Very often, university students deliberately form self-organized study groups, e.g. to study collaboratively for an upcoming exam. Yet, very little is known about what regulation problems such self-organized study groups encounter during their learning process and how they try to cope with these problems. Therefore, this study investigates how completely self-organized groups (i.e., non-guided groups outside the classroom that form without external impulse) regulate their collaborative learning process when faced with different kinds of regulation problems. More specifically, we tested the hypotheses that members of self-organized study groups are more satisfied with their group learning experience (a) the more homogeneous their problem perceptions are within their group, (b) the more they apply immediate (rather than non-immediate) strategies to remedy their regulation problems, and (c) the more frequently they apply regulation strategies. In a longitudinal study, = 122 students, voluntarily studying for their exams in = 52 groups, were asked to indicate the types of problems they experienced, the types of strategies they used to tackle those problems, and their satisfaction with their group learning experience after each of their self-organized study meetings. Hierarchical linear modeling confirmed all hypotheses. Qualitative analysis of two selected groups' self-reported situational data provided additional insights about the mechanisms that may have contributed to the results. Our study provides important directions for future research, including the recommendation to identify the processes by which groups (a) can reach homogeneity of problem perceptions and (b) coordinate the choice of appropriate strategies within the group.
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http://dx.doi.org/10.1007/s11412-020-09323-5 | DOI Listing |
Adv Sci (Weinh)
January 2025
Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan, 430071, China.
Liver organoids have been increasingly adopted as a critical in vitro model to study liver development and diseases. However, the pre-vascularization of liver organoids without affecting liver parenchymal specification remains a long-lasting challenge, which is essential for their application in regenerative medicine. Here, the large-scale formation of pre-vascularized human hepatobiliary organoids (vhHBOs) is presented without affecting liver epithelial specification via a novel strategy, namely nonparenchymal cell grafting (NCG).
View Article and Find Full Text PDFPhys Rev E
November 2024
Institute of Earthquake Prediction Theory and Mathematical Geophysics, RAS, Profsoyuznaya 84/32, 117997 Moscow, Russia.
We study two prototypical models of self-organized criticality, namely sandpile automata with deterministic (Bak-Tang-Wiesenfeld) and probabilistic (Manna model) dynamical rules, focusing on the nature of stress fluctuations induced by driving-adding grains during avalanche propagation, and dissipation through avalanches that hit the system boundary. Our analysis of stress evolution time series reveals robust cyclical trends modulated by collective fluctuations with dissipative avalanches. These modulated cycles attain higher harmonics, characterized by multifractal measures within a broad range of timescales.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Electrical Engineering, College of Engineering, Qatar University, Doha 2713, Qatar.
Accurate liver and tumor detection and segmentation are crucial in diagnosis of early-stage liver malignancies. As opposed to manual interpretation, which is a difficult and time-consuming process, accurate tumor detection using a computer-aided diagnosis system can save both time and human efforts. We propose a cascaded encoder-decoder technique based on self-organized neural networks, which is a recent variant of operational neural networks (ONNs), for accurate segmentation and identification of liver tumors.
View Article and Find Full Text PDFDiagnostics (Basel)
November 2024
Department of Digital Forensics Engineering, Technology Faculty, Firat University, Elazig 23119, Turkey.
Background: The primary objective of this research is to propose a new, simple, and effective feature extraction function and to investigate its classification ability using electrocardiogram (ECG) signals.
Methods: In this research, we present a new and simple feature extraction function named the minimum and maximum pattern (MinMaxPat). In the proposed MinMaxPat, the signal is divided into overlapping blocks with a length of 16, and the indexes of the minimum and maximum values are identified.
Small
December 2024
State Key Laboratory of Chemical Resource Engineering, Key Lab of Biomedical Materials of Natural Macromolecules (Beijing University of Chemical Technology, Ministry of Education), Beijing Laboratory of Biomedical Materials, Beijing University of Chemical Technology, Beijing, 100029, China.
Living organisms take in matter and energy from their surroundings, transforming these inputs into forms that cells can use to sustain metabolism and power various functions. A significant advancement in the development of protocells and life-like materials has been the creation of cell-like microcompartments capable of evolving into higher-order structures characterized by hierarchy and complexity. In this study, a smart emulsion system is designed to digests chemical substrates and generates organic or inorganic products, driving the self-organization and structuration of microcompartments.
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