resource allocation—with applications in kidney transplantation & family planning by Joris van de Klundert, Harwin de Vries, Francisco Pérez-Galarce, Nieves Valdes, Felipe Simon

“…The current advances in machine learning present opportunities to better predict allocation effects and to prescribe solutions that better balance effectiveness and equity. …”
Get full text

A Low Computational Cost Deep Learning Approach for Localization and Classification of Diseases and Pests in Coffee Leaves by Clecio Elias Silva E. Silva, Jonatan Borges Fragoso, Thuanne Paixao, Ana Beatriz Alvarez, Facundo Palomino-Quispe

“…In this context, deep learning presents itself as a promising solution for the automatic identification of plant diseases, reducing dependence on human inspection and increasing efficiency in crop management. …”
Get full text

A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…Traditional bioinformatics methods often struggle to capture the intricate sequence patterns and high-dimensional signals characteristic of epitope data. Deep learning presents a compelling alternative, with its ability to perform automatic feature learning and model complex dependencies inherent in biological sequences. …”
Get full text

Comparison of sample preparation methods for higher heating values in various sugarcane varieties using near-infrared spectroscopy by Kantisa Phoomwarin, Khwantri Saengprachatanarug, Jetsada Posom, Seree Wongpichet, Kittipong Laloon, Arthit Phuphaphud

“…The integration of NIR spectroscopy with machine learning presents a practical and scalable approach for accelerating the evaluation of sugarcane clones, offering significant advantages in terms of time efficiency, cost reduction, and sample throughput.…”
Get full text