Planning gamification strategies based on user characteristics and DM : a gender-based case study.

Gamification frameworks can aid in gamification planning for education. Most frameworks, however, do not provide ways to select, relate or recommend how to use game elements, to gamify a certain educational task. Instead, most provide a "one-size-fits-all" approach covering all learners, without considering different user characteristics, such as gender. Therefore, this work aims to adopt a data-driven approach to provide a set of game element recommendations, based on user preferences, that could be used by teachers and instructors to gamify learning activities. We analysed data from a novel survey of 733 people (male=569 and female=164), collecting information about user preferences regarding game elements. Our results suggest that the most important rules were based on four (out of nineteen) types of game elements: Objectives, Levels, Progress and Choice. From the perspective of user gender, for the female sample, the most interesting rule associated Objectives with Progress, Badges and Information (confidence=0.97), whilst the most interesting rule for the male sample associated also Objectives with Progress, Renovation and Choice (confidence=0.94). These rules and our descriptive analysis provides recommendations on how game elements can be used in educational scenarios.Comment: https://drive.google.com/file/d/1UI28N2UtrOfL06k2mzHIUdPcgQtdfmy9/view?usp=sharin

Transcriptome Analysis and SNP Development Can Resolve Population Differentiation of Streblospio benedicti, a Developmentally Dimorphic Marine Annelid

Next-generation sequencing technology is now frequently being used to develop genomic tools for non-model organisms, which are generally important for advancing studies of evolutionary ecology. One such species, the marine annelid Streblospio benedicti, is an ideal system to study the evolutionary consequences of larval life history mode because the species displays a rare offspring dimorphism termed poecilogony, where females can produce either many small offspring or a few large ones. To further develop S. benedicti as a model system for studies of life history evolution, we apply 454 sequencing to characterize the transcriptome for embryos, larvae, and juveniles of this species, for which no genomic resources are currently available. Here we performed a de novo alignment of 336,715 reads generated by a quarter GS-FLX (Roche 454) run, which produced 7,222 contigs. We developed a novel approach for evaluating the site frequency spectrum across the transcriptome to identify potential signatures of selection. We also developed 84 novel single nucleotide polymorphism (SNP) markers for this species that are used to distinguish coastal populations of S. benedicti. We validated the SNPs by genotyping individuals of different developmental modes using the BeadXPress Golden Gate assay (Illumina). This allowed us to evaluate markers that may be associated with life-history mode

Finding New Genes for Non-Syndromic Hearing Loss through an In Silico Prioritization Study

At present, 51 genes are already known to be responsible for Non-Syndromic hereditary Hearing Loss (NSHL), but the knowledge of 121 NSHL-linked chromosomal regions brings to the hypothesis that a number of disease genes have still to be uncovered. To help scientists to find new NSHL genes, we built a gene-scoring system, integrating Gene Ontology, NCBI Gene and Map Viewer databases, which prioritizes the candidate genes according to their probability to cause NSHL. We defined a set of candidates and measured their functional similarity with respect to the disease gene set, computing a score () that relies on the assumption that functionally related genes might contribute to the same (disease) phenotype. A Kolmogorov-Smirnov test, comparing the pair-wise distribution on the disease gene set with the distribution on the remaining human genes, provided a statistical assessment of this assumption. We found at a p-value that the former pair-wise is greater than the latter, justifying a prioritization strategy based on the functional similarity of candidate genes respect to the disease gene set. A cross-validation test measured to what extent the ranking for NSHL is different from a random ordering: adding 15% of the disease genes to the candidate gene set, the ranking of the disease genes in the first eight positions resulted statistically different from a hypergeometric distribution with a p-value and a power. The twenty top-scored genes were finally examined to evaluate their possible involvement in NSHL. We found that half of them are known to be expressed in human inner ear or cochlea and are mainly involved in remodeling and organization of actin formation and maintenance of the cilia and the endocochlear potential. These findings strongly indicate that our metric was able to suggest excellent NSHL candidates to be screened in patients and controls for causative mutations