The document discusses the use of data and information in decision making through an education management information system (EMIS). The EMIS aims to ensure children receive quality education by providing timely, accurate educational statistics to decision makers. Data is collected from schools and analyzed to produce reports and charts for authorities to make informed decisions. Good information for decision making should be relevant, complete, economical, reliable, simple, and timely. The organization collects data through questionnaires then analyzes, checks for errors, and writes reports to guide education policies.
Technology is part and parcel of any development agenda across all sectors including but not limited to Health, Education, Agribusiness, Tourism, Infrastructure and Construction, Gas and Oil, Transport, Financial Services, Manufacturing.
Online Educa Berlin conference: Big Data in Education - theory and practiceMike Moore
Online Educa Berlin Conference Presentation
Big Data in Education - Theory and Practice
Presented December 6, 2013 by
Mike Moore, Sr. Advisory Consultant - Analytics
Desire2Learn, Inc.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
From Asset to Impact - Presentation to ICS Data Protection Conference 2011Castlebridge Associates
This is a presentation I delivered to the Irish Computer Society Data Protection Conference in February 2011 and again on a webinar for dataqualitypro.com in March 2011.
It looks (for what I believe was the first time) at the relationship between Information Quality and Data Governance principles and practices and the objectives of Data Protection/Privacy compliance. it includes my first version of the mapping of the 8 Data Protection principles to the POSMAD Information Life Cycle referred to by McGilvray and others in the IQ/DQ fields.
Technology is part and parcel of any development agenda across all sectors including but not limited to Health, Education, Agribusiness, Tourism, Infrastructure and Construction, Gas and Oil, Transport, Financial Services, Manufacturing.
Online Educa Berlin conference: Big Data in Education - theory and practiceMike Moore
Online Educa Berlin Conference Presentation
Big Data in Education - Theory and Practice
Presented December 6, 2013 by
Mike Moore, Sr. Advisory Consultant - Analytics
Desire2Learn, Inc.
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
From Asset to Impact - Presentation to ICS Data Protection Conference 2011Castlebridge Associates
This is a presentation I delivered to the Irish Computer Society Data Protection Conference in February 2011 and again on a webinar for dataqualitypro.com in March 2011.
It looks (for what I believe was the first time) at the relationship between Information Quality and Data Governance principles and practices and the objectives of Data Protection/Privacy compliance. it includes my first version of the mapping of the 8 Data Protection principles to the POSMAD Information Life Cycle referred to by McGilvray and others in the IQ/DQ fields.
A community needs assessment identifies the strengths and resources available in the community to meet the needs of children, youth, and families. The assessment focuses on the capabilities of the community, including its citizens, agencies, and organizations.
1. The use of DataThe use of Data
in decision makingin decision making
Better DecisionsBetter Decisions
throughthrough
Better InformationBetter Information
SALEEM IT EXPERT
2. EMIS Mission StatementEMIS Mission Statement
The information that EMIS manages willThe information that EMIS manages will
help to ensure that more children receivehelp to ensure that more children receive
a higher quality of education by ensuringa higher quality of education by ensuring
that the decision makers have the bestthat the decision makers have the best
information available, presented in aninformation available, presented in an
appropriate format at the time of makingappropriate format at the time of making
decisiondecision
SALEEM IT EXPERT
3. What does EMIS do?What does EMIS do?
1.1. It provides a timely, reliable, relevantIt provides a timely, reliable, relevant
and accurate information to the decisionand accurate information to the decision
makers regarding educational statistics inmakers regarding educational statistics in
the most efficient ,economical andthe most efficient ,economical and
appropriate mannerappropriate manner
2. The quality of education by taking2. The quality of education by taking
rational decision on empirical datarational decision on empirical data
SALEEM IT EXPERT
4. Data and informationData and information
• Data:
Data consists of letters, symbols, raw
facts events and transactions which have
been recorded but not yet into a form
which is suitable for making decisions.
Data on its own is not generally useful
SALEEM IT EXPERT
5. Data and informationData and information
• Information:
The data which has been processed in
such a way that it has a meaning to
person who receive it, It may then be used
to improve the quality of decision making
DATA+MEANING=INFORMATION
SALEEM IT EXPERT
7. • We have many types of data according to their
context and application
• Here we are concern about two types of data
which are mostly applicable in our project.
• Quantitative Data
• Qualitative Data
SALEEM IT EXPERT
8. Quantitative DataQuantitative Data
• If the data exists in numerical form, then it
is said to be Quantitative data.
• For example
• Total strength of students in a school
• Number of male and female teachers who
are teaching to class 8th
• Weekly weather forecast
SALEEM IT EXPERT
9. Qualitative DataQualitative Data
Data which exists in more than just words or text.
For example
• Maps
• Charts
• Sound Recordings
• Videos
• Photographs and so on
SALEEM IT EXPERT
11. Data Collection and its significanceData Collection and its significance
• What motivates people to go through the often
complex and costly process of collecting data?
• To make proper planning for the development of
the system using the provided information or data.
• By analyzing provided data, the planners of the
system make policies and search out he ways and
procedures to implement those policies
SALEEM IT
EXPERT
13. Attribute of good InformationAttribute of good Information
Relevant: Information must be relevant to
the problem under consideration .Irrelevant
information usually irritates the user. Care
must be taken to provide the user data
she/he requires.
Complete: Complete information contain
all the important .For example ,school
enrollment should mention both the
genders otherwise the data on enrollment
will be incomplete.
15. Attribute of good InformationAttribute of good Information
Economical: Information should be
relatively economical to produce. Decision
makers always balance the value of
information with the cost of producing it.
Reliable: Information should be sufficiently
reliable of accurate for its intended
purpose. The decision makers should be
able to rely on the information.
16. Attribute of good InformationAttribute of good Information
Simple: Information should be simple,
complex and difficult information reduces
the understanding of the user. Busy users
will likely not use complex information.
Timely: Information can only be used if
received in time to influence the decision
making process.
Verifiable : information should be
verifiable ,it should be the same when
checked through different sources.
17. How data is collected in ourHow data is collected in our
organizationorganization
•Before proceeding to collect data,
questionnaires are designed.
•Usually we collect data from
concerned officials (DDOs,ADIs by
providing relevant questionnaires and
form.
•These filled questionnaires are then
submitted to central EMIS
18. Coding and AnalysisCoding and Analysis
•The collected data is then fed into
computer systems for its analysis and
scrutiny.
•Before storing data in computer
systems, errors and duplications are
removed
19. Report WritingReport Writing
•The extracted outcomes are then
summarized
•The outcomes are interpreted
•These reports and charts are then sent
to the higher authorities and policy
makers.
20. What is AssessmentWhat is Assessment
• The Process of obtaining information
that is used to make educational
decisions about students, to give
feedback to the student about his or
her progress, strengths and
weaknesses ,to judge instructional
effectiveness and curricular adequacy
and to inform policy
21. National AssessmentNational Assessment
• An Exercise designed to describe the
level of achievement ,not of individual
students, but of a whole education
system or a clearly defined
22. WELL COMEWELL COME
TOTO
Gilgit Baltistan EducationGilgit Baltistan Education
Assessment CentreAssessment Centre
((GBEACGBEAC))
23. • VISSION: Promoting quality learning
among children of Pakistan
• MISSION: To carry out fair and valid
national assessments with the overall
objective of enhancing quality, equity
and access to education
24. FAST FACTSFAST FACTS
• Use of blackboard improves students
learning
• Reward for good work motivates
students
• Majority of students excel in reading
skills
25. • Teaching students at home improves
their achievement
• Corporal punishment in schools did
not improve students achievement