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

Victims’ Voices:Understanding the Emotional Impact of Cyberstalking and Individuals’ Coping Responses

Recent quantitative research has identified similar detrimental effects on victims of cyberstalking as those that arise from traditional stalking. The current study thematically analyzed one hundred victim narratives gathered by means of an online survey with a view to assessing the mental health and well-being implications of the experience of cyberstalking. Coping strategies employed by victims and the perceived effectiveness of each strategy were also explored. The findings suggest that the emotional impact of cyberstalking predominantly includes comorbid anxiety and depression. Common coping strategies adopted by victims in our sample include avoidant coping, ignoring the perpetrator, confrontational coping, support seeking, and cognitive reframing. Taken together, the findings demonstrate that the ramifications of cyberstalking are widespread, affecting psychological, social, interpersonal, and economic aspects of life. To adapt, some victims made major changes to both their work and social life, with some ceasing employment and others modifying their usual daily activities. The widespread negative effects of cyberstalking identified in this study highlight that this phenomenon should be a concern to both legal and mental health professionals, particularly as the comments made by our sample illustrate the current inadequacy of response and provision. Recommendations are discussed and provided for law enforcement and mental health professionals

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

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 /

CROSSMMLA Futures: Collecting and analysing multimodal data across the physical and the virtual

Workshop proposal for CrossMMLA focused on collecting and analysing multimodal data across the physical and the virtual. Under the current global pandemic, cross physical and virtual spaces play a substantial factor and challenge for MMLA, which is focused on collaborative learning in physical spaces. The workshop proposes an asynchronous format that includes pre-recorded video demonstrations and position papers for discussion, followed by a half-day virtual meeting at LAK'2021

Barriers and facilitators to accessing and utilising post-treatment psychosocial support by Black men treated for prostate cancer—a systematic review and qualitative synthesis

Purpose: To synthesise findings from published studies on barriers and facilitators to Black men accessing and utilising post-treatment psychosocial support after prostate cancer (CaP) treatment. Methods: Searches of Medline, Embase, PsycInfo, Cochrane Database of Systematic Reviews and Central, CINAHL plus and Scopus were undertaken from inception to May 2021. English language studies involving Black men aged ≥18 and reporting experiences of, or suggestions for, psychosocial support after CaP treatment were included. Low or moderate quality studies were excluded. Searches identified 4,453 articles and following deduplication, 2,325 were screened for eligibility. Two independent reviewers carried out screening, quality appraisal and data extraction. Data were analysed using thematic synthesis. Results: Ten qualitative studies involving 139 Black men were included. Data analysis identified four analytical constructs: experience of psychosocial support for dealing with treatment side effects (including impact on self-esteem and fear of recurrence); barriers to use of psychosocial support (such as perceptions of masculinity and stigma around sexual dysfunction); facilitators to use of psychosocial support (including the influence of others and self-motivation); and practical solutions for designing and delivering post-treatment psychosocial support (the need for trusted healthcare and cultural channels). Conclusions: Few intervention studies have focused on behaviours among Black CaP survivors, with existing research predominantly involving Caucasian men. There is a need for a collaborative approach to CaP care that recognises not only medical expertise but also the autonomy of Black men as experts of their illness experience, and the influence of cultural and social networks

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

Bayesian Blocks, A New Method to Analyze Structure in Photon Counting Data

I describe a new time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The input is raw counting data, in any of three forms: time-tagged photon events (TTE), binned counts, or time-to-spill (TTS) data. The output is the most likely segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant -- i.e. has a fixed intensity without statistically significant variations. Since the analysis is based on Bayesian statistics, I call the resulting structures Bayesian Blocks. Unlike most, this method does not stipulate time bins -- instead the data themselves determine a piecewise constant representation. Therefore the analysis procedure itself does not impose a lower limit to the time scale on which variability can be detected. Locations, amplitudes, and rise and decay times of pulses within a time series can be estimated, independent of any pulse-shape model -- but only if they do not overlap too much, as deconvolution is not incorporated. The Bayesian Blocks method is demonstrated by analyzing pulse structure in BATSE $\gamma$-ray data. The MatLab scripts and sample data can be found on the WWW at: http://george.arc.nasa.gov/~scargle/papers.htmlComment: 42 pages, 2 figures; revision correcting mathematical errors; clarifications; removed Cyg X-1 sectio