24 papers · ranked by Valyu relevance
KAILASH CHAROKAR, PUJA DULLOO
The traditional education strategy is insufficient to meet the demands of dynamically changing medical science and the fast-growing medical field. The present Competency-Based Medical Curriculum for medical undergraduates in India emphasizes acquisition of a set of competencies for self-directed learning (SDL) through…
Hsin-Lan Liu, Tao-Hua Wang, Hao-Chiang Koong Lin, Chin-Feng Lai + 1 more
'Yueh-Min Huang'] The outbreak of the two-year corona virus has made a great difference on existing methods of learning and instruction. Online education has become a crucial role to maintain non-stop learning after the post-epidemic period. The advanced technologies and growing popularity of network equipment have…
Jun Li, Dong Yang, Ziao Hu
This study explored the chain-mediating roles of optimism and mental health in the relation of self-directed learning with academic performance among college students in Wuhan during long-term online teaching. In total, 473 valid responses were obtained from students at three Wuhan universities. Self-directed learning…
Wenwu Zhu, Xin Wang, Pengtao Xie
—Conventional machine learning (ML) relies heavily on manual design from machine learning experts to decide learning tasks, data, models, optimization algorithms, and evaluation metrics, which is labor-intensive, time-consuming, and cannot learn autonomously like humans. In education science, self-directed learning…
Pramith Devulapalli, Steve Hanneke
In this paper, we study the self-directed learning complexity in both the binary and multi-class settings, and we develop a dimension, namely SDdim, that exactly characterizes the self-directed learning mistake-bound for any concept class. The intuition behind SDdim can be understood as a two-player game called the…
Meina Zhu, Min Young Doo
In massive open online learning courses (MOOCs) with a low instructor-student ratio, students are expected to have self-directed learning abilities. This study investigated the relationship among motivation, self-monitoring, self-management, and MOOC learners’ use of learning strategies. An online survey was embedded…
Gideon P. Van Tonder, Magdalena M. Kloppers, Mary M. Grosser
Background The international crisis of declining learner wellbeing exacerbated by the COVID-19 pandemic with its devastating effects on physical health and wellbeing, impels the prioritization of initiatives for specifically enabling academic and personal wellbeing among school learners to ensure autonomous functioning…
Mingming Shao, Jon-Chao Hong, Li Zhao
Online learning has become an important learning approach in universities. However, since many students may have been exposed to online learning for the first time during this period of the COVID-19 pandemic, the quality factors of online learning and psychological distress of students need to be considered in the…
Qianrun Mao
In an era increasingly shaped by decentralized knowledge ecosystems and pervasive AI technologies, fostering sustainable learner agency has become a critical educational imperative. This paper introduces a novel conceptual framework integrating Generative Artificial Intelligence (GAI) and Learning Analytics (LA) to…
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
In online classification, a learner is presented with a sequence of examples and aims to predict their labels in an online fashion so as to minimize the total number of mistakes. In the selfdirected variant, the learner knows in advance the pool of examples and can adaptively choose the order in which predictions are…
Wim van Lankveld, Marjo Maas, Joost van Wijchen, Volcmar Visser + 1 more
'J. Bart Staal'] Background There is a concern that traditional instruction based methods of learning do not adequately prepare students for the challenges of physical therapy practice. Self-directed learning is considered to be the most appropriate educational approach to enhance life-long learning as it enhances…
Changiz Mohiyeddini
Over recent decades, the complexity of higher education in general, and teaching specifically, has increased significantly, resulting in a myriad of challenges for educators. Traditional approaches to teaching often rely on standardized curricula and top-down instructional methods. Therefore, they are critically…
Kristjan-Julius Laak, Jaan Aru
goals Authors: ['Kristjan-Julius Laak' 'Jaan Aru'] Personalized learning (PL) aspires to provide an alternative to the one-size-fits-all approach in education. Technology-based PL solutions have shown notable effectiveness in enhancing learning performance. However, their alignment with the broader goals of modern…
Yi-Jing Zhao, Feng-Qing Huang, Qun Liu, Ying Li + 3 more
This study aimed to comprehensively evaluate the effect of PBL on problem-solving, self-directed learning, and critical thinking ability of pharmaceutical students through a randomized controlled trial (RCT) and meta-analysis of RCTs. In 2021, 57 third-year pharmacy students from China Pharmaceutical University were…
Noah Zarr, Joshua W. Brown
The question of how animals and humans can solve arbitrary problems and achieve arbitrary goals remains open. Model-based and model-free reinforcement learning methods have addressed these problems, but they generally lack the ability to flexibly reassign reward value to various states as the reward structure of the…
Sofia Fregni, Uta Wolfensteller, Hannes Ruge
We used fMRI to investigate the neural changes and representational dynamics associated with different learning modes during initial learning and subsequent implementation of previously acquired stimulus-response (S-R) associations. We compared instruction-based learning (INS) and trial-and-error learning (TE) via a…
Authors not listed
The integration of machine learning methods is transforming many areas of research by, for instance, accelerating molecular dynamics simulations and enabling improved prediction and optimization of chemical reactions. However, despite this progress, the adoption of data-driven approaches in atomic layer deposition…
Omar D. Perez, Anthony Dickinson
Theories of instrumental actions assume the existence of multiple behavioral systems, one goal-directed which takes into account the consequences of actions, and one habitual that depends on previous reward history, both of which are predicated upon the notion of prediction-error to learn which actions should be…
Authors not listed
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Etinosa Osaro, Yamil Colón
The application of machine learning (ML) techniques in materials science has revolutionized the pace and scope of materials research and design. In the case of metal-organic frameworks (MOFs), a promising class of materials due to their tunable properties and versatile applications in gas adsorption and separation, ML…
Ronald Marquez, Laura Tolosa, Ruben Gomez, Cesar Izaguirre + 3 more
The teaching-learning process in traditional university education uses strategies that position the student as a recipient of information conveyed by the teacher and conceptualized as knowledge. The reality in which we live, including the characteristics of new generational groups, requires the generation of training…
Yannick Ureel, Maarten R. Dobbelaere, Yi Ouyang, Kevin De Ras + 3 more
By combining machine learning with design of experiments, so-called active machine learning, more efficient and cheaper research can be conducted. Machine learning algorithms are more flexible, and are better at investigating the processes spanning all length scales of chemical engineering. While the active machine…
Alexander Pomberger, Antonio Pedrina McCarthy, Ahmad Khan, Simon Sung + 4 more
Multivariate chemical reaction optimization involving catalytic systems is a non-trivial task due to the high number of tuneable parameters and discrete choices. Closed-loop optimization featuring active Machine Learning (ML) represents a powerful strategy for automating reaction optimization. However, the translation…
Yunan Luo, Lam Vo, Hantian Ding, Yufeng Su + 4 more
Protein engineering seeks to design proteins with improved or novel functions. Compared to rational design and directed evolution approaches, machine learning-guided approaches traverse the fitness landscape more effectively and hold the promise for accelerating engineering and reducing the experimental cost and…