How can Learning Analytics be used to bring about the true revolution traditionally assumed for MOOCs? With audiences in the thousands of users, the key is massive personalization, and Learning Analytics privide an ideal paradigm for this.
Bringing Teachers, Students and Learning Resources Contextually Closerfzablith
Traditionally, classrooms have been the major channels of interaction between teachers and students. With the advancements in internet, social media and mobile technologies, learning environments are becoming more enriched with sophisticated interaction and a wealth of online learning material. While this offers a range of improvements, it is posing a set of challenges for educators to accommodate such changes to the benefit of their students. One particular problem is that current teachers are not well equipped with tools to guide students towards the discovery of learning material relevant to the context of their course. For example while it is easy in a classroom to discuss how a video connects to a topic or learning activity within a course, it is much harder to infer such cognitive connections in an online environment. We believe that one of the major bottlenecks is the lack of explicit context alignment between teachers, students and learning resources. We propose using semantic technologies to elicit the contexts in learning environments, and provide the means for teachers to better orchestrate the delivery of their learning concepts in classrooms. We discuss in this seminar a plan to build semantic graphs (i.e. knowledge graphs or maps) to connect existing courses, learning material and other entities involved in leaning environments. This work contributes to enhancing personalized learning, and empowering educators to have better control over learning resources to support their teaching duties.
Let me intervene. . Influencing a learning environment through analyticsAbelardo Pardo
Presentation given at the 8th JTEL Summer School held in May 2012 in Estoril. The hands-on workshop presented a description of Learning Analytics and then participants loaded two data sets into a statistical tool and manipulate them to deduce potential interventions
Analytics to understand learning environmentsAbelardo Pardo
Seminar for the CHAI Group at The University of Sydney. A summary of the initiatives I have worked on in the past years plus a brief account of my current work.
Connecting Pedagogical Intent with Analytics in a Flipped ClassroomAbelardo Pardo
Description of how to use learning analytics techniques to collect evidence about student engagement while preparing a flipped classroom. A case study is presented in which students interact with various electronic resources and a measure of such engagement is produced and returned to them.
Active learning methods are known to improve academic achievement. Flipped learning takes advantage of preparation activities to increase student engagement. But how do we approach the design of such experiences?
Bringing Teachers, Students and Learning Resources Contextually Closerfzablith
Traditionally, classrooms have been the major channels of interaction between teachers and students. With the advancements in internet, social media and mobile technologies, learning environments are becoming more enriched with sophisticated interaction and a wealth of online learning material. While this offers a range of improvements, it is posing a set of challenges for educators to accommodate such changes to the benefit of their students. One particular problem is that current teachers are not well equipped with tools to guide students towards the discovery of learning material relevant to the context of their course. For example while it is easy in a classroom to discuss how a video connects to a topic or learning activity within a course, it is much harder to infer such cognitive connections in an online environment. We believe that one of the major bottlenecks is the lack of explicit context alignment between teachers, students and learning resources. We propose using semantic technologies to elicit the contexts in learning environments, and provide the means for teachers to better orchestrate the delivery of their learning concepts in classrooms. We discuss in this seminar a plan to build semantic graphs (i.e. knowledge graphs or maps) to connect existing courses, learning material and other entities involved in leaning environments. This work contributes to enhancing personalized learning, and empowering educators to have better control over learning resources to support their teaching duties.
Let me intervene. . Influencing a learning environment through analyticsAbelardo Pardo
Presentation given at the 8th JTEL Summer School held in May 2012 in Estoril. The hands-on workshop presented a description of Learning Analytics and then participants loaded two data sets into a statistical tool and manipulate them to deduce potential interventions
Analytics to understand learning environmentsAbelardo Pardo
Seminar for the CHAI Group at The University of Sydney. A summary of the initiatives I have worked on in the past years plus a brief account of my current work.
Connecting Pedagogical Intent with Analytics in a Flipped ClassroomAbelardo Pardo
Description of how to use learning analytics techniques to collect evidence about student engagement while preparing a flipped classroom. A case study is presented in which students interact with various electronic resources and a measure of such engagement is produced and returned to them.
Active learning methods are known to improve academic achievement. Flipped learning takes advantage of preparation activities to increase student engagement. But how do we approach the design of such experiences?
Extending Course Level Learning Analytics with Linked DataAbelardo Pardo
Presentation at the Learning Analytics and Linked Data workshop held at the International Conference on Learning Analytics and Linked Data 2012 Vancouver, BC, April/May 2012
Technology for Active and Personalised Engineering EducationAbelardo Pardo
What type of educational technology is better suited for engineering education? What are the possible improvements? In this talk I present how educational technology can be used to improve engineering education and provide some samples of my past and current research.
Analytics for decision making in Learning EnvironmentsAbelardo Pardo
Presentation given at the IARU EdTech Horizons Workshop about learning analytics, the main stages in the process, some examples, and finally, how to approach it from the institutional and course level.
Presentation Delivered on 21st May 2012. The National Conference on ICT in Education.
Theme: formulating a viable national policy framewor for ICT in education.
Oraganised by Federal Ministry of Education
The higher education ministry of Malaysia has set forth new initiatives as part of its effort to cultivate holistic, entrepreneurial and balanced graduates to be globally competitive and meet the needs of Industry 4.0. Minister Datuk Seri Idris Jusoh said that the ministry has introduced a range of initiatives such as the integrated cumulative grade point average (iCGPA), in addition to its existing academic-driven CGPA system, the 2u2i Programme and CEO@Faculty Programme, to address the challenges and critical needs of Industry 4.0.
What if we could observe all events in a learning environment?Abelardo Pardo
If we could observe all the events in a learning environment, even the most hidden ones, what kind of interventions would become feasible? The presentation finishes with a workshop to manipulate a dataset with R.
Learning and Behavioral Analytics From concept to realityAbelardo Pardo
How can learning analytics be taken from its design to its deployment in an educational institution? What are the issues, limitations, strategies? This presentation includes a descirption of Learning Analytics, examples, how to tackle systemic deployment and suggestions on how to build institutional capacity.
Feedback at scale with a little help of my algorithmsAbelardo Pardo
Talk exploring how to use data to provide scalable feedback in learning experiences. The solutions explored propose the use of algorithms to enhance how humans instructors provide feedback to students more effectively
Presentation at Association of MBAs (AMBA) 2014 Asia-Pacific Conference for Deans and Directors on the topic of Massive Online Open Courses (MOOC) and Technology-Enabled Education
Using OnTask for Student Coaching in Large Student CohortsAbelardo Pardo
The provision of student feedback is a challenging and resource intensive
task for any instructor but at the same time it has the potential of
significantly improve the overall quality of a learning experience.
This challenge is magnified even further in the context of large student
cohorts. Current initiatives such as the one captured by the OnTask project
have explored how to use data about student engagement to support instructors
of large student cohorts in this process. But despite the use of technology
there are still important aspects to consider. What is the ideal tone of the
message? Should they focus on the material? Assessments? Strategies? How
often is idea to send these messages? In this talk we will cover some
principles and examples of how instructors are addressing the problem.
Using data to provide personalised feedback at scaleAbelardo Pardo
The current state of higher education has increasing pressure over academics to offer high quality experience at scale. But what could be the actions that can be deployed to achieve this increase? What would be a good guiding principle to decide these actions? In this talk we explore first the possibility of using feedback and a coach mentality to provide student support, and then how data can help us scale that technique. There are examples of potential scenarios to deploy this at the level of a course, program or overall student experience.
More Related Content
Similar to Pushing the MOOC envelope with Learning Analytics
Extending Course Level Learning Analytics with Linked DataAbelardo Pardo
Presentation at the Learning Analytics and Linked Data workshop held at the International Conference on Learning Analytics and Linked Data 2012 Vancouver, BC, April/May 2012
Technology for Active and Personalised Engineering EducationAbelardo Pardo
What type of educational technology is better suited for engineering education? What are the possible improvements? In this talk I present how educational technology can be used to improve engineering education and provide some samples of my past and current research.
Analytics for decision making in Learning EnvironmentsAbelardo Pardo
Presentation given at the IARU EdTech Horizons Workshop about learning analytics, the main stages in the process, some examples, and finally, how to approach it from the institutional and course level.
Presentation Delivered on 21st May 2012. The National Conference on ICT in Education.
Theme: formulating a viable national policy framewor for ICT in education.
Oraganised by Federal Ministry of Education
The higher education ministry of Malaysia has set forth new initiatives as part of its effort to cultivate holistic, entrepreneurial and balanced graduates to be globally competitive and meet the needs of Industry 4.0. Minister Datuk Seri Idris Jusoh said that the ministry has introduced a range of initiatives such as the integrated cumulative grade point average (iCGPA), in addition to its existing academic-driven CGPA system, the 2u2i Programme and CEO@Faculty Programme, to address the challenges and critical needs of Industry 4.0.
What if we could observe all events in a learning environment?Abelardo Pardo
If we could observe all the events in a learning environment, even the most hidden ones, what kind of interventions would become feasible? The presentation finishes with a workshop to manipulate a dataset with R.
Learning and Behavioral Analytics From concept to realityAbelardo Pardo
How can learning analytics be taken from its design to its deployment in an educational institution? What are the issues, limitations, strategies? This presentation includes a descirption of Learning Analytics, examples, how to tackle systemic deployment and suggestions on how to build institutional capacity.
Feedback at scale with a little help of my algorithmsAbelardo Pardo
Talk exploring how to use data to provide scalable feedback in learning experiences. The solutions explored propose the use of algorithms to enhance how humans instructors provide feedback to students more effectively
Presentation at Association of MBAs (AMBA) 2014 Asia-Pacific Conference for Deans and Directors on the topic of Massive Online Open Courses (MOOC) and Technology-Enabled Education
Similar to Pushing the MOOC envelope with Learning Analytics (20)
Using OnTask for Student Coaching in Large Student CohortsAbelardo Pardo
The provision of student feedback is a challenging and resource intensive
task for any instructor but at the same time it has the potential of
significantly improve the overall quality of a learning experience.
This challenge is magnified even further in the context of large student
cohorts. Current initiatives such as the one captured by the OnTask project
have explored how to use data about student engagement to support instructors
of large student cohorts in this process. But despite the use of technology
there are still important aspects to consider. What is the ideal tone of the
message? Should they focus on the material? Assessments? Strategies? How
often is idea to send these messages? In this talk we will cover some
principles and examples of how instructors are addressing the problem.
Using data to provide personalised feedback at scaleAbelardo Pardo
The current state of higher education has increasing pressure over academics to offer high quality experience at scale. But what could be the actions that can be deployed to achieve this increase? What would be a good guiding principle to decide these actions? In this talk we explore first the possibility of using feedback and a coach mentality to provide student support, and then how data can help us scale that technique. There are examples of potential scenarios to deploy this at the level of a course, program or overall student experience.
Facilitating feedback processes at scale through personalised support actionsAbelardo Pardo
As education keeps advancing into the era of ubiquitous data availability there are certain challenges that are also increasing. The connection between data and direct improvements or benefit for students in terms of the overall quality of the learning experience is still an area under significant evolution. Learning analytics promises the use of data to improve learning experiences, but bridging the distance between widespread data availability and meaningful, effective and relevant actions informed by this data is still important. The current focus when considering the use of data tends to gravitate towards institutional interventions that target only a subset of the students (e.g. those at risk of dropping a course or abandoning the institution). But the student experience is much more complex and varied.
In this talk we will describe OnTask, a platform and approach to facilitate the connection between data and actions in the context of a learning experience. The framework used by the tool contains a generic architecture to simplify the combination of multiple data sources under a single data structure with an intuitive design of rule-based personalized support actions that can be scaled to large student cohorts. OnTask approaches the problem from the benefits of feedback processes that rely on a conversation between students and instructors at the level of a course.
Providing personalised student support in blended learning at scaleAbelardo Pardo
Blended learning environments can be used to deploy strategies to increase student engagement in learning experiences. However, for these strategies to be effective, this increase in engagement requires an increase in student support which can pose serious challenges for large cohorts. The increase in technology mediation offers unprecedented opportunities to collect information
about how students interact in a learning environment. Can this data be used to provide student support at scale? Is it feasible to blend data management techniques as part of a learning design to provide personalised suggestions to students? This talk will offer various practical examples of personalised
student support actions in the context of a large flipped classroom.
Designing Engaging Learning Experiences in Digital EnvironmentsAbelardo Pardo
Talk about how to address the design of learning experiences in the current digital environments and how to take into account the student perspective, motivation, feedback, and other various aspects.
Provision of personalized feedback at scale using learning analyticsAbelardo Pardo
The increasing presence of technology mediation offers an unprecedented opportunity to use detailed data sets about the interactions that occur while a learning experience is being enacted. Areas such as Learning Analytics or Educational Data Mining have explored numerous algorithms and techniques to process these data sets. Additionally, technology now offers the opportunity to increase the immediacy of interventions. However, not much emphasis has been placed on how to extract truly actionable knowledge and how to bring it effectively as part of a learning experience. In this talk, we will use the concept of feedback as the focus to establish a specific connection between the knowledge derived from data-analysis procedures and the actions that can be immediately deployed in a learning environment. We will discuss how there is a trade-off between low-level automatic feedback and high-level complex feedback and how technology can provide efficient solutions for the case of large or highly diverse cohorts.
Articulating the connection between Learning Design and Learning AnalyticsAbelardo Pardo
Learning analytics is a discipline that uses data captured by technology during a learning experience to increase our level of understanding, increase its quality, and improve the environment in which it occurs. But these experiences need to be designed first. In this talk we start from the statement that there is no such thing as a neutral design. In the era of increasing technology mediation Learning experiences need to be designed considering the capacity to capture data, the possibility of making sense and derive knowledge from the data, and the need to act on that knowledge. In this talk we will explore some initiatives to make these connections explicit in a learning design. Using a flipped learning experience, we will explore how to embed data and data analysis as part of the design tasks.
The role of data in the provision of feedback at scaleAbelardo Pardo
Technology mediation allows to capture comprehensive data sets about interactions occurring in learning experiences. Although these data sets have the potential of increasing the insight on how learning occurs, their use strongly depends on two aspects: the data has to be properly situated in the learning design, and the insights derived need to be translated into actions. In this talk we will explore how to establish this connection for the case of the provision of feedback. We will approach the problem from the point of view of intelligence amplification, that is, how data can support instructors to provide better support to learners through feedback. The talk will discuss some preliminary results from the Ontasklearning.org project.
Increasing student engagement has been one of the main focus to improve the quality of a learning experience. In this talk we cover two aspects that can contribute to this increase: flipped learning, and feedback.
The role of data in the provision of feedback at scaleAbelardo Pardo
The abundance of data in learning environments poses both a potential and a challenge. Improvements in the student experience need a strong connection between data, learning design and the delivery platform. In this talk we explore some ideas on how to establish this connection with respect to feedback.
Exploring hands-on multidisciplinary STEM with Arduino EsploraAbelardo Pardo
In this presentation we describe the Madmaker project. The use of Arduino Esplora to promote STEM activities in High Schools. It contains a description of our approach and data derived from the evaluation.
One of the objectives of the recently created Faculty of Engineering and IT Education Innovation unit is to promote "sustained innovation" in engineering educaiton. Innovation is a word that gets thrown around quite frequently and it is assumed we all know what it means. In recent times the term appears in more complex expressions such as "sustained innovation" or
"culture of innovation". Organisations in general are facing challenges to go from stating the intent of adopting a culture of innovation and actually achieving it. Engineering and IT education is no exception. In fact, there are recent studies that point to the disparity of perception among academics about
what exactly means innovation in the context of learning and teaching engineering and IT disciplines. In this session we will discuss several elements that need to be present for innovation to occur and collaboratively distil some conditions that would provide the right climate so that learning and teaching innovation flourishes in the faculty.
The role of institutional data in Learning AnalyticsAbelardo Pardo
Learning analytics has the potential of improving how higher education institutions operate. A significant portion of this potential derives from the use of institutional data. In this talk we review the role of these units in achieving institutional capacity and show some examples of the type of solutions possible at the level of instructors.
Generating Actionable Predictive Models of Academic PerformanceAbelardo Pardo
Exploring predictive models that are closer to action by instructors. The talk proposes the use of hierarchical partitioning algorithms to produce decision trees that can be used to divide students into groups and simplify how feedback is provided.
Exploring the relation between Self-regulation Online Activities, and Academi...Abelardo Pardo
Can we combine self-regulation indicators with digital footprints to understand how students learn? This talk describes a case study with a first year engineering course exploring this problem.
Data2U: Scalable Real time Student Feedback in Active Learning EnvironmentsAbelardo Pardo
Active learning environments require sustained student engagement in learning scenarios. Can we use data to provide feedback in real time about this participation?
Scaling the provision of feedback from formative assessmentAbelardo Pardo
Informal notes about a presentation in the New South Wales Learning Analytics Work group about how to send meaningful feedback to a large student cohort using learning analytics and semi-automatic processing.
Using data to support active learning experiencesAbelardo Pardo
How can you leverage the use of data to improve a learning experience? Learning analytics helps increase the accuracy of how we perceive the complexity of a learning scenario. In this talk I present some suggestions and an example of how to achieve this.
How to approach the design of flipped classroom. Discuss the rational and motivation to adopt flipped learning, the use of resources and the steps designing a module.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
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.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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.
Embracing GenAI - A Strategic ImperativePeter 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.
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.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
Pushing the MOOC envelope with Learning Analytics
1. thisisbossi flickr.com
Pushing the MOOC envelope
with Learning Analytics
Seminar on the Future of MOOCs
and Digital Libraries
Fukuoka, 24 February 2013
Abelardo Pardo (@abelardopardo)
The University of Sydney
www.slideshare.net/abelardo_pardo
2. DarrelBirkett Flickr
Associate Head of Teaching and
Learning
Two courses Tech to empower
Grad/Undergrad individuals and
communities
Active learning Behavioral analytics
Use of technology User validation
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 2
3. Simonov flickr.com
Where: MOOC Scenario
What: Challenges
How: Solutions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 3
4. Simonov flickr.com
Where: MOOC Scenario
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 4
5. IAN RANSLEY DESIGN + ILLUSTRATION flickr.com
MOOCs
Course in a stadium
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 5
6. Emorse flickr.com
Overcome initial
surprise!
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 6
7. Daikrieg flickr.com
Why should we be impressed
that an online course can reach
100,000 students at once?
(Guthrie, 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 7
8. danceinthesky flickr.com
MOOCs change
interaction radically
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 8
9. Some interactions do not scale!
Deep and meaningful formal learning occurs if
one of the interactions is at a high level
(Anderson, 2003)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 9
10. nateOne flickr.com
Say Hi!
1,200
emails
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 10
11. Curious
but...
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 11
12. paddynapper Flickr.com
Discussion board
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 12
13. HikingArtist.com Flickr.com
Massive activity misfit!
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 13
14. Secretlondon123 Flickr.com
Ideal for polls
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 14
15. Simonov flickr.com
Where: MOOC Scenario
What: Challenges
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 15
16. Size vs Interactivity
Intense
course
Level of interaction
cMOOCs
Transition to
MOOC easier
Cs
High
when low
O
O
interactivity
M
effort
xMOOCs
Trivial
course Low effort
Number of students
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 16
17. Size vs Tutoring
Manually Technologically
Unfeasible Challenging
Tutoring intensity
Technological
intervention is
Learning Analytics
Intense
course essential!
High Cs
O
O
effort
M
Trivial
course Low effort
Number of students
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 17
18. Scope vs Automation
MOOCs
Scope of intervention
Learning
Analytics allow
s
ic
yt
more generic
al
An
interventions
ng
ni
ar
Le
Intelligent Tutoring Systems
Level of automation
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 18
19. Chandra Marsono Flickr.com
Massive automatic
assessment
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 19
20. Joe Flickr.com
Early drop-out
detection
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 20
21. dklimke Flickr.com
Erratic
engagement
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 21
22. Quinn.Anya Flickr.com
Process, digest,
Connect prior summarize, apply
knowledge
Feedback
Focus
Attention Interaction with others
(Svinicki, 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 22
23. Simonov flickr.com
Where: MOOC Scenario
What: Challenges
How: Solutions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 23
24. Werner Kunz Flickr.com
Refine Collect
Act The five steps Report
of analytics
Predict
(Campbell, De Blois, Oblinger 2007)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 24
25. Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 25
26. Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 26
27. Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 27
28. burge5k Flickr.com
Microscopic
view of learning
events
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 28
29. Riccardo Cecchi Flickr.com
A clearly identified
environment within
your computer
(Romero-Zaldívar et al., 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 29
30. Track App Usage
kvnmcl Flickr.com
Collect interaction
events
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 30
31. Sean Dreilinger flickr.com
Automatic discovery
of complementary
learning resources
(Romero-Zaldívar et al., 2011)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 31
32. Unobtrusive Collection
Embedded Question
Collect feedback Effort
(Pardo et al., 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 32
33. Monitor Writing
(Calvo et al., 2011)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 33
34. Measure Engagement
(Liu et al., 2013, To appear)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 34
35. Eleaf Flickr.com
Automatic Question Generation
What evidence is provided to ...?
What are the strength and
limitations of ...?
(Liu et al., 2010)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 35
36. Facial Expressions
Detect emotions
(Monkaresi et al., 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 36
37. robpatrick Flickr.com
Massive
Personalization of
Interactions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 37
38. Mary Witzig Flickr.com
Massively Personalized Online Open Course
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 38
39. ribarnica Flickr.com
Massive Hyper-Personalization
“The Snowflake Effect”
(Duval & Hodgins, 2006)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 39
40. Personalize Everything
woody1778a Flickr.com
Which notifications?
Work individually? Collaboratively?
Reduce interaction to a small group
Hierarchical summaries of contributions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 40
41. pylbug Flickr.com
Learning Analytics
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 41
42. thisisbossi flickr.com
Pushing the MOOC envelope
with Learning Analytics
Seminar on the Future of MOOCs
and Digital Libraries
Fukuoka, 24 February 2013
Abelardo Pardo (@abelardopardo)
The University of Sydney
www.slideshare.net/abelardo_pardo
43. References
Dogh Guthrie, 2012.
Jump Off the Coursera Wagon
The Chronicle of Higher Education, 17 December 2012
T. Anderson, 2003.
Getting the Mix Right Again: An updated and theoretical rationale for interaction Equivalency of Interaction
The International Review of Research in Open and Distance Learning, 4 (2)
Academic Analytics
Campbell J., DeBlois P., Oblinger D.
EDUCAUSE White paper, 2007
MOOCs: What Part of Learning Goes on Where and How?
Marilla Svinicki
The National Teaching and Learning Forum, Dec, 2012
http://ntlf.com/sample-articles/moocs-what-part-of-learning-goes-on-where-and-how.aspx
The signal project
Purdue University
http://www.itap.purdue.edu/studio/signals/
Last accessed February 2013
Blackboard Analytics
Blackboard Inc.
http://www.blackboard.com/Platforms/Analytics/Overview.aspx
Last accessed February 2013
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 43
44. References (II)
Desire2Learn Analytics
Desire2Learn
http://www.desire2learn.com/products/analytics/
Last accessed February 2013
Romero-Zaldívar, V.A., Crespo García, R., Burgos, D., Delgado Kloos, C., Pardo, A., 2012
Automatic Discovery of Complementary Learning Resources
European Conference on Technology Enhanced Learning, 2011
Romero-Zaldívar, V.A., Pardo, A., Burgos, D., Delgado Kloos, C., 2012
Monitoring Student Progress Using Virtual Appliances: A Case Study
Computer & Education, 58(4):10580–1067, 2012
Pardo, A., Pérez-Sanagustín, M., Parada G., H., Leony, D. 2012
Flip with Care
SoLAR Southern Flare Conference, November, 2012
Calvo, R., O’Rourke, S.T., Jones, J., Yacef, K., Reimann, P., 2011
Collaborative Writing Support Tools on the Cloud
IEEE Transactions on Learning Technologies, 4(1):88–97
Liu M., Calvo, R.; Pardo, A., 2013
Visualizing the effect of actions in personal informatics systems
Workshop on Personal Informatics, CHI’13
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 44
45. References (III)
Liu M., Calvo, R.; Rus, V., 2010
Automatic Question Generation for Literature Review Writing Support
Intelligent Tutoring Systems 2010
Monkaresi, H., Hussain, M. S., Calvo, R., 2012
A dynamic approach for detecting naturalistic affective states from facial videos during HCI
Australasian Joint Conference on Artificial Intelligence, Sydney, Australia. LNAI, Springer 2012, pp.170-181
Duval, E., Hodgins, W., 2006
Standardized Uniqueness: Oxymoron or Vision of the Future?
IEEE Computer, 32(3):96-98
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 45