College Students Attitudes Toward Learning Process And Outcome Of Online Instruction And Distance Learning Across Learning Styles

This study uses the Learning-Style Inventory LSI (Smith & Kolb, 1985) to explore to what extent student attitudes toward learning process and outcome of online instruction and Distance Learning are affected by their cognitive styles and learning behaviors. It finds that there are not much statistically significant differences in perceptions on many learning process and outcome indicators across learning styles. However, students who learn from concrete experience and reflective experimentation/observation didnt appreciate the flexible class schedule, need instant questions and feedback, and expect more leniency from the instructor

An Empirical Study Of Student Attitudes Toward Acceptance Of Online Instruction And Distance Learning

This study investigates to what extent student attitudes toward acceptance of online instruction and Distance Learning are affected by determinants such as demographics, learning environment, learning domains, delivery methods, and web-based instructional technology. Logistic Regression and Discriminant Analysis use statistically significant determinants to predict student preference on future online classes. Factor Analysis provides an exploratory model of online learning acceptance having three factors; namely, Communication/Feedback, Course Outcome, and Effort Required. Practical implications of findings and insights on field observations are offered. Overall, students agreed that they had learned sufficient knowledge from an online course. Students satisfied with their recent learning outcome tend to take more online courses in the future

Virtual Group Learning Effectiveness via eLearning Mediums

Online learning provides the potential for more differentiated, integrated, and open learning environments to solve team project assignments. We argue that although it is feasible to increase information richness via adopting multimedia technologies, the effectiveness to promote interpersonal skills, critical thinking, and cognitive learning processes via virtual group discussion is uncertain. To substantiate the argument, we invited 156 subjects, divided into 46 groups, to resolve decision- and intellective-tasks in text-messaging and audio-conferencing e-learning environments. A pedagogical interpretation of how we can use these two e-learning systems to improve effectiveness for group-based tasks was posited

FEE-BASED ONLINE SERVICES: EXPLORING CONSUMERS\u27 WILLINGNESS TO PAY

Many online service businesses are beginning to charge fees for services that they used to provide for free. It is unclear whether consumers are ready to embrace this practice. This study explores consumer attitudes toward fee-based online services. The results of the study indicate that consumers\u27 willingness to pay for online services is likely to be influenced by their perceived value of convenience these services provide, and by the extent to which they utilize these services. While consumers appear more willing to pay for services that are qualitatively better than free services, there is also indication that the belief remains strong among many that online services that were free in the past should remain free

Texture development and coercivity enhancement in cast alnico 9 magnets

The effect of Y addition and magnetic field on texture and magnetic properties of arc-melted alnico 9 magnets has been investigated. Small additions of Y (1.5 wt.%) develop a (200) texture for the arc-melted alnico 9 magnet. Such a texture is hard to form in cast samples. To achieve this goal, we set up a high-field annealing system with a maximum operation temperature of 12500 C. This system enabled annealing in a field of 45 kOe with subsequent draw annealing for the solutionized buttons; we have been able to substantially increase remanence ratio and coercivity, from 0.70 and 1200 Oe for the Y-free alnico 0 to 0.90 and 1400 Oe for the Y-doped alnico 9, respectively. A high energy product of 7.3 MGOe has been achieved for the fully heat-treated Y-doped alnico 9. The enhancement of coercvity is believed to arise from the introduction of magnetocrystalline anisotropy from 80 nm Y2Co17- type grains, which are exchange-coupled to the main-phase alnico rods

Ancestral roles of the Fam20C family of secreted protein kinases revealed in C. elegans.

Fam20C is a secreted protein kinase mutated in Raine syndrome, a human skeletal disorder. In vertebrates, bone and enamel proteins are major Fam20C substrates. However, Fam20 kinases are conserved in invertebrates lacking bone and enamel, suggesting other ancestral functions. We show that FAMK-1, the Caenorhabditis elegans Fam20C orthologue, contributes to fertility, embryogenesis, and development. These functions are not fulfilled when FAMK-1 is retained in the early secretory pathway. During embryogenesis, FAMK-1 maintains intercellular partitions and prevents multinucleation; notably, temperature elevation or lowering cortical stiffness reduces requirement for FAMK-1 in these contexts. FAMK-1 is expressed in multiple adult tissues that undergo repeated mechanical strain, and selective expression in the spermatheca restores fertility. Informatic, biochemical, and functional analysis implicate lectins as FAMK-1 substrates. These findings suggest that FAMK-1 phosphorylation of substrates, including lectins, in the late secretory pathway is important in embryonic and tissue contexts where cells are subjected to mechanical strain

BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources

BioGPS is a community based customisable gene annotation portal bringing together gene annotation resources on to a single platform

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead