Accommodating Different Learning Styles in the Teaching of Economics: with Emphasis on Fleming and Mills’s Sensory-based Learning Style Typology

Students prefer to learn in different ways. These learning preferences are commonly known as learning styles. This variety in learning styles among students suggests that instructors should teach their course materials in different ways to cater to different learning styles. In addition, according to (Nilson 2010), when our society is concerned with fairness and equality, teaching to different styles is a main facet of equity. This paper focuses on Fleming and Mill’s VARK model (1992) to describe students’ different learning styles and explain why and in what ways economics instructors can accommodate different learning styles in their teaching. More specifically, the present paper aims to examine different learning styles and introduce teaching tools for accommodating different learning styles in the context of teaching economics. In addition to identifying learning-style-specific teaching instruments for the teaching of economics, the paper provides some prominent examples of each in the literature of economic education. Finally, considering recent advancements and availability of various technologies, existing evidence, general growing consensus on the issue, and many other reasons mentioned throughout the paper, it is argued and suggested that it makes more sense to take a multimodal approach to the teaching of economics

Placental Vacuolar ATPase Function Is a Key Link between Multiple Causes of Preeclampsia

Preeclampsia, a relatively common pregnancy disorder, is one of the major causes of maternal and fetal morbidity and mortality. Despite numerous research, the etiology of this syndrome remains not well understood as the pathogenesis of preeclampsia is complex, involving interaction between genetic, immunologic, and environmental factors. Preeclampsia, originating in placenta abnormalities, is induced by the circulating factors derived from the abnormal placenta. Recent work has identified various molecular mechanisms related to placenta development, including renin-angiotensin system, 1, 25-dihydroxyvitamin D, and lipoxin A4. Interestingly, advances suggest that vacuolar ATPase, a key molecule in placentation, is closely associated with them. Therefore, this intriguing molecule may represent an important link between various causes of preeclampsia. Here, we review that vacuolar ATPase works as a key link between multiple causes of preeclampsia and discuss the potential molecular mechanisms. The novel findings outlined in this review may provide promising explanations for the causation of preeclampsia and a rationale for future therapeutic interventions for this condition

A note on the total chromatic number of Halin graphs with maximum degree 4

AbstractIn this paper, we prove that χT(G) = 5 for any Halin graph G with Δ(G) = 4, where Δ(G) and χT(G) denote the maximal degree and the total chromatic number of G, respectively

Large Language Models Are Also Good Prototypical Commonsense Reasoners

Commonsense reasoning is a pivotal skill for large language models, yet it presents persistent challenges in specific tasks requiring this competence. Traditional fine-tuning approaches can be resource-intensive and potentially compromise a model's generalization capacity. Furthermore, state-of-the-art language models like GPT-3.5 and Claude are primarily accessible through API calls, which makes fine-tuning models challenging. To address these challenges, we draw inspiration from the outputs of large models for tailored tasks and semi-automatically developed a set of novel prompts from several perspectives, including task-relevance, supportive evidence generation (e.g. chain-of-thought and knowledge), diverse path decoding to aid the model. Experimental results on ProtoQA dataset demonstrate that with better designed prompts we can achieve the new state-of-art(SOTA) on the ProtoQA leaderboard, improving the Max Answer@1 score by 8%, Max Incorrect@1 score by 4% (breakthrough 50% for the first time) compared to the previous SOTA model and achieved an improvement on StrategyQA and CommonsenseQA2.0 (3% and 1%, respectively). Furthermore, with the generated Chain-of-Thought and knowledge, we can improve the interpretability of the model while also surpassing the previous SOTA models. We hope that our work can provide insight for the NLP community to develop better prompts and explore the potential of large language models for more complex reasoning tasks

Spatial patterns of correlation between conspecific species and size diversity in forest ecosystems

Recently correlations between spatial species and size diversity have been found in many forest ecosystems around the world. They are likely to play a prominent role in nature's mechanisms of maintaining species and size diversity. In this study, we analysed the species population means of spatial species-mingling and sizeinequality indices in 36 large forest monitoring plots from the temperate and subtropical zones in China. Based on the literature we included eleven diversity-index combinations and considered their correlations for increasing numbers of nearest neighbours. Generally, positive correlations are related to between-species population size differences whilst negative correlations reflect within-species population size differences. Our results showed that the selected species-mingling and size-inequality indices produced different correlation patterns in one and the same monitoring site. We therefore defined a species-mingling size-inequality correlation space by computing the 0.025 and the 0.975 quantiles from the correlation data of the eleven index combinations. We noticed that each observed correlation space included 1-3 combinations of five basic geometric types and can be interpreted as the unique signature of a forest ecosystem in time. The correlation space allowed us to understand more clearly at which spatial scale within-species correlation was more influential than between-species inequality and vice versa. The shape of the correlation space is interpretable and gives important clues about the forest development stage of a forest ecosystem

Mobilization and Role of Starch, Protein, and Fat Reserves During Seed Germination of Six Wild Grassland Species

Since seed reserves can influence seed germination, the quantitative and qualitative differences in seed reserves may relate to the germination characteristics of species. The purpose of our study was to evaluate the correlation between germination and seed reserves, as well as their mobilization during germination of six grassland species (Chloris virgata, Kochia scoparia, Lespedeza hedysaroides, Astragalus adsurgens, Leonurus artemisia, and Dracocephalum moldavica) and compare the results with domesticated species. We measured starch, protein, and fat content in dry seeds and the initial absorption of water during imbibition. Starch, soluble protein, fat, and soluble sugar content also were determined at five stages during germination. Starch, protein, and fat reserves in dry seeds were not significantly correlated with germination percentage and rate (speed), but soluble sugar and soluble protein contents at different germination stages were positively significantly correlated with germination rate for the six species. Starch was mainly used during seed imbibition, and soluble protein was used from the imbibition stage to the highest germination stage. Fat content for all species remained relatively constant throughout germination for six species, regardless of the proportion of other seed reserves in the seeds. Our results for fat utilization differ from those obtained for cultivated grasses and legumes. These results provide new insight on the role of seed reserves as energy resources in germination for wild species