This document discusses the architecture of an educational data system that allows for comprehensive collection and analysis of student data from multiple sources. It includes a single sign-on identity management system, operational data store to combine and unify real-time data, data warehouse to store historical and accountability data, and analytics tools to power dashboards and reporting. The system provides a unified student identifier and secure data sharing between state, district, and application systems.
SharePoint and CRM are often used side by side in organisations. In some cases they have similar functions, and with some configuration you could bend one to work a bit like the other. Where do you draw the line? This presentation covers my take on this topic.
Talk on Algorithmic Bias given at York University (Canada) on March 11, 2019. This is a shorter version of an interactive workshop presented at University of Minnesota, Duluth in Feb 2019.
SharePoint and CRM are often used side by side in organisations. In some cases they have similar functions, and with some configuration you could bend one to work a bit like the other. Where do you draw the line? This presentation covers my take on this topic.
Talk on Algorithmic Bias given at York University (Canada) on March 11, 2019. This is a shorter version of an interactive workshop presented at University of Minnesota, Duluth in Feb 2019.
Artificial Intelligence (AI) in Education.pdfThiyagu K
Artificial intelligence (AI) is rapidly transforming the education industry. AI-powered tools and applications are being used to personalize learning, provide real-time feedback, and automate tasks, freeing up teachers to focus on more creative and strategic work. This presentation explores the many ways that AI is being used in education today, and how it is poised to revolutionize the way we learn and teach.
This presentation is intended for anyone interested in learning more about the role of AI in education. The target audience includes educators, students, parents, policymakers, and anyone else who is curious about how AI is changing the way we learn.
Software evolution research is a thriving area of software engineering research. Recent years have seen a growing interest in variety of evolution topics, as witnessed by the growing number of publications dedicated to the subject. Without attempting to be complete, in this talk we provide an overview of emerging trends in software evolution research, such as extension of the traditional boundaries of software, growing attention for social and socio-technical aspects of software development processes, and interdisciplinary research applying research techniques from other research areas to study software evolution, and software evolution research techniques to other research areas. As a large body of software evolution research is empirical in nature, we are confronted by important challenges pertaining to reproducibility of the research, and its generalizability.
ML practitioners and advocates are increasingly finding themselves becoming gatekeepers of the modern world. The models you create have power to get people arrested or vindicated, get loans approved or rejected, determine what interest rate should be charged for such loans, who should be shown to you in your long list of pursuits on your Tinder, what news do you read, who gets called for a job phone screen or even a college admission... the list goes on. My goal in this talk is to summarize the kinds of disparate outcomes that are caused by cargo cult machine learning, and recent academic efforts to address some of them.
Technology for everyone - AI ethics and BiasMarion Mulder
Slides from my talk at #ToonTechTalks on 27 september 2018
We all see the great potential AI is bringing us. But is it really bringing it to everyone? How are we ensuring under-represented groups are included and vulnerable people are protected? What to do when our technology is unintended biased and discriminating against certain groups. And what if the data and AI is correct, but the by-effect of it is that some groups are put at risk? All questions we need to think about when we are advancing technology for the benefit of humanity.
Sharing what I've learned from my work in diversity, digital and from following great minds in this field such as Joanna Bryson, Virginia Dignum, Rumman Chowdhury, Juriaan van Diggelen, Valerie Frissen, Catelijne Muller, and many more.
Coping with Data Variety in the Big Data Era: The Semantic Computing ApproachAndre Freitas
Big Data is based on the vision of providing users and applications with a more complete picture of the reality supported and mediated by data. This vision comes with the inherent price of data variety, i.e. data which is semantically heterogeneous, poorly structured, complex and with data quality issues. Despite the hype on technologies targeting data volume and velocity, solutions for coping with data variety remain fragmented and with limited adoption. In this talk we will focus on emerging data management approaches, supported by semantic technologies, to cope with data variety. We will provide a broad overview of semantic computing approaches and how they can be applied to data management challenges within organizations today. This talk will allow the audience to have a glimpse into the next-generation, Big Data-driven information systems.
This is a CIDR 2009 presentation. See http://infoblog.stanford.edu/ for more information and http://www-db.cs.wisc.edu/cidr/cidr2009/program.html for downloads.
Presentation given by Evan Estola (Meetup, New-York) at the Big Data & Society conference held at RTBF on 13 Dec 2016. Main topic was the design of recommendation algorithms and how to make them ethical
Making light work of data- improving the UX of data rich interfaces- UX Austr...Stephen Hall
Not so long ago, back in the days of brochure ware online, we used to be glad just to see live data dished up in web sites. It was real, it was (sometimes) up to date, even if it was also inevitably dry, dense and tabular, and was often only there to be looked at. Those of us making web sites then didn’t have too many data presentation options; our challenge was usually just to make it as clean and fast loading as possible.
How we have moved on! These days, the web browser is a window onto a sea of rich data. Now, we expect to be able to understand it, personalise how we view it, add our own input to it and transact with it. At the same time, the volume of what is available threatens to overwhelm us. In short, the User Experience of data has changed completely.
Public and private sector organisations are increasingly willing and able to expose aspects of their data both internally and externally, and are using the web as a key channel to do so. Looking internationally we are starting to see pressure on governments to ‘open source’ key data holdings to allow organisations, community groups and individuals to re-use it creatively and in ways that government owners would never imagine. The reality is that User Experience designers and Information Architects are more and more likely to be dealing regularly with the challenges of rich data presentation.
This talk examines some approaches to the analysis and presentation of rich data sets on the web.
Drawing on the presenter’s own direct experiences from large scale projects in the pharmaceutical, educational, aged care and consumer advocacy sectors.
Healthcare Best Practices in Data Warehousing & AnalyticsDale Sanders
This is from a class lecture that I gave in 2005. Rather dated, but 95% of content is still very relevant today, which is a bit unfortunate. That's an indication of how little we've progressed in the healthcare domain.
Omosola Odetunde - Fantastic Data and Where to Find Them: The Importance of K...Codemotion
ML applications are expanding at a rapid rate as we now leverage pre-trained models and ML APIs from the likes of Google, Amazon, IBM, and Microsoft. Innovation comes with risk, however. By heavily depending on these trained models/transfer learning, applications are also heavily dependent on the data on which these models were trained, for better or for worse. Often times, these models can freeze bias and ensure your application under-serves many of your users. We will discuss the data which backs these models, how they were constructed, who and what is missing, and important effects.
This is the presentation for the keynote I delivered at Global AI Nights in Redmond in September 2019. It is about the main use cases businesses can use today to transform their business with AI.
Artificial Intelligence (AI) in Education.pdfThiyagu K
Artificial intelligence (AI) is rapidly transforming the education industry. AI-powered tools and applications are being used to personalize learning, provide real-time feedback, and automate tasks, freeing up teachers to focus on more creative and strategic work. This presentation explores the many ways that AI is being used in education today, and how it is poised to revolutionize the way we learn and teach.
This presentation is intended for anyone interested in learning more about the role of AI in education. The target audience includes educators, students, parents, policymakers, and anyone else who is curious about how AI is changing the way we learn.
Software evolution research is a thriving area of software engineering research. Recent years have seen a growing interest in variety of evolution topics, as witnessed by the growing number of publications dedicated to the subject. Without attempting to be complete, in this talk we provide an overview of emerging trends in software evolution research, such as extension of the traditional boundaries of software, growing attention for social and socio-technical aspects of software development processes, and interdisciplinary research applying research techniques from other research areas to study software evolution, and software evolution research techniques to other research areas. As a large body of software evolution research is empirical in nature, we are confronted by important challenges pertaining to reproducibility of the research, and its generalizability.
ML practitioners and advocates are increasingly finding themselves becoming gatekeepers of the modern world. The models you create have power to get people arrested or vindicated, get loans approved or rejected, determine what interest rate should be charged for such loans, who should be shown to you in your long list of pursuits on your Tinder, what news do you read, who gets called for a job phone screen or even a college admission... the list goes on. My goal in this talk is to summarize the kinds of disparate outcomes that are caused by cargo cult machine learning, and recent academic efforts to address some of them.
Technology for everyone - AI ethics and BiasMarion Mulder
Slides from my talk at #ToonTechTalks on 27 september 2018
We all see the great potential AI is bringing us. But is it really bringing it to everyone? How are we ensuring under-represented groups are included and vulnerable people are protected? What to do when our technology is unintended biased and discriminating against certain groups. And what if the data and AI is correct, but the by-effect of it is that some groups are put at risk? All questions we need to think about when we are advancing technology for the benefit of humanity.
Sharing what I've learned from my work in diversity, digital and from following great minds in this field such as Joanna Bryson, Virginia Dignum, Rumman Chowdhury, Juriaan van Diggelen, Valerie Frissen, Catelijne Muller, and many more.
Coping with Data Variety in the Big Data Era: The Semantic Computing ApproachAndre Freitas
Big Data is based on the vision of providing users and applications with a more complete picture of the reality supported and mediated by data. This vision comes with the inherent price of data variety, i.e. data which is semantically heterogeneous, poorly structured, complex and with data quality issues. Despite the hype on technologies targeting data volume and velocity, solutions for coping with data variety remain fragmented and with limited adoption. In this talk we will focus on emerging data management approaches, supported by semantic technologies, to cope with data variety. We will provide a broad overview of semantic computing approaches and how they can be applied to data management challenges within organizations today. This talk will allow the audience to have a glimpse into the next-generation, Big Data-driven information systems.
This is a CIDR 2009 presentation. See http://infoblog.stanford.edu/ for more information and http://www-db.cs.wisc.edu/cidr/cidr2009/program.html for downloads.
Presentation given by Evan Estola (Meetup, New-York) at the Big Data & Society conference held at RTBF on 13 Dec 2016. Main topic was the design of recommendation algorithms and how to make them ethical
Making light work of data- improving the UX of data rich interfaces- UX Austr...Stephen Hall
Not so long ago, back in the days of brochure ware online, we used to be glad just to see live data dished up in web sites. It was real, it was (sometimes) up to date, even if it was also inevitably dry, dense and tabular, and was often only there to be looked at. Those of us making web sites then didn’t have too many data presentation options; our challenge was usually just to make it as clean and fast loading as possible.
How we have moved on! These days, the web browser is a window onto a sea of rich data. Now, we expect to be able to understand it, personalise how we view it, add our own input to it and transact with it. At the same time, the volume of what is available threatens to overwhelm us. In short, the User Experience of data has changed completely.
Public and private sector organisations are increasingly willing and able to expose aspects of their data both internally and externally, and are using the web as a key channel to do so. Looking internationally we are starting to see pressure on governments to ‘open source’ key data holdings to allow organisations, community groups and individuals to re-use it creatively and in ways that government owners would never imagine. The reality is that User Experience designers and Information Architects are more and more likely to be dealing regularly with the challenges of rich data presentation.
This talk examines some approaches to the analysis and presentation of rich data sets on the web.
Drawing on the presenter’s own direct experiences from large scale projects in the pharmaceutical, educational, aged care and consumer advocacy sectors.
Healthcare Best Practices in Data Warehousing & AnalyticsDale Sanders
This is from a class lecture that I gave in 2005. Rather dated, but 95% of content is still very relevant today, which is a bit unfortunate. That's an indication of how little we've progressed in the healthcare domain.
Omosola Odetunde - Fantastic Data and Where to Find Them: The Importance of K...Codemotion
ML applications are expanding at a rapid rate as we now leverage pre-trained models and ML APIs from the likes of Google, Amazon, IBM, and Microsoft. Innovation comes with risk, however. By heavily depending on these trained models/transfer learning, applications are also heavily dependent on the data on which these models were trained, for better or for worse. Often times, these models can freeze bias and ensure your application under-serves many of your users. We will discuss the data which backs these models, how they were constructed, who and what is missing, and important effects.
This is the presentation for the keynote I delivered at Global AI Nights in Redmond in September 2019. It is about the main use cases businesses can use today to transform their business with AI.
The Student Data Privacy Manifesto begins a reasonable conversation among parents, education leaders, and technology providers on the future of student data privacy protection and transparency.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
SEA Architecture
1. Demographic
Assessments
At Risk, SPED, Intervention
Grades, Behavior, Other
Teachers
Single Pane of Glass
Comprehensive Data
Behavioral
Authentication
Administration
Storage
User
Experience
State
Assessments
Authentication
Administration
Storage
User
Experience
Grades
Authentication
Administration
Storage
User
Experience
Local
Assessments
Authentication
Administration
Storage
User
Experience
SPED
Authentication
Administration
Storage
User
Experience
Demographic
Authentication
Administration
Storage
User
Experience
Other
Unstructured
These are real
words that will not
cause any red
squiggly lines in
the automatic spell
checker program
Sometimes I say
to myself, self
what are you
doing?
These are real
words that will not
cause any red
squiggly lines in
the automatic spell
checker program
Sometimes I say
to myself, self
what are you
doing?
These are real
words that will not
cause any red
squiggly lines in
the automatic spell
checker program
Sometimes I say
to myself, self
what are you
doing?
It started with a vision…
3. … that led to a system architecture
3
Secure State Infrastructure
Unique Person ID
System
Accountability
DataMart
BI Analytics Tools
District Systems
Student
Information
System
Student
Information
System
Student
Information
System
Student
Information
Systems
EDFacts
Files
EDFacts
Files
EDFacts
Files
EDFacts
Files
EDFacts
Files
State
Reports
State
Reports
State
Reports
Student
Information
System
Student
Information
System
Student
Information
System
HR
Systems
Student
Information
System
Student
Information
System
Student
Information
System
Assessment
Systems
Student
Information
System
Student
Information
System
Student
Information
System
Other
Systems
e.g. EasyIEP
Granular data flows
from districts and
other sources
transactionally or
in bulk uploads
Operational Data
Store (ODS)
ODS combines and
unifies current data from
different sources
Student
Performance
Dashboards
Dashboards drive student-
level decision making for
teachers and administators
DataWarehouse
(DW)
Transfer student data
automatically flows to
the new school upon
enrollment
Unique identity is
maintained throughout
the system
Unified and validated data
moves to thedata warehouse
Snapshots of data and
aggregates arecaptured for
accountability reporting
Warehouseholds
Near-real-timeoperational data
Historical/longitudinal data
Accountability data
KPIs
Single Sign-On
Identity Management System
Data on a person’s
roles and
assignments and the
students they teach
determine access to
application and data
Transactional
Web Service
Interface
Bulk Data
Interface
UniquePerson ID
Web Service
Student Data
Record Transfer
Service
Analytics
Views
4. … with a bold generative API approach
7/27/2014
4
5. … and an unprecedented Azure identity
solution
School Districts with
Tennessee Department of
Education
Identity Synchronization
Cloud Identity Provisioning
Federated Authentication
Federation Hub
Azure Access Control
Server (ACS 2.0)
Claims taken from
Application Database
Active Directory Federation Services
School District
With internal AD Domain
and ADFS
ODS Application
Database (provided by
DLP)
FIM Synchronization
Server
Claims-Aware
Application
State Managed
Azure AD
