Julien Lavergne, lead developer of lubuntu, gave a presentation about the lubuntu project and ways to involve at the FOSSASIA conference in Ho Chi Minh City (Saigon), Vietnam. Here are the slides.
Lubuntu, Xubuntu, CrunchBang, Peppermint, and Puppy Linux are some of the top lightweight Linux distributions that can run well on older computers with low system requirements. A lightweight distro uses few system resources and focuses on speed and efficiency. Lubuntu and Xubuntu use the LXDE and Xfce desktop environments respectively, keeping their requirements low. CrunchBang offers a modern Debian system without sacrificing performance using the Openbox window manager. Peppermint is based on Lubuntu but is cloud-centric, while Puppy Linux can run entirely from RAM.
Creative Commons in Vietnam - Presentation by Mario Behling and Hong Phuc Dan...Mario B.
The document discusses an organization that promotes Creative Commons licenses in Vietnam to foster collaboration. The organization operates consulting, marketing, and software development businesses using open source tools and Creative Commons licensed content. While the organization does not directly earn money from Creative Commons, using the licenses has indirect benefits and allows cooperation with other groups. The organization aims to increase Creative Commons usage among partners and publish more open content materials.
CouchDB is a document-oriented database that uses JSON documents, has a RESTful HTTP API, and is queried using map/reduce views. Each of these properties alone, especially MapReduce views, may seem foreign to developers more familiar with relational databases. This tutorial will teach web developers the concepts they need to get started using CouchDB in their projects. CouchDB’s RESTful HTTP API makes it suitable for interfacing with any programming language. CouchDB libraries are available for many programming languages and we will take a look at some of the more popular ones.
This document discusses big data in education and its importance. It defines big data as large datasets that are difficult to store, manage, and analyze using typical database tools due to their size. While big data is often defined by its size, what matters more is what is done with the data. The document advocates understanding how big data can be applied to learning to provide valuable insights into what works well and how to replicate successes. It discusses moving from simply collecting data to making connections with data through analytics and mashing up different data sources. The benefits of learning analytics and academic analytics are noted. Examples of potential big data demonstrations and directions are also provided.
This document provides an overview of software-defined networking (SDN) and the HPE VAN SDN Controller. It defines SDN and describes its key concepts including the separation of the control plane and data plane. The benefits of SDN like centralization, dynamism, and optimization are outlined. The architecture of the HPE SDN Controller is presented along with the core applications it provides for network discovery, path selection, topology management and more. In conclusion, SDN is positioned to transform static networks into scalable, programmable platforms.
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This document provides an overview of software-defined storage (SDS) concepts and discusses several SDS solutions from major vendors. It defines SDS and explains how adding a control layer allows for visibility, communication, and allocation of storage resources. Benefits highlighted include efficiency, automation, flexibility, scalability, reliability and cost savings. Specific SDS products are then profiled from vendors such as EMC, HP, IBM, NetApp, VMware, Coraid, DataCore, Dell, Hitachi, Pivot3, and RedHat.
Julien Lavergne, lead developer of lubuntu, gave a presentation about the lubuntu project and ways to involve at the FOSSASIA conference in Ho Chi Minh City (Saigon), Vietnam. Here are the slides.
Lubuntu, Xubuntu, CrunchBang, Peppermint, and Puppy Linux are some of the top lightweight Linux distributions that can run well on older computers with low system requirements. A lightweight distro uses few system resources and focuses on speed and efficiency. Lubuntu and Xubuntu use the LXDE and Xfce desktop environments respectively, keeping their requirements low. CrunchBang offers a modern Debian system without sacrificing performance using the Openbox window manager. Peppermint is based on Lubuntu but is cloud-centric, while Puppy Linux can run entirely from RAM.
Creative Commons in Vietnam - Presentation by Mario Behling and Hong Phuc Dan...Mario B.
The document discusses an organization that promotes Creative Commons licenses in Vietnam to foster collaboration. The organization operates consulting, marketing, and software development businesses using open source tools and Creative Commons licensed content. While the organization does not directly earn money from Creative Commons, using the licenses has indirect benefits and allows cooperation with other groups. The organization aims to increase Creative Commons usage among partners and publish more open content materials.
CouchDB is a document-oriented database that uses JSON documents, has a RESTful HTTP API, and is queried using map/reduce views. Each of these properties alone, especially MapReduce views, may seem foreign to developers more familiar with relational databases. This tutorial will teach web developers the concepts they need to get started using CouchDB in their projects. CouchDB’s RESTful HTTP API makes it suitable for interfacing with any programming language. CouchDB libraries are available for many programming languages and we will take a look at some of the more popular ones.
This document discusses big data in education and its importance. It defines big data as large datasets that are difficult to store, manage, and analyze using typical database tools due to their size. While big data is often defined by its size, what matters more is what is done with the data. The document advocates understanding how big data can be applied to learning to provide valuable insights into what works well and how to replicate successes. It discusses moving from simply collecting data to making connections with data through analytics and mashing up different data sources. The benefits of learning analytics and academic analytics are noted. Examples of potential big data demonstrations and directions are also provided.
This document provides an overview of software-defined networking (SDN) and the HPE VAN SDN Controller. It defines SDN and describes its key concepts including the separation of the control plane and data plane. The benefits of SDN like centralization, dynamism, and optimization are outlined. The architecture of the HPE SDN Controller is presented along with the core applications it provides for network discovery, path selection, topology management and more. In conclusion, SDN is positioned to transform static networks into scalable, programmable platforms.
Deploying & Scaling OpenShift on OpenStack using Heat - OpenStack Seattle Mee...OpenShift Origin
This document provides an overview and agenda for deploying OpenShift on OpenStack. It begins with a brief introduction to Platform as a Service (PaaS) and OpenShift. It then discusses the various flavors of OpenShift including the open source Origin project, public cloud service, and on-premise private cloud software. The remainder of the document focuses on deploying OpenShift on OpenStack using Heat templates, including an overview of Heat and its orchestration capabilities, the OpenShift architecture, and a demonstration of deploying OpenShift Enterprise templates with Heat.
This document provides an overview of software-defined storage (SDS) concepts and discusses several SDS solutions from major vendors. It defines SDS and explains how adding a control layer allows for visibility, communication, and allocation of storage resources. Benefits highlighted include efficiency, automation, flexibility, scalability, reliability and cost savings. Specific SDS products are then profiled from vendors such as EMC, HP, IBM, NetApp, VMware, Coraid, DataCore, Dell, Hitachi, Pivot3, and RedHat.
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The role of data managers is integral to improving results for students with disabilities. Data managers ensure timely and accurate special education data submission, provide data analysis to inform decision making, and help local districts understand and leverage their own data. Effective data governance, cross-department information sharing, and making data accessible are important responsibilities of data managers. Summarizing data and using it to tell the story of progress can influence policy and support students.
Pam Muth and Lisa Bolton: Optimising QILT to improve the student experienceStudiosity.com
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Stakeholders across Arkansas provided feedback that informed the development of the Arkansas StudentGPS Dashboards. The dashboards provide a centralized location for teachers, schools, and districts to access student data to guide instruction. Educators can view assessment results, attendance, grades and other information to identify strengths and weaknesses. The dashboards are updated nightly and allow filtering of data in customizable ways. Arkansas has implemented the dashboards statewide through a multi-year process with training and support.
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This presentation was given by Cláudia Sarrico of the Lisbon School of Economics and Management, University of Lisbon at the GCES Conference on Education Governance: The Role of Data in Tallinn on 12 February 2015 during the afternoon session workshop on Developing data systems.
This document discusses plans to create a data dashboard to track education and workforce outcomes for students in central Ohio. The dashboard will combine K-12, postsecondary, and employment data from state sources. It aims to help education and business leaders understand pathways and outcomes for graduates. The dashboard is being developed through a collaboration of research and education organizations for the Central Ohio Compact, which has a goal of increasing postsecondary attainment rates in the region. It will allow tracking items like dual enrollment participation, college credits earned, college readiness, career credentials, and employment outcomes at the district and institutional levels.
This document provides an overview of the Office of the Vice President for Student Affairs and Academic Support at the University of South Carolina. It discusses the division's budget, capital planning projects, departments, and core functions. The division aims to provide access to education, facilitate student progress and persistence, advance learning, and develop citizenship and leadership. The Planning, Assessment and Innovation Council guides departmental planning, assessment, and innovation efforts to improve division effectiveness and accountability.
Creating Interactive Dashboards with Microsoft ExcelAACRAO
Sign up to view the archived webinar here: http://www.aacrao.org/conferences/conferences-detail-view/creating-interactive-dashboards-in-excel
Other college’s dashboards making you see green even though it is not your school color? No budget for specialized dashboard programs? Can’t keep up with end-user demands for different analyses?
New features in Excel 2010 and 2013 allow even casual users to create interactive dashboards that are both functional and great looking allowing you and your end-users to explore your data in ways you have only imagined—allowing you to convert your data into actionable information.
Even if you are a Pivot Table novice, you can create functional and great looking dashboards. In this webinar, we will show you the basic steps for creating interactive dashboards in Excel 2010 and 2013. Taking a holistic SEM approach, we will examine several use-cases throughout the student lifecycle.
From setting up your data, to creating the dashboard and modifying it to your own school colors, we will cover the basics of setting up a simple, yet interactive and informative dashboards. Some basic knowledge of Pivot Tables is useful but not required.
The document summarizes a workshop on redesigning North Carolina's school performance grades. It reviewed federal accountability requirements under ESSA and examined the state's current accountability system. Participants were tasked with brainstorming the characteristics of a ready student and high-quality school, as well as potential accountability indicators, to inform the redesign. The workshop was facilitated by an independent organization focused on improving educational assessment and accountability.
Through the contracted services of a local non-profit organization, Education Pioneers, data was compiled and analyzed by one of their fellows over the course of a ten month fellowship.
The following slide deck contains the framework for which the actions and services of the West Contra Costa Unified School District (WCCUSD) 2016-2017 Local Control Accountability Plan (LCAP) were evaluated.
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This document summarizes a presentation about using data analytics to improve student enrollment and retention. It discusses trends in enrollment, persistence, and completion rates based on data from national sources. It also provides an overview of Rapid Insight's analytics software for data preparation, predictive modeling, and sharing results. Additionally, the presentation discusses using predictive modeling to identify metrics that affect student success and retention at different points. Examples of factors that may be considered in the models are listed. The last sections discuss institutions' use of analytics for student success based on a landscape analysis and the importance of transparency when using predictive modeling.
This document provides guidance on finding and critically analyzing data about schools and communities. It discusses key sources of data like government agencies, non-profits, academic institutions, and the private sector. When finding data, it's important to consider topics that may be controversial, sampling techniques, and publication timeframes. The document outlines how to evaluate data sources and methodology, identify potential biases, and distinguish between correlations and causation. Specific data sources mentioned include the California Department of Education, California Healthy Kids Survey, School Accountability Report Cards, U.S. Census Bureau's American FactFinder, and the American Community Survey. Exercises are provided to have users find and analyze data for a particular school and neighborhood.
This document discusses the importance of data in education and provides an overview of key topics related to data use. It defines different types of data, sources of data, and how data can be used at various levels within the education system. The goal is to shift toward using data in strategic and thoughtful ways to inform decisions and improve student outcomes. Leaders are encouraged to develop a culture of inquiry and data-informed decision making.
This document summarizes Vermont's approach to using data-driven decision making to support Positive Behavioral Interventions and Supports (PBIS) in schools. It provides an overview of the PBIS implementation in Vermont, describing the various state agencies and organizations involved in supporting schools. It also describes the tiered system of support for schools, including the data tools and resources available at each level to facilitate data-driven problem solving. Data is shown on the growth of PBIS implementation in Vermont schools over time, as well as outcomes like decreased office discipline referrals and time out of school/class. The role of data analysis to support decision making is emphasized.
This document discusses creating a system of on-site technical assistance for instructors to improve program performance. The system is designed to help instructors use student assessment data to improve performance, understand how assessment data links to state performance targets, gain insight from classroom observations, and develop professional development plans. The first step is to review class and program data on performance, then determine changes needed like professional development, program design, populations served, or service delivery methods. An implementation plan would be created based on review findings and priorities. The goal is for instructors to use data and assistance to positively impact student outcomes and meet state performance targets.
The document provides an overview of the U.S. higher education system, including its size, governance, funding sources, and degree programs. It notes that the system includes over 4,500 public, private non-profit, and for-profit institutions enrolling nearly 20 million students. The system is facing pressures like decreased state funding, rising tuition costs, and changing student demographics. It suggests innovation is needed, such as new learning models, credentials, and partnerships between education and employers.
Overview of the New Jersey Education to Earnings Data SystemKathy Krepcio
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3. What is SLICE?
How it Works
Data Quality
Training & Support
Security & Access
Next Steps
Objectives
4. SLICE????
• A new statewide system for collecting and
reporting education data.
• Efficient data collection process & data
dashboards, providing educators with tools to
evaluate & enhance student academic
performance
• Provide the public with a depth of educational
information from the school to the state.
5. Dept. Of
Employment &
Workforce
(DEW)
Dept. Of Social
Services
(DSS)
Office of Research
& Statistics
(ORS)
SLICE
Commission
on Higher
Education
(CHE)
Other
State Agencies
(to be
determined)
6. Office of Research
& Statistics
(ORS)
SLICE Components
State
Assessments
PASS, HSAP,
EOCEP
SCDE Division
of School
Effectiveness
(Educator data
system)
SCDE
SC Curriculum
& Standards
District
PK-12
Individual
Graduation
Plan System
(IGP)
SCDE
Enrollment
and Finance
Data
7. Under The Hood
Data Governance:
Policies and Security
Training and Technical Assistance (The Seven A’s):
Acquisition, Access, Analysis, Application, Assessment, Action, and Advancement
Public Interface Educator InterfaceResearch and Policy InterfaceParent and Student
Interface
Unique ID
Systems
Instructional
ProgramsSIS:
Students
Teachers
Courses
Classes
Behavior
Grades
More
Curriculum Management
System:
Curriculum Content
Standards
Assessments
Assessment
Management System:
Assessment Results
Links to Other Student Data
Academic Plans
Educator Data:
Teachers
Evaluations
Credentials
Schedules
Staff Development
Higher Education:
Student Readiness
Teacher Preparation
Reporting
Research
Workforce Agencies:
Student Readiness
Business Partners
Armed Forces
Reporting
Research
Common
Data Standards
Data and Queries
Unique Student ID
Unique Educator ID
Unique Program ID
SIS
Assessments
De-Identified Indices
8.
9. Data Quality
• Data Load Process
• Final Transition from Consulting Firm to
SCDE
• Core Data Sources
• Data Mapping Documentation in
Progress
• Upload Schedule
• Private Pilot Data ( NOW) = 180 day 2010-11
• Upload of 180 day 2012-13 in Progress
16. Personally Identifiable Information
• PII is ―any information about an individual
maintained by an agency, including;
– any information that can be used to distinguish or
trace an individual‘s identity, such as name, social
security number, date and place of birth, mother‘s
maiden name, or biometric records
– any other information that is linked or linkable to
an individual, such as medical, educational,
financial, and employment information.
18. SLICE PORTAL
PUBLIC ACCESS
• http://publicslice.ed.sc.gov
• No Log on
• PII Data Removed
DISTRICT ACCESS
• Required User ID & Password
• Audited
19.
20. Roles & Access
• Individual Student Records
• Individual Teacher Data
• Class Data
• School Data
• District Data
• State Data
21. Roles & Access
• Individual Student Records
• Individual Teacher Data
• Class Data
• School Data
• District Data
• State Data
NO PUBLIC ACCESS
NO PUBLIC ACCESS
SUMMARY DATA ONLY *
SUMMARY DATA ONLY
SUMMARY DATA ONLY
SUMMARY DATA ONLY
* Nothing Displayed if less than 10
22. Roles & Access
• Individual Student Records
• Individual Teacher Data
• Class Data
• School Data
• District Data
• State Data
CURRENT STUDENT PII
SELF PII
CURRENT PII
SUMMARY DATA ONLY
SUMMARY DATA ONLY
SUMMARY DATA ONLY
23. Roles & Access
• Individual Student Records
• Individual Teacher Data
• Class Data
• School Data
• District Data
• State Data
PII
Self PII
PII
PII
SUMMARY DATA ONLY
SUMMARY DATA ONLY
24. Roles & Access
• Individual Student Records
• Individual Teacher Data
• Class Data
• School Data
• District Data
• State Data
PII
PII
PII
PII
SUMMARY DATA ONLY
SUMMARY DATA ONLY
25. Roles & Access
• Individual Student Records
• Individual Teacher Data
• Class Data
• School Data
• District Data
• State Data
PII
PII
PII
PII
SELF PII ONLY
SUMMARY DATA ONLY
District Administrator
26. District Administrator
• Due to the amount of PII, this role will
require authorization from the District
Superintendent.
• SCDE will conduct audits to ensure
compliance.
29. Involvement!
• Webinar
SLICE information session
– Review the progress that has been made
working with the embargo site,
– Review both current & future Training activities
– Discuss next steps in the development of SLICE.
• 3 Working Groups
1. Data
2. Training
3. Technology
30. We need your participation!
? Training materials & sessions
? Training coordinator @ District
31. – Basic platform developed.
– Need your input
• Additional Dashboards
• Additional Data Sources
– Comparisons
• Side by Side?
• Over Time?
– What Else?
Foundation
@ed.sc.gov