Multimodal data as a means to understand the learning experience

Most work in the design of learning technology uses click-streams as their primary data source for modelling & predicting learning behaviour. In this paper we set out to quantify what, if any, advantages do physiological sensing techniques provide for the design of learning technologies. We conducted a lab study with 251 game sessions and 17 users focusing on skill development (i.e., user's ability to master complex tasks). We collected click-stream data, as well as eye-tracking, electroencephalography (EEG), video, and wristband data during the experiment. Our analysis shows that traditional click-stream models achieve 39% error rate in predicting learning performance (and 18% when we perform feature selection), while for fused multimodal the error drops up to 6%. Our work highlights the limitations of standalone click-stream models, and quantifies the expected benefits of using a variety of multimodal data coming from physiological sensing. Our findings help shape the future of learning technology research by pointing out the substantial benefits of physiological sensing.     

Understanding how social worker compassion fatigue and years of experience shape custodial decisions

BackgroundCompassion fatigue (i.e., a worker’s diminished ability to empathize with clients) is common among “helping workers” and can result in psychological detachment from clients as a coping mechanism.ObjectiveIn the present research, we explored the relationship between social workers’ compassion fatigue and years of job experience on hypothetical child custody case judgments.Participants and settingIn two separate studies, individuals with experience working with children in child dependency court (predominantly social workers, Study 1: N = 173, Study 2: N = 119) were recruited on Amazon’s Mechanical Turk and read a vignette depicting a mother attempting to regain custody.ResultsSupporting hypotheses, compassion fatigue significantly mediated the relationship between increased years of social worker job experience on recommendations that a neglectful mother receive custody, Indirect Effect = .06, CIs [.026, .127] (Study 1). We also found preliminary support for our hypothesized theoretically derived serial path model, in which (a) social worker compassion fatigue predicts anticipated secondary traumatic stress associated with the child neglect case, B = .54, p = .0001; (b) secondary traumatic stress predicts detachment from the neglected child, B = .27, p = .0003; (c) detachment from the child predicts job efficacy cynicism B = .65, p < .0001; and (d) job efficacy cynicism predicts decisions to allocate custody to the neglectful mother, B = .46, p = .005 (Study 2).ConclusionOur research shows that compassion fatigue among social workers may change the lens through which they perceive cases of child abuse.     

A Study on the Anxiety of Mongolian Undergraduates in Public English Class

Anxiety is a complicated psychological phenomenon in foreign language learning process, involving both cognitive and affective factors, especially for those with cross culture background. This essay fo...     

Learning through artful knowing

Unfinished and ongoing exploration, Oil Painting, 1.30?*?1?m, September 2015.     

The advantage of mixing examples in inductive learning: a comparison of three hypotheses

Mixing examples of different categories (interleaving) has been shown to promote inductive learning as compared with presenting examples of the same category together (massing). In three studies, we tested whether the advantage of interleaving is exclusively due to the mixing of examples from different categories or to the temporal gap introduced between presentations. In addition, we also tested the role of working memory capacity (WMC). Results showed that the mixing of examples might be the key component that determines improved induction. WMC might also be involved in the interleaving effect: participants with high spans seemed to profit more than participants with low spans from interleaved presentations. Our findings have relevant implications for education. Practice schedules should be individually customised so society as a whole can profit from differences between learners.     

Social relations as predictors of achievement in math in Kenyan primary schools

In sub-Saharan Africa, where there is limited financial and human capital, it is important to examine how social relationships may serve to promote or undermine human capital formation. However, little is known about the contributions of social relations to human capital development, especially in terms of academic achievement in Africa. This study examined how variations in key aspects of social relations among teachers; between teachers and students; between principals, teachers, parents and students affect achievement in mathematics among sixth graders in 70 schools in six districts in Kenya. We modeled mathematics achievement as a function of measures of social perception and support while adjusting for school-, classroom- and student level background characteristics. We found that net of teacher subject knowledge and background characteristics, teachers who display commitment to teaching by always correcting homework and keeping students engaged during math lessons had their students performing better. Teacher absenteeism and lack of interest in teaching were negatively associated with performance in math. Lack of parental involvement in the classroom also had negative effects on grades. At the school level, the level of engagement of the principal, measured by supervision of teachers and good interpersonal interactions with parents had positive effects on math achievement. Schools where parents provided material and financial support had better grades, while student delinquency and absenteeism negatively affected grades.     

Unconscious and unnoticed professional practice within an outstanding school for children and young people with complex learning difficulties and disabilities

This article describes a three‐year project undertaken at Pear Tree School for children and young people with severe and multiple and profound learning difficulties. Lesley Sullivan, the school's head teacher, believed that much of the value within the work of this outstanding school went unidentified by existing approaches to planning, monitoring and evaluation. Richard Crombie, educational psychologist, was engaged to work on the project. Also involved were Kate Walker and Rebecca Warnock, deputy head teachers, as well as the whole staff, children and some parents. The project takes as its starting point that essential, but very often unnoticed and unconscious, professional practice is rooted in implicit processes learnt experientially. We set ourselves the task of finding meaningful frameworks for identifying and developing that practice. This meant close observation within and outside school coupled with feeding back to staff, and their subsequent engagement with and use of explanatory frameworks.     

Community sport and social inclusion: international perspectives

Abstract

This opening article examines the relationship between community sport and social inclusion in research and practice. We discuss the notion of community sport, its multifarious meanings and diverse applications in different parts of the world. We further explore the conceptual and practical links between community sport and different conceptions of social inclusion. In doing so, the article draws together key themes, issues and debates addressed in the collection of articles in this special issue. We conclude by formulating implications and directions for future research and practice.     

Co-occurrence of adverse childhood experiences and its association with family characteristics. A latent class analysis with Dutch population data

BackgroundAlthough adverse childhood experiences (ACEs) are relatively common among children, there is limited knowledge on the co-occurrence of such experiences.ObjectiveThe current study therefore investigates co-occurrence of childhood adversity in the Netherlands and whether specific clusters are more common among certain types of families.Participants and SettingRepresentative data from the Family Survey Dutch population 2018 (N = 3,128) are employed.MethodWe estimate Latent Class Analysis (LCA) models to investigate co-occurrence of ACEs. As ACEs we examine maltreatment, household dysfunction, demographic family events, as well as financial and chronic health problems. Gradual measures for maltreatment and financial problems are studied to make it possible to differentiate with regard to the severity of experiences.ResultsOur results show that four ACE clusters may be identified: ‘Low ACE’, ‘Moderate ACE: Household dysfunction’, ‘Moderate ACE: Maltreatment’ and ‘High ACE’. Regression analyses indicated that mother’s age at first childbirth and the number of siblings were related to experiencing childhood adversity. We found limited evidence for ACEs to be related to a family’s socioeconomic position.ConclusionThe found clusters of ACEs reflect severity of childhood adversity, but also the types of adversity a child experienced. For screening and prevention of childhood adversity as well as research on its consequences, it is relevant to acknowledge this co-occurrence of types and severity of adversity.     

Managing What We Can Measure: Quantifying the Susceptibility of Automated Scoring Systems to Gaming Behavior

As methods for automated scoring of constructed‐response items become more widely adopted in state assessments, and are used in more consequential operational configurations, it is critical that their susceptibility to gaming behavior be investigated and managed. This article provides a review of research relevant to how construct‐irrelevant response behavior may affect automated constructed‐response scoring, and aims to address a gap in that literature: the need to assess the degree of risk before operational launch. A general framework is proposed for evaluating susceptibility to gaming, and an initial empirical demonstration is presented using the open‐source short‐answer scoring engines from the Automated Student Assessment Prize (ASAP) Challenge.