Social And Emotional Learning And Support For Students Living In Rural Communities

Some schools have started implementing programs to assist with social and emotional development in students. Social and emotional skills include the ability to get along well with others, manage one’s emotions, and self-motivate; all of which impact the academic performance and behaviors of students (Zins, Weissberg, Wang, & Walberg, 2004). Unfortunately, many schools are lacking the additional supports needed, such as school counselors and social workers, to implement social and emotional learning programs or to provide social and emotional support to students (Education Week Research Center, 2015). The purpose of this study was to examine the effects of social and emotional learning and social and emotional support on academic achievement and behaviors of students in a rural school in Maine. The site of this study was an elementary school in a rural town in northern Maine. The reason this school was chosen for the study was because it was a part of a three-year grant from the 2015-16 school year through the 2017-18 school year, in which a school counselor and social worker were added to the school to provide social and emotional support and teach social and emotional skills to students. The study explored three research questions: 1) How do teachers and administrators perceive SEL and SES implementation and its impact on the school? 2) What changes occurred in NWEA scores during the two years that additional social and emotional supports were in place? 3) What changes occurred in student behavior incidents during the two years that additional social and emotional supports were in place? Data collection included student testing and behavioral data, teacher surveys, and a teacher focus group discussion. The findings suggest the need for social and emotional supports, such as school counselors and social workers, in all schools, especially rural schools that often lack those additional supports. Teachers perceived the additional supports were important to students’ wellbeing. The additional social and emotional supports in place through the school counselor and social worker were associated with positive changes in student behavior student behavior

The Effects of Exercise and Human Relationships on Interpreting

In this action research project, I analyzed the impact exercise and human relationships had on my interpreting work. It is well known that exercise and human relationships and connection do influence our actions and behavior in a manner (see, for example, Humphrey, 2015; Zenizo, 2013). In this current research, I explore exercise and human relationship, each in its own entity and then compare the two to each other, to see their influence towards interpreting. The aim of this study is to contribute to the field of American Sign Language/English interpreting by adding knowledge of what I found through this research about exercise, human relationships and the extent they impact my interpreting. I hope to provide more evidence to show the implications of applying self-care to one’s daily routine, in hopes of promoting improvement in one’s work. The method conducted for this action research project is through the mode of journaling, logs, and a recording of a work sample. I would make note of my day considering what I observed in my work, my workouts, the interactions I had with people, and when and if these two self-care approaches were implemented. I used the qualitative method approach to analyze the data. Through this, I focus on myself and interpreting by making alterations to the amount of exercise and human relationships and/or connections I incorporate into my self-care (before and after work). The results of the study show that human relationships and connections have a bigger impact on my interpreting work than exercise and the two together are stronger and more influential. By exploring exercise and human connection, I get to investigate self-care, its importance, and benefits while interpreting

A study on Analysis and Utilization of Crowd-sourced Spatio-temporal Contexts from Social Media

兵庫県立大学大学院201

Sensing, Understanding, and Shaping Social Behavior

The ability to understand social systems through the aid of computational tools is central to the emerging field of computational social systems. Such understanding can answer epistemological questions on human behavior in a data-driven manner, and provide prescriptive guidelines for persuading humans to undertake certain actions in real-world social scenarios. The growing number of works in this subfield has the potential to impact multiple walks of human life including health, wellness, productivity, mobility, transportation, education, shopping, and sustenance. The contribution of this paper is twofold. First, we provide a functional survey of recent advances in sensing, understanding, and shaping human behavior, focusing on real-world behavior of users as measured using passive sensors. Second, we present a case study on how trust, which is an important building block of computational social systems, can be quantified, sensed, and applied to shape human behavior. Our findings suggest that:1) trust can be operationalized and predicted via computational methods (passive sensing and network analysis) and 2) trust has a significant impact on social persuasion; in fact, it was found to be significantly more effective than the closeness of ties in determining the amount of behavior change.U.S. Army Research Laboratory (Cooperative Agreement W911NF-09-2-0053

Human-Centered Technologies for Inclusive Collection and Analysis of Public-Generated Data

The meteoric rise in the popularity of public engagement platforms such as social media, customer review websites, and public input solicitation efforts strives for establishing an inclusive environment for the public to share their thoughts, ideas, opinions, and experiences. Many decisions made at a personal, local, or national scale are often fueled by data generated by the public. As such, inclusive collection, analysis, sensemaking, and utilization of pubic-generated data are crucial to support the exercise of successful decision-making processes. However, people often struggle to engage, participate, and share their opinions due to inaccessibility, the rigidity of traditional public engagement methods, and the lack of options to provide opinions while avoiding potential confrontations. Concurrently, data analysts and decision-makers grapple with the challenges of analyzing, sensemaking, and making informed decisions based on public-generated data, which includes high dimensionality, ambiguity present in human language, and a lack of tools and techniques catered to their needs. Novel technological interventions are therefore necessary to enable the public to share their input without barriers and allow decision-makers to capture, forage, peruse, and sublimate public-generated data into concrete and actionable insights. The goal of this dissertation is to demonstrate how human-centered approaches involve the stakeholders in the design, development, and evaluation of tools and techniques that can lead to inclusive, effective, and efficient approaches to public-generated data collection and analysis to support informed decision-making. To that end, in this dissertation, I first addressed the challenges of empowering the public to share their opinions by exploring two major opinion-sharing avenues --- social media and public consultation. To learn more about people\u27s social media experiences and challenges, I built two technology probes and conducted a qualitative exploratory study with 16 participants. This study is followed up by exploring the challenges of inclusive participation during public consultations such as town halls. Based on a formative study with 66 participants and 20 organizers, I designed and developed CommunityClick to enable reticent share their opinions silently and anonymously during town halls. Equipped with the knowledge and experiences from these works, I designed, developed, and evaluated technologies and methods to facilitate and accelerate informed data-driven decision-making based on increased public-generated data. Based on interviews with 14 analysts and decision-makers in the civic domain, I built a visual analytics system CommunityClick that can facilitate public input analysis by surfacing hidden insights, people\u27s reflections, and priorities. Leveraging the lessons learned during this work, I created a visual text analytics system that supports serendipitous discovery and balanced analysis of textual data to help make informed decisions. In this work, I contribute an understanding of how people collect and analyze public-generated data to fuel their decisions when they have increased exposure to alternative avenues for opinion-sharing. Through a series of human-centered studies, I highlight the challenges that inhibit inclusivity in opinion sharing and shortcomings of existing methods that prevent decision-makers to account for comprehensive public input that includes marginalized or unpopular opinions. To address these challenges, I designed, developed, and evaluated a collection of interactive systems including CommunityClick, CommunityPulse, and Serendyze. Through a rigorous set of evaluation strategies which include creativity sessions, controlled lab studies, in-the-wild deployment, and field experiments, I involved stakeholders to assess the effectiveness and utility of the built systems. Through the empirical evidence from these studies, I demonstrate how alternative designs for social media could enhance people\u27s social media experiences and enable them to make new connections with others to share opinions. In addition, I show how CommunityClick can be utilized to enable reticent attendees during public consultation to share their opinions while avoiding unwanted confrontation and allowing organizers to capture and account for silent feedback. I highlight how CommunityPulse allowed analysts and decision-makers to examine public input from multiple angles for an accelerated analysis and more informed decision-making. Furthermore, I demonstrate how supporting serendipitous discovery and balanced analysis using Serendyze can lead to more informed data-driven decision-making. I conclude the dissertation with a discussion on future avenues to expand this research including the facilitation of multi-user collaborative analysis, integration of multi-modal signals in the analysis of public-generated data, and potential adoption strategies for decision-support systems designed for inclusive collection and analysis of public-generated data

D7.2 1st experiment planning and community management

The present deliverable, outlines the overall strategy for approaching the tasks of (a) developing and sustaining an engaged school-based community of ProsocialLearn users; and (b)planning and facilitating small-scale and large-scale school-based evaluation studies of the Prosocial Learn technological solution. It also presents the preliminary work undertaken so far, and details the activities planned for M9-15 with respect to community development and small-scale studies

Player agency in interactive narrative: audience, actor & author

The question motivating this review paper is, how can computer-based interactive narrative be used as a constructivist learn- ing activity? The paper proposes that player agency can be used to link interactive narrative to learner agency in constructivist theory, and to classify approaches to interactive narrative. The traditional question driving research in interactive narrative is, ‘how can an in- teractive narrative deal with a high degree of player agency, while maintaining a coherent and well-formed narrative?’ This question derives from an Aristotelian approach to interactive narrative that, as the question shows, is inherently antagonistic to player agency. Within this approach, player agency must be restricted and manip- ulated to maintain the narrative. Two alternative approaches based on Brecht’s Epic Theatre and Boal’s Theatre of the Oppressed are reviewed. If a Boalian approach to interactive narrative is taken the conflict between narrative and player agency dissolves. The question that emerges from this approach is quite different from the traditional question above, and presents a more useful approach to applying in- teractive narrative as a constructivist learning activity

Spartan Daily, November 22, 1999

Volume 113, Issue 59https://scholarworks.sjsu.edu/spartandaily/9488/thumbnail.jp