Mobile | Fiona MacNeill | Macknowlogist

A technical perspective on a telepresence robot

Thu, 20 Jun 2019 00:00:00 +0000

From January until May 2019 the eLearning team evaluated the AV1 robot avatar, a telepresence robot manufactured by the company No Isolation, based in Norway. This post aims to provide a brief overview of what we learned during our pilot project.

Controlling the robot at Falmer campus from Moulsecoomb

Our findings are shared with the caveat that they are specific to our institution and in different circumstances the end-user acceptance of the technology and the results may have varied.

About the pilot

This pilot project was designed to establish the functionality of a telepresence robot, the AV1, with a view to providing a bookable service for eligible students in the future. The AV1 robot’s purpose is to provide an avatar for an individual student who wishes to attend a class but may not be able to be present in-person. Such a student, due to circumstances including, but not limited to, medical conditions, learning disabilities or caring responsibilities could benefit from attending virtually from home or in an alternative location. The AV1 robot provided a different type of value proposition when compared to existing solutions such as video conferencing; it provided an individual, encrypted connection to the classroom for a single student user.

The aim of this pilot project in the first instance was to establish the functionality and usability of the AV1 robot device. We planned to do this by inviting students from a specific school to participate in testing the robot during a class session. These students were invited irrespective of need as it was not possible to target a specific student population, for instance those with learning support plans. We had hopes that having established the functionality of the robot we could progress to a second phase of the project. This second phase would be in collaboration with colleagues who work to support students directly so that we could make the technology accessible to those students who need it.

AV1 Robot

How does the telepresence robot work?

The robot unit is positioned in the classroom for the student and then the student uses a phone or tablet to control the robot’s line of sight and display facial expressions on the robot’s face from afar. The phone/tablet can also be used to ask the instructor questions and to access the video stream. For the privacy of other students, any recording facilities on the smartphone/tablet are disabled. The video stream therefore is also time-specific, just as it would be for in-person attendance at a lecture. The robot also allows for a level of anonymity if desired, so the student can choose to silently observe and attend the lecture or seminar without calling attention to their absence or revealing their identity.

We created¹ this video to provide a quick description for student of how the robot works…

Aims for the pilot project

We have provided some information about the proposed research methods at the bottom of this post. The aims listed below are provided with an indication of how successful we were at achieving each.

Aim #1

To establish the utility of the device in lecture and seminar settings.

Aim #1 - Result

We were able to test the robot in two seminars sessions through technical staff use (no use by students). We did not use it in a lecture setting due to scheduling.

Aim #2

To build expertise in Information Services, as such devices may be recommended as assistive technologies for students in the near future. It is important to establish the telepresence robot’s function and how to accommodate such devices on the wireless network.

Aim #2 - Result

We were successful in this area, both the eLearning team and our colleagues in network services learned about how the robot worked on our network.

Aim #3

To understand the student experience of using the telepresence robot from a location beyond the classroom.

Aim #3 - Result

We were unsuccessful. The robot was demonstrated to two different groups of students in different year groups and the pilot project failed to recruit.

Aim #4

To establish the telepresence robot’s suitability to potential requirements and understand the limitations of the technology.

Aim #4 - Result

We were successful in learning about some of the requirements and also understanding the limitations of the technology in our particular setting.

Aim #5

To understand how the presence of the robot affects the taught environment, including the experiences of academic staff who teach with such a device present in-place of a student.

Aim #5 - Result

We were unsuccessful in this venture as we were not able to test the robot in situ without the presence of a technical staff person in a naturalistic way due to not having student participants.

What actually happened?

While we sought ethical approval for user testing, the robot went on a little roadshow to meet members of staff. It was introduced at one of our regular ‘All things eLearning’ tech afternoons and was enthusiastically received by staff. The robot was also taken to meet the university’s disabilities and dyslexia team, who were interested in how the technology could be used to support students. During this time the robot was tested in a few locations at the university’s Falmer and Moulsecoomb campuses. Colleagues in network services also spent some time testing the robot to establish the network load of the streaming video functions. Everything seemed hunky dory and ready to go.

After ethical approval was gained. A small number of willing academic staff were recruited, and the robot was taken to visit two separate classes by a member of the eLearning team. These class visits were put in place to demonstrate the robot’s capabilities, to explain the aims of the project and to allow for recruitment of student participants by a neutral third-party² This is where our story takes a downturn.

During the first class visit we discovered some limitations related to connectivity. The AV1 can automatically assess the available network connections and choose the best connection based on signal strength. This is a helpful trait, but we encountered an issue where the robot routinely dropped off eduroam. We would have liked to be able to enforce which signal the robot selected, but we had no control of this setting. As a result, the reliable little robot failed spectacularly when confronted with the 4G connection in the South Downs National Park where the Falmer Campus is based³. There is an assistant app which allows for a level of technical oversight, but the controls were too basic for our needs and did not include any diagnostic functions. Alas, the robot did not give a good first impression through a combination of circumstances. No Isolation were great at working with us to resolve the Wi-Fi issues and willingly took onboard feedback related to the robot control apps. Another class visit was arranged.

During the second class visit the robot was demonstrated successfully, but the video stream was very poor quality as the signal once again reverted to 4G having been on WIFI successfully earlier in the day. Other devices in the room were connected to WIFI. What was different about this visit is that the students were not keen on the robot and their response to its presence seemed to imply an air of ‘uncanny valley’⁴. They didn’t want the camera to look in their direction and there was a feeling of unease in the room.

Testing the AV1 robot out in a classroom

Personal reflection from project lead

There are a variety of factors that led to the early cancellation of this project, but the main reason was lack of student study participants. To reflect, this could have been due to the time of term and the proximity to assessments. Another point is that as the main researcher on the project, perhaps I did not articulate the value of the tests adequately. I also could not pay students or offer them any incentives for participation beyond helping other students; for time-strapped students with many competing demands this may not have been enough. If the project had been working with a small focus group of students in different settings, that could have worked better, particularly if those students were in need of such a solution. However, such a venture would require a different group of stakeholders than we had for this basic pilot.

From a technical standpoint I felt that the staff overhead was too high to be sustainable. On a logistical level we would need a person to take the robot to the correct building and lecture/seminar room at the correct time and to then coordinate with the student user to ensure that they were able to connect. Furthermore, the assistant app for remote support of the robot was not yet sophisticated enough to meet our needs in terms of providing diagnostic information about the robot and its connectivity.

In our proposed service model, the robot would belong to the university and could be borrowed; based on testing the robot is not really designed for that type of deployment. In reality the robot really has a one-to-one relationship with the student, and it is not easy to reset it for use with a new mobile device without contacting support and requesting a new activation code. For instance, it would not be possible to have a service where a student could call/email our help desk and request a telepresence robot for their session in the afternoon, as their phone/tablet needs to be coupled to the robot. That is not something that we could do easily on an ad hoc basis from afar and it would then need to be reset again to allow the next student borrower. The ideal use model is that the robot _is _a representative of an individual student in the classroom, which is fine, but implies that the student also owns the equipment themselves. In our HE context, it may be that students would not need such a service for all their lectures, but for example only on particular days where they might have had a flare-up of a health condition. So, in our borrowing model, we would have to provide an iPad to couple-with the robot and that iPad would have to stay with the student for as long as they used it.

Following on from the point above, I believe that a borrowing model could work in HE for planned leave such as, maternity/paternity, medical and personal. Maternity leave has already been explored by a pilot project at the University of Oxford (European Bioinformatics Institute, 2018). In these cases, it would be possible for a student to pick up the robot’s accompanying iPad prior to going on leave and then keep the iPad for the duration of their leave, so that they could attend classes. This also implies that there would be a need for more than one robot and for there to be means-tested or referral-based eligibility criteria. Without considerable service planning, it would be easy to see that such a service might be underutilised in the reality of a busy HE setting.

Verdict

There is certainly potential for a future service provision, but more sophisticated management tools are needed for HE settings. Anecdotally speaking, the reaction of some students to the aesthetic design of the robot suggests that a different approach may be needed for the device to feel appropriate for adult learners.

References

Gibbs, G. (1988) _Learning by doing: A guide to teaching and learning methods_. Further Education Unit. Oxford Polytechnic: Oxford.

European Bioinformatics Institute (2018) _Meet the robot avatars helping Cambridge students combine education and motherhood_. https://www.cam.ac.uk/research/news/meet-the-robot-avatars-helping-cambridge-students-combine-education-and-motherhood (Accessed: 24 October 2018).

No Isolation (2018) _The impact of AV1 on children with long-term illness and absence_. Available at: https://www.noisolation.com/global/research/the-impact-of-av1-on-children-with-long-term-illness-and-absence/ (Accessed: 24 October 2018).

Schrepp, M., Hinderks, A. and Thomaschewski, J. (2017) Design and evaluation of a short version of the User Experience Questionnaire (UEQ-S). _International Journal of Interactive Multimedia and Artificial Intelligence,_ 4(6), 103-108.

University of Edinburgh (2019) _Reflection toolkit_. Available at: https://www.ed.ac.uk/reflection/reflectors-toolkit/reflecting-on-experience/gibbs-reflective-cycle (Accessed: 26 March 2019).

Research methods

The following qualitative research methods were planned:

A testing session would be arranged during a scheduled class. The student would have attended remotely during the class and would have been asked to use the telepresence robot independently after receiving basic instruction.
The student would have been asked to complete a short questionnaire at the beginning of the session prior to use. A second version of the same questionnaire would have been repeated at the end of the testing session. The core questions are based on a validated user experience questionnaire (UEQ-S; Schrepp, Hinderks and Thomaschewski, 2017).
Anonymised typed notes would have been taken during the testing session to record any verbal feedback that the student tester wished to share with the researcher.
Academic staff participants would have been asked to complete a written reflection of a minimum one-page in length based on Gibbs’ Reflective Cycle (1988; see also University of Edinburgh, 2019).

The following quantitative research method were planned:

The bandwidth used by the telepresence robot during the testing sessions would have been monitored by the university's network services team.

Addendum

about parents’ privacy concerns related to use of an AV1 robot in a classroom setting.

we used to create the video. ↩︎
The member of the eLearning team who does not have an existing service-based relationship with students. ↩︎
quite a rural and hilly area]. ↩︎
. ↩︎

[Talk] Factors of Trust in IoT App Interfaces Redux

Tue, 14 Jun 2016 00:00:00 +0000

Talk presented at UX Camp Brighton 2016 - Redux on 14/06/16 at 68 Middle Street

for the version of this talk given at UX Camp Brighton, 2016 (19/03/16). Video version of original talk. from on .

Session description:

Does your app rely on OAuth to offer connection to other apps and services? Based on my research studying app-to-device relationships in Internet of Things systems (e.g. Fitbit, Jawbone UP, Nest, SmartThings, Glooko), I have uncovered some best practice recommendations when it comes to inspiring trust within your interface. Trust definitions used in this video are from Pavlidis, Islam, Mouratidis, and Kearney (2014). This research is aligned with the SenSe research Cluster at the University of Brighton (secure and dependable software systems).

About SenSe

aims to develop novel and pragmatic ways to assure the dependability of software systems with particular emphasis on security, trust and risk. We focus on theories from model-based engineering and analysis-based assurance to develop methods, models, practices and tools that promote the provision of security and dependability in complex interconnected and heterogeneous systems and information infrastructures that underpin our economy and society.

Preliminary recommendations:

UX Questions to Ask in Relation to IoT Apps

#	Category	Questions to ask
1	System dialogues and Semantics	Are system dialogues consistent? For data permissions for use tips for motivational messages
2	Settings	Are all the settings housed together? Are items like the privacy policy and standards adherence available from this area? Can the Terms of Service (or a shortened format of ToSs) be accessed from within the app? Can connected apps and devices be reviewed/managed from within the app? Can support documentation be accessed from within the app?
3	Checkups for Setup/Workflow/Privacy An essential part of onboarding. Also a method for supporting trust and helping users to invest time in learning the higher-level functions of an app, which promotes realisation of app benefits and long-term commitment to use of the app (Brignull, 2013).	Periodic reminders about setup: Can the setup be improved? What devices could be added safely? What benefits might be available as part of the system that the user may be unaware of? Periodic review of workflow: ask users to review the workflow in the system to add a level of human oversight. If the app is not accessed frequently then email and text message may be effective ways to prompt engagement. Think of it like entering a monthly gas meter reading. Is an automated workflow still operating as intended? Is the function still needed? A possible incentive could be that the workflow will stop/timeout if it is not reviewed a la IFTTT. Periodic review of privacy: privacy overview and audit tools within the app. What information is shared with third-party developers? For what purpose/s is it shared? Non-legalese overview of changes to T&Cs should be included in privacy checks.
4	Role/function of the app Applies to central app and third-party apps.	This sounds really obvious, but a lot of primary IoT apps don't actually explain their purpose within the system. What service does the app offer? What need does the app fulfill? What does the app do? How important is the app to the operation of the system? E.g. is it the primary interface or management tool for the system? What data does it need? - Make it clear what is used and why, in plain English.
5	Health/status of hub/sensor/device At any point in time the user should be able to view a basic log of what is currently going on in the system.	What is going on in the system right now? Is recent system activity accessible? Is it possible to access logs from other time periods? Is it possible to see what communication channels are in operation? What third-party apps are connected to the system, what are they doing? What third-party devices are connected to the system, what are they doing? This should be more like what you expect from your banking app when it comes to overseeing the operation of high-importance health, home/business automation IoT systems.
6	OAUTH and API: secondary app data use	Respect users and prove that your app is more trustworthy by only calling data that you are actually using. What data is needed into order to provide the desired third-party service? How is the data used to provide the service? Note: platform manufacturers/developers need to ensure that third-party apps aren't over-privileged in terms of the data they access and the calls they can make via APIs (See the work of Fernandes, Jung and Prakesh, 2016). Developers need to state their intention when it comes to use of information that they call via the API. This doesn't stop those with malicious intent, but it helps users to distinguish between those who pay due diligence to privacy and those who are either malicious or sloppy.
7	What is shared?	Can data access be allowed/disallowed? Once disallowed from the primary app, is this decision upheld? Ideal world: provide granular options for allowing/disallowing access to data which is not necessary for the operation of the service offered by the app. Better yet, don't ask for the data at all if it isn't essential to operation.
8	Access control	Is two-step authentication an option for the web app and login from a new device? Does the smartphone/tablet app offer biometric authentication? Does the app offer the option of setting a passcode for auto screen lock? Particularly if the app controls home appliances.
9	Dependency and operational relationship	As systems become more complicated it is crucial that the user is aided in building a mental picture of the basic configuration of the system. I [keep thinking of Max](https://cycling74.com/products/max/) when I think of this issue. Is logging available? What is going on in the system right now? What is attached to this system (devices/sensors/users)? Is the system visualised in any way?
10	Try before you buy	Wearables have the right idea on this one, allowing you to trial a wearable companion app using your smartphone's built-in sensors. What if you could try out the perks of the system before you buy the actual device? Is a preview of how the app will operate with devices, provided as part of onboarding? Can you try of some of the functionality of the system without buying a system-specific device?

References

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My current personal hero:

The Adjustment Bureau: The Case for Adjustment in Mobile Apps

Sun, 07 Sep 2014 00:00:00 +0000

Introduction

Recently I was asked to present at the Media-Enhanced Learning Special Interest Group (MELSIG) event hosted by the University of Sussex. MELSIG is a special interest group originally formed in 2008 (MELSIG, 2014). The group’s focus has evolved, alongside contemporary developments in technology, to include investigation of a wide variety of digital media when applied to the support of learning and teaching. The theme for the University of Sussex event was Digital Media Interaction and Inclusivity and this was exactly the prompt I needed to engage in more thorough research of in-app adjustment functions which has been preoccupation of mine for a while.

Learning as a community

Through my work building ‘communities of practice’ (Wenger, 1998) on both sides of the Atlantic, and in particular during the development of events at the University of Brighton something always bothered me about apps or mobile applications/software. Namely why, when developers have such rich to work with, isn’t there more attention to paid to inclusivity when designing apps? Both the iOS and Android operating systems have a number of built-in functions which have the potential to greatly aid accessibility in addition to the benefits afforded by the touchscreens and the form factors of the devices themselves. However, due to the unique conditions under which apps are developed a combination of factors including time/monetary constraints, corporate interests and the lack of a common accessibility guidelines seem to stifle the potential of certain apps on the accessibility front. Indeed within app development no equivalent to the seems to have emerged and the rule systems applied to website design such as the have no bearing on the design of apps. On the one hand this is quite liberating for interface designers and has led to something of a Wild West populated by some truly innovative interface designs.

Bringing greater intention to development for accessibility

My intention with this post, I should point out, is not to stifle innovation, but rather I would like to propose that when an app’s primary purpose falls within certain categories of use, ‘categories’ which can be applied to the creation or consumption of educational materials or be used in support of learning, that extra attention be paid to the accessibility features of ‘said’ apps. Perhaps in the future this could resemble a set of agreed standards, but at this time I would like to make more of a humble request rather than a full recommendation. The core idea I put forth in relation to my ‘request’ is the notion of letting the user choose and customise the app through the presence of ‘adjustment’; this I believe is a key facet of the path to accessibility. I shall expand on ‘categories of use’ later in this post.

Using the Kindle app as dyslexic person

A personal experience which prompted this line of enquiry was my use of Amazon’s Kindle app for iPad. In October 2011 Apple introduced support of text-to-speech (TTS) within their iOS5 operating system (Moren, 2012); as a Dyslexic person I was eager to make use of this function and to this day find it immensely useful. Imagine my disappointment to find out that the ‘Speak Selection’ tool is actively blocked within the Kindle app. The ‘VoiceOver’ tool was later allowed within the Kindle for iPad app (Ingber, 2013) and Amazon had introduced its own text-to-speech function to the Kindle 2 device in 2009 but eBook publishers could choose to disallow the function with the viewpoint that it might damage audiobook sales (Schofield, 2009). There is another aspect of the Kindle app which always seems a bit of an oversight; reading background colours. Given the development resources available to Amazon, there are only three options provided for the text background colour: White, Black (X-Ray) and Sepia. Why not make the reading experience as accessible as possible by including customisable background colours as evidenced by apps like , and ? When comparing Kindle to particularly Kobo reader and Goodreader one is reminded of the oft used technological paradigm of VHS and Betamax; VHS won due to market share in combination with other factors rather than viewing quality.

On the topic of background colour more specifically, from a personal perspective this is the number one ‘adjustment’ which I would like to see made available in apps. Particularly those apps which are promoted as ‘readers’. My own perception of black text on a white background has been a persistent barrier to my consumption and enjoyment of reading. To help elaborate on my own experience I even created a javascript web application using to show what this experience is like for me. This is a condition sometimes known as Irlen Syndrome, Meres-Irlen Syndrome, Visual Stress or Scoptopic Sensitivity syndrome. I am hesitant to adopt any of these definitions as an explanation of my experience, as I have never received an official diagnosis. Furthermore there are some sceptical viewpoints in the medical fields when assessing the diagnostic procedures and the original studies which led to the recognition of the symptoms (Coyle, 1995; Lawrence, 2008). I prefer to view it as a complex part of my own dyslexic puzzle and one thing is not in doubt, the ability to adjust background colours, fonts and font-sizes makes a huge difference to my experience of reading.

The Adjustment Bureau

So why the title of The Adjustment Bureau? The 2011 film, The Adjustment Bureau based on the Phillip K. Dick’s short story, The Adjustment Team (1954 - ) which tells of characters whose life choices deviate from a preordained plan set-out by a mysterious organisation. Inspired by this idea I postulated that there may be a parallel between that concept and app developers whose choices are guided or pushed by a combination of external factors and client influences, ultimately I wondered whether this explains why the avenues to accessibility are so seldom followed? With all of this in mind I decided to enter into an assessment of the adjustment functionality available within some of the most prominent and popular apps I have encountered while working in Higher Education. I focused on apps available for iOS for this pursuit as that is the primary device type supported in my workplace and I had access to the devices. This also prompted me to define some basic ‘categories of use’ when applied to app use within academia for the support of learning and teaching.

Categaries of Use

The Categories of Use are as follows:

Category	Definition
Browser	A web browser for navigating web-based information. May include other features such as reader functions and RSS curation.
Composer	In this context for the composition of text-based materials and documents.
Consumer	For curation and consumption of RSS content, blogs and online news sources.
Notetaker/annotation	Apps with the main purpose of taking notes and/or placing notes and annotation on documents.
Reader	Apps with the primary purpose of reading text, eBooks, ePubs, PDF and other text formats. May have limited annotation tools.

When defining the categories I tried to resist the use of pre-existing desktop software definitions such as for example ‘word processing’. These definitions have established associations and many apps reach beyond the format-based outputs which are expected from these former software definitions.

The Adjustment Criteria upon which each app was judged are listed below. If an app includes a feature it is awarded a point for that criterion, it may partially allow a feature which would result in a 0.5 of a point. The total score is a point value out of a total of 8, for the 8 criteria and is shown as a final percentage. Apps which achieve >=60% are highlighted in purple.

Criterion	Definition
Font Size	Font size can be changed specifically, within the app. In the case of ‘composer’ categorised apps this is included in their writing functionality.
Line Height	Line height can be changed specifically, within the app. In the case of ‘composer’ categorised apps this is included in their writing functionality.
Font Style	Font style can be changed specifically, within the app. In the case of ‘composer’ categorised apps this is included in their writing functionality.
Background Colour: Invert/Brightness	Brightness of the display or invert (white text on black background) is a specific option within the app.
Background Colour: Sepia	A sepia background (beige/mild yellow) is a specific option within the app.
Background Colour: Sliders/Colour	A selection of colours or Red/Green/Blue sliders allow the user to adjust and specify the background colour within the app.
Pinch zoom	The pinch zoom is a built-in function of the iOS. Some apps do not make/allow full use of this touch-based function.
iOS Speak Selection	A function which can be enabled in the General > Accessibility functions in the iOS this can be used by selecting text in certain apps and pressing the ‘speak’ option which comes up. This is distinct from the ‘Voiceover’ option which is a complete audio interface and harder use for quick impromptu needs.

The scores as an embedded Google Spreadsheet - a work in progress. NB: this list is not designed to be exhaustive and if you have other apps which you would like me to assess using these criteria, please add them to the comments area below. The “+” next to the app title identifies that the app is available for both iPhone and iPad.

Conclusion

Through this process of investigation and app functionality testing I feel that I have only begun to scrape the surface of how accessibility functions are implemented and the possible avenues for improvement. I think that there is certainly scope to devise a more concrete scoring and testing system with the view to helping teachers and learners make informed decisions about the accessibility functions of certain apps. Such a system would also have the potential to help inform developers about the needs of specific user groups. However the responsibility cannot be squarely that of the developers, as users we also have a responsibility to let developers know what we want and need. One of the benefits of working with apps is that developers are often small to medium sized companies and really benefit from the suggestions from their user-base, this may extend to use testing. In the Wild West of apps we as the user have an opportunity to make a difference and we shouldn’t miss out by sticking to the easy path.

Appendix I - Some particularly successful adjustment interfaces discovered as a result of this investigation

Bluefire reader - this free reader app features some very nice adjustment features. However there is only a small selection of free, public domain ebooks available. The app does allow you to connect a DropBox account so you could in theory use it to read ePub files with the reader functionality.

Feedly - is a free rss feed curator with built-in links to social media services. It is very helpful for the organising categories of news sources including blogs, news sites and trends. It does have some basic and helpful tools to customise the reading experience, such as invert text colour and font size.

Goodreader 4 - an excellent and very powerful reader app. This app includes extensive adjustment capabilities as well as file conversion, compression and on-document annotation. This is the only app to score 100% in the criteria ratings and £1.99 it is a good deal.

Kindle for iPad - somewhat limited capabilities compared to some of the other reader apps, but does allow for a number of adjustments including: brightness, font size, font style, background colour, screen layout and line height.

Index Card for iPad - although this app is limited in terms of altering the background colour when you are composing text it does allow for the display of your resulting Index Cards on tinted backgrounds. This app does allows for text size adjustments and is very helpful for planning out essays and verbal presentations.

Kobo Reader for iPad - Kobo books need to be managed through an account on their website and can also be bought via WHSmiths. The app allows you to search and review free samples. This app has nice adjustment functions and also has a good notifications area which helps users to discover new features which are added to the app.

Microsoft OneNote for iPad - Unfortunately the Microsoft Office apps do not score very highly on this accessibility rating. The OneNote app by contrast has some nice function, including a number of ‘Page Color’ options under the ‘View’ tab.

Notability for iPad - this is a great app for reading, notetaking and annotation. One of its lesser known functions is the flexibility of page background colours and layouts when viewing and annotating PDF files. This app has excellent written and audio annotation options. It is comparable to iAnnotatePDF for iPad with the main difference that audio annotations can be placed contextually throughout the text in iAnnotate.

OverDrive Media Console - a reader app which will allow you to download eBooks from certain public libraries and retailers such as Waterstones. The extent of adjustment depends upon the individual eBook but this app has a lovely intuitive interface both as a local app and as a web-based reader app. The app also allows access to eBooks.

Scribd. - this reader app requires a subscription (£5.99/month) for full access to books and they carry a comprehensive catalogue of both fiction and non-fiction as well as self-published and scholarly works. It is possible to access book samples for free through the app. The text and font related adjustment options are similar to the Kindle app.

(discussed during MELSIG presentation)

This screenshot shows the reader mode adjustments which are available when you turn a page to reader mode. You can save pages to PDF with these settings.

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