The biology of learning

Lecture Artificial intelligence: Artificial neural network. This lecture provides students with content including: computing systems inspired by biological neural networks; consists of several processing elements that receive inputs and deliver outputs; "learn" to perform tasks by considering examples; be able to model nonlinear processes;... Please refer to the detailed content of the lecture!

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Self-regulation is an active and constructive process in which students regulate and observe their own behaviour, motivations and cognition by setting their own goals during their learning process. In this study, the aim is to investigate the effects of biology laboratory practices that are supported by self-regulated learning strategies on students’ readiness for self-directed learning and their attitudes towards science experiments in laboratory settings.

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The objectives of this study were to analyze the validity, practicality, and effectiveness of South Kalimantan local wisdombased biology learning and its effect on student learning outcomes. The research method used is research and development. This research was in a Develop stage of Thiagarajan’s Model.

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Professional teaching competence is significantly influenced by beliefs about teaching and learning. Prospective teachers start their teacher training with quite persistent beliefs about learning processes. The present study investigated how prospective teachers remembered their previous biology lessons as well as how they imagine the lessons they will conduct in the future.

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This study, therefore, developed a game-based learning activity called the VERT card game to enhance students’ learning of the phylogenetic taxonomy of chordates. The VERT card game was designed to lay the foundation for different characteristics of chordate classes, as well as to allow students to construct and interpret their evolutionary relationships based on the phylogenetic tree.

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The performance in biology at the secondary level has not been as good as expected. This has been a matter of concern. Thus, there has been a continuous focus on exploring newer innovative learner-centered and friendly instructional strategies to enhance understanding and retention in biology.

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For biology students, the diversity, complexity, and abundance of content in this field yield a heavy study load. Hence, appropriate learning strategies are key in supporting learners’ academic success. In biology, the factors gender and interest hold a unique position within the natural sciences, as there is an academic imbalance to the disadvantage of male students.

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This review explores research into the effects of collaborative learning interventions on critical thinking, creative thinking, and metacognitive skill ability on biological learning. The search was conducted from 2000 to 2021. We found 36 critical thinking studies, 18 creative thinking studies, and 14 metacognitive skill studies that met the criteria.

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This phenomenological research explored the teachers’ articulation in the delivery of online distance learning (ODL) in BLC. Specifically, this study identified various methods and alternatives employed by biology teachers in conducting laboratory activities.

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This study examined the impact of teaching biology using interactive multimedia on the students’ academic performance in biology at Community Day Secondary Schools (CDSS). This study was conducted in three secondary schools in the Dedza district, in the central region of Malawi. A pretest-posttest quasi-experimental approach was used in this investigation.

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This qualitative study examines the experiences of pre-service high school biology teachers in the Mekong Delta, Vietnam, focusing on the challenges and transformative learning experiences encountered during their school-based internship.

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Ebook "TNF receptor associated factors (TRAFs)" is the only literature that is entirely devoted to TRAFs. Almost every aspect of TRAF signaling is covered, including the different TRAF family members, their distinct biological functions, the TRAF structures, their modes of receptor recognition, the signaling mechanisms, and the roles of TRAFs in normal cellular functions and in viral infection.

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Part 1 book "Psychology - A self teaching guide" includes content: Introduction - The foundations of psychology; research methods in psychology - gathering data; the biology of behavior - is the brain the organ of mental life; sensation - studying the gateways of experience; perception - why do things look the way they do; learning - understanding acquired behavior; motivation - why do we do what we do.

118p muasambanhan10 06-04-2024 2 0   Download

Neurodevelopmental disorders (NDDs) such as autism spectrum disorder, intellectual disability, developmental disability, and epilepsy are characterized by abnormal brain development that may affect cognition, learning, behavior, and motor skills. High co-occurrence (comorbidity) of NDDs indicates a shared, underlying biological mechanism.

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Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear.

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Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across healthcare domains together with the availability of highly characterised cancer datasets has accelerated research into the utility of deep learning in the analysis of the complex biology of cancer.

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Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes.

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Ebook "Understanding the dynamics of biological systems: Lessons learned from integrative systems biology" intended as a communication platform to bridge the cultural, conceptual, and technological gap among the key systems biology disciplines of biology, mathematics, and information technology. To support this goal, contributors were asked to adopts an approach that appeals to audiences from different backgrounds.

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Genotypes are strongly associated with disease phenotypes, particularly in brain disorders. However, the molecular and cellular mechanisms behind this association remain elusive. With emerging multimodal data for these mechanisms, machine learning methods can be applied for phenotype prediction at different scales, but due to the black-box nature of machine learning, integrating these modalities and interpreting biological mechanisms can be challenging.

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Ebook "Application of computational intelligence to biology" is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

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