The AccessForAll 3.0 PNP Specification and its potential in Learning Analytics for Disabled Students

Introduction

The development of a match set of resource metadata and student functional profiles was recognised in the late 1990s as the best way of achieving automated personalisation for accessibility in any Web based system but particularly an Virtual Learning Environment (VLE) or Learning Management System (LMS).  In 2000 and accessibility working group was established within IMS Global Inc. to work on this.  I was a member of that group and have continued to be associated with this work.  In September 2013 IMS published a public draft of the specification of AccessForAll 3.0 stating:

“The Accessibility project group has released a public draft of IMS Access for All v3.0. The public draft is provided so that implementors have the opportunity to begin work and provide comments before production of the final specification.”

This blog post outlines the specification of part of this, the part that relates to user profiles known in IMS as PNP (Personal Needs and Preferences).  Note – no details are given here of the corresponding resource metadata specification known as the DRD (Digital Resource Description).  For authoritative details please refer to the IMS publications available at:
http://www.imsglobal.org/accessibility/

 

Overview of the IMS AccessForAll 3.0 PNP Specification

To quote from the primer to the specification:

Guiding Themes

The themes that guided the development of AfA 3.0 are described here:

• Simplicity and ease of understanding are crucial to adoption;
•  Easy modifiability will support changing requirements and the needs of organizations that require some parts of the model but not all, or require some parts of the model but use a different set of properties for other parts of it. Here, the work takes a knowledge-oriented approach, which will in future versions support Semantic Web technologies, as further explained in the Best Practices and Implementation Guide;
• Easy integration with other metadata should be possible;
• Integration with standards for device properties will, in future versions, permit matching to device properties as well as user requirements.
• The standard should properly relate user agents, accessibility APIs and producer-oriented accessibility standards;
• Widespread adoption within accepted accessibility frameworks and tools will promote wider impact.

 

The long-term goal of IMS AfA3.0 is to produce a sustainable, general and effective model integrated with the other standards efforts. It has to work across environments, device contexts and organizations; it is not limited to the educational domain. It aims to support accessibility through an “architecture” for personalization. It needs to be recognized, however, that at this point, the work is prototypical and intended to support progression towards such a model.

 

The Data Elements

The specification is for a “core” specification, but this is designed to be extensible where this is needed for specific implementations.  Using extensions to the core will impact on interoperability with other system components or external systems; thus it is an important design decision.

The Core Profile of the IMS Global AfA PNP v3.0 specification is defined in Table 4.1. [Taken from IMS Global Access for All (AfA) Core Profiles, Version 3.0 Specification, Public Draft 1.0]

 

Table 4.1 Core Profile for an AfA PNP v3.0 instance.
ID	Element/Attribute Name	Spec M’plicity	Profile M’plicity	Profile Commentary
Root	accessForAllUser	1		Each AfA PNP v3.0 instance file will contain one and only one accessForAllUser.
1	accessModeRequired	0..*
(1.1)	existingAccessMode	1		The following vocabulary terms are not permitted: itemSize, olfactory, orientation and position.
(1.2)	adaptationRequest	1
2	adaptationTypeRequired	0..*
(2.1)	existingAccessMode	1		The following vocabulary terms are not permitted: itemSize, olfactory, orientation and position.
2.2	adaptationRequest	1
3	atInteroperable	0..1
4	educationalComplexityOfAdaptation	0..1
5	hazardAvoidance	0..*
6	inputRequirements	0..1
7	languageOfAdaptation	0..*
8	languageOfInterface	0..*
-9-	adaptationDetailRequired	0..*	Prohibited
-9.1-	existingAccessMode	1	Prohibited
-9.2-	adaptationRequest	1	Prohibited
-10-	adaptationMediaRequired	0..*	Prohibited
-10.1-	existingAccessMode	1	Prohibited
-10.2-	adaptationRequest	1	Prohibited
-11-	educationalLevelOfAdaptation	0..*	Prohibited
-12-	extensions	0..*	Prohibited	Extensions not supported.

Figure 1: data elements in AccessForAll 3.0 PNP Core Profile

 

AfA3.0 Statements – a functional model of disability

Now in the existing data at the OU we can use in Learning Analytics we have , which is a binary that just indicates that the student has, or has not, declared a disability.  Then there is .  There are 12 categories of disability used to collect data for national reporting to the Higher Education Statistical Agency (HESA) which constitute the values of ; these are:

1. Sight
2. Hearing
3. Mobility
4. Manual skills
5. Speech
6. Specific learning difficulty e.g. dyslexia
7. Mental health
8. Personal care
9. Fatigue/pain
10. Other
11. Unseen disability e.g. diabetes, epilepsy, asthma
12. Autistic Spectrum Disorder

 

The AccessForAll 3.0 specification by contrast allows machine-readable statements like the following to be stored in a user profile database:

•          Student ‘x’ has a Access Mode Requirement of textual alternatives to graphics;
  [c.f. has a sight impairment as would be stated in the above categorisation]

 

In other words AccessForAll 3.0 allows a functional model rather than a medical model of disabilities to be constructed.  This is very important for the Accessibility use case for Learning Analytics and will enable refinements in the Support use case.

 

Applications in Learning Analytics

Previous blog posts on Learning Analytics form a useful introduction to this section – see:

•          https://martyncooper.wordpress.com/2012/10/12/use-case-scenarios-learning-analytics-disabled-students-accessibility/
•          https://martyncooper.wordpress.com/2012/10/16/la4stem-project-descriptio/
•          https://martyncooper.wordpress.com/2013/01/09/learning-analytics-for-supporting-disabled-students-and-identifying-accessibility-deficits/
•          https://martyncooper.wordpress.com/2014/01/22/perspectives-on-the-student-as-e-learner/
•          https://martyncooper.wordpress.com/2014/02/17/ethics-learning-analytics-and-disability/
•          https://martyncooper.wordpress.com/2014/03/14/internal-project-proposal-learning-analytics-for-disabled-students-in-stem-subjects/
•          https://martyncooper.wordpress.com/2014/03/16/jisc-digital-festival-2014-notes-day1-cont/

 

What is desirable in the envisaged Learning Analytics applications is a user profile that can describe how each individual user interacts with their computer (or other device) and the Web environment.  This will enable the Accessibility use case to be implemented meaningfully.  This follows from the fact that if users with similar profiles encounter access problems with the same learning activity (object) then there is a high degree of probability that it has accessibility deficits.

It will also be of benefit in the Support use case as users with similar needs can be targeted with specific support for them.  E.g. before screen reader users undertake a particular activity they could be directed towards a help page.

Now is AccessForAll 3.0, in its core specification sufficient for this?  Probably not, extensions will be required to give the level of detailed information sort but these extensions are allowed in the specification.  However, the specification allows for such extensions and their devising although application specific could be fed back into later versions of AccessForAll as recognised extensions that other applications could use and thus be interoperable.

 UML Diagram of a Learning Analytics System Deploying AccessForAll

Figure 2: UML diagram of a future e-learning system incorporating Learning Analytics and Personalisation.

 

The above UML diagram shows a future system integrating a Virtual Learning Environment (VLE), Analytics Engine, Personalisation Engine.  The functional user database at the bottom of the diagram could be based on a data model itself based on AccessForAll 3.0 (with or without extensions).

In summary, when a student requests a learning resource from the VLE the Personalisation Engine determines what format of the resource best suits that user based on the data stored in the functional user database. The Analytics Engine records all the student’s interactions with the VLE and the resultant system responses.  In fact the only elements on the above systems diagram not already in place are the Personalisation Engine and the Functional User Database towards the bottom of the diagram.

Conclusions

So AccessForAll 3.0 holds enormous promise for being able to implement Learning Analytics approaches, for both Support and Accessibility use cases, that incorporate detailed user profiles and has many advantaged over the medical model based classification .  Now it is time to do some implementation and validate the approach with end users and other stakeholders.

 

— end —

 

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Why Educators Need to Know Learning Theory

I highly recommend the following blog post on Learning Theory: Why Educators Need to Know Learning Theory.

Ethics, Learning Analytics and Disability

Today I have been writing a contribution for a paper requested by the Open University’s Ethics Committee about ethics in Learning Analytics.  This blog post is adapted from that.

There are two broad use case scenarios where learning analytics approaches may benefit disabled students:

1. Targeting support to disabled students or their tutors (Support)
2. Identifying online activities that seem to be problematic for some disabled students (Accessibility)

As far as we are aware these approaches are yet to be deployed anywhere world-wide but we are actively researching them here at the Open University where we have approximately 20,000 disabled students.  We envisage that if the early promise of this research holds up, deployment on about a 3 year horizon.  These approaches, especially the accessibility one, are reported in more detail in Section 5. of Cooper et. al. 2012.

Firstly, a few definitions:

IMS Global Learning Consortium offered education-specific definitions of both disability and accessibility when introducing its work on the development of technical standards for accessibility in e-learning:

[…] the term disability has been re-defined as a mismatch between the needs of the learner and the education offered. It is therefore not a personal trait but an artifact of the relationship between the learner and the learning environment or education delivery. Accessibility, given this re-definition, is the ability of the learning environment to adjust to the needs of all learners. Accessibility is determined by the flexibility of the education environment (with respect to presentation, control methods, access modality, and learner supports) and the availability of adequate alternative-but-equivalent content and activities. The needs and preferences of a user may arise from the context or environment the user is in, the tools available (e.g., mobile devices, assistive technologies such as Braille devices, voice recognition systems, or alternative keyboards, etc.), their background, or a disability in the traditional sense. Accessible systems adjust the user interface of the learning environment, locate needed resources and adjust the properties of the resources to match the needs and preferences of the user. (IMS Global 2004)

Thus disability is not an attribute of a person, but an attribute of the relationship between that person and the tools they are using to meet their goals; in this case online learning.  And, accessibility is a property of the learning resources that makes is usable by all, including those traditionally labelled as disabled.

The principle ethical dilemma when approaching learning analytics and learners who might experience a disability in the context of online learning is:

• For what purpose has the individual students declared their disability to the university or other educational establishment, and is this consistent with how that information is to be used in the learning analytics approaches?

No other literature has been found explicitly addressing this issue.  So this blog post might represent the first public statement of the problem.

At the Open University students who declare a disability so that they can be provided with support in their studies.  This is consistent with the first use case scenario (Support).  It is a moot point if it is consistent with the second use case scenario (Accessibility).  More critically at this stage of development of these approaches it is not obvious that it is consistent with research into these approaches.  Is it ethical to use historic or current data relating to students with disabilities to undertake research into future approaches of applying learning analytics?

References

Cooper, M,Sloan, D., Kelly, B.,  and Laithwaite, S. (2012) A Challenge to Web Accessibility Metrics and Guidelines: Putting People and Processes First, Proc. W4A2012, April 16-17, 2012, Lyon, France. Co-Located with the 21st International World Wide Web Conference.

IMS Global Learning Consortium (2004), IMS AccessForAll Meta-data Overview. Available online at: http://www.imsglobal.org/accessibility/accmdv1p0/imsaccmd_oviewv1p0.html (accessed 17/02/14)

UK Government cancels Code of Practice for Higher Education on Equality Act 2010

Today I have been writing a section on Disability and Accessibility for a paper for LAK13 entitled “What Can Learning Analytics Contribute to Disabled Students’ Learning and to Accessibility in e-Learning Systems?”.  In doing so I had cause to check on the status of the long promised Code of Practice for Higher Education covering the UK’s Equality Act 2010 .  I discovered this on the Equality and Human Rights Commission’s web site:

Other Codes of Practice

We were intending to produce further statutory codes of practice on the Public Sector Equality Duty (PSED), which came into force on 5 April 2011, and codes for the Further and Higher Education (FEHE) sector and schools.

Unfortunately, we are no longer able to proceed with these plans. The Government is keen to reduce bureaucracy around the Equality Act 2010, and feels that further statutory guidance may place too much of a burden on public bodies. Although the Commission has powers to issue codes, it cannot do so without the approval of the Secretary of State, as we are reliant upon government to lay codes before parliament, in order for them to be statutory.

It is the Commission’s view that, rather than creating a regulatory burden, statutory codes have a valuable role to play in making clearer to everyone what is and is not needed in order to comply with the Equality Act. However, as this is no longer an option, we feel the best solution is to issue our draft codes as non statutory codes instead. These non statutory codes will still give a formal, authoritative, and comprehensive legal interpretation of the PSED and education sections of the Act and will make it clear to everyone what the requirements of the legislation are.

Source: http://www.equalityhumanrights.com/legal-and-policy/equality-act/equality-act-codes-of-practice/

These now non-statutory codes do not seem to be published yet and with the further discouragement from Government who knows when they will be.  I and many others had been eagerly hoping that among other things the statutory codes would have provided clear legal guidance on “reasonable adjustments” generally and web accessibility specifically.  It was hoped that they would include reference to the key external accessibility standards: WCAG 2.0 and BS8878.

To my view this is a very retrograde step.  The old CoP relating to the previous legislation, the Disability Discrimination Act (1995 as amended 2005) is still available but now has no statutory basis and is outdated in terms of educational practice, web accessibility standards, technology and the law.  Available at: http://www.equalityhumanrights.com/uploaded_files/code_of_practice__revised__for_providers_of_post-16_education_and_related_services__dda_.pdf

I am now chairing the newly formed Open University Web Accessibility Standards Working Group defining a common web accessibility standard for the OU and developing associated support documentation for managers and developers.  This is part of a overall Web Governance Review.  This work needs a secure legal underpinning which I had hoped would come from the CoP. It would be helpful is we could authoritatively point to a statutory statement of what is considered as the appropriate level of web accessibility under the term “reasonable adjustment”.  That being said it is probably optimistic to think the CoP would have given that.

As commented elsewhere in this blog defining levels of accessibility is problematic. This follows from the fact that accessibility is a property of the relationship between the user and the web resource and depends on the circumstances in which and technology they use to access it. More generally it is a summation of these relationships for the full diversity of potential users. Web accessibility is not, as usually inferred from WACG2.0 and in most work on accessibility metrics, a property of the resource alone. However, organisations in education, commerce and the public sector are longing for a way of authoritatively asserting that they have sufficiently addressed accessibility in terms of their legal obligations.

Personalisation for Accessibility

Last November (2010) I wrote on 40 page report for a major eLearning strategic development project at the Open University on personalisation for accessibility. This gives an overview of the topic, highlights the rational for adopting personalisation approaches to achieve accessibility, summarise the different approaches that are available and points to technologies and standards that can underpin them.  The report is intended for both a technical and non-technical readership.  This blog post summarises the information from that report.  If you wish to know more detail please post a request in the comments box.

The rationale for personalisation for accessibility is clear.  Accessibility is essentially dealing with diversity – personalisation avoids the always flawed attempt of doing so by a “one size fits all” solution.

There are different approaches to achieving personalisation for accessibility.  These may be used in combination.  Any systems developer has to consider which, if any, of these can be adopted within its specification, which need to be considered as likely for future adoption and thus raise an issue for future proofing or which are unlikely to be adopted in their context. The different approaches are:

• User selected options directly controlled from the (web) interface
• User profiles containing preferences that can be set for all content and tools
• User profiles used to select style sheets applied server side
• User profiles used in combination with accessibility content metadata to facilitate content personalisation, e.g. automatic serving of alternative formats

There is a close link between meeting the mobile platform agenda and personalisation for accessibility. The approaches adopted for both should be considered in tandem.  (One way to view mobile is a special case of accessibility requirements).

Content personalisation approaches can facilitate greater browser independence.

Only limited user requirements work has been done on personalisation for accessibility. Examples include from the EU4ALL project and the BBC’s ”MyDisplay” (probably the most significant enterprise level approach to personalisation for accessibility).

Notes were made in the report on key drivers, ongoing standards work and emerging technologies that are likely to impact significantly on content personalisation for accessibility in the near future.  These include soon anticipated technical innovation; maturing technical standards and new and updated legislation, accessibility standards and codes of practice.  Without further comment here these key divers include:

• WAI-ARIA work in W3C
• The IMS project group developing AccessForAll 3.0
• HTML 5.0
• Mobile technologies
• The cloud-based accessibility vision is being driven in an initiative called NPII/GPII (National Public Inclusive Infrastructure/Global Public Inclusive Infrastructure)
• In the USA Section 508 refresh
• W3C’s WCAG 2.0,
• In the European Union Mandate 376
• In the UK BS 8878:2010 Web accessibility – Code of practice

Rich Schwerdtfeger (Chief Technology Officer Accessibility, IBM Software Group, based in Austin, Texas) considers we are reaching a “Perfect Storm” (excuse the American cliché) that should promote the widespread adoption of advanced and systems based approaches to accessibility such as personalisation.  I think that a lot more pieces of the picture are now in place than 5 years ago but the challenge remains the political will (in diverse organisations and companies) to bring these together to facilitate systems that truly adapt to meet people’s access needs.

The Evolution towards a Personalised Web and the Impact on Education

A highlight for me of the IMS Learning Impact conference was the keynote talk by Rich Schwerdtfeger (IBM) entitled “The Evolution towards a Personalised Web and the Impact on Education”.  Rich co-chairs the IMS Accessibility group currently finalising the AccessForAll 3.0 specification.

A key point in the talk was that many of the issues of accessibility to the web were the same as when wanting to serve web pages to mobile devices.  The below is adapted from one of Rich’s slides:

Personalisation approaches depend on preferences profiles.  Rich raised the possibility for mobile devices to include the users preferences thus negating the need for a “preferences server” in this case.

The information needed for personalisation was summarised in the following slide:

Rich also introduced the AccessForAll 3.0 specification which I will blog about when it is released for public comment in a month or so.

Rich gave and overview of the National Public Inclusive Infrastructure (NPII).  This provides software enhancements to the nation’s broadband  Infrastructure to ensure that people facing interface barriers due to ageing, disability, or literacy can use broadband information and services available to others.  It supports AccessForAll 3.0.

The below slide shows the multiple approaches that are possible, as supported by the NPII:

The presentation finished highlighting the importance of this approach to accessibility to education.

[All slides used with permission and thanks to Rich Schwerdtfeger (IBM) and Gregg Vanderheiden (The Trace Center, University of Wisconsin-Madison ).]

UK Accessibility Projects Feature Highly in IMS Learning Impact Awards!

Two UK accessibility projects were winners of the Platinum Awards in the New and Research and Development category of the IMS Learning Impact Awards announced today.  They were:

1. BBC Accessibility Settings Kit, Accessibility Preferences System, and
2. Xerte Online Toolkits: Open Source eLearning

I would like to commend both these projects.

I saw a demonstration of a locally installed version of Xerte while at the conference.  It is a wonderful example of a Flash based application that is truly accessible.  What is more they have solved a long standing problem of how to make drag-and-drop interactions accessible to blind and visually impaired users.  Further information is available at and it can be downloaded from: http://www.nottingham.ac.uk/xerte/toolkits.htm.

An article about the BBC Accessibility Toolkit is online at: http://www.bbc.co.uk/blogs/access20/2007/01/customising_the_bbc_website.shtml.

Congratulations to both projects!