Deriving value from analytics requires much more than purchasing technology. University of Kentucky's analytics journey utilized fostering a bottom-up emergent community of practice as well as top-down organizational maneuvers. This presentation shares different aspects of the University of Kentucky score.
Innovation and economic growth depends on company's ability to gain insight into data. However, data is growing exponentially, but our ability to make use of it is not. Untapped economic value resides in this unutilized data, called "dark data." This presentation looks at some of the causes for the explosion of data, some of the impediments preventing exploring and creating business value from dark data; and some ideas for ways around those impediments.
Logistics, Data in Motion and Paradigm Shift of the CIO: The economics and psychology of the flow of information. Advances in IT, especially cloud technologies, are causing a shift in the role of the CIO.
Artificial Intelligence AI in Libraries Training for Innovation WebinarSaid Ali Said
Objectives The objectives of the webinar are to:
• introduce AI in libraries
• describe the IDEA Institute on AI and its contribution to providing professional, innovative training in AI to library and other information professionals
• understand challenges and opportunities in implementing AI in libraries based on real-world experiences of the first cohort of Institute Fellows
• consider equity, diversity, inclusion and accessibility issues, and ethical questions, in AI implementation.
Speakers
Prof. Dr. Dania Bilal
Professor, School of Information Sciences at the University of Tennessee in Knoxville, TN.
Researcher, scholar and educator in Human Information Behavior, Human–Computer Interaction (HCI), User Experience and Design (UXD), Human–AI Interaction, and Information Science Theory.
Research focus is on user information interaction and behavior (children, teenagers and adults) with information systems, products and interfaces; and on user-centered design for better user engagement and experiences.
Principal Investigator and co-developer, IDEA Institute on Artificial Intelligence.
Clara M. Chu
Director and Mortenson Distinguished Professor, Mortenson Center for International Library Programs, University of Illinois at Urbana-Champaign, IL.
• Expert in developing appropriate and strategic solutions to deliver equitable and relevant library services in culturally diverse and dynamic libraries.
• Studies the information needs of culturally diverse communities in a globalized and technological society.
• Co-developer, IDEA Institute on Artificial Intelligence.
Target Audience
• Staff in any type of library and information center or information environment.
• Library and information science students, educators and researchers.
Innovation and economic growth depends on company's ability to gain insight into data. However, data is growing exponentially, but our ability to make use of it is not. Untapped economic value resides in this unutilized data, called "dark data." This presentation looks at some of the causes for the explosion of data, some of the impediments preventing exploring and creating business value from dark data; and some ideas for ways around those impediments.
Logistics, Data in Motion and Paradigm Shift of the CIO: The economics and psychology of the flow of information. Advances in IT, especially cloud technologies, are causing a shift in the role of the CIO.
Artificial Intelligence AI in Libraries Training for Innovation WebinarSaid Ali Said
Objectives The objectives of the webinar are to:
• introduce AI in libraries
• describe the IDEA Institute on AI and its contribution to providing professional, innovative training in AI to library and other information professionals
• understand challenges and opportunities in implementing AI in libraries based on real-world experiences of the first cohort of Institute Fellows
• consider equity, diversity, inclusion and accessibility issues, and ethical questions, in AI implementation.
Speakers
Prof. Dr. Dania Bilal
Professor, School of Information Sciences at the University of Tennessee in Knoxville, TN.
Researcher, scholar and educator in Human Information Behavior, Human–Computer Interaction (HCI), User Experience and Design (UXD), Human–AI Interaction, and Information Science Theory.
Research focus is on user information interaction and behavior (children, teenagers and adults) with information systems, products and interfaces; and on user-centered design for better user engagement and experiences.
Principal Investigator and co-developer, IDEA Institute on Artificial Intelligence.
Clara M. Chu
Director and Mortenson Distinguished Professor, Mortenson Center for International Library Programs, University of Illinois at Urbana-Champaign, IL.
• Expert in developing appropriate and strategic solutions to deliver equitable and relevant library services in culturally diverse and dynamic libraries.
• Studies the information needs of culturally diverse communities in a globalized and technological society.
• Co-developer, IDEA Institute on Artificial Intelligence.
Target Audience
• Staff in any type of library and information center or information environment.
• Library and information science students, educators and researchers.
learning in the digital age looks at the way our students our controlled and constrained by orthodox protocols and methodologies. The presentation challenges conventional beliefs yet grounds the challenge in a 'can do' way. We have to work from within a system in order to be able to change it.
CORE's ten trends presentation from the Learning at School conference in Rotorua, February 2009. CORE's annual ten trends summary represents a view of some key areas of interest for NZ educators with regards to the impact of ICTs on teaching and learning.
ETHICS IN E-LEARNING
Assist.Prof.Dr. Elif TOPRAK – Anadolu University
etoprak1@anadolu.edu.tr
Assist.Prof.Dr. Berrin ÖZKANAL – Anadolu University
Res. Assist.Dr. Sinan AYDIN – Anadolu University
Instructor Seçil KAYA – Anadolu University
TOJET: The Turkish Online Journal of Educational Technology – April 2010, volume 9 Issue 2
CORE publishes its ten trends annually to highlight issues and themes that will impact on the work of educators in early childhood, schools and tertiary institutions in the NZ context.
Forces & Trends Shaping Higher Ed in 2016Kimberly Eke
A closer look at some of the trends closing 2015 and opening 2016 that are shaping the conversations and thinking around higher ed. Presented during the ELI 2016 Annual Meeting Pre-conference Workshop, "Powering the Innovation Engine" held in San Antonio, Texas (2/2/16)
Systemic Learning Analytics Symposium, October 10th 2013Adam Cooper
Slides for the talk "Barriers and Pitfalls to Systemic Learning Analytics" by Adam Cooper, Cetis, for the online Systemic Learning Analytics Symposium, organised by George Siements and held on October 10th 2013.
Related blog post at: http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/
See http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/ for an extended blog post on the subject.
Relief Operations: How to Improve Humanitarian Systems with Smart Analytics &...Haluk Demirkan
Haluk Demirkan, Presentation "Relief Operations: How to Improve Humanitarian Systems with Smart Analytics & Knowledge Management," 84th Civil Affairs “PHOENIX” Battalion Academic Week, Joint Base Lewis-McChord (JBLM), WA, March 2015.
Stratosphere - Learning in a Connected World is a summary of Fullan's book, Stratosphere and the requirement to link pedagogy, technology and change knowledge if the goal is to have system transformation for learning and teaching in the 21st Century.
COVID-19 and the Future of AI in Education and TrainingLewisJohnson34
Slides from the Panel on COVID-19 and the Future of AI in Education and Training, presented at the 21st International Conference on AI in Education, July 8, 2020
Sdal air education workforce analytics workshop jan. 7 , 2014.pptxkimlyman
The American Institutes for Research (AIR) and Virginia Tech are collaborating to explore and develop new approaches to combining, manipulating and understanding big data. The two are also looking at how big data analytics can help answer questions critical to solving issues in education, workforce, health, and human and social development. They held two workshops on January 7 and 27, 2014- the first on Education and Workforce Analytics and the second on Health and Social Development Analytics.
learning in the digital age looks at the way our students our controlled and constrained by orthodox protocols and methodologies. The presentation challenges conventional beliefs yet grounds the challenge in a 'can do' way. We have to work from within a system in order to be able to change it.
CORE's ten trends presentation from the Learning at School conference in Rotorua, February 2009. CORE's annual ten trends summary represents a view of some key areas of interest for NZ educators with regards to the impact of ICTs on teaching and learning.
ETHICS IN E-LEARNING
Assist.Prof.Dr. Elif TOPRAK – Anadolu University
etoprak1@anadolu.edu.tr
Assist.Prof.Dr. Berrin ÖZKANAL – Anadolu University
Res. Assist.Dr. Sinan AYDIN – Anadolu University
Instructor Seçil KAYA – Anadolu University
TOJET: The Turkish Online Journal of Educational Technology – April 2010, volume 9 Issue 2
CORE publishes its ten trends annually to highlight issues and themes that will impact on the work of educators in early childhood, schools and tertiary institutions in the NZ context.
Forces & Trends Shaping Higher Ed in 2016Kimberly Eke
A closer look at some of the trends closing 2015 and opening 2016 that are shaping the conversations and thinking around higher ed. Presented during the ELI 2016 Annual Meeting Pre-conference Workshop, "Powering the Innovation Engine" held in San Antonio, Texas (2/2/16)
Systemic Learning Analytics Symposium, October 10th 2013Adam Cooper
Slides for the talk "Barriers and Pitfalls to Systemic Learning Analytics" by Adam Cooper, Cetis, for the online Systemic Learning Analytics Symposium, organised by George Siements and held on October 10th 2013.
Related blog post at: http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/
See http://blogs.cetis.ac.uk/adam/2013/10/31/policy-and-strategy-for-systemic-deployment-of-learning-analytics-barriers-and-potential-pitfalls/ for an extended blog post on the subject.
Relief Operations: How to Improve Humanitarian Systems with Smart Analytics &...Haluk Demirkan
Haluk Demirkan, Presentation "Relief Operations: How to Improve Humanitarian Systems with Smart Analytics & Knowledge Management," 84th Civil Affairs “PHOENIX” Battalion Academic Week, Joint Base Lewis-McChord (JBLM), WA, March 2015.
Stratosphere - Learning in a Connected World is a summary of Fullan's book, Stratosphere and the requirement to link pedagogy, technology and change knowledge if the goal is to have system transformation for learning and teaching in the 21st Century.
COVID-19 and the Future of AI in Education and TrainingLewisJohnson34
Slides from the Panel on COVID-19 and the Future of AI in Education and Training, presented at the 21st International Conference on AI in Education, July 8, 2020
Sdal air education workforce analytics workshop jan. 7 , 2014.pptxkimlyman
The American Institutes for Research (AIR) and Virginia Tech are collaborating to explore and develop new approaches to combining, manipulating and understanding big data. The two are also looking at how big data analytics can help answer questions critical to solving issues in education, workforce, health, and human and social development. They held two workshops on January 7 and 27, 2014- the first on Education and Workforce Analytics and the second on Health and Social Development Analytics.
Learning analytics and Moodle: So much we could measure, but what do we want to measure? A presentation to the USQ Math and Sciences Community of Practice May 2013
Presentation by Rebecca Ferguson (IET, The Open University, UK) at the Learning Analytics Summer Institute event (LASI Asia) run in Seoul, South Korea, in September 2016. This presentation, on Visions of the Future of learning analytics, is based on work carried out by the European consortium working on the Learning Analytics Community Exchange (LACE) project.
Presentation on learning analytics given by Rebecca Ferguson at the Nordic Learning Analytics Summer Institute (Nordic LASI), organised by the SLATE Centre, in Bergen Norway, 29 September 2017.
Ellen Wagner, Executive Director, WCET.
Putting Data to Work
This session explores changing data sensibilities at US post-secondary institutions with particular attention paid to how predictive analytics are changing expectations for institutional accountability and student success. Results from the Predictive Analytics Reporting Framework show that predictive modeling can identify students at risk and that linking behavioral predictions of risk with interventions to mitigate those risks at the point of need is a powerful strategy for increasing rates of student retention, academic progress and completion.
presentation at the 15th annual SLN SOLsummit February 27, 2014
http://slnsolsummit2014.edublogs.org/
Keynote talk given at the Learning Analytics Summer Institute 2016 (LASI16) at the University of Deusto, Bilbao, Spain in June 2016 by Rebecca Ferguson.
What does the future hold for learning analytics? In terms of Europe’s priorities for learning and training, they will need to support relevant and high-quality knowledge, skills and competences developed throughout lifelong learning. More specifically, they should improve the quality and efficiency of education and training, enhance creativity and innovation, and focus on learning outcomes in areas such as employability, active-citizenship and well-being. This is a tall order and, in order to achieve it, we need to consider how our work fits into the larger picture. Drawing on the outcomes of two recent European studies, Rebecca will discuss how we can avoid potential pitfalls and develop an action plan that will drive the development of analytics that enhance both learning and teaching.
Analytics Goes to College: Better Schooling Through Information Technology wi...bisg
The focus on the tremendous volume of information about target markets that can be gleaned through the use of powerful analytics technology obscures the reality that, much of the time, that information lacks predictive capacity, and can really only provide a very detailed retrospective analysis of behaviors of interest. Vince Kellen discusses the ways that his university has reorganized and deployed their IT resources to acquire better, more useful information -- and, more importantly, how that information can be immediately translated into decisive action.
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.
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.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
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
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
1. Organizing to Ret Analytics RightVince Kellen, Ph.D. Senior Vice Provost, Analytics and TechnologiesVince.Kellen@uky.eduThis is a living document subject to substantial revision! September, 2014
2. Silos
Are recursive
Get reproduced across time
and space reliably, without
effort
Arise naturally due to human
sociological/biological
tendencies
It takes constant effort to
mitigate their adverse effects
Sharing data and analysis
widely requires a
reconceptualization of silo
structures
2
3. Organization dysfunction
Information as power
Defensiveness
Data hoarding
Process separation
Empire building
Excessive control
Fear of scrutiny
Loss of power
3
4. We are competitive animals
Information becomes a [tool, weapon]
We instinctually manage information to enhance our competitiveness
Competition relies on information hiding
IT tools become part of our body
How we personally utilize information is part of our biological heritage. This is hardto change, if at all
4
5. Shift from production concerns to consumption ones
Production
•
Collecting, integrating, cataloging, categorizing, transforming, abstracting, analyzing, model-building, visualization, dashboarding, distributing, publishing. If you build it they will come (hopefully)
Consumption
•
Motivating, collaborating, expressing, integrating, improving action, increasing ambition, desire, recognition. If theybuild it everyonewill come
5
8. A.
Merging of mobile and BI strategy
B.
Merging of IR and BI units
C.
Super high-speed infrastructure
D.
Single analytic value chain
E.
Analytics community of practice
F.
Data transparency
G.
Community sourcing and norming
H.
Community rules of etiquette
8
9. Our Community of Practice Rules of Etiquette
Be safe and secure. Respect the acceptable use of information policies and guidelines the university has in place. Please have
good passwords and secure your laptop, desktop and other devices appropriately. Treat private student and university
information appropriately.
Be collegial. University data is a community asset and a community of people steward the data. Use and share the data with
the best interests of the university community in mind. Since parts of our data analysis environment is designed to allow for
greater transparency, analysis will potentially be able to see other unit data. While we will make private to a unit what absolutely
needs to be private, the way the university runs it's business often involves multiple colleges and units at the same time. Don't
use your access to take unfair advantage of another unit.
Help improve data quality. If you see data that doesn't appear to be correct, let someone know. We have a team of staff
dedicated to helping improve data quality. This team can work with colleges and units on any data entry and data management
processes that might need to be changed to improve data quality.
Be open-minded and inquisitive. Data can be represented in multiple ways at the same time. While the teams are taking great
care to enable multiple views of the data to support the community, you might have a valid and unique perspective. In time, we
can accommodate more ways of looking at the same data while not interfering with other views or taxonomies.
Share. The main benefit from open analytics is the power of a community of analysts learning from each other rather than a few
select individuals hoarding knowledge or access. As the community improves its knowledge and skill with the data, the university
can improve accordingly.
9
10. Organizing IT
Our organizational model makes a big difference. Other universities fail to take advantage of a tool like this for purely political reasons
Making key data transparent to all does not help those who made their living being the data ‘go to’ person
We had to merge two units (Institutional Research and Business Intelligence), losing 1/3 of the staff. This let us hire three data scientists with different analytic backgrounds
The tool let the staff transition their skills
10
11. What we have done and what we would like to do
First steps over the past year
•
Mobile micro-surveys: Learning from the learner. In one year, 134,458 surveys harvested. Survey response rates are holding at about 40%. We can instantly analyze all responses for retention and progression issues
•
Student enrollment, retention, demographics, performance, K-Score, facilities utilization, instructor workload, student revenue and financial aid, student progression and more
•
High speed, in-memory analytics architecture. Lowest level of detail, maximum semantic expressiveness, one- second per click for analyst are key design philosophies
•
Open data and organizational considerations
Coming down the road?
•
Micro-segmentation tool to enhance user and IT productivity, develop personalized mobile student interaction/intervention
•
Models for learner technographics, psychographics, in addition to behaviors, performance, background
•
Advanced way-finding for streaming content like lecture capture
•
Content metadata extraction and learner knowledge discovery
•
Real-time measures of concept engagement and mastery
•
Real-time learner recommendations and support engine
•
Use graphing algorithms to perform more sophisticated degree audit what ifs
11
13. List builder
Iteratively query any/all fields of your choosing, linking in an AND or ORfashion
Combine different lists using SET manipulations
Refresh lists regularly (nightly or otherwise)
Apply the set name as a filter on ALL models
This provides advanced filtering and combining that works regardless of the user interface
Our AA team can build and maintain Lists easily. So can some users
Since lists are refreshed nightly, we can keep track of each time a student (or other entity) as it added or removed from a list
We can develop workflow apps using this. Backend, front-end agnostic
13
16. 2009201020112012201320142015Academic year81012141618202224262830323436 Avg 19109107810716016111836154551551654716214195110916216556Fast/Slow ProgressionStudent headcount850100165Cohort YearFall 2008Fall 2009Fall 2010Fall 2011Fall 2012
List builder visualization example
Found all students who take a lot of classes at one point in their career and then took less classes at another point in their career.
Interpretation: These students start with a bang but fade at the finish
How long did this analysis take? Start to finish with this visualization:
25 minutes
16
18. Identifying smaller segments of students
In addition to our work on difficult student cases, we needed to find a way to reach a ‘murky middle’ group of students
Identify students who are just as likely to come back as they are not
The predicted reenrollment was about 50%
After interventions, the actual enrollment was about 65%
19. The whole enchilada
Personalize learning, learning analytics and IPAS analytics into one real-time architecture
•
Real-time personalized interactions
•
Target on-demand peer tutoring based on student’s profile
•
Deliver micro-surveys and assessments to capture additional information needed to improve personalization
•
Give students academic health indicators that tell students where they can improve in study, engagement, support, etc.
•
Let students opt their parents in to this information so the family can support the student
•
Tailor and target reminder services, avoid over messaging, enable timing of message delivery based on user temporal proclivities, mix and match messages across learning, support and progression areas
•
Allow for open personalized learning
•
How content gets matched to students is psychologically complex
•
Several theories of how humans learn give many insights
•
Students differ in the following abilities and attributes: visual-object, visual-spatial, reasoning, cognitive reflection, need for sensation, need for cognition, various verbal abilities, confidence, persistence, prospective memory, etc.
•
We need an open architecture to promote rapid experimentation, testing and sharing of what works and what doesn’t
University of Kentucky
20. Herding cats
We shared with everyone that we are building the bridge as we walked on it
We established a community of practice and rules of analysis etiquette
We built tailored objects for colleges, let users choose their own front end tool
We relied on word-of-mouth adoption and some teasing-revealing
Guess what happened?
20
21. Top-down versus bottom-up
Doing this top down is like pushing water uphill. Its harder than pushing a rock uphill
The great leader is one who the people say “We did this ourselves”
Consider analytics to be a process of self discovery. Each person has to go through the stages of maturity
Paradoxically, this also requires strong top-down commitment and action! Organizational maneuvers like reorganizations are [normally] required
21