On the Challenges of Quantum Circuit Encoding Using Deep and Reinforcement Learning by Patrick Selig, Niall Murphy, David Redmond, Simon Caton

“…To this end, we trained neural networks to directly learn to predict the unitary of a circuit and applied reinforcement learning to train neural networks to solve circuit based quantum state preparation. …”
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Exploring the effectiveness of the Merdeka curriculum in promoting effective learning practices by Lara Prahastina, Mintasih Indriayu, Matsuri Matsuri

“…The data were analyzed using an inductive model to generate themes and interpret The results indicate that SDN Bolo 01 has made significant efforts to implement innovative, student-centered learning practices aligned with the Merdeka Curriculum, such as Project-Based Learning accommodating the Pancasila Student Profile. …”
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Challenges in preparing and implementing project-based learning – teachers’ experience by Dušan P. Ristanović, Biljana D. Radović, Мirko S. Marković

“…Data analysis was performed using the qualitative method of inductive-type thematic analysis. Determining the project topic, forming teacher teams and selecting students who will participate in the project were identified as the key challenges faced by teachers in preparing project-based learning. …”
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Faculty perceptions and conveyance of academic ethics to students in distance learning by Maigi Lepik, Kateriina Rannula, Liina Männiksaar

“…The applied research project at Tallinn Health University of Applied Sciences, titled Ê»Academic ethics as lecturerâs toolkit in the teaching process â adapting to the changing environmentʼ, explores how faculty perceive ethical values and how they communicate these values during distance learning. The study aims to describe how faculty perceive and convey academic ethics in the context of distance learning. …”
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Cost-Effective Multitask Active Learning in Wearable Sensor Systems by Asiful Arefeen, Hassan Ghasemzadeh

“…Multitask learning models provide benefits by reducing model complexity and improving accuracy by concurrently learning multiple tasks with shared representations. …”
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Survey on multi-agent reinforcement learning methods from the perspective of population by XIANG Fengtao, LUO Junren, GU Xueqiang, SU Jiongming, ZHANG Wanpeng

“…This article first outlined the relevant research progress of multi-agent reinforcement learning. Secondly, a comprehensive overview and induction of multi-agent learning methods with multiple types and paradigms were conducted from the perspectives of scalability and population adaptation. …”
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Diagnóstico de tumores do ângulo ponto-cerebelar com o auxílio de técnicas de inteligência artificial A diagnostic model for cerebellum-pontine angle tumors using artificial intell... by FLÁVIO LEITÃO, FERNANDO C. GOMES, SEBASTIÃO DIÓGENES, FLÁVIO LEITÃO FILHO

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Reliable machine learning models in genomic medicine using conformal prediction by Christina Papangelou, Konstantinos Kyriakidis, Pantelis Natsiavas, Ioanna Chouvarda, Andigoni Malousi, Andigoni Malousi

“…Machine learning and genomic medicine are the mainstays of research in delivering personalized healthcare services for disease diagnosis, risk stratification, tailored treatment, and prediction of adverse effects. …”
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Graph Knowledge Structure for Attentional Knowledge Tracing With Self-Supervised Learning by Zhaohui Liu, Sainan Liu, Weifeng Gu

“…As intelligent education advances and online learning becomes more prevalent, Knowledge Tracing (KT) has become increasingly important. …”
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Opportunities for belonging and becoming: using outdoor learning programmes with adolescent students by Lucy Wenham

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Distanced Large Group Simulations as a Learning Method for Interprofessional Collaboration by Marja Silén-Lipponen, Eija Piippo-Savolainen, Mina Azimirad, Terhi Saaranen

“…The quantitative data were analyzed using descriptive statistical methods, and the open-ended questions were analyzed with inductive content analysis. As a result, the participants were satisfied with the large group simulation intended for learning interprofessional collaboration (mean = 4.42, SD = 0.759). …”
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Learning about social suffering through illness narrative: possibilities and challenges by Young-Gyung Paik, Jidong Sung

“…Using an iterative coding process with both inductive and deductive elements, we identified patterns in how students conceptualized suffering and engaged with social dimensions of illness. …”
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Explainable Reinforcement and Causal Learning for Improving Trust to 6G Stakeholders by Miguel Arana-Catania, Amir Sonee, Abdul-Manan Khan, Kavan Fatehi, Yun Tang, Bailu Jin, Anna Soligo, David Boyle, Radu Calinescu, Poonam Yadav, Hamed Ahmadi, Antonios Tsourdos, Weisi Guo, Alessandra Russo

“…However, this progress also raises significant trust and safety concerns. The machine learning systems orchestrating these advanced services will widely rely on deep reinforcement learning (DRL) to process multi-modal requirements datasets and make semantically modulated decisions, introducing three major challenges: (1) First, we acknowledge that most explainable AI research is stakeholder-agnostic while, in reality, the explanations must cater for diverse telecommunications stakeholders, including network service providers, legal authorities, and end users, each with unique goals and operational practices; (2) Second, DRL lacks prior models or established frameworks to guide the creation of meaningful long-term explanations of the agent’s behaviour in a goal-oriented RL task, and we introduce state-of-the-art approaches such as reward machine and sub-goal automata that can be universally represented and easily manipulated by logic programs and verifiably learned by inductive logic programming of answer set programs; (3) Third, most explainability approaches focus on correlation rather than causation, and we emphasise that understanding causal learning can further enhance 6G network optimisation. …”
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SmartLabAirgap: Helping Electrical Machines Air Gap Field Learning by Carla Terron-Santiago, Javier Martinez-Roman, Jordi Burriel-Valencia, Angel Sapena-Bano

“…This paper describes a new test equipment design aimed at helping students achieve these learning goals. The test equipment is designed based on four main elements: a modified slip ring induction machine, a winding current driver board, the DAQ boards, and a PC-based virtual instrument. …”
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LEARNING ENGLISH THROUGH THE INTEGRATION OF STUDENTS’ EDUCATIONAL-COGNITIVE AND SELF-EDUCATIONAL ACTIVITIES by Liliya A. Dmytruk

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University students’ subjective experiences with problem-based learning and associated generic skills by Ahram Lee, Eunju Jung

“…Students were provided with open-ended questions that prompted them to give detailed descriptions of their learning experiences during PBL. The content of the papers was analyzed using inductive thematic analysisFindingsThe analysis revealed four key themes related to students’ experiences with PBL: collaboration within the team, personal growth, higher-order thinking, and connection to the real world. …”
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Learning from the diversity of national structures, processes and intentions with regard to extended education by Bettina Krepper, Alexandra Efstathiades, James Loparics, James Loparics

“…The article discusses how national EE policies can learn from the diversity of their structures, processes and intentions.…”
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Millealab as A Virtual Reality-based Learning Platform for Slow Learners Students by Lusiana Nurliasari, Erwin Hari Kurniawan, M Syaichul Muchyidin

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“I Could Really Use This”: Occupational Therapy Students’ Perceptions of Learning to Coach by Marie-Christine Potvin, Erin K. West, Alexis N. Morales, Katherine S. Sailor, Natalie Coronado

“…This phenomenological study explored OT students’ (n=14) perceptions of the value of learning to coach while in fieldwork. Three themes emerged from the inductive qualitative analysis: Coaching Requires a Mindset Shift, Change is a Journey, and Impact on Clients. …”
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Modeling rapid language learning by distilling Bayesian priors into artificial neural networks by R. Thomas McCoy, Thomas L. Griffiths

“…Abstract Humans can learn languages from remarkably little experience. …”
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