An Effective Online Framework for Lifelong Learning (WCOL 2019)

By Gerard Creaner
Publication Date: November 2019

This paper was presented at the World Conference in Online Learning (WCOL) 2019

Table of Contents (click to the section you would like to read):

• Abstract
• Introduction
• Background and Previous Research
• Conceptual Framework
• Research Methods
• Results of Research
• Theoretical Framework for Analysis
• Analysis of Results
• Discussion
• Conclusion
• Bibliography
• Further Reading

This paper examines one private training provider’s experience building an effective online framework for lifelong learning.

With a focus on delivering training for the pharmaceutical manufacturing industry, and using the

analytical lens of behavioural economics, it draws on this experience to model the development of a mature workforce over a seven-year case study (2012-2019), across two locations (Ireland and Singapore), involving 2,000 workers.

Contextual data for the paper were drawn from relevant economic policy and employment literature for each case study location, from relevant pharmaceutical sector publications, and from original training documentation generated during the seven-year case study.

This paper is broadly practitioner research using case studies as illustrative of real-world phenomena. The perspective is reflective, rational enquiry with the aim of better understanding the successes achieved for replication in the future. The case study data are presented and analysed using Bereday’s four stages in both methodology and structure: description, interpretation, juxtaposition, and comparison, augmented with a fifth initial stage ‘intuition’ as suggested by Cirigliano (Cirigliano,1996).

The study aims to better understand the underlying motivations and drivers of experienced workers who wished to make a mid-career change. This is achieved by testing the effectiveness of the training provider’s established framework for online programme delivery and analysing participant feedback.

Insights into current programme effectiveness as well as areas for improvement lay out a process that could be implemented across a range of next-generation, high-tech industries, in many countries.

The conclusions are based on interpretation of the data using the analytical lens of behavioural

economics, and offer insights into how governments might harness the potential of online lifelong learning for experienced workforces, to transform lives and societies.

Key findings include:

• Proof of the robustness of the previously developed Sourcing, Education & Career Coaching (SEC) framework.
• Successful outcomes (completing the programme and/or finding a job) were independent of the individual’s years of work experience or highest previous academic qualification.
• Satisfaction rates with the programme screening and delivery were generally higher than the number of students who had a successful outcome from the programme at the time of survey.  It appears that many currently unsuccessful participants remained optimistic about their future potential and, therefore, provide an engaged cohort for further intervention.
• Nudge Theory (from the field of behavioural economics) could provide insights to increase the percentage of students with initial successful outcomes, as well as ways to further develop currently unsuccessful participants.

Key Words: Online Learning Initiative, Lifelong Learning, Behavioural Economics, Prospect Theory, Loss Aversion, Nudge Theory

This paper aims to examine the success of a current online framework for lifelong learning, and consider areas for further development. The private training provider in question reskills experienced workers from other industries to meet the skills shortages currently being experienced in both Ireland and Singapore’s pharmaceutical manufacturing industries. 

The pharmaceutical manufacturing industry is a key pillar of the Irish economy (17% of GDP, 45% of exports, $50 Billion Capital Asset Replacement Value, and employing 50,000 workers)(IDA, 2015). Likewise, in Singapore, it is the fourth pillar of their economy (5% of GDP, $15 Billion Capital Asset Replacement Value, and employing 6,000 workers)(EDB, 2019). 

The opportunities that pharmaceutical manufacturing industry growth and ongoing investment brings to both Ireland and Singapore are numerous, and include: 

1. Employment – one of the most obvious opportunities this level of investment brings is well-paid locally-based jobs. 
2. Development of an industrial “cluster” – as pharmaceutical companies expand their operations, the number and range of specialist supporting companies who offer services to the industry will increase. 
3. Specialised workforce – the presence of specialised manufacturing sites means the workforce develops to reflect that need through flexible vocational education programmes. 
4. Financial – at a Government level, strong high-tech industries are needed for a strong economy. At an individual level, these local jobs are well-paid, stable, and secure. 

Over the past seven-years, this private training provider’s vocational education (VE) programmes have been delivered to experienced workers with five to twenty-five years’ work experience, who are returning to employment or changing their career. They are particularly focused on individuals appropriate for operator and quality technician roles in the pharmaceutical manufacturing industry, since this is where significant skills gaps occur when the industry expands in a given location. These online programmes also provide a pathway to academic accreditation at Bachelor degree level. 

The key objectives of this online VE are: 

1. To help governments and industry build local talent pools of operator and quality technicians 
2. To support the expanding pharmaceutical manufacturing industry 
3. To utilise online VE to teach the quality systems necessary to consistently manufacture safe and effective medicines for patients 
4. To give individuals the knowledge and skills needed to make a successful career change into the pharmaceutical manufacturing industry 

This paper will focus on three different groups across two locations – unemployed workers in Ireland, employed workers in Ireland, and employed workers in Singapore. It aims to objectively measure the success of the current Sourcing, Education & Career Coaching (SEC) framework and identify areas for further improvement. 

Insights into current programme effectiveness as well as areas for improvement will lay out a process that could also be implemented across a range of next generation, high-tech industries, in many countries.

The private training provider has developed VE programmes that are academically accredited as Continuous Professional Development (CPD) certificates leading to a BSc degree in the Manufacture of Medicinal Products (Level 7). Programmes have been validated, approved, and accredited for an online delivery format. Curriculum development is rooted in delivering career-focused VE to meet specific industry sector requirements.

Previous work in this area was reported by the author at the Research Work Learning Conference 2015 in Singapore. The main finding from that work was that while current theory and Government strategies support the building of a knowledge-based economy through lifelong learning of its workers, it appears that neither employers nor workers want to invest their time and effort once the resource is hired or the job is secured (Creaner, 2015). That paper also raised the question of whether a nation can develop a knowledge-based economy without the emotional support of its citizens and employers for lifelong learning. (Creaner, 2015)

This study further builds on the conclusions of that paper, and aims to uncover more insight into the drivers and motivations of experienced workers using VE to facilitate a mid-career change.

Previous data gathering, research, and analysis of student statistics and feedback to the training provider has led to the development of a three-stage process – the SEC framework – Sourcing, Education, Career Coaching.

Sourcing and screening of candidates is the process by which the training provider assesses whether a candidate is a good fit for the programme and for a career in the industry.

Rather than selecting candidates exclusively on their previous academic achievement, each candidate is assessed for their overall suitability for a career in the industry, with a focus on their transferable skills gained across a wide range of work experience. To help establish this, a phone call is conducted with every candidate prior to their acceptance onto the programme. This rigorous screening process results in only 300 people (6%) of the 5,000 initial applicants being accepted every year. This combination of sourcing and screening is a key component to having only the most suitable candidates being enrolled.

This is the part of the SEC process where the technical modules are delivered in a virtual environment. The modules utilise a variety of learning methods including short videos, lecture notes, self-assessment quizzes, and reflective questions each week to deliver the technical knowledge needed for working in this highly-regulated industry. 

This is accompanied by regular weekly contact from a course coordinator (i.e. pastoral support) to maintain accountability and motivation by the student to progress through the course.

In response to feedback from previous students, an online career coaching module was added.

Since these students are experienced workers looking to make a mid-career change, some are apprehensive about how easily they’ll be able to find a job in a new industry and others are overly confident. This module has been designed to normalise those different mindsets and it includes a step-by-step process for navigating the complex path to finding a job in a new industry. The end of module assignment is a simulation of a job application (using a real job advert) and each student is given specific feedback on areas for improvement in future job applications.

When this was first introduced (as an elective module), less than 25% of students chose to take it. After proving its effectiveness, it has now become a mandatory component of the overall mid-career change programme. It was observed that a significant proportion of students display the Dunning-Kruger Effect (where they believe their abilities in a particular area are greater than they actually are) (Kruger & Dunning, 1999) and they believe, as experienced workers, that they already possess the necessary job hunting skills to secure a new job. Many are shocked by the amount of information they were previously unaware of and, as a result, students are overwhelmingly positive about the module’s content.

Using the SEC framework, a robust system for finding and training local workers has now been established. This study is aimed to objectively assess the success of this framework before going on to look at areas for further improvement.

This paper is broadly practitioner research using case studies as illustrative of real-world phenomena. The methodology for comparison of the three case study groups draws heavily on Bereday’s model of comparative styles and their predispositions (Bereday, 1964). 

In Bereday’s model, ‘everyday’ comparability is distinguished from socially-scientific or laboratory methods. The everyday comparability approach fits with individualistic practitioner research in that it favours establishing relations between observable facts, noting similarities and graded differences, drawing out universal observations and criteria, and ranking them in terms of similarities and differences. 

In everyday comparability, the view is subjectively from within and deliberately without perspectives detachment. It focuses on group interests, social tensions, impact factors and collective beliefs, patterns, and behaviours as experienced by the author. 

In terms of analytical steps, this paper uses Bereday’s four stages as illustrated by Jones (Jones, 1971), as follows: 

• Stage 1: Description of each case using a common approach to present facts 
• Stage 2: Interpretation of the facts in each case using knowledge other than the author’s 
• Stage 3: Juxtaposition for preliminary comparison using a set of relevant criteria 
• Stage 4: Simultaneous comparison, emergence of conclusions and hypotheses 

The perspective in this paper is the author’s own as the private training provider of vocational education programmes in the two case study locations, mindful of the particular risks of insider research (Rooney, 2005).

As part of the validation and quality system metrics for this academically accredited programme, the training provider carries out an annual survey of students. 

The data gathered for this paper are quantitative. The limitations of quantitative studies – as potentially statistically relevant due to large data sets while being humanly irrelevant, missing the contextual details surrounding the results – are acknowledged. However, in this case, in the straddling between insideractor mode and outsider-observer mode (Robson, 2011), and due to the research question in hand, the research generated provides a large enough basis on which to build observations. 

This is a descriptive study where the subjects are only measured once after course completion. The training provider surveys an average of 200 students per year, out of a total student population of 300 students. 

Students answer 60 questions across five different categories to establish a full profile of the answers in relation to each other and in relation to other students, past and present. The five categories are: 

1. Employment status update 
2. Application screening process feedback 
3. VE programme feedback 
4. Career coaching programme feedback 
5. Recommendations for future improvements to the programme (this section provides some qualitative data through open-ended written responses) 

The following demographic data are also gathered from each respondent:

1. Age (using 5-year bands through 24-50 age range) 
2. Highest previous qualification (Levels 5-9) 
3. Exam results for each module 
4. Employment outcome 

The data for this paper were gathered directly by the training provider using tools including Survey Monkey and Typeform. The data has been processed for ease of reading using Microsoft Excel. For data organization, interpretation, analysis and presentation, the total answers have been processed into descriptive statistics (i.e. summary statistics broken down answer-by-answer, year-by-year).

Data analysis began by looking at student “satisfaction” surrounding the full SEC process (i.e. screening process, the delivery of the online study materials, and technical support during the programme).

Table 1. Analysing key metrics surrounding student’s satisfaction with the programme delivery, pastoral, and academic and technical support for the 2017 and 2018 student years.

When asked about their attitudes and outlooks on lifelong learning, career advancement, and future job security, the following data resulted:

Table 2. Analysing key metrics surrounding student’s attitudes to lifelong learning, career advancement, and future job security for the 2017 and 2018 student years.

The number of experienced workers who had a successful outcome, defined as completion of the programme and/or getting a job by the time of survey, is noted in Table 3 below. This confirms the high percentages of successful outcomes for 2017 and 2018 (82% and 76% respectively) and the robustness of the online SEC framework for lifelong learning.

Table 3. Comparison of 2017 and 2018 looking at students and their outcomes in the case study of “Unemployed Workers in Ireland”.

An analysis of the survey feedback data indicated that successful completion of the VE programme and finding a job were independent of a student’s years of work experience or their previous highest academic qualification.

Figure 1. Analysis of “Employment Outcome (%)” as it relates to “Work Experience (Years)” and “Highest Qualification at Entry (Level)”

Figure 2. Analysis of “Academic Outcome (%)” as it relates to “Work Experience (Years)” and “Highest Qualification at Entry (Level)”

Bereday (Bereday, 1964) suggests that setting cases out in juxtaposition using criteria or variables that emerge naturally from the data, will identify areas of convergence and areas of difference. Following this process, the variables and findings are presented in Table 4.

Table 4. Cross-comparison of variables across the three case study groups (in the two locations) including sample size, qualification, % completion, % employment, % satisfaction.

The processed data has surfaced three main questions:

1. Why did some people complete the programme and others did not (when all were capable of doing so)?
2. Why did some people get a job and make a mid-career change during/after the programme and others did not (when all were capable of doing so)?
3. Why are people equally happy with the programme irrespective of whether they have had a successful outcome from it or not?

In order to answer these questions and better understand the reasons why a number of students did not achieve a successful outcome (and with a view to increasing that percentage), a discussion in the area of human decision making was explored, focusing on the field of behavioural economics.

The aim of the field of behavioural economics is to understand and apply the “human factor” to the decision-making process in economics, unlike classical economists who construct their theories on people making simple rational/logical decisions and choices (i.e. the theoretical concept of the logical/rational “Economic Man”).

The analytical lens of behavioural economics in understanding the “how” and “why” of human factors in decision making, and in particular Bounded Rationality, Prospect Theory, Nudge Theory and the Dual System Planner-Doer model to interpret the data about successful outcomes for this group, will lend insight into building a sustainable and effective online framework for lifelong learning.

The founder of modern behavioural economics was Herbert A. Simon, who won the Noble Prize for Economics in 1978 for this theory of Bounded Rationality. He suggests that humans are satisficers and not optimisers i.e humans are bound by three things when making a decision:

• Amount of information available
• Their cognitive limitations
• The amount of time they have

Herbert Simon’s work was further built upon by Daniel Kahneman and Richard Thaler, both of whom also won the Noble Prize in Economics (2002 and 2017 respectively) for their contributions to this field.

Prospect Theory was developed by Daniel Kahneman and Amos Tversky in 1979 after completing detailed research to explain how people make decisions that involve risk and uncertainty. This resulted in developing models to explain Loss Aversion and the Sunk Cost Fallacy.

Loss Aversion:
Where “Losses loom larger than gains” in our minds (Kahneman & Tversky, 1979), suggesting that the psychological pain surrounding a loss is twice as powerful as the happiness that surrounds a gain.

Sunk Cost Fallacy:
Sunk Cost Fallacy is where individuals will continue a behaviour or project to avoid a loss of time, effort, or money they have previously invested or “sunk” into a project and they will keep sinking time, effort, or money into the project to avoid having to cut ties. Research suggests that humans are sensitive to sunk costs after they have decided to pursue a rewar

The Dual-System Planner-Doer Model is about self-control in decision making and how humans appear to utilise a dual-system for making decisions. This was identified by Thaler as the Planner-Doer Model in 1981 and it was developed upon by Kahneman (& Tversky) as the System-1/System-2 Model in the book “Thinking Fast and Slow” (Kahneman, 2008). The theory explains some people’s ability to invest effort now or to plan/wait for a future benefit. This model further explains the theory of Delayed Gratification.

Delayed Gratification Theory – the Stanford Marshmallow Experiment:
In the 1960’s, Walter Mischel tested 4-year old children’s ability to demonstrate delayed gratification (commonly known as the marshmallow experiment). Following up 10-years later, he found that the ability to demonstrate delayed gratification at this early age was a valid predictor of success in adult life.

Nudge Theory was developed by Richard Thaler and Cass Sunstein in 2008. It suggests that the framing of a choice can significantly change the decision that people make, and so “choice architecture” can help people make “better” choices for themselves (Thaler & Sunstein, 2008). Nudge theory has now been adopted by several government agencies, including the UK Government’s Behavioural Insights Team. It is hypothesised that nudge theory design can provide the basis for future improvements to increase the number of successful outcomes from this VE programme.

Following the juxtaposition of the three groups within the two case study locations (Stage 3 Bereday) in Section 5, a simultaneous comparison is now conducted for the emergence of conclusions and hypotheses in tabular form below (Stage 4 Bereday). This is focused on considering the decision making process for these students looking to make a mid-career change, through the analytical lens of behavioural economics.

The three tables below are constructed with each of the three key questions (outlined Section 5) and are examined separately against each of the relevant behavioural economic theories.

Table 5. Comparison of why some people finished the courses and others did not, through the analytical lens of Bounded Rationality, Prospect Theory, and Dual-System Planner-Doer Model, with suggested Nudges to increase successful outcomes.

Table 6. Comparison of why some people got a job and others did not, through the analytical lens of Bounded Rationality, Prospect Theory, and Dual-System Planner-Doer Model, with suggested Nudges to increase successful outcomes.

Table 7. Comparison of why people were overall satisfied with the programme even if they did not achieve a successful outcome, through the analytical lens of Bounded Rationality, Prospect Theory, and Dual-System Planner-Doer Model, with suggested Nudges to increase successful outcomes.

The data gathered shows that overall, students are extremely satisfied with both the operational procedures and the content of the VE programme.

Successful outcomes (either completing the VE programme or getting a job) for students are seen to be independent of their years of work experience and previous academic qualifications. This suggests that the online SEC framework is successful in both finding appropriate candidates and comprehensively training them for a career in this high-tech and highly-regulated industry.

When the online Sourcing methodology of the SEC framework is applied to the initial pool of enquiries, it leads to approximately 6% being accepted and enrolled as students. It is suggested that this methodology is creating a normalised pool of candidates who are all a good fit for the pharmaceutical manufacturing industry (and that the industry is a good fit for them).

If this online framework can be successfully applied to this high-tech and highly-regulated industry, it is suggested that it could be applied more widely to identify and train workers for other industries.

With successful outcomes independent of the work experience or highest previous academic qualification, 82% of 2017 students and 76% of 2018 students completed the programme and/or got a job. To better understand how to improve on this success, an analytical lens of behavioural economics was applied. Not only do the theories set out possible explanations for unsuccessful outcomes, they provide areas where Governments, policy-makers and other private training providers might look to implement strategies and nudges to increase overall success metrics.

This analysis shows that more students were generally satisfied with the programme, than had a successful outcome from it (i.e. more workers who take this mid-career change programme are “happy” and have had a positive experience from it than simply those who completed the course or got a job).

One hypothesis is that, through the introduction of the career coaching module (the “C” in the SEC framework), participants are gaining confidence in basic job hunting techniques. With this knowledge, they feel confident that they will secure a role, even when they haven’t done so by the time the survey is taken.

This level of confidence in the future and satisfaction in the process means that, even with a current “unsuccessful” outcome, this group remains positive and engaged. These students still have ambition for a better career, hopes for the future, and enjoyment for lifelong learning – all of which can be tapped into going forward with new initiatives. These experienced workers are not shutdown to the lifelong learning process and are open to maintaining their engagement with it.

Further work and follow up is needed to track success metrics over a longer period of time and to identify if there are additional areas of support (or nudges) that could be provided to this group to ensure that their motivation remains consistent throughout their lifelong learning path.

This data might also be useful to help Governments and policy-makers to identify nudges that reframe the benefits of lifelong learning / mid-career change for their citizens and increase the percentage of successful completions (and therefore the pool of resources available) for attracting the next generation of high-paying high-tech industries into areas experiencing a downturn in their traditional or sunset industries.

This paper has presented an online framework for finding appropriate candidates and training them for technician level jobs in a high-tech and highly-regulated industry. Through this study, that framework has been validated and could now be transferred to other industries looking to encourage experienced workers to make a mid-career change, in support of industry expansion.

To better understand and increase the success metrics of this online framework, the field of behavioural economics was examined. Explanations were found for some of the more surprising outcomes of the study, and methods by which future users of this SEC framework might adapt it to improve overall success were proposed.

Governments, policy-makers, and other private training providers can take this versatile online SEC framework and build upon it, tailoring it to their specific needs. Different industry sectors and cultures will likely have to experiment to find those nudges that best move their audience to positive action.

It is proposed that this online SEC framework can be an important step in harnessing the potential of lifelong learning to support sustained and productive industrial growth.

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This is one in a series of papers in the area of Lifelong Learning.

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