Mobile language app learners’ self-efficacy increases after using generative AI by Audrey K. Kittredge, Elise W. M. Hopman, Ben Reuveni, Danielle Dionne, Cassie Freeman, Xiangying Jiang

“…Across studies, the majority of learners agreed that the AI-based features effectively supported learning, and reported using their learning outside the app.DiscussionThese results provide the first evidence of enhanced language learning self-efficacy after use of generative AI, building on findings from classroom interventions.…”
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Exploring Reading Comprehension Challenges in the Setswana Home Language Classroom: Learners’ and Techers’ Perspectives by Paulinah M. Mahoro, Mary M. Makgato, Tilla Olifant

“…This research contributes to the broader discourse on language-in-education in multilingual contexts and emphasizes the importance of addressing reading comprehension challenges to improve academic outcomes and support learners’ cognitive development and cultural identity.…”
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Navigating the Dynamics of Learner Absenteeism in South African Urban Secondary Schools: An In-Depth Management Analysis and Strategic Framework by Richard Moloele, Madikela T. Lekalakala

“…This research contributes to the broader discourse on language-in-education in multilingual contexts and emphasizes the importance of addressing reading comprehension challenges to improve academic outcomes and support learners’ cognitive development and cultural identity.…”
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Leveraging BiLSTM-CRF and adversarial training for sentiment analysis in nature-based digital interventions: Enhancing mental well-being through MOOC platforms by Juanjuan Zang

“…Objective This study aims to leverage annotated textual data from a Massive Open Online Course (MOOC) platform to conduct sentiment analysis of learners’ interactions with nature-based digital interventions, which seeks to enhance sentiment classification and provide insights into learners’ affective experiences, ultimately facilitating timely psychological interventions and improving curriculum design. …”
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Association of [¹⁸F]-FDG PET/CT-Derived Radiomic Features with Clinical Outcomes and Genomic Profiles in Patients with Chronic Lymphocytic Leukemia by Fabiana Esposito, Luigi Manco, Guglielmo Manenti, Livio Pupo, Andrea Nunzi, Roberta Laureana, Luca Guarnera, Massimiliano Marinoni, Elisa Buzzatti, Paola Elda Gigliotti, Andrea Micillo, Giovanni Scribano, Adriano Venditti, Massimiliano Postorino, Maria Ilaria Del Principe

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Investigating the Impact of CALL on EFL Students' Speaking Skills at Islamic Boarding School: A Mix-Method Approach by Nona Safira Timur, Slamet Asari, Nirwanto Ma'ruf

“…Results revealed significant improvements, with the average fluency score increasing from 55.46 to 75.67 and confidence score from 58.63 to 80.58 after an eight-week CALL intervention. Qualitative findings highlighted that CALL’s interactive features and real-time feedback supported students in improving their pronunciation and reducing speaking anxiety. …”
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Prehospital transfusion training in Canada: a national survey of critical care transport organizations by Pierre-Marc Dion, Andy Pan, Andrew Beckett, Kanwal Singh, Adam Greene, Axel Benhamed, Melissa McGowan, Brodie Nolan

“…However, limited evidence exists on how providers are trained to deliver this intervention. While simulation-based education and instructional design features improve skill retention in other contexts, their application in prehospital transfusion training has not been systematically evaluated. …”
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Leveraging the Power of Deep Learning Technique for Creating an Intelligent, Context-Aware, and Adaptive M-Learning Model by Muhammad Adnan, Duaa H. AlSaeed, Heyam H. Al-Baity, Abdur Rehman

“…Subsequently, adaptive feedback and support are provided to those learners who struggle in their studies. …”
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Impact of Augmented Reality and Game-Based Learning for Science Teaching: Lessons from Pre-Service Teachers by Valerie Czok, Holger Weitzel

“…This indicates that AR and game-based learning support the learning process and strengthen learners’ computer self-efficacy. …”
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Prediction of Survival in Patients With Esophageal Cancer After Immunotherapy Based on Small-Size Follow-Up Data by Yuhan Su, Chaofeng Huang, Chen Yang, Qin Lin, Zhong Chen

“…Our method incorporates five sub-learners and one meta-learner. Leveraging optimal features from the training dataset, this approach achieved compelling accuracy (89.13%) and AUC (88.83%) in predicting three-year survival status, surpassing conventional techniques. …”
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ASSISTITO, SUPPORTATO O GENERATO DALL’IA: UNA TASSONOMIA ISPIRATA DALLA CAPTOLOGIA PER L’USO DELL’INTELLIGENZA ARTIFICIALE NELLA DIDATTICA by Martin Ruskov

“…We propose a taxonomy of AI use through the lens of captology - how a range of learner-facing educational interventions could be mapped in terms of captology, and illustrate this with case studies. …”
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Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study by Jingchao Lei, Jia Zhai, Yao Zhang, Jing Qi, Chuanzheng Sun

“…ObjectiveThis study aims to develop an explainable machine learning model, incorporating stacking techniques, to predict the occurrence of liver injury in patients with sepsis and provide decision support for early intervention and personalized treatment strategies. …”
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Constructing a predictive model of negative academic emotions in high school students based on machine learning methods by Shumeng Ma, Ning Jia, Xiuchao Wei, Wanyi Zhang

“…We applied various machine learning models, such as logistic regression, naive Bayes, support vector machine, decision tree, random forest, gradient boosting decision tree, and adaptive boosting, to analyze the students’ negative academic emotions. …”
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Brain-Inspired Multisensory Learning: A Systematic Review of Neuroplasticity and Cognitive Outcomes in Adult Multicultural and Second Language Acquisition by Evgenia Gkintoni, Stephanos P. Vassilopoulos, Georgios Nikolaou

“…Immersion intensity, multimodal design features, learning context, and individual differences, including age and sociocultural background, moderate the effectiveness of interventions across adult populations. …”
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Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks by Ankur Bhatt, Ko Watanabe, Jayasankar Santhosh, Andreas Dengel, Shoya Ishimaru

“…Our results underscore the superior performance of the deep-learning model in estimating self-confidence in video-based learning contexts compared to hand-crafted feature-based methods. The outcomes of this research pave the way for more personalized and effective educational interventions, ultimately contributing to improved learning experiences and outcomes.…”
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Smart Learning Ecosystems beyond 2030 by Gabriella Dodero, Carlo Giovannella, Francesca Pozzi

“…The paper “The value perspective of technologically disrupted social dimension of a learning space” [12], by Andrea Annus, Kai Pata, Terje Väljataga, Halliki Põlda, investigates the social dimension of a learning space supporting adult education practices. The investigation took place within group-interview workshops, involving learners, facilitators and educational technologists. …”
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Analysing learning behaviour: A data-driven approach to improve time management and active listening skills in students by Vinayak Hegde, Vishrutha M, Pallavi M. Shanthappa, Rekha Bhat, Nisha Raveendran, Roshin C

“…By analyzing learning behavior, researchers and educators can gain insights into effective learning strategies, identify barriers to learning, and develop interventions to support learners in achieving their educational goals. …”
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