This document discusses the synergies between learning analytics and learning design. Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. Learning design is the intentional design of learning experiences to achieve specific educational goals. When combined, learning analytics and learning design can provide insights to continuously improve learning environments and make them more data-informed.
Jeanviet, le roi du Web (L'indépendant du 5 mars 2017) ;)Jean Baptiste Viet
Le journal L'indépendant m'a interviewé pour que je leur parle du phénomène des créateurs sur YouTube et notamment de l'émergence des chaînes de vulgarisation du savoir.
Jeanviet, le roi du Web (L'indépendant du 5 mars 2017) ;)Jean Baptiste Viet
Le journal L'indépendant m'a interviewé pour que je leur parle du phénomène des créateurs sur YouTube et notamment de l'émergence des chaînes de vulgarisation du savoir.
A brand guideline I have created for Modeshift - not for profit membership organisation funded by the public, private and community sectors in the United Kingdom for promoting active and sustainable travel. I was also involved in designing of their identity.
Can predictive learning analytics empower teachers to support students at risk? Can they enhance students' performance? A large scale study @TheOpenUniversity, UK.
Presenters: Beth Thornton, Mary Ann Cullen.
Presented at the Georgia Libraries Conference in Columbus, GA on 10/04/2017.
In this presentation learn about one librarian’s success and lessons learned while creating, delivering, and marketing her successful information literacy webinar series.
The Science of a Great Career in Data ScienceKate Matsudaira
A data scientist's job is all about details, but a data scientist's career path is much more ambiguous. When you're working in a hot, brand new field, the traditional career ladder just doesn't apply.
So how do you succeed when there is no clear path for success? How can you be amazing at your job when "amazing" is still being defined? It starts with knowing exactly why your job is so different from others (there are no right answers), and learning how to explain your complicated work in an uncomplicated way.
In this talk, you'll learn how to achieve success by leveraging your unique role to create the career you really want.
A brand guideline I have created for Modeshift - not for profit membership organisation funded by the public, private and community sectors in the United Kingdom for promoting active and sustainable travel. I was also involved in designing of their identity.
Can predictive learning analytics empower teachers to support students at risk? Can they enhance students' performance? A large scale study @TheOpenUniversity, UK.
Presenters: Beth Thornton, Mary Ann Cullen.
Presented at the Georgia Libraries Conference in Columbus, GA on 10/04/2017.
In this presentation learn about one librarian’s success and lessons learned while creating, delivering, and marketing her successful information literacy webinar series.
The Science of a Great Career in Data ScienceKate Matsudaira
A data scientist's job is all about details, but a data scientist's career path is much more ambiguous. When you're working in a hot, brand new field, the traditional career ladder just doesn't apply.
So how do you succeed when there is no clear path for success? How can you be amazing at your job when "amazing" is still being defined? It starts with knowing exactly why your job is so different from others (there are no right answers), and learning how to explain your complicated work in an uncomplicated way.
In this talk, you'll learn how to achieve success by leveraging your unique role to create the career you really want.
The 2011 edition of The National Biometrics Challenge updates the 2006 National Science and Technology Council (NSTC) report of the same name. This new report provides an overview of current challenges related to strengthening the scientific foundation of biometrics and improving identity-management system capabilities. It clarifies biometrics-related priorities for Federal agencies and provides context for non-governmental entities considering collaborations with agencies as private-sector partners. This report’s recommendations are based on analyses provided in two key National Research Council reports, a National Science Foundation workshop and two workshops organized by the NSTC Subcommittee on Biometrics and Identity Management specifically designed to gather input for this report.
A guide for adolescents who are undertaking Internet-based research, to help them decide which websites are worth saving (whether to their browser's favourites or within a social bookmarking utility).
Data Modelling is an important tool in the toolbox of a developer. By building and communicating a shared understanding of the domain they're working with, their applications and APIs are more useable and maintainable. However, as you scale up your technical teams, how do you keep these benefits whilst avoiding time-consuming meetings every time something new comes along? This talk reminds ourselves of key data modelling technique and how our use of Kafka changes and informs them. It then examines how these patterns change as more teams join your organisation and how Kafka comes into its own in this world.
Organizations are loathe to accept that a rewrite is the only solution for modernizing a legacy application. After much analysis, discussions, deliberations, the decision is to demonolith the monolith!
Conceptually simple but often not feasible, the architecture, design, and implementation decisions makes it all but impossible to refactor-in-place and arrive at your destination.
Economic Development 411 | 2015 | Dustin HaislerOne Columbus
Dustin Haisler, chief innovation officer of e.Republic, works with Fortune 500 companies, government agencies, academia and nonprofits on innovation and engagement strategies. As the finance director and CIO for Manor, TX, a small city outside Austin, Haisler quickly built a track record and reputation as an early innovator in civic tech. Haisler pioneered government use of commercial technologies not before used in the public sector.
Evidence Based Decision Making in the Classroom Panelalywise
Slides from Daltai-supported seminar to explore the role of continuous professional development in supporting staff & student engagement with learning analytics.
Data Archeology - A theory- and context-informed approach to analyzing data t...alywise
Theoretical overview and two examples of Data Archeology - a need to deeply understand context and engage in ground-truthing when analyzing large sets of digital data.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
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.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
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.
4. Sub UniquePostsRead()
For k = 1 To MaxUser Step 1
RowCount = Range("A1").CurrentRegion.Rows.Count
For w = 1 to MaxWeek Step 1
StartTime = Sheets("Week").Cells(w + 1, 2)
EndTime = Sheets("Week").Cells(w + 1, 3)
PostNum = 0
PostsIndex = 0
Do While Cells(i, datestamp) <= EndTime And i <= RowCount
If Cells(i, Source) = “Read" Then
If Cells(i, Message_Author) <> Val(ActiveSheet.Name)
And Cells(i, Scan) <> "X" Then
flag = 0
For j = 1 To PostsIndex Step 1
If Posts(j) = Cells(i, Message_Id) Then
flag = 1
j = PostsIndex
End If
Next j
If flag = 0 Then
PostsIndex = PostsIndex + 1
Posts(PostsIndex) = Cells(i, Message_Id)
End If
End If
End If
Sheets(“Stats").Cells(Line, 22) = PostsIndex
Next w
Next k
End Sub
PercentPostsRead =SUniquePostsRead
TotalPostNumber
9. THE COLLECTION AND
ANALYSIS OF DATA
TRACES RELATED TO
LEARNING IN ORDER TO
INFORM AND IMPROVE
THE PROCESS AND/OR
ITS OUTCOMES
( S I E M E N S E T A L . , 2 0 1 1 )
LEARNING
ANALYTICS
10. “[LEARNING] ANALYTICS
EXIST AS PART OF A SOCIO-
TECHNICAL SYSTEM WHERE
HUMAN DECISION-MAKING
AND CONSEQUENT ACTIONS
ARE AS MUCH A PART OF
ANY SUCCESSFUL ANALYTICS
SOLUTION AS THE
TECHNICAL COMPONENTS”
V A N H A R M E L E N & W O R K M A N ( 2 0 1 2 )
LEARNING
ANALYTICS
27. Adding a linguistic filter to the discussion forums would
let students and instructors focus on only content-related
discussion when they wanted to.
This could reduce the number of threads to look at by
HALF and increase the hit rate from ~40% to 80%.
28. L E A R N I N G A N A LY T I C S &
L E A R N I N G D E S I G N S Y N E R G Y
# 3
CHECK
ASSUMPTIONS
29. E X P E C T E D I N T E R A C T I V E
D I S C U S S I O N P A T T E R N
( B A S E O N B L E N D E D C L A S S )
A C T U A L D I S C U S S I O N
P A T T E R N F O R F U L L Y
O N L I N E C O U R S E
F R O M B R O O K S , G R E E R & G U T W I N ( 2 0 1 4 ) T H E D A T A - A S S I S T E D A P P R O A C H T O
B U I L D I N G I N T E L L I G E N T T E C H N O L O G Y E N H A N C E D L E A R N I N G E N V I R O N M E N T S .
30. Image Credit: Pedro Figueiredo via Flickr (CC BY 2.0), adapted
O N E S I Z E
D O E S N ’ T
F I T A L L
32. L E A R N I N G A N A LY T I C S &
L E A R N I N G D E S I G N S Y N E R G Y
# 4
GUIDE
INSTRUCTOR
INQUIRY
33. Image Credit: Nicolas Raymond’s Grunge Warning Sign via Flickr (CC BY 2.0), adapted
FROM ANALYTICS-DRIVEN INTERVENTION
TO ANALYTICS-INFORMED IMPROVEMENTS
34. FROM ANALYTICS-DRIVEN INTERVENTION
A
A’
A A’’
POINT-IN-TIME
INTERRUPTIONS TO
ADDRESS PROBLEMS
PRODUCTIVE ONGOING
ADJUSTMENTS TO
TEACHING & LEARNING
TO ANALYTICS-INFORMED IMPROVEMENTS
39. Starburst
A Graphical Discussion Forum with
Embedded & Extracted Analytics
Metric Your Data
(Week X)
Class
Average
(Week X)
% of posts read 72% 87%
% of real reads
41% 66%
Av. length of
real reads
2.37m 4.12m
#of reviews of
own posts
22 13
#of reviews of
others’ posts
8 112
41. INTEGRATING STUDENT USE OF
ANALYTICS AS PART OF
LEARNING PRACTICES IN A
PRINCIPLED WAY OFFERS EXCITING
OPPORTUNITIES TO HELP
STUDENTS BECOME
PURPOSEFUL ABOUT THEIR
LEARNING BASED ON DATA-
INFORMED DECISIONS
42. S U M M A R Y O F ( J U S T S O M E )
S Y N E R G I E S B E T W E E N L E A R N I N G
A N A L Y T I C S & L E A R N I N G D E S I G N
- C O L L E C T S M A R T E R D A T A
- C H E C K A S S U M P T I O N S
- I D E N T I F Y C R I T I C A L P A T T E R N S
- G U I D E I N S T R U C T O R I N Q U I R Y
- S T U D E N T S E L F - R E G U L A T I O N
43. S O M E T H I N G S T O
K E E P I N M I N D
C H A L L E N G E S O F B O T H
I N T E R P R E TA T I O N & A C T I O N
P R I N C I P L E S O F
C O O R D I N A T I O N , C O M P A R I S O N
& C U S T O M I Z A T I O N
44. F O R F U R T H E R R E A D I N G
Wise, A. F. & & Vysatek, J. M. (in review). Learning analytics implementation
design. Handbook of learning analytics and educational data mining.
Brooks, C., Greer, J. & Gutwin, C. (2014). The data-assisted approach to building
intelligent technology enhanced learning environments. In J. Larusson & B. White
Eds. Learning analytics: From research to practice (pp123-156). NY: Springer.
Marbouti, F., & Wise, A. F. (2016). Starburst: a new graphical interface to support
purposeful attention to others’ posts in online discussions. Educational Technology
Research and Development, 64(1), 87-113.
Winne, P. H., & Hadwin, A. F. (2013). nStudy: Tracing and supporting self-regulated
learning in the Internet. In The international handbook of metacognition and learning
technologies (pp. 293-308). Springer New York.
Wise, A. F., Cui, Y. & Vysatek, J. M. (in press). Bringing order to chaos in MOOC
discussion forums with content-related thread identification. To appear in the
Proceeding of the International Conference on Learning Analytics and Knowledge.
45. E V E N F U R T H E R R E A D I N G
Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing pedagogical action:
Aligning learning analytics with learning design. American Behavioral Scientist,
57(10), 1439-1459.
Persico, D., & Pozzi, F. (2015). Informing learning design with learning analytics to
improve teacher inquiry. British Journal of Educational Technology, 46(2), 230-248.
van Leeuwen, A. (2015). Learning analytics to support teachers during synchronous
CSCL: balancing between overview and overload. Journal of Learning Analytics, 2(2),
138-162.
Wise, A. F. Vysatek, J. M., Hausknecht, S. N. & Zhao, Y. (in press). Developing learning
analytics design knowledge in the “middle space”: The student tuning model and
align design framework for learning analytics use. To appear in Online Learning.
Wise, A. F., Zhao, Y. & Hausknecht, S. N. (2014). Learning analytics for online
discussions: Embedded and extracted approaches. Journal of Learning Analytics,
1(2), 48-71.
data can come from digital or physical environments
High Inference to Low Inference – remove the black box of guessing what data means
High Inference to Low Inference – remove the black box of guessing what data means
From Chris Brooks:
“And one final parting thought: as you try to roll out a learning analytics system institution wide you immediately run into the issue that many (every?) class is unique because they use the resources differently. Rarely do higher ed institutions move with one mind as to how the LMS and supporting tools should be integrated into teaching and curriculum. And this throws off all of the coefficients for regression models and prior probabilities for bayesian models. Isn't this "complexity" in a raw form?”
From Rebecca Ferguson:
“At Open-UK we are interested in relating learning design to learning analytics. A forum may be used for collaboration, for conversation, for resource sharing, for reflection, for socialising with people on the course or for questioning tutors. Sometimes a course has a forum, but nobody has really thought about why and how learners will use it. Unless you know what the educational purpose of a tool (such as a forum) is, it is extremely difficult to make sense of the related data.”
From Wolgang (Freedom of Choice) http://www.greller.eu/wordpress/?p=1868
It still bugs me slightly that gravitating towards a single algorithmic model of pedagogy (as the statistical average performance) may lead to a kind of industrialisation, where everything converges towards a computerised quantification of a single vision, instead of personalisation and diversity.
Opportunities for Synergies Between Learning Analytics and Learning Design
dynamic, responsive, mobile, and learner-controlled sites of learning and engagement. The key to this transformation is the feedback loop provided by learner-generated data.
Takeaways
LA not just about systems and tools but people using them
Start with a problem or an opportunity
For learning design...
Opportunities for Synergies Between Learning Analytics and Learning Design
dynamic, responsive, mobile, and learner-controlled sites of learning and engagement. The key to this transformation is the feedback loop provided by learner-generated data.
Takeaways
LA not just about systems and tools but people using them
Start with a problem or an opportunity
For learning design...
Opportunities for Synergies Between Learning Analytics and Learning Design
dynamic, responsive, mobile, and learner-controlled sites of learning and engagement. The key to this transformation is the feedback loop provided by learner-generated data.
Takeaways
LA not just about systems and tools but people using them
Start with a problem or an opportunity
For learning design...
Opportunities for Synergies Between Learning Analytics and Learning Design
dynamic, responsive, mobile, and learner-controlled sites of learning and engagement. The key to this transformation is the feedback loop provided by learner-generated data.
Takeaways
LA not just about systems and tools but people using them
Start with a problem or an opportunity
For learning design...