Advanced HE’s flexible learning framework

Flexible learning is about student choice, putting learners at the centre of the learning experience and providing them with the flexibility to access learning opportunities around the different areas of their lives. To deliver this requires balanced pragmatism in delivery methods and institutional agility in the structures and systems used by the university to provide choice in an economically viable and sustainable way.

Flexible learning in higher education | Advance HE
Advanced HE Flexible learning framework

According to the HEA’s flexible learning framework, a choice should be offered to students in how, what, when, and where they learn through the pace, place, price, and mode of delivery.

“When well supported, this positively impacts recruitment, retention and progression; widens participation; and offers opportunities to learners of all ages, backgrounds, ethnicities and nationalities.”

Advanced HE


An undergraduate degree is 360 credits. A postgraduate degree is 180 credits. One credit is equivalent to ten notional learning hours; an undergraduate (UG) course should take a maximum of 3600 hours and a postgraduate taught (PGT) degree a maximum of 1800 hours. Current rules on the maximum duration of study for UG studies is eight years and five years for PGT; this means that the pace of study can be anywhere from 90 weeks to eight years at UG and 45 weeks to five years at PG based on a maximum 40-hour study week. Most university courses currently run off 32 weeks a year for institutional convenience, but the pace could be altered considerably to fit the student.


The place where learning is delivered or received is becoming more flexible. Traditionally courses have been offered on-campus with students travelling to the lecturer and their facilities. The Univerity of London began offering courses by correspondence in 18, posting out study materials, and asking students to attend in-person for the exam only. More recently, these correspondence courses have been replaced with online learning. As work-based learning becomes essential and workplaces increasingly partner with universities for higher education, this provision is being delivered in the workplace or other facilities where specialist equipment or experiences are avalible. 


Most mature students see higher education prices as the most significant barrier to enrollment. Changes to funding have seen considerable drops in part-time student numbers over the last ten years. The Augar report made suggestions to address this, and the Government is set to enact many of these, including a part-time postgraduate loan that allows students to study flexibly. Many part-time postgraduate courses have begun to offer flexible payment options, including per module, per term, or annually.


The OECD lists the mode of study as the student’s study load, whether full-time or part-time, but may also refer to distance, a mixture of on-campus access methods, or various work-based learning options. HESA, the higher education statistics agency, lists up to 16 different modes of study, categorised primarily for funding purposes, including: 

  • Full-time – according to funding council definitions or other
  • Sandwich – thick, thin, or other
  • Part-time – regular, released from employment, or not released from employment
  • Evening only
  • Open or distance learning
  • Writing-up – previously full-time
  • Continuous delivery

These modes aim to provide students with options to access study that fits their need and availability.

Sign up to view the full framework on the Advanced HE website.

Narrowing the digital divide

To learn online, you need a stable internet connection and an internet-enabled device such as laptops or smartphones. However, when the March 2020 lockdown hit in the UK and universities and schools moved online, 11% of households did not have access to the internet, according to the Office of Communications (OFCOM). One year later and that number was down to 6%.

A new OFCOM report on Adults’ Media Use and Attitudes published on the 28th of April states that “The pandemic had been the catalyst for a step-change in digital skills…” but warned that 1.5 million UK homes still do not have access to the internet. The research showed that 10% of users access the internet via a smartphone only, and 20% of children did not have constant access to a device for online learning during the lockdowns.

The recent Office for Students guidance paper found that around 30% of university students surveyed lacked good internet access, and 30% lacked a suitable study space. If the 30% from the survey translates to the whole 2.38 million UK student population, that is roughly 300,000 students with digital access issues. 

During a regular year, this would have been covered by on-campus facilities. The University I work at provides computers in study spaces across its campuses, includes a computer finder tool in the student app, and high-speed internet in all its accommodation. But with social distancing and full lockdowns, these facilities were in limited supply, halls become the primary social spaces as external spaces were forced to close, and many students found themselves returning home to shared devices, bandwidth, and workspaces with parents and siblings. 

The Gravity assist paper recommends that university providers make digital access a priority:

  • Appropriate hardware for students to access course content with parity of experience. 
  • Appropriate software for students to access course content
  • Robust technical infrastructure that works seamlessly and repaired promptly
  • Reliable access to the internet with sufficient bandwidth
  • A trained teacher or instructor equipt to deliver high-quality digital learning and teaching 
  • An appropriate study place that is quiet and consistently avalible

Most universities have adapted to the challenge, providing year-long laptop loans, broadband dongles, and technical support to those students that need it. Academics have rapidly upskilled with digital teaching practices and redesigning courses to adapt to the changing access to students. Software vendors like Microsoft and Virtual Learning Environment vendors like D2L have adapted too, rapidly releasing new tools and dramatically increasing infrastructure to handle the shift to online. 

Many of these fixes were put in place as short-term solutions, and universities, academics, and tech companies must now find long-term solutions that do not disadvantage this 30% of students. The Office for students suggests that institutions start to engage with students individually before their courses start. Universities should offer solutions where needed, such as loaning laptops, financial support, and creative study space solutions, in the same way other additional needs are currently handled.

Flexible learning should hold an advantage for students from the most deprived areas of the UK, allowing them to study around their many additional commitments caring responsibilities, part-time work, and commutes. Significant progress has been made over the last twelve months to provide equal access to higher education; we need to put the same level of planning into maintaining digital access for all.  

September 2021: Back to what normal?

Today I attended AulaCon, the annual conference of the UK based Virtual Learning Environment provider. The title of the event was ‘September 2021: Back to what normal?’ and hosted a range of expert speakers giving views on the future of higher education in the UK. the underlying theme for the day was that returning to campus is an opportunity to refocus on designing and delivering outstanding learning.  

My three key takeaways:

  • Lecturers must focus on doing what works best
  • Returning to campus should be designed to build better learning communities
  • Learning should be structured to spark curiosity

John Hattie opened to conference with a conversation about evidence-based teaching. He suggested the most lectures find a way to teach that works but do not then spend the time investigating the best ways to teach. Hattie, who has spent his career studying teaching methods that have the highest impact on student outcomes, recommends looking at the most successful practice in your institution and scaling that up as a starting point. Hatti also stressed the importance of monitoring student conversations and feedback and the impact of your teaching rather than being overly worried about the exact method. A final piece of advice that Hattie has picked up from working with athletes, a theme of this blog, is to start each teaching session by setting an expectation of what success in that session looks like and then trying to stick to that, 

One of the common themes in student feedback this year has been the loss of community. The social elements of learning and being a part of the university community are essential to keep students engaged and feel belonging, helping them stay and succeed. Multiple speakers also pointed out that these communities should move beyond the classroom and individual modules; they should start in the transition period before students begin the course, build while studying, and continue after they graduate. Recommendations for building community came from several presenters; most said to start small, make it inviting for students to talk and take the time to build up trust within groups. Students need to feel comfortable interacting with each other and are not afraid to ask questions and make mistakes. Get students to start talking using breakout rooms and chat functions, and let them know it is there thinking you want to influence, not just taking in information. Conversations are also to keep students engaged in their learning. The critical point was that academics must be a part of the community to make them impactful and lasting.

Ramsey Musallam presented his take on how lessons should begin by sparking curiosity in students before delivering all the content. He suggested that story narrative such as the heroes journey could be used as a model for providing lessons where the students are moved into uncertainty through open questions and missing information. Only when curiosity is teased in students that the teacher can then reveal the complete picture. The narrative approach allows students to make connections between ideas and engage with the learning process. Musallam provides a lesson planning template lecturers can use to structure a session using the hero’s journey following the 5E inquiry learning cycle. 

Aula has a fresh take on what a VLE should be and has built its platform on internet technology without the difficulties existing providers face with bloated, sometimes over-complicated software that has evolved over decades of updates to serve multiple industries across the globe. The co-founder and CEO, Anders Krohn’s focus on learning design is also refreshing. It is not yet clear how much of the market Aula will capture in the next few years, but the new kid on the block is set to disrupt the now established Virtual Learning Environment market currently dominated by three companies. The incumbents need to take note of Aula’s approach if they want to stay competitive. 

The four points of a good start up pitch

This morning the following tweet was trending globally. Paras Chopra is a Delhi based tech entrepreneur and founder of Wingify, a web platform. Although I work in an established institution, I have created my learning design team from scratch. We are currently working on expanding our impact at the university, so it caught my interest.

The four points of a good start up pitch

According to Investopedia, an intrapreneur is “an employee who is tasked with developing an innovative idea or project within a company.” As an intrapreneur, you can borrow much of the behaviours and tools of an entrepreneur, such as risk-taking and innovative approaches to build and launch your internal project. The idea of a startup pitch for a new business function set up to target a new market, such as non-traditional students, can help to justify funding from the company in the same way a startup seeks funding from venture capital.

Paras’ four elements of a startup pitch are:

  • How is the product 10x better than alternatives (with proof)
  • What’s their moat
  • How they can acquire users profitably at scale (with evidence)
  • Hustles that the team has done in their careers

The first point, how is the product significantly better than alternatives, should be easy to answer and forms the basis of what your business function does. Once you have a hypothesis, it needs testing. Testing the product to get proof of its superiority over alternatives needs to be done with prototypes and prospective customer interviews in the early stages. Once up and running, the next job is to gain as much data as possible from early customers that the product is 10x better or continue to iterate until this is true.

A startups moat is how the new business can protect its product, gain and retain market share. A startup pitch must suggest how the company can avoid or create barriers to entry that stop other companies from taking over their business. Moats might include brand loyalty, economies of scale, geographical barriers, being first, integration with other parts of a supply chain and legal obstacles such as a patent. As an internal project, it is likely that fully integrating into the organisation, geographic access, and brand loyalty are likely moats to pursue.

Shareholders don’t pay for the castle, they pay for the moat.

Warren Buffet

The prototype testing should provide some data for acquiring users as, without a solid plan to build customers, the rest of the plan is not important. Word of mouth is the most reliable user acquisition method, but some form of advertising will be needed for this to scale. Popular user acquisition methods include building a social media following, paid search ads and search optimisation, and ad agencies and networks. Internal project teams can use cross-promotion with existing users from other business areas.

The pitch is about getting much-needed funding to support growth. To get people to part with money, they need to trust the team can deliver on the other three points. Many venture capital firms and large companies may be more interested in backing people than the idea. Good people will adapt and change an idea till they find something that works. It is essential to leverage what the team had done before joining the startup in the early stages. This currency will only last so long before the people expect to see what the team members have been able to do since joining the startup. Spend time developing the narrative around the people in the team to build trust that you can deliver what you say you can in the other three points.

Paras Chopra list of four points for a startup pitch provides an excellent framework for either an entrepreneur or intrapreneur starting or building a new project. By focusing on how the product is better, how it will stay better, how it will grow, and evidencing that the team can deliver this, you will build trust from internal or external investors. Can you answer these questions convincingly for where you currently work? If you can, then great; if not, you know what you have to do.

Searching (2018)

Today I rewatched the 2018 film ‘Searching’ directed by Aneesh Chaganty. The movie is worth a watch just for the way it is filmed. All the shorts are through the desktop of the main character’s computer, with the story told through video calls, text messages, web searches, and the occasional TV news report. It sounds like it would not work, but it does, partly down to the excellent editing.

The exciting thing about this film is how much you can do with your computer if you set up a link between your phone and laptop. The main character approaches the investigation into his daughter’s disappearance like a ninja project manager. He starts by creating a table with questions that he then goes through each of his daughters 96 Facebook friends completing a row for each. He goes through search history, social media accounts, text messages, and email, meticulously logging everything he learns and gradually finding clues to create a timeline of the days running up to the disappearance. 

The situation in the film is extreme, but it showcases how much of the world’s information is online and how a computer can aid a systematic approach to solve a problem. It raises the question about how much more productive you might be if you learned to use your computer better and how methodical you are in your approach and documentation when problem-solving.

Two tasks for me this week:

  1. Become a power user with my computer
  2. Be deliberate in my approach and documentation in my problem-solving.

The four stages of changing a VLE

Virtual Learning Environments (VLE) are web-based platforms for the online elements of courses. Over the past year, they have been essential tools in the delivery of learning as most teaching has gone remote, and their role is likely to remain a crucial part of courses in the future. With this dramatic increase in prominence, many universities are likely to evaluate the tools they currently have and begin to assess what is missing and how their platforms can be improved. 

The big question is should we invest in our current platform or spend the next two years and considerable resource moving to a different one?

Moving VLE is a two-year project. It can be broken down into two broad areas; year one is completing the tender process to select a new platform, and year two is for implementing that chosen solution. You can further break these two areas down into four six month stages for changing your VLE:

  1. Writing the tender
  2. Selecting a vendor
  3. Technical implementation and pilot
  4. User implementation

Writing a tender

The first stage starts with a review of the current platform’s strengths and weaknesses and a collection of requirements for the future of teaching and learning at the institution. You may choose to bring in selected vendors, including your current provider, to present their software’s latest features and future roadmaps as a soft market test before the decision to stay or move are finally made. The information collected at this stage is documented in the tender paperwork and sent to vendors for a written response. This final step and the next stage are likely to be through a formal procurement process that your finance team will support your through.

Selecting a vendor

The vendors will formally respond in writing to your tender documents, and the university will need to go through each scoring the responses against the requirements. The top-scoring vendors can then be invited in to present how their software will meet the stated needs. Getting as many academics involved in these sessions is crucial to selecting the best fit for the university. Once the successful VLE provider is specified, the contract negotiations and procurement checks start. Do not underestimate how long this process might take – I would suggest leaving a minimum of three months from when you have selected the successful provider for all the contract details to be agreed upon and data protection and legal checks to be processed.

Technical implementation

You now have a new shiny VLE! It needs to be integrated into the Universities systems, the single sign-on, the student record system, and other teaching and learning platforms. The platform will also have to be configured with the options that best suit the way it will be used. The better you have captured the requirements in stage one, the easier this stage will be. Getting the VLE set up and ready to use by the whole university can be challenging. A large scale pilot, moving over a department or school during the technical implementation, can be an effective way to identify and fix any minor oversights or fine-tune settings. Make sure you select courses that are happy to get the new shiny toy in the understanding that it will have bugs.

User implimentation

You have collected requirements in a tender document, you have selected the best provider to meet these requirements with a great deal, and you have integrated it into your systems; you now need to manage the change. The final stage can be the most disruptive; most academics will not have been involved in selecting the tool and will be unforgiving if the move over is not smooth. Communication, automated processes, well-planned training and support, and a much better system will help the user implementation but do not underestimate the resource requirements for this stage; it might cost in time and effort multiples of the contracts first-year costs. 

There is some excellent information on the internet on how to manage the four stages introduced here successfully. Most countries have HE specific learning technology networks that can provide a lot of help and guidance. If in doubt, get the VLE vendors in as early as possible to start the conversation and ask many questions, it is a highly competitive market between the top three providers, so the quality of the customer service can be outstanding.

Please feel free to get in touch on Twitter if you are going through the process and have any questions. I am happy to pass on the excellent help I have received during reviews and tenders in the past. 

eCommerce Benchmarks

I have been following Dynamic Yield since it was purchased by McDonald’s in March 2019. Dynamic Yield works with over 350 global brands developing online customer personalisation. The tech firm has an excellent newsletter covering marketing, data analytics, and digital personalisation. It offers several free services on its website, including case studies, a learning centre, and an eCommerce benchmarking tool. 

Dynamic Yield provides monthly eCommerce benchmark data for seven key markers. The data can help companies keep track of what is going on in their industries, identify strengths and weaknesses in their eCommerce platforms performance, and aid the creation of marketing plans. The data is aggregated from over 200 million monthly users and 300 million sessions from Dynamic Yield’s customer base.

The benchmarks and their 12-month global averages:

  1. Device Usage – % of traffic per device: 65% mobile, 32.17% desktop, and 2.83% tablet
  2. Conversion Rate – % of completed purchases by visitors: 3.21%
  3. Add-to-Cart Rate – % of items added to cart after product page view(s) by visitors: 7.16%
  4. Cart Abandonment Rate – % of items left in carts and not purchased by visitors: 70.83%
  5. Average Order Value (AOVs) – Average dollar amount per order: $130 
  6. Units per Transaction (UPTs) – Average number of products bought per order by visitors: 2.87
  7. Average Transaction per User (ATPU) – Average number of transactions made per visitor: 0.09

Each benchmark can be filtered by device, region and one of eight industries. The data is updated monthly and includes the last twelve months worth of averages for identifying trends. The Conversation rate and Cart abandonment rate KPIs also have detailed explanations, strategies for improvement, and additional resources. 

You can find Dynamic Yield’s benchmark tool on their website. 

The digital marketing funnel

Smart Insights is a digital marketing publisher and online learning platform run by Dr Dave Chaffey. Chaffey is the author of the excellent book Digital business and e-commerce management, which I studied during my Information systems and management degree. I have been reading up on digital marketing this week, and I came across one of Chaffey’s frameworks that organise and simplify modern marketing.  

Smart Insights RACE framework lays out the marketing funnel to help people plan and manage a digital marketing strategy. The framework includes; plan, reach, act, convert and engage and shows the critical measures for target setting and evaluating each stage of the marketing funnel.

The Smart Insights RACE Framework

  1. Plan: Define your goals and strategy 
  2. Reach: Grow your audience using paid, owned, and earned media
    1. Buyer stage: exploration
    2. Key measure: audience volume, audience quality, audience value and cost
  3. Act: Prompt interactions, subscribers, and leads
    1. Buyer stage: decision making
    2. Key measure: leads/lead conversion rate, time on site, subscribers/likes/shares 
  4. Convert: Achieve sales online or offline
    1. Buyer stage: purchase
    2. Key measure: sales, revenue/profit, conversion and order value
  5. Engage: Encourage repeat business
    1. Buyer stage: advocacy
    2. Key measures: repeat purchase (lifetime value), brand satisfaction and loyalty, advocacy 

Find out more about the marketing RACE planning framework on the Smart Insights website.  

How many hours does it take to transform a campus-based university module to online learning?

recent post on WONKHE, the higher education policy news site stated that it takes 80 hours to convert an existing module into an online or blended one. WONKHE gave no details for where this number came from other than academics had repeatedly mentioned it as the time required.

This comes as no surprise; speaking with hundreds of educators across the sector, we know that, on average, it will take 80 hours to transform a module from face to face delivery with lectures and seminars to high quality online or blended delivery.


I want to do a thought experiment for fun as to where these hours might go. I will make many assumptions, so comment at the bottom to correct me or suggest better hypotheses to use. 

My first assumption is that the 80 hours are on top of the existing workload allocation. The module team would use the standard hours for prep and delivery of live (synchronous) learning and facilitation of on-demand (asynchronous) learning.

Assuming the average university module is 20 credits, and one credit is equal to 10 hours of notional learning, students should spend 200 hours on average completing each module. 

The term ‘notional learning time’ is used to denote all time expected to be spent by a student in pursuit of a higher education qualification. This includes independent study and reading, preparation for contact hours, coursework, revision and summative assessment. This term is used because the actual time that learners need to achieve designated learning outcomes varies considerably. Notional study time of ten hours per credit is the agreed tariff that higher education providers use in designing their programmes and learning outcomes for higher education qualifications, with 360 credits making up an honours degree.

Let us assume that a module might be delivered over half an academic year, over 15 weeks, with a one hour lecture and two one hour small group seminars per week as contact time. That would mean that the academic would have 45 hours of teaching time to convert from campus-based to entirely online or a blend of online and campus-based. The other 155 hours would be made up of independent study and working on assessments. This conversion is due to the pandemic, so the independent study and assessment would probably not change too much, even if the assessment is transformed from a three-hour exam to a 24-hour open book exam done remotely.

So, 80 hours to convert 45 hours of teaching to online learning.

Let us further assume that the seminars will stay live (synchronous) through Microsoft Teams or Zoom or, if they are lucky with rooming and social distancing, stay live on campus. That gives us 15 hours of online content and activities to create to replace lectures. 

So, 80 hours to convert 15 hours of teaching to online learning. Suppose the academic spends four hours redesigning their module through a workshop activity like ABC, and six hours of training and experimentation to use the software. In that case, this gives our fictional academic 70 hours to create 15 hours of online content and activities for our made-up module.

70 hours of development time to produce 15 hours of video content, text, activities, and self-mark questions mean 4 hours and 40 minutes of development time per hour of online learning. 

Let us say that each one hour lecture is 40 minutes of content and then 20 minutes of discussion and answering questions on an audience response tool like Mentimeter. If we allocate 40 minutes of development time to set up a discussion forum and convert the questions to the VLE quiz tool, that leaves four hours to develop four ten minute videos or one hour per ten-minute video.

To sum up, a Module Leader might spend 80 hours converting their existing module to online:

  • 6 hours of training
  • 4 hours of design using the ABC model
  • 70 hours creating content
    • 1 hour for each 10-minute video
    • 40 minutes for each 20 minute activity time

This is a tough ask for academics that may not have the digital skills or technology at the start of the pandemic to transform their modules in just 80 additional hours. It is important to note that these 80 hours will not have been given to academics within their usual workload but instead done on top of everything else.

Let me know what you think in the comments or via Twitter if you want some discussion.

The basics of learner analytics

Each time a student logs into your institutions Virtual Learning Environment (VLE), a new session is logged in its database. The summary of login information can be helpful to assess student engagement over time. Three metrics are beneficial:

  1. Average session duration: The average time students are active on the VLE for each login.
  2. Frequency: how often a student logs in over a given period, such as a week or month.
  3. Recency: The duration since the last session on the VLE.

You can use the average session duration to assess if students are engaging longer with their online learning. This metric requires your VLE to accurately measure when the student is active and does not just have the VLE open in a tab while watching Average session duration is beneficial at the course or module level to track the time students are on the VLE against the expected time and at the institution level to track progress from year to year.

The average frequency of sessions is a good marker for how engaged students are on a course. You may set expectations of how often a full-time student is supposed to log in, at least once per working day, for instance, and then you can track against this. 

Identifying students at risk of dropping out of a course is crucial as they may need support. Tracking students who have not logged into the system for a set number of days, say five during term-time on a full-time course, will allow you to identify students who might need academic or pastoral help. The recency table will help you determine how long it has been since students last logged in and show the number that falls outside your expectations. 

For these three metrics to be valid, you need to have trust in their accuracy; this includes the technical accuracy of how they are tracked and how it captures all the online activity a student might complete. Other metrics can help, but these are a great starting point.