Showing posts with label #opened12. Show all posts
Showing posts with label #opened12. Show all posts

Wednesday, October 26, 2011

Assessment and Accreditation of an OER Learner

A Wikiversity Logo for Open Educational Resour...Image via WikipediaSpeakers: Rory McGreal, Wayne Macintosh
Learners accessing OER can acquire knowledge formally or informally. This project reports on assessment and accreditation policies worldwide.

A major function of colleges and universities is to validate and credentialise learning by conferring qualifications and degrees. They are well equipped and experienced in the process of assessing the quality of learning for formal academic or professional credit. However, digital media are transforming the ways individuals create, share and learn both formally and informally from content and applications available on the web. There is considerable ambiguity regarding the validity of this type of learning or self-study online and the use of individualized learning paths. The problem is that learners who access OER on the Web and do acquire knowledge and skills either formally or informally, alone or in groups, cannot readily have their learning assessed and subsequently receive appropriate academic recognition for their efforts. So, there is a need for ongoing research in order to understand the different ways that institutions are addressing the needs of this growing learner population.

This paper will report on a Canadian Social Sciences and Humanities Research project. The project is original in that it will research existing and nascent international protocols and practices leading to formal academic credit for non-traditional learners. This provides a framework to evaluate the transferability and applicability of these means for assessing OER learning on the web leading to formal credentials. Existing organisational and policy barriers will be identified and categorized. The project proposes a conceptual framework to overcome these barriers for widening access to post-secondary education through digital learning in ways, which are more accessible cost-effective and responsive to the diverse, changing needs of the knowledge economy and society.

This research is significant because the core mission of any modern university is to contribute to society. Many universities incorporate the mission of community service, as publicly funded institutions, to serve the wider interests of society by sharing expertise and scholarship. An understanding of how different institutions are approaching the recognition of non-formal and informal digital learning can provide change agents with new knowledge on how to expand their community service and learning missions by creating flexible pathways to credentialise learning for non-traditional students.

Recent transformational advances in digital media, the web and mobile devices have changed the learning landscape, ensuring that this research project is different. The exponential increase in accessibility to quality educational as OER provides unprecedented opportunities for learning. Thousands of course modules are presently available online, as OER from respected institutions, along with millions of websites that can be used to support a wide variety of learning objectives. This exponential growth has opened up opportunities for learners leading to potential obligations from our institutions.

The UNESCO/COL Chair has partners on all continents. This project will contribute to the advancement of knowledge of the assessment of learning experience for non-traditional learners. The outputs of this research could potentially have wide social impact in expanding access to learning opportunities for those students currently under-served by the formal sector while enhancing the efficiency of taxpayer funded institutions by refining existing mechanisms for assessment and accreditation or non-traditional learners.

Notes:
Their work in OERs was driven by digital rights management issues, digital licenses, and the idea that a license is a privilege not ownership. These are not conditions that encourage education.

Going to open education is not a choice - we must get away from proprietary materials.

Research objectives
Map existing projects on assessment/accreditation

They are building an open education resource university - OERU
This is to accredit students who are using open ed resources. Learning is free but you pay for the accreditation. To guarantee the credibility the assessment process must be strictly equivalent to that for mainstream students.

Participating institutions, they must have credible local accreditation. They are working with agencies to ensure quality assessment standards.

Learners access courses based solely on OER. Open students supported via "Academic Volunteers" and possible student mentors. Open assessment from participating institutions. Participating inst. grant credit and degrees.

They want to accredit all forms of learning, informal, formal, non-formal, and previous learning - also will include transfer credit, challenge for credit, and portfolio learning.

Research Questions?
Is a MOOC formal learning?
How does a "badge" system fit in?
How do we assess prior learning?

Breaking the "Iron Triangle" you can increase quality and lower cost.

University of London has been doing this for years.

"The Tragedy of the Commons" - the commons still exists in Britain and Canada. They really didn't take away the commons - private property is what is robbing people.

OER Red Herrings:
Quality issues
No credible credentials
Too rigid/flexible

Enhanced by Zemanta

Openness and Learning Analytics

Human Graphing - 20Image by nep via FlickrSpeakers: John Rinderle Norman Bier
Revise/Remix can build a 1000 points of OER light. Can these lights converge to fire authentic learning analytics & share-alike data models?

Conventional wisdom in the OER community maintains that one of the more important features of the open education approach is the malleability and customizability of materials, allowing freely available component resources to be remixed, adapted and modified to suit specific institutional directives, student needs or faculty interests. These features are important enough that the ability to revise and remix content is a core part of the commonly accepted 4R framework that defines open content. While the ability to tailor OER to meet changing or specific needs is one compelling part of the open model, the infinity variety that this encourages creates serious obstacles for another expected benefit of openness: using learning analytics to drive adaptive teaching and learning, support iterative improvement, and demonstrate effectiveness.

The ability to deliver meaningful learning analytics has been one promise of the open education approach. A use-driven design process for OER depends on the resources being used by a large number of students with varied background knowledge, relevant skills and future goals—a student population that open and well-used resources should be able to provide. Such a process can use such interaction data to iteratively improve courses in a meaningful and empirical way. Beyond improvement analytics, this same data can be used mid-stream to improve the effectiveness of learners and instructors.

Despite this promise, the OER community has not been able to create or take advantage of widespread, generally applicable learning analytics tools. While some organizations have had success in developing analytics platforms and approaches, such successes have tended to focus on specific resources, often developed with data collection in mind and not always falling at the “most open” end of the open content continuum. One barrier to more widespread analytic tools has been the variety of OER afforded by remixing and revising.

This presentation will explore the benefits and trade-offs to be made between adaptability and analytics. In the course of this exploration, we will argue that the benefits to be had from an approach that places a higher priority on analytics may outweigh those to be gained from endless variety in the OER space. Similarly, we will discuss some approaches to better harness open education’s promised ability to drive learning analytics, with greater and lesser compromises to the adaptability of OER. We will propose open communities of use and evaluation coalesced around individual OERs using learning analytics to improve the resource through coordinated revision and remix. Open education has embraced share alike licenses for materials. The next logical step is the open exchange of learning data and evidence of effectiveness, to “share alike and share data”. We will also suggest approaches to integrating disparate analytics-enabled OER into common platforms and the development of OER to published standards for learning analytic data.

Notes:
Open Learning Initiative:
Produce and improve scientifically-based courses and course materials which enact instruction and support instructors

Outcomes:
Shared understanding of challenges, tensions, and possibilities in learning analytics
Describe community-based analytics plans

Driving feedback loops. We have a huge opportunity to use assessment data around OERs. There are enormous amounts of data available.  "Infinite points of light" around all the OER repositories and initiatives.

Infinite proliferation

The 4 Rs

  1. Reuse
  2. Redistribute
  3. Revising
  4. Remix

Not recreate but to evaluate - recreate is a barrier to reuse.

What drives change in these settings?

  • Data 
  • Intuition
  • Market demand
  • Instructor preferences - change happens because an instructor gets bored with material, but with no real idea if the changes are improving the course.
Effectiveness: An OER is effective when it demonstrably supports students in meeting articulated, measurable learning outcomes in a given set of contexts. 

They are also looking at new forms of assessment for gathering data.

Rory McGreal asked whether or not there was a clearer way to talk about what is demonstrable. There are a lot of variables in the initial statement.

Why have we not been doing this?
  • It's hard
  • Costly
  • Individual faculty need support
  • It can be threatening to educators
  • Disparate systems for collecting data

What do we mean by "learning analytics"?
Proxies vs. authentic assessment and evaluation

Analytics Definition
Data collection > reporting > Decision making > Intervention > Action
Collecting data is not enough. We also need to make sense of it in ways that are actionable.

Types of analytics
Education/classroom management
Learning outcomes

We need common, agreed upon standards, a core collection, and a space for exploration.

Problems include privacy and technical issues.

Tools that already exist:
DataShop, Evidence Hub, Learning registry, and communities of evidence

Community College Open Learning Initiative

And build new things:
We need better mechanisms to share data.
We need a community-based approach.

Learning Intelligence Systems
What would be giving up? This approach forces us to allow our minds to be charged by evidence.

Next Steps?
Innovate
Standardize
Scale

  • Commitment to assessment and evaluation
  • Community definition of analytics enabled OER
  • Common approach to data
  • Shared and private analytics platforms

Enhanced by Zemanta