Positivity of the English language

Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is broadly invariant with respect to frequency of word use.Comment: Manuscript: 9 pages, 3 tables, 5 figures; Supplementary Information: 12 pages, 3 tables, 8 figure

Does the mind map learning strategy facilitate information retrieval and critical thinking in medical students?

<p>Abstract</p> <p>Background</p> <p>A learning strategy underutilized in medical education is mind mapping. Mind maps are multi-sensory tools that may help medical students organize, integrate, and retain information. Recent work suggests that using mind mapping as a note-taking strategy facilitates critical thinking. The purpose of this study was to investigate whether a relationship existed between mind mapping and critical thinking, as measured by the Health Sciences Reasoning Test (HSRT), and whether a relationship existed between mind mapping and recall of domain-based information.</p> <p>Methods</p> <p>In this quasi-experimental study, 131 first-year medical students were randomly assigned to a standard note-taking (SNT) group or mind map (MM) group during orientation. Subjects were given a demographic survey and pre-HSRT. They were then given an unfamiliar text passage, a pre-quiz based upon the passage, and a 30-minute break, during which time subjects in the MM group were given a presentation on mind mapping. After the break, subjects were given the same passage and wrote notes based on their group (SNT or MM) assignment. A post-quiz based upon the passage was administered, followed by a post-HSRT. Differences in mean pre- and post-quiz scores between groups were analyzed using independent samples <it>t</it>-tests, whereas differences in mean pre- and post-HSRT total scores and subscores between groups were analyzed using ANOVA. Mind map depth was assessed using the Mind Map Assessment Rubric (MMAR).</p> <p>Results</p> <p>There were no significant differences in mean scores on both the pre- and post-quizzes between note-taking groups. And, no significant differences were found between pre- and post-HSRT mean total scores and subscores.</p> <p>Conclusions</p> <p>Although mind mapping was not found to increase short-term recall of domain-based information or critical thinking compared to SNT, a brief introduction to mind mapping allowed novice MM subjects to perform similarly to SNT subjects. This demonstrates that medical students using mind maps can successfully retrieve information in the short term, and does not put them at a disadvantage compared to SNT students. Future studies should explore longitudinal effects of mind-map proficiency training on both short- and long-term information retrieval and critical thinking.</p

Meta-KANSEI modeling with Valence-Arousal fMRI dataset of brain

Background: Traditional KANSEI methodology is an important tool in the field of psychology to comprehend the concepts and meanings; it mainly focusses on semantic differential methods. Valence-Arousal is regarded as a reflection of the KANSEI adjectives, which is the core concept in the theory of effective dimensions for brain recognition. From previous studies, it has been found that brain fMRI datasets can contain significant information related to Valence and Arousal. Methods: In this current work, a Valence-Arousal based meta-KANSEI modeling method is proposed to improve the traditional KANSEI presentation. Functional Magnetic Resonance Imaging (fMRI) was used to acquire the response dataset of Valence-Arousal of the brain in the amygdala and orbital frontal cortex respectively. In order to validate the feasibility of the proposed modeling method, the dataset was processed under dimension reduction by using Kernel Density Estimation (KDE) based segmentation and Mean Shift (MS) clustering. Furthermore, Affective Norm English Words (ANEW) by IAPS (International Affective Picture System) were used for comparison and analysis. The data sets from fMRI and ANEW under four KANSEI adjectives of angry, happy, sad and pleasant were processed by the Fuzzy C-Means (FCM) algorithm. Finally, a defined distance based on similarity computing was adopted for these two data sets. Results: The results illustrate that the proposed model is feasible and has better stability per the normal distribution plotting of the distance. The effectiveness of the experimental methods proposed in the current work was higher than in the literature. Conclusions: mean shift can be used to cluster and central points based meta-KANSEI model combining with the advantages of a variety of existing intelligent processing methods are expected to shift the KANSEI Engineering (KE) research into the medical imaging field

Teaching the science of learning

The science of learning has made a considerable contribution to our understanding of effective teaching and learning strategies. However, few instructors outside of the field are privy to this research. In this Tutorial Review, we focus on six specific cognitive strategies that have received robust support from decades of research: spaced practice, interleaving, retrieval practice, elaboration, concrete examples, and dual coding. We describe the basic research behind each strategy and relevant applied research, present examples of existing and suggested implementation, and make recommendations for further research that would broaden the reach of these strategies

Consonant-Vowel-Consonants for Error-Free Code Entry

International audienceRecent work on passwords has focused on choosing secure codes, while design for ability to type them error-free has not received as much attention. The difficulties people were having transcribing codes in a security demonstration motivated this study of code transcription difficulty. A pilot study with 33 subjects and a follow-up study with 267 subjects from 24 countries measured performance and preference for codes of varying lengths, patterns, and character sets. The study found long codes with alternating consonant and vowel patterns are preferred and can be more accurately transcribed than shorter numeric or alphabetic codes. Mixed-case and alphanumeric character sets both increased transcription errors. Our proposed CVC 6 code design composed of six Consonant-Vowel-Consonant trigrams is more secure, faster to enter, highly preferred by users, and more impervious to user error when compared to standard codes currently used for security purposes. An extension integrates error detection and correction, essentially eliminating typo problems

Using Science Songs to Enhance Learning: An Interdisciplinary Approach

Music is recognized as an effective mode of teaching young children but is rarely used in university-level science courses. This article reviews the somewhat limited evidence on whether and how content-rich music might affect college students' understanding of science and offers practical suggestions for incorporating music into courses. Aside from aiding memorization, songs may potentially improve learning by helping students feel relaxed and welcome in stressful settings, engaging students through multiple modes (verbal vs. nonverbal) and modalities (auditory vs. visual vs. kinesthetic) simultaneously, challenging students to integrate and “own” the material through the medium of song lyrics, and increasing students' time on task outside of class through enjoyable listening or songwriting assignments. Students may produce content-rich songs of good quality if given sufficient assistance and encouragement by instructors and peers. The challenges ahead include 1) defining the circumstances in which music is most likely to promote learning and 2) developing rubrics for evaluating the quality of songs