Situating multimodal learning analytics

The digital age has introduced a host of new challenges and opportunities for the learning sciences community. These challenges and opportunities are particularly abundant in multimodal learning analytics (MMLA), a research methodology that aims to extend work from Educational Data Mining (EDM) and Learning Analytics (LA) to multimodal learning environments by treating multimodal data. Recognizing the short-term opportunities and longterm challenges will help develop proof cases and identify grand challenges that will help propel the field forward. To support the field's growth, we use this paper to describe several ways that MMLA can potentially advance learning sciences research and touch upon key challenges that researchers who utilize MMLA have encountered over the past few years

Can the unresolved X-ray background be explained by emission from the optically-detected faint galaxies of the GOODS project?

The emission from individual X-ray sources in the Chandra Deep Fields and XMM-Newton Lockman Hole shows that almost half of the hard X-ray background above 6 keV is unresolved and implies the existence of a missing population of heavily obscured active galactic nuclei (AGN). We have stacked the 0.5-8 keV X-ray emission from optical sources in the Great Observatories Origins Deep Survey (GOODS; which covers the Chandra Deep Fields) to determine whether these galaxies, which are individually undetected in X-rays, are hosting the hypothesised missing AGN. In the 0.5-6 keV energy range the stacked-source emission corresponds to the remaining 10-20 per cent of the total background -- the fraction that has not been resolved by Chandra. The spectrum of the stacked emission is consistent with starburst activity or weak AGN emission. In the 6-8 keV band, we find that upper limits to the stacked X-ray intensity from the GOODS galaxies are consistent with the ~40 per cent of the total background that remains unresolved, but further selection refinement is required to identify the X-ray sources and confirm their contribution.Comment: 7 pages, 1 figure, accepted for publication in MNRA

Types and correlates of school non-attendance in students with autism spectrum disorders

School non-attendance in autism spectrum disorders (ASD) has received very little attention to date. The study aimed to provide a comprehensive description of school non-attendance in students with ASD. Through an online survey, parents of 486 children (mean age 11 years) reported on school attendance over one month, and reasons for instances of non-attendance. On average, students missed five days of school of a possible 23 days. Persistent non-attendance (absent on 10%+ of available sessions) occurred among 43% of students. School non-attendance was associated with child older age, not living in a two-parent household, parental unemployment and, especially, attending a mainstream school. School refusal accounted for 43% of non-attendance. School exclusion and school withdrawal each accounted for 9% of absences. Truancy was almost non-existent. Non-problematic absenteeism (mostly related to medical appointments and illness) accounted for 32% of absences. Non-problematic absenteeism was more likely among those with intellectual disability, school refusal was more likely among older students, and school exclusion was more likely among students from single-parent, unemployed, and well educated households. Findings suggest school non-attendance in ASD is a significant issue, and that it is important to capture detail about attendance patterns and reasons for school non-attendance

Income differences in food consumption in the 1995 Australian national nutrition survey

Objective: To assess the relationships between an index of per capita income and the intake of a variety of individual foods as well as groups of food for men and women in different age groups. Design: Cross-sectional national survey of free-living men and women. Subjects: A sample of 5053 males and 5701 females aged 18 y and over who completed the Australian National Nutrition Survey 1995. Methods: Information about the frequency of consumption of 88 food items was obtained. On the basis of scores on the Food Frequency Questionnaire, regular and irregular consumers of single foods were identified. The relationships between regularity of consumption of individual foods and per capita income were analysed via contingency tables. Food variety scores were derived by assigning individual foods to conventional food group taxonomies, and then summing up the dichotomised intake scores for individual foods within each food group. Two-way ANOVA (income age group) were performed on the food variety scores for males and females, respectively. Results: Per capita income was extensively related to the reported consumption of individual foods and to total and food group variety indices. Generally, both men and women in low income households had less varied diets than those in higher-income households. However, several traditional foods were consumed less often by young high-income respondents, especially young women. Conclusions: Major income differentials in food variety occur in Australia but they are moderated by age and gender. Younger high-income women, in particular, appear to have rejected a number of traditional foods, possibly on the basis of health beliefs. The findings also suggest that data aggregation has marked effects on income and food consumption relationships.<br /

Allogeneic Stem Cells Alter Gene Expression and Improve Healing of Distal Limb Wounds in Horses.

Distal extremity wounds are a significant clinical problem in horses and humans and may benefit from mesenchymal stem cell (MSC) therapy. This study evaluated the effects of direct wound treatment with allogeneic stem cells, in terms of gross, histologic, and transcriptional features of healing. Three full-thickness cutaneous wounds were created on each distal forelimb in six healthy horses, for a total of six wounds per horse. Umbilical cord-blood derived equine MSCs were applied to each wound 1 day after wound creation, in one of four forms: (a) normoxic- or (b) hypoxic-preconditioned cells injected into wound margins, or (c) normoxic- or (d) hypoxic-preconditioned cells embedded in an autologous fibrin gel and applied topically to the wound bed. Controls were one blank (saline) injected wound and one blank fibrin gel-treated wound per horse. Data were collected weekly for 6 weeks and included wound surface area, thermography, gene expression, and histologic scoring. Results indicated that MSC treatment by either delivery method was safe and improved histologic outcomes and wound area. Hypoxic-preconditioning did not offer an advantage. MSC treatment by injection resulted in statistically significant increases in transforming growth factor beta and cyclooxygenase-2 expression at week 1. Histologically, significantly more MSC-treated wounds were categorized as pro-healing than pro-inflammatory. Wound area was significantly affected by treatment: MSC-injected wounds were consistently smaller than gel-treated or control wounds. In conclusion, MSC therapy shows promise for distal extremity wounds in horses, particularly when applied by direct injection into the wound margin. Stem Cells Translational Medicine 2018;7:98-108

Current and future multimodal learning analytics data challenges

Multimodal Learning Analytics (MMLA) captures, integrates and analyzes learning traces from different sources in order to obtain a more holistic understanding of the learning process, wherever it happens. MMLA leverages the increasingly widespread availability of diverse sensors, highfrequency data collection technologies and sophisticated machine learning and artificial intelligence techniques. The aim of this workshop is twofold: first, to expose participants to, and develop, different multimodal datasets that reflect how MMLA can bring new insights and opportunities to investigate complex learning processes and environments; second, to collaboratively identify a set of grand challenges for further MMLA research, built upon the foundations of previous workshops on the topic

A procedure for the change point problem in parametric models based on phi-divergence test-statistics

This paper studies the change point problem for a general parametric, univariate or multivariate family of distributions. An information theoretic procedure is developed which is based on general divergence measures for testing the hypothesis of the existence of a change. For comparing the accuracy of the new test-statistic a simulation study is performed for the special case of a univariate discrete model. Finally, the procedure proposed in this paper is illustrated through a classical change-point example

Frações de N do solo cultivado com milho e plantas de cobertura.

O milho é uma cultura de relevância no país e exige quantidades elevadas de nitrogênio (N) durante o seu crescimento. A sua disponibilidade para as plantas depende tanto do teor imediatamente disponível no solo, representada pelas formas inorgânicas, quanto do N das formas orgânicas, mineralizáveis durante o seu ciclo. O objetivo deste trabalho foi avaliar as alterações de frações do nitrogênio sob cultivo de plantas de cobertura na cultura do milho. O experimento está sendo conduzido há oito anos em Latossolo Vermelho sob milho cultivado em sistema plantio direto em sucessão às seguintes plantas de cobertura: Urochloa ruziziensis, Canavalia brasiliensis, Cajanus cajan e Sorghum bicolor. O delineamento experimental foi de blocos ao acaso com parcelas subdivididas e três repetições. Nas parcelas foram semeadas as plantas de cobertura e nas subparcelas foi feita a adubação fertilização nitrogenada em cobertura (com e sem N) na cultura do milho. Em Abril de 2013, após a colheita do milho foi realizada a coleta do solo nas profundidades de 0-10 e 10-20 cm. As plantas de cobertura apresentaram comportamento diferenciado em relação às camadas de solo. O solo sob U. ruziziensis apresentou maior N total e particulado que aquele sob C. cajan

Principal Component Regression predicts functional responses across individuals

International audienceInter-subject variability is a major hurdle for neuroimaging group-level inference, as it creates complex image patterns that are not captured by standard analysis models and jeopardizes the sensitivity of statistical procedures. A solution to this problem is to model random subjects effects by using the redundant information conveyed by multiple imaging contrasts. In this paper, we introduce a novel analysis framework, where we estimate the amount of variance that is fit by a random effects subspace learned on other images; we show that a principal component regression estimator outperforms other regression models and that it fits a significant proportion (10% to 25%) of the between-subject variability. This proves for the first time that the accumulation of contrasts in each individual can provide the basis for more sensitive neuroimaging group analyzes

High precision X-ray logN-logS distributions: implications for the obscured AGN population

We have constrained the extragalactic source count distributions over a broad range of X-ray fluxes and in various energy bands to test whether the predictions from X-ray background synthesis models agree with the observational constraints provided by our measurements. We have used 1129 XMM-Newton observations at |b|>20 deg covering a sky area of 132.3 deg^2 to compile the largest complete samples of X-ray objects to date in the 0.5-1 keV, 1-2 keV, 2-4.5 keV, 4.5-10 keV, 0.5-2 keV and 2-10 keV energy bands. Our survey includes in excess of 30,000 sources down to ~10^-15 erg/cm^2/s below 2 keV and down to ~10^{-14} erg/cm^2/s above 2 keV. A break in the source count distributions was detected in all energy bands except the 4.5-10 keV band. An analytical model comprising 2 power-law components cannot adequately describe the curvature seen in the source count distributions. The shape of the logN(>S)-logS is strongly dependent on the energy band with a general steepening apparent as we move to higher energies. This is due to non-AGN populations, comprised mainly of stars and clusters of galaxies, contribute up to 30% of the source population at energies 10^{-13} erg/cm^2/s, and these populations of objects have significantly flatter source count distributions than AGN. We find a substantial increase in the relative fraction of hard X-ray sources at higher energies, from >55% below 2 keV to >77% above 2 keV. However the majority of sources detected above 4.5 keV still have significant flux below 2 keV. Comparison with predictions from the synthesis models suggest that the models might be overpredicting the number of faint absorbed AGN, which would call for fine adjustment of some model parameters such as the obscured to unobscured AGN ratio and/or the distribution of column densities at intermediate obscuration.Comment: Accepted for publication in Astronomy and Astrophysics. Abridged Abstract. 23 pages, 47 figures, 8 table