charting the future of adult learning research in

CHARTING THE FUTURE OF ADULT

LEARNING RESEARCH IN

SINGAPORE

New Perspectives, Directions and Approaches:

Recommendations for the Future of Adult

Learning Research in Singapore

31 March 2020

2

Note This report is an output of the Taskforce on the Future of Adult Learning Research, Singapore. It

provides the Taskforce’s recommendations in putting together a coordinated and forward-looking

research agenda for adult learning in Singapore.

The views and suggestions presented in this report are those of the Taskforce. This report should be

attributed as Taskforce on the Future of Adult Learning Research, Singapore. (2020). New Perspectives,

Directions and Approaches: Recommendations for the Future of Adult Learning Research in Singapore.

This report remains the copyright of the the Taskforce and may not be reproduced without its permission.

The Institute for Adult Learning, an autonomous institute of the Singapore University of Social Sciences,

performs the secreatriat functions for the Taskforce. For further information on this report, please email

[email protected]. For further information on the work of the Taskforce on the Future of Adult

Learning Research Singapore, visit https://ial.edu.sg. The contents in this report are not necessarily the

views or policy prescriptions of the Institute for Adult Learning or the Singapore University of Social

Sciences.

https://ial.edu.sg/

3

Contents

Preface by the Taskforce Chairman ...................................................................................... 4

Executive Summary .............................................................................................................. 7

A. Introduction .................................................................................................................... 10

Lifelong learning imperatives in a digital era ................................................................... 10

New perspectives, directions and approaches for adult learning research ...................... 11

Structure of this report .................................................................................................... 12

B. Global Research Trends, and Outcomes and Impact of Adult Learning .......................... 13

Global research trends underpinning the research agenda ............................................. 13

Broadening the outcomes and impact of adult learning .................................................. 15

C. Recommendation 1 – Four Priority Research Areas ....................................................... 17

Priority area 1: Science of adult learning ....................................................................... 18

Priority area 2: Technology and innovation in adult learning ........................................... 20

Priority area 3: Learning cultures × smart cities .............................................................. 23

Priority area 4: Digital futures and human capabilities .................................................... 25

D. Recommendation 2 – Shared Data Infrastructure to Support Adult Learning Research,

Policy Evaluation and Practice ....................................................................................... 28

E. Recommendation 3 – Research Collaboratories to Enable Large-Scale Research-Practice

Collaborations ................................................................................................................ 32

Augmenting the adult learning research landscape ........................................................ 32

Key working concepts for setting-up research collaboratories ........................................ 33

International examples of research collaboratories or equivalent .................................... 36

F. Recommendation 4 – Flagship Platforms for a Leading Research-User Community in

Singapore ....................................................................................................................... 37

G. Concluding Remarks…………………………………………………………………………… 38

References ......................................................................................................................... 40

Annex 1: Approach to the Recommendations and Process of Deliberations

Annex 2: Towards the Science of Adult Learning

Annex 3: Innovative Technologies for Adult Learning Research

Annex 4: Learning Cultures × Smart Cities

Annex 5: Future of Human Capabilities in a Digital Economy and Society

Annex 6: Report on Deliberations at the Future of Adult Learning Research Symposium

4

Preface by the Taskforce Chairman

In July 2019, a Taskforce on “The Future of Adult Learning Research Agenda” was jointly

appointed by the National Research Foundation and SkillsFuture Singapore to report on the

state-of-the-art in adult learning research, and propose forward-looking recommendations to

the Singapore Government on charting the next phase of adult learning research for its

consideration. The Taskforce comprises 13 members who are appointed from various

Institutes of Higher Learning and Research Institutes in Singapore. The Taskforce conducted

literature review on the subject, and identified four areas for in-depth examination namely, (1)

Towards the science of adult learning; (2) Innovative technologies for adult learning research;

(3) Learning cultures × smart cities; and (4) The future of human capabilities in the digital

economy and society. Four Subgroups were subsequently assembled by the Taskforce to look

into each area, leading to the development of four distinctive scoping papers written by

members of the four Subgroups. In addition to converging national efforts to examine these

various areas, the Taskforce sought views and advice from international experts. These efforts

culminated in the organisation of the Future of Adult Learning Research Symposium, entitled

“Charting the Future of Adult Learning Research Agenda in Singapore: New Directions,

Approaches, and Perspectives”, on 14-15 November 2019 at the Lifelong Learning Institute,

Singapore. Further, the Taskforce invited comments from wider international networks,

especially renowned experts who could not participate in the Symposium. The concerted

efforts of the Taskforce and Subgroup members and the engaged international researchers

led to this Report on The Future of Adult Learning Research Agenda.

In all, the Taskforce took nine months to study the subject areas, including producing the

above-mentioned four scoping papers and organising the Future of Adult Learning Research

Symposium that put Singapore on the international map of adult learning research. Several

cross-cutting themes emerged in this process that are worth highlighting, namely:

1. Adult learners constitute the largest proportion of learners in the population of any country,

if lifelong learning is to be regarded as a “must” for every citizen. Anchored from this

perspective, we begin to discover that “adult learning” has been significantly ignored in the

discourse and research on education. Theories of education are largely influenced by or

grounded upon research in schools or the Pre-Employment Training (PET) sector. There

are significant differences in the mode of education between the PET and Continuing

Education and Training (CET) sectors. PET is by and large conducted in schools, which is

separated from the rest of the daily life; whereas CET transpires across settings in daily life

– both at work and after work, and can take place in family life and outdoor activities. The

purpose of education is also different. The PET curriculum by and large prepares students

for national examinations and entrance to higher institutions, whereas it is difficult to find a

fixed set of CET curriculum that can be applied to the very diverse learning needs and

levels of proficiency of adult learners. Thus, various experts engaged by the Taskforce

pointed out that adult learning is conducted in composite contexts and complexities,

intermingled with the life course of each individual who has a life agenda that is different

from other learners. From this perspective, while cognitive learning remains important,

5

sense-making may be more vital and relevant to adult learners, as it links learning to their

life, social and work experiences. How to design and provide learning for learners with

diverse backgrounds and diverse purposes of learning is by itself a great challenge.

2. In the process of examining a diverse range of topics such as human-machine relationship

with increased automation technologies and artificial intelligence, the neuropsychology of

learning among adults, and learning cultures in smart cities, a common observation raised

by various international experts and our four scoping papers is: adult learners tend to focus

on what is important to them, which can vary at different life stages and in different contexts.

In relation to this observation, it has been further identified by various scholars that the

meaningfulness of learning for the adults depends on how learning is related to their

personal, social and economic contexts. The scoping paper “Towards the science of adult

learning” particularly points out that while neuroscience is helpful to explore and understand

the plasticity of the adult brains in learning, whether learning is meaningful to the adults

depends on its relevancy to them personally, and their social and economic groups. Thus,

it is important to explore the social ecology of adult learning, as it also casts light on how

much the collective impacts on the learning motivation of the individuals and the

interactions across these different contexts. Another terminology mentioned by various

experts is “connectivity”. The significance of connectivity is particularly stressed by the

experts engaged to deliberate on enhancing human capabilities and learning cultures in

smart cities. The emphasis on social ecology and connectivity prompts the need to provide

the kind of learning process that would allow the adult learners to relate what they are

learning to their social circles, as well as their life experiences involving human and

machine interactions.

3. The complexities of adult learning and lifelong learning in terms of learning design, learning

processes, learning contexts and learning outcomes have led to calls for adopting a

transdisciplinary approach to research that is proposed by almost every speaker at the

Future of Adult Learning Research Symposium and the authors of this Report. The

significance of learning for practice and real life applications calls for the need to adopt the

use-inspired approach in adult learning research. Indeed, academic discourse on

knowledge production has increasingly migrated towards use-inspired emphases, as

revealed by the increased attention to concepts such as knowledge transfer, knowledge

exchange, knowledge utilisation and knowledge mobilisation. What is more, the recent

increased emphases on knowledge building, knowledge creation and co-creation suggest

that learners can create knowledge that are relevant and useful for themselves, which by

itself is a contribution to, or an addition to existing knowledge. How should we move forward

in coping with the complexities of adult learning research? All participants of the

Symposium and members of the Taskforce support the establishment of “collaboratories”

in Singapore, in order to provide a platform to facilitate cross-institutional and

transdisciplinary collaborative research on adult learning and lifelong learning, as well as

bring together the users and researchers to realise the use-inspired approach that will drive

our research objectives.

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It is envisaged that the new perspectives, directions and approaches put forth in this Report

will pave the way for advancing academic excellence on adult learning, while furthering the

nexus between research, policy and practice for new solutions and approaches that best

support adult learning in a digital age.

Professor Lee Wing On

Executive Director, Institute for Adult Learning, SUSS

Chair of the Taskforce for the Future of Adult Learning Research, Singapore

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Executive Summary

Five global research trends underpin the proposed adult learning research agenda

for Singapore.

The Taskforce for the Future of Adult Learning Research anchor its recommendations on an

in-depth understanding of international developments, and key trends and issues on adult

learning and adult learning research, including but not limited to the sciences of learning. The

five key global research trends relevant to the future of adult learning research are:

1

New role for adult and lifelong learning in society that demands new paradigms, approaches and methods A review of the research landscape in learning shows significant emphasis on

research in early childhood, school-age and the ageing process, but limited focus

on adult learning. This creates a window of opportunity to advance adult learning

research for the broad mass of adults (‘the middle group’). Understanding how

they learn demands new paradigms, approaches and methods customised to

their needs, roles and responsibilities in societies and economies.

2

Shift towards situated and social contexts of adult learning creates a more complex agenda for adult learning research Behavioural and cognitive approaches to learning have generally given way to

situated and socio-cultural approaches. This gives rise to a more complex adult

learning research agenda with a focus on learning ecosystems, social ecologies

of learning and learning in contexts.

3

Rapid advancement of digital technologies creates tensions but also new opportunities for adult learning

Digital technologies are a double-edged sword, with risks that digital

technologies may support the deployment of less (not more) human capabilities.

Adult learning can play an important role to facilitate socio-technical coevolution

of an algorithm-rich world that optimises human potential and augments human

performance. New conceptions of human learning may also be required for an

optimal mix between human and artificial cognition systems.

4

Emergence of new players in adult learning research, and prospects for inter- and transdisciplinary research New scientific techniques have introduced new players and approaches to adult

learning research such as in the fields of neuroscience, computational sciences

and urban sciences. This development creates a higher research capacity for

adult learning research.

5

New paradigms for thinking of knowledge production

The linear knowledge production model of researchers creating knowledge that

is then translated into society’s use is being contested. There is growing

recognition that scientific research that is both excellent and useful, can be

pursued through researcher-user collaborations.

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The Four Key Recommendations

From the examination and synthesis of the above five global trends, the Taskforce developed

the following four key recommendations that will not only advance research in adult learning

but also facilitate the use of the resulting research to inform policy and practice:

Recommendation 1: Four highly-complex priority research areas to advance adult

learning research in Singapore in the next 5-10 years.

Curated on the basis of their potential for scientific excellence and significance to national

priorities in Singapore, the four proposed research areas are:

1

Science of Adult Learning

Develop the science of adult learning into a

distinct academic field based on bi-directional

bottom-up and top-down investigations of adult

learning using a range of scientific disciplines

and involving practitioners and learners

2

Technology and Innovation in Adult Learning

Advance theoretical paradigms and new

empirical approaches for pedagogically-

grounded use of technologies for an innovative

adult learning ecosystem

3

Learning Cultures × Smart Cities Pioneer city-scale research on learning cultures

in smart cities, and leverage the smart city

infrastructure to build a data lake to support an

inclusive, smart and learning ecosystem

4

Digital Futures and Human Capabilities Develop new ways of conceptualising digital

futures by exploring the role and relevance of

human capabilities and learning in the socio-

technical deployment of digital technologies, to

optimise human potential and augment human

performance

Recommendation 2: Shared data infrastructure to support adult learning research,

policy evaluation and data-driven practices.

A shared data infrastructure will enable open research, support theoretically-grounded policy

evaluation and measurement, and build data-driven capabilities in adult learning practice. Key

data approaches include a public-private data lake on adult learning, big data streams, and

long-range studies, including panel and birth cohort studies.

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Recommendation 3: Research collaboratories as new mechanisms to facilitate

large-scale research-practice collaborations, driven by use-inspired,

transdisciplinary research.

Research collaboratories are novel platforms for dialogue and co-creation between

researchers and various user communities. They facilitate the development of use-inspired

science and transdisciplinary research, creating a built-in pathway to research impact and

adoption through the early and sustained involvement of stakeholders.

Recommendation 4: New flagship platforms to signal the building of a leading

research-user adult learning community in Singapore.

Signature international research-user conference on adult learning

Interdisciplinary peer-reviewed journal

on adult learning

Showcase labs where researchers and users dialogue and generate ideas, utilising emerging research

Living labs / sandbox environments

at workplaces & other communities to support the development and

piloting of research-informed practice

Professorships & investigatorships on adult learning

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A. Introduction

Lifelong learning imperatives in a digital era Now more than ever, adult learning plays an integral role in every economy and society. We

are confronted by significant structural changes such as changing global value chains, rapid

advancement of digital technologies, and seismic demographic shifts that are transforming the

way people live, work and connect with one another. To thrive and flourish in a volatile world

demands that each individual learns throughout life, picking up new skills and adapting to new

contexts quickly. In this climate of change, the front-loading education system is no longer

sufficient. Instead, what is needed is a shift towards a continuous, life-wide and lifelong

learning system that integrates both the pre-employment and continuing education and

training systems, and facilitates seamless learning opportunities throughout life. From this

perspective, adult learners form the largest proportion of learners in any country. It is crucial

to rethink conventional educational approaches to enable the full range of learning across the

life-course. We need to recognise that learning extends well beyond the initial years of formal

education in schools, occurring in multiple work and social spaces, and across life stages.

Internationally, Singapore stands out for making a head-start in lifelong learning provisions.

Lifelong learning has been identified as a critical socio-economic strategy to advance human

potential, sustain Singapore’s economic competitiveness and facilitate social inclusion. In a

review of Singapore’s economic strategies for the next decade, the Committee on the Future

Economy noted that “our people should have deep skills and be inspired to learn throughout

their lives”, in order to build a high quality, agile workforce that is equipped with in-demand

skills, and ready to adapt to new job demands.1 The SkillsFuture movement is a critical vehicle

to support Singaporeans to develop to their fullest potential throughout life regardless of

starting points. This turn towards lifelong learning in Singapore began with the first CET

Masterplan in 2008 that put the focus on continuing education for the wider workforce.2 With

the launch of the SkillsFuture movement in 2014, the range of lifelong learning provisions has

been expanded to include individual learning accounts, work-study programmes for early-

career and mid-career individuals, as well as workplace and digital learning initiatives.

Universities in Singapore are now playing a greater role in lifelong learning, with a paradigm

shift in thinking from graduating students to nurturing lifelong learners and supporting their

progress well beyond initial graduation. Workplaces are also called upon to be crucibles of

learning, thus departing from conventional classroom and didactic approaches. All these

initiatives deserve the support of robust research in adult learning.

Alongside the growing importance of lifelong learning, we are confronted by another complex

phenomenon due to advancements in digital technologies such as artificial intelligence (AI),

machine learning, virtual reality and equivalent. On the one hand, the increasing

pervasiveness of digital technologies presents opportunities for innovation and higher value-

1 See p.1 of the Report of the Committee on the Future Economy (2017), available at https://www.mti.gov.sg/Resources/publications/Report-of-the-Committee-on-the-Future-Economy.

2 Refer to https://www.skillsfuture.sg/ for more information on SkillsFuture.

https://www.mti.gov.sg/Resources/publications/Report-of-the-Committee-on-the-Future-Economy

https://www.skillsfuture.sg/

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added activities in our economy. On the other hand, it raises important questions on the

development of human capabilities to access and harness these technologies, and whether

these opportunities are accessible for all. Accordingly, how do we harness the role and

relevance of learning to enable and develop these human capabilities? Adult learning research

has much to offer to support national programmes and policies on digital innovation and digital

inclusion, including the Smart Nation initiatives3 as well as the push for Singapore to be a

Global-Asia node of technology, innovation and enterprise. Our ability to harness adult

learning to build a digital future that complements human ingenuity, and supports sustainable

growth, is key to the dynamic stability of our society.

New perspectives, directions and approaches for adult learning research This Report puts forth new perspectives, directions and approaches on the future of adult

learning research in Singapore based on deliberations with a wide range of Singapore and

international researchers led by the Taskforce on the Future of Adult Learning Research

Singapore. Appointed by Singapore’s National Research Foundation (NRF) and SkillsFuture

Singapore (SSG), the Taskforce comprises 13 academic and policy personnel from

Singapore’s six Autonomous Universities, the Agency for Science, Technology and Research

(A*STAR), NRF, SSG and the Ministry of Education (MOE). The Taskforce consulted with

more than 100 researchers to propose a coordinated and forward-looking research agenda

that takes cognisance of the range of developments in academic research and key dialogues

in societies. The disciplinary expertise of the researchers includes computational sciences,

economics, learning sciences, neuroscience, psychology, sociology and more, tackling a wide

range of research areas spanning adult learning theory, ageing research, educational

research, human-computer interaction, science of learning, smart cities and urban cultures,

among others. The Taskforce also consulted with some Chief Learning Officers for their

perspectives.

The goal of the Taskforce is to develop an adult learning research agenda that not only fosters

scientific excellence, but also creates the pathways for scientific knowledge to contribute

strategically to policy-making and practices. Specifically, the strategic objectives that

undergird the development of the future of adult learning research are:

To advance Singapore’s research leadership in adult learning and aspects of digitalisation

that can contribute to national economic and societal priorities including the objectives of

SkillsFuture, the Future Economy and Smart Nation;

To take cognisance of digital imperatives, including socio-technical readiness and well-

being in a digital economy and society, as well as harnessing digital technologies for

research; and

To suggest new models and approaches for connecting the research and user

communities to strengthen research translation and impact.

3 Refer to https://www.smartnation.sg/ for more information on Smart Nation.

https://www.smartnation.sg/

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In developing the agenda, the Taskforce took a broad approach. It surveyed the latest

theoretical and empirical investigations on adult learning, the critical gaps that exist, and the

new opportunities and issues that come with digital technologies. It also reviewed the latest

academic discourse on knowledge production, and emerging models of research translation.

Surveying national imperatives, it identified current and potential future contributions from

adult learning research. Finally, the Taskforce deliberated on how to build on the significant

investments in adult learning-related research in Singapore in the last decade. A key

observation is the broad set of capabilities that now exists in Singapore that could be

marshalled more powerfully to push the frontiers in adult learning research, policy and practice

as a key socio-economic strategy for Singapore.

Four subgroups were set up to deliberate in-depth on specific research areas. In addition, a

Future of Adult Learning Research Symposium was organised from 14-15 November 2019 to

discuss specific research topics as well as tackle the broader challenge of research translation.

There was also further engagement with specific international experts and Chief Learning

Officers. All views have been incorporated into this report to the extent possible. More

information on the process of consultation and deliberations is at Annex 1.

Structure of this report The next section outlines our survey of international research trends, upon which we build the

proposed adult learning research agenda for Singapore. Section C introduces our first

recommendation, which is the four priority research areas on adult learning that Singapore

should invest in. Section D describes our second recommendation of a shared data

infrastructure to support adult learning research, policy evaluation and data-driven practice.

Section E outlines our third recommendation of research collaboratories as novel mechanisms

to facilitate large-scale research-practice collaborations. These collaboratories are designed

to foster excellent use-inspired science with a built-in pathway to impact. Section F details our

final recommendation of the creation of flagship platforms to signal the building of a leading

researcher-user adult learning community in Singapore. Section G concludes the report.

Included at Annexes 2-5 are the four scoping papers that provide detailed examination of each

of the four priority research areas on adult learning. Annex 6 captures the key deliberations at

the Future of Adult Learning Symposium 2019.

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B. Global Research Trends, and Outcomes and Impact of

Adult Learning

Global research trends underpinning the research agenda Combining a broad literature scan, discussions at both Taskforce and Subgroup levels,

deliberations at the Future of Adult Learning Research Symposium and further engagement

with key experts, the following global research trends and issues of relevance to adult learning

have been observed:

New role for adult and lifelong learning in society that demands new paradigms,

approaches and methods

As adult and lifelong learning assumes a new role in society, it becomes apparent that

adult learners have hitherto been underserved by the research community. Research in

learning sciences and science of learning tend to give prominence to learning in early

childhood, learning in formal educational settings, and the ageing process. There is a

window of opportunity to advance adult learning research for the broad mass of working

adults (the ‘middle group’). To draw on theories of learning and education developed from

research on early-age learners for generalisation to adult learners is to ignore the

fundamentally different developmental stages, roles, needs and responsibilities of adults

in society. Adult learners are not ‘captive’ students in the sense of having to go through an

education system based on a fixed curriculum and standardised assessments as a rite of

passage and social marker for joining the adult world. On the contrary, the world of learning

for adults is dynamic, complex and diverse.

To adequately understand and support adult learners, we therefore need to transcend

educational settings and venture into other sites of learning such as workplaces and virtual

communities. We also need to develop a deeper understanding of their diverse

backgrounds, motivations and life-stages. Given the rich prior knowledge that they have,

the design of lifelong learning provisions for adult learners is likely to look dramatically. 4

For instance, adult learning has been conceptualised as knowledge-building with peers.

This is a fundamentally different pedagogical model than regular mono-logic approaches

or even the socio-cultural model of zone of proximal development (ZPD) that requires

expert guidance. In educational neuroscience, the adult brain has been found to be a

superior learning device with strong evidence of neuroplasticity for abstract systems and

superior cognitive strategies. 5 More research is needed to uncover new paradigms,

approaches and methods for understanding, conceptualising and advancing adult and

lifelong learning.

4 Refer to Annex 6 (pp. 16-17) for discussion by Associate Professor Tan Seng Chee on adult learning as knowledge-building.

5 Refer to Annex 6 (p. 25) for discussion by Professor Michael Thomas on the adult brain as a superior learning device. See also Knowland and Thomas (2014).

14

Shift towards situated and social contexts of learning that demands a more complex

agenda for adult learning research

Within the community of adult learning researchers, behavioural and cognitive approaches

have generally given way to situated and socio-cultural approaches. The latter gives focus

to the development of human capabilities as social and collective. The emphasis is on

connected learning, social ecologies of learning and social situations that create interest,

motivation and passion for learning.6 Rapidly changing contexts in work, education and

labour markets increase the complexity to understand, support and facilitate adult learning

as an ecosystem.

Rapid advancement of digital technologies creates new tensions but also

opportunities for adult learning

There is recognition of digital technologies as a double-edged sword, with risks of a digital

economy that in fact demands less (not more) human capabilities. Adult learning research

can play an important role to facilitate socio-technical evolution of human-machine

interaction for an algorithm-rich world that is ethical and socially-inclusive.7 More research

is needed to ground the use of digital technologies on theoretical approaches that augment

human learning and performance.8 A related issue is the ability for adult learners to control,

manage and leverage the intelligence behind the machine, and not lose their own

capabilities. 9 New conceptualisations of human learning may also be required. For

instance, with machines having greater capacity to perform cognitive tasks, human

learning systems may evolve to give greater focus to sense-making that is heavily social.10

Emergence of new players in adult learning research, and prospects for inter- and

transdisciplinary research

New scientific techniques have introduced new players to adult learning research including

the fields of neuroscience, computational sciences and urban sciences. These players

introduce new ways of thinking and conducting research. They complement the

established core disciplines in adult learning research such as anthropology, economics,

philosophy and psychology. This mix of established and new approaches creates a higher

research capacity to respond to an increasingly complex adult learning research agenda

through inter- and transdisciplinary research, if properly harnessed.

6 Refer to Annex 6 (pp. 23-24) for discussion by Professor Geoffrey Cohen on the power of the social contexts for facilitating learner engagement. See also Evans, Waite and Kersh (2011).

7 Refer to Annex 6 (pp. 10-11) for discussion by Professor Nancy Law on socio-technical co-evolution for augmented performance for social well-being. See also Miller (2018).

8 Refer to Annex 6 (p. 13) for discussion by Professor Lee Kwan Min and Associate Professor Rabindra Ratan on theoretically-grounded applications of human-machine interaction for learning technologies.

9 Refer to Annex 6 (pp. 19-20) for discussion by Dr Carlo Giovanella on human augmentation and people-centricity in smart city design. See also Letaifa (2015).

10 Refer to Annex 6 (p. 15) for discussion by Professor George Siemens on adult learning as sense-making.

15

New paradigms for thinking of knowledge production

The paradigm of a linear knowledge production process in which researchers create new

knowledge that is then translated into use in society is increasingly being contested within

the academic community. There is growing recognition of the bi-directional relationship

between researchers and users, where excellent and useful scientific research can be

inspired by and conducted in collaboration with users.11 Emerging conceptualisations of

knowledge production include: (1) use-inspired science (focus on producing high-quality

scientific work that illuminates or help solve practical problems); (2) transdisciplinary

research (integration of multiple academic disciplines and the expertise of non-research

stakeholders to address a societal problem); and (3) knowledge mobilisation (relational

expertise between researchers and practitioners to improve outcomes). This shift towards

non-linear model of the knowledge production process opens up new ways of organising

research translation for impact.

Broadening the outcomes and impact of adult learning Based on the survey of trends and issues on adult learning, it becomes increasingly clear that

the dominant discourse of adult and lifelong learning being narrowly tied to economic

outcomes, as in Singapore till recently, is inadequate. Without a doubt, the relationship

between adult learning and economic well-being remains critical, to enable individuals to thrive

in a changing job market in the transition into a digital economy. However, equally important

is a focus on personal well-being. Adult learning should facilitate the fulfilment of an individual’s

aspirations and potential beyond as a homo economicus to include his or her wider

contributions to society. More fundamentally, we should recognise the contributions of adult

learning to social well-being in terms of creating capacity to tap on the collective and

distributed intelligence and range of talents in society to address current and future challenges.

Table 1 proposes a broad inter-linked framework for the provision of sustainable and inclusive

learning opportunities spanning personal, economic and social well-being.

11 Refer to Annex 6 (pp. 29-30) for expert discussions on alternative paradigms for research translation. See also Buizer et al. (2015), Cooper & Levin (2010), and O’Brien, Marzano and White (2013).

16

Table 1: Broad inter-linked framework of personal, economic and social well-being

Su

sta

ina

ble

an

d I

nclu

siv

e

Lif

elo

ng

Le

arn

ing

Op

po

rtu

nit

ies

Personal

Wellbeing

Fostering individual resilience and personal growth, realising each

individual’s potential, to lead constructive and meaningful life

Economic

Wellbeing

Facilitating the building of deep skills, adapting to changing skills

demand and manage transitions, to sustain participation and thrive

in the changing job market

Social

Wellbeing

Developing social structures that harness the collective and

distributed intelligence and range of talents in society, to foster

social inclusiveness and cohesiveness, active citizenry, and

vibrant culture

The broadening of outcomes and impact of adult learning allows us to see new roles for adult

learning in society. For instance, a focus on social well-being positions adult learning as a key

strategy to strengthen socio-technical readiness for a digital future that augments human

capabilities. Similarly, while the most popular conceptualisation of a ‘smart city’ gives

emphasis to technological infrastructure, a focus on people as both the architect and

beneficiary of a smart city provides an opportunity to embed a learning culture in a smart city.

This will maximise the positives such a city can offer to the individual and the community.

It should be highlighted that the broadening of the adult learning agenda does not imply that

economic outcomes are less important. On the contrary, economic outcomes will be better

supported by a broader development of human capabilities and potential. The next section

describes the Taskforce’s recommendation of four priority research areas on adult learning

that are built upon a broader conception of the outcomes and impact of adult learning to society.

17

C. Recommendation 1 – Four Priority Research Areas

Four highly-complex priority research areas on adult learning are proposed by the Taskforce.

They are drawn from a broader conception of the outcomes and impact of adult learning based

on the global trends surveyed in the preceding section. The four priority research areas have

been curated for (1) academic novelty and potential for Singapore to demonstrate research

leadership; and (2) significance to Singapore’s national priorities. All the ideas put forth in this

Report have received strong validation from the research community.

Table 2 summarises the four priority areas, with the rest of this section providing detailed

descriptions. The full scoping of each of the four areas are at Annexes 2-5.

Table 2: Four priority research areas for the future of adult learning research

1

Science of Adult Learning Develop the science of adult learning into a

distinct academic field based on bi-directional

bottom-up and top-down investigations of adult

learning using a range of scientific disciplines

and involving practitioners and learners

2


Advance theoretical paradigms and new

empirical approaches for pedagogically-

grounded use of technologies for an innovative

adult learning ecosystem

3

Learning Cultures × Smart Cities Pioneer city-scale research on learning cultures

in smart cities, and leverage the smart city

infrastructure to build a data lake that supports

an inclusive, smart and learning ecosystem

4

Digital Futures and Human Capabilities Develop new ways of conceptualising digital

futures by exploring the role and relevance of

human capabilities and learning in the socio-

technical deployment of digital technologies, to

optimise human potential and augment human

performance

18

Priority area 1: Science of adult learning

Academic Novelty & Strategic Contributions to National Priorities

Science of Adult Learning bridges a critical gap in the fields of ‘learning sciences’ and the

‘science of learning’ that thus far have lacked a distinct focus on the adult learner. A dedicated

focus on adult learning, as compared to early-childhood and school-age learning, is necessary,

given that adults have agency and taking into accounts their roles and responsibilities in

society. This priority research area aims to raise the field of adult learning research into a

science, integrating the latest theories and techniques in scientific inquiry built upon use-

inspired and transdisciplinary science. It is designed to be inclusive by bringing together social

sciences, biological sciences, computational sciences as well as the practice of adult learning

to enable multi-directional investigations of adult learning. It therefore expands beyond the

more conventional scope of science of learning research that emphasises the biological

sciences12. The proposed scope of the science of adult learning has received very strong

endorsement from researchers across disciplines, including from internationally-renowned

adult learning experts who have called the proposed research area “ambitious” and

“innovative”.

This priority research area is pertinent to inform current and future investments in continuing

education, training, and lifelong learning in Singapore, in support of key SkillsFuture strategies

and initiatives. Key impact envisaged from the research include supporting the design of

personalised and social infrastructure for learning, and the development of theoretically-

informed data-driven frameworks on adult learning to support policy-making.

Scope of Research Area

The vision of the Science of Adult Learning is to create a coherent, integrated body of

knowledge on adult learning, harnessing the latest theories and techniques in scientific inquiry,

to anchor the provisions of lifelong learning in society. A transdisciplinary approach is

proposed to embrace the interconnectedness and interdependence between several fields of

studies and enable bi-directional (and even multi-directional) learner-inspired research

incorporating the following:

traditional social sciences and emerging branches such as social economics and

management science;

biological sciences, whereby neuroscience, physiology and genetics can support the

development of biologically- and neurologically- informed pedagogical principles for adult

learners;

computational sciences, including computational social science, computational

neuroscience and computational genomics; and

the practice of adult learning design, development and delivery.

12 For instance, the Science of Learning and Augmented Intelligence Research Programme of the US’ National Science Foundation has a very strong focus on the ‘biological learner’. For more information, visit https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505731.

https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505731

19

Key areas of emphasis for the science of adult learning is as follows:

Social ecology of adult learning: Develop new approaches, tools and methodologies for the

study of the social ecology of adult learning, which includes the adult learners in his or her

natural context(s).

Neurobiological prospects for and processes of adult learning: Integrate neurobiological

investigation with a social ecology approach to develop pedagogically important principles

relevant to adult learning.

Data-driven frameworks for investigating adult learning and learning outcomes: Design

and develop data-driven frameworks to study the interplay between learning, neural activities

and the social ecology of the adult learner, leveraging advancements in computational

sciences.

Translational research to anchor policy and practice in rigorous empiricism: Explore

alternative approaches to test and scale up pedagogical approaches in authentic learning

environments, before they are cemented into policy or as leading practices.

Figure 1. Framework for the Science of Adult Learning

Existing Capabilities

This research area will build on existing research capabilities and investments in Singapore,

including but not limited to adult learning research, ageing research, computational sciences,

20

educational neuroscience and learning sciences. Given its transdisciplinary focus, other

research expertise may be included as needed such as complexity science and more.

Selected Indicative Research Questions13

While adult learning may occur in educational settings, it occurs more abundantly

through daily practices, such as family life, workplaces, online platforms and other

social contexts, or in what is called ‘learning in the wild’. How do we capture the

learning that occurs ‘in the wild’, and convert them into meaningful learning for the

individual and community?

How do we adopt the growing field of socio-cultural approach for adult learning

research in informal settings, such as teamwork, collaboration, group dynamics and

the role of social contexts? If adults in different social contexts learn differently, what

are the differentiating factors that influence or hinder effective adult learning?

What is a possible framework that integrates neurobiological investigation of adult

learning towards developing pedagogically important principles relevant to adult

learning (bearing in mind the social ecology approach), as well as support the design,

implementation, and evaluation of adult learning interventions?

How can the advancements in non-invasive neuroimaging and neurophysiological

techniques be deployed to provide more precise understanding of changes in

neuroplasticity and neural resources (e.g. grey matter volume), and the implications

for proficiency and attainability of new skills across different stages of the adult lifespan?

Priority area 2: Technology and innovation in adult learning


The proposed Technology and Innovation in Adult Learning research area puts forth a

much needed, but thus far lacking systematic and pedagogically-grounded approach towards

the design and deployment of technologies within the whole adult learning ‘ecosystem’. The

research area will advance theoretical paradigms of learning in a digital world with a focus on

pedagogically-sound deployment of technologies in adult learning. This will be taken up via

an ecosystem approach, integrating the roles of technology providers, educators, businesses,

learners and professional bodies. The research area will also support new empirical

approaches, driven by data availability and capabilities (e.g. learning analytics, machine

learning), and parallel processes of co-creating, experimenting and distributed learning.

This research area is critical in driving innovation in the Training and Adult Education (TAE)

sector, and empowering adult educators, training providers and Institutes of Higher Learning

to deliver high quality and future-oriented adult learning provisions. There is also high potential

in commercial applications and spin-offs of learning technologies by businesses and start-ups

to enhance learning at workplaces and other learning settings.

13 Refer to Annex 2 (pp. 20-22) for the full list of indicative research questions.

21


Up-and-coming technologies, such as AI, user analytics and augmented reality, if leveraged

well within the TAE sector, are all potential game-changers for revolutionising the way adults

learn. These innovative technologies are important tools that adult educators and training

providers can capitalise on to deliver enhanced and more effective learning experiences for

their learners. Yet, for learning technologies to be impactful, they have to be grounded in

sound understandings of learning and learning design principles, and well-integrated into the

learning process. This requires a focus beyond technology as the innovation, towards the role

of technology to innovate the whole learning ‘ecosystem’ with the learner in the centre. That

is, technology is a tool for enabling learning, instead of the driver of learning.

In adopting a ‘learning ecosystem’ approach, this research area seeks to advance theoretical

paradigms of learning in a digital world. It can provide a critical and systematic take on the

design and deployment of innovative technologies in adult learning, founded on pedagogically-

grounded theories. At the same time, it integrates the roles of technology providers, educators,

businesses, learners and professional bodies as crucial players within this ecosystem. In

particular, the focus of innovative research is shifted from the technology itself to learning, with

technology deployed as a tool for enabling, affording and supporting innovative learning,

individually and collectively. The research area also proposes a focus on the role of the

business of education, in how organisations should think about their business models vis-à-

vis new learning technologies to meet context-specific needs of learners.

Complementing the theoretical undertakings, new empirical approaches in technology and

learning innovations are proposed. They present immense potential for the TAE sector to offer

more complex and personalised learning opportunities to enhance the effectiveness and

relevancy of learning experiences. In particular, the massive advancements in data availability

and capabilities, such as in machine learning and learning analytics, provide important

foundations to drive the parallel processes of co-creating and experimenting on learning

innovation. These areas are high in impact and have high potential for translation.

Some focus areas based on these data-driven approaches could include:

Recognising informal learning: Technology to identify and assess when workers have

achieved competency in necessary skills on the job, beyond formal education and training.

Personalised learning opportunities: Technology to develop personalised and adaptive

integration of learning resources that meet context-specific needs of the learner, and shorten

the time from identifying the need to meeting the need.

22

Figure 2. Proposed Framework for the Technology and Innovation in Adult Learning Research Area



including: workplace and blended learning, educational technologies, pedagogy in teaching

and learning, computer science and artificial intelligence research, and learning analytics. The

emerging research-practice nexus in the TAE sector with a ready network of stakeholders that

consists of policy-makers, researchers, and practitioners, provides a solid socio-cultural

infrastructure for the development and implementation of an integrated and learner-centric

system of innovative learning technologies.


What new understandings of learning can innovative technology bring about to reflect

the complexities of everyday lives and system ecologies beyond the cognitive and

behaviourist understanding of learning with the focus of competencies and skills?

How can we leverage on learning technologies to develop complex, sophisticated

capabilities such as teamwork, critical thinking, learning-to-learn, and other such

future-oriented capabilities?

Taking learning as a social and highly contextualised and interactive process among

humans or between humans and technologies, how can knowledge be co-created

and/or further enriched and developed with the aid of technologies?

How are educational institutions leveraging technology to tap on learning in and across

multiple spaces, including in industries? What are the implications of expanded spaces

for learning for the required capabilities of educators, labour relations and policies, and

the culture and structure of educational institutions?


23

Defined as socially constructed and negotiated, how is technology used to develop

realistic accounts that are context-rich, capturing conflicts and politics to draw out the

underpinnings in the design, use, challenges and possibilities of technology in and

across the multiple contexts of adult lives?

Priority area 3: Learning cultures × smart cities


Learning Cultures × Smart Cities will pioneer research in learning cultures at a national /

societal level, by integrating concepts related to learning cultures and smart cities within the

framework of urban cultures and lifelong learning cities. It addresses pertinent questions about

the co-creation of an inclusive, smart and learning ecosystem for cities – one that includes not

just technologies, but also people as learners and contributors augmented by digital

technologies. It examines and uncovers learning across different contexts and spaces, in

workplaces as well as all aspects of everyday life. Leveraging the ‘smart’ infrastructure of the

smart city, this priority area includes a proposal to build a public-private data lake on adult

learning that will enable new paradigms for data-driven investigation to inform policies and

programmes for a learning city.

This research area presents immense potential in twinning the objectives of SkillsFuture and

Smart Nation, making an essential shift beyond a techno-centric lens of a smart city, towards

one that is at once people- and learner-centric. This shift is necessary to reap more from the

investments in designing a smart city that empowers citizens through their range of everyday

life experiences. The development of a data infrastructure that comprises both a data lake and

user accessibility posits a data-driven future that is in line with the aspirations behind big data.


This research area proposes to adopt urban cultures as a starting point, to unpack the

connections between the smart city and its learning culture. This will allow us to address

fundamental questions that will contribute to understanding how we can integrate learning into

the city, so that the city is both a resource and a space for learning and enhanced from the

learning of its inhabitants. this research area seeks to examine and uncover how people

navigate the myriad of learning opportunities within multiple spaces and contexts, and across

life stages – whether physical, virtual or social; formal, non-formal or informal; childhood,

adulthood, or through senior-hood – to foster a culture that celebrates and support lifelong

learning. In particular, to strengthen the opportunities for translation, this research area further

proposes the following focus areas:

The emergent significance of corporate universities: Examine potential collaborative

approaches and models between traditional universities (particularly their increased

engagement in CET provisions) and corporate universities, to enhance lifelong learning

provisions within the smart learning city.

24

A focus on mid-career and senior learners: Examine specific learning needs and barriers,

and learning systems and infrastructure, to facilitate lifelong productivity of key segments in

the context of Singapore’s rapidly ageing population.

Figure 3. Proposed Framework for the Learning Cultures × Smart Cities Research Area

As an important resource to drive the culture of innovation and experimentation in the smart

city, this research area proposes to explore ways to consolidate public and private data on

learning – such that data and data sensors are democratic, available, and modularised – to

facilitate both top-down and bottom-up solutions to enhance our learning experiences in the

smart city. The integration of diverse data in smart cities is necessary to create new ways to

sense and understand the city and its people from a systems perspective. This will nurture a

robust, data-driven decision-making culture to further enhance learning experiences for

greater effectiveness and outcomes.


This research area will build on existing research capabilities in Singapore, including: data

lake architecture and analytics, smart cities lab, and adult learning system, in complementing

Smart Nation and SkillsFuture initiatives. The strong culture of collaboration between

researchers, policymakers, and practitioners, with emphasis on coordinated planning and

delivery of integrated infrastructure and solutions, strongly positions Singapore to pursue this

area of research.

25


What are some ways to make adult learning in the smart city highly personalised and

precisely tied to their specifically desired well-being and economic needs, including

addressing pain points to adult learning?

How can we track, over the medium and long term, the evolution of learning cultures

and environments in Singapore, to yield insights on how related initiatives, strategies

and policies will need to involve?

How can a systemic understanding of the smart city nurture urban cultures for

improved transparency, robust data-driven policy debate and decision making, and

stronger citizen engagement and participation?

What is the role of corporate universities in enhancing lifelong learning, and what could

a potential traditional university – corporate university partnership framework entail?

What are some ways to make public and private data and data sensors democratic,

available, visible and modularised?

Priority area 4: Digital futures and human capabilities

Academic Novelty and Strategic Contributions to National Priorities

Digital Futures and Human Capabilities invite new ways of thinking and conceptualising

‘digital futures’, posing new questions about optimising human potential, social trust, safety

and risk, and well-being in a digitally connected and algorithm-rich worlds. A possibility is a

digital future that uses less, rather than more human capabilities, where machines outperform

humans. Yet, it is also possible to deploy digital technologies to augment human performance,

enabling a flourishing of human capabilities. This priority area will thus make an important

contribution to on-going global dialogue on sustaining the relevance and role of human

capabilities in a digital world. The focus areas such as the nature of human-computer

collaboration, socio-technical readiness of societies, and changing roles of education and

learning are cutting-edge areas in many research centres globally.

This research area will provide critical insights to anchor national policies and strategies

related to AI and digital innovation to support the flourishing of human capabilities as a core

objective. It is aligned to the broader national economic, social, education, manpower, and

digital strategies of inclusive growth amidst the digital transformation of the economy and

society, per the objectives of SkillsFuture, Future Economy, and Smart Nation.


Digital technologies are potential disruptors of the economy and society, transforming how we

live, work, and learn. As our reliance on digital technologies increases across various facets

of our lives, it raises questions about what it means to be human in this ‘digital future’. What

is the value of human capabilities? What is the role and nature of capabilities in human-

15 Refer to Annex 4 (pp.17-18) for the full list of indicative research questions.

26

machine interaction? What capabilities do we need as we use, interact with and manage the

technologies? As we seek answers to these questions, it is important to recognise that these

technologies do not create their use by themselves. What is demanded of human capabilities

and how we gain access to these capabilities in the digital future is shaped by a bigger

question of how, as a society, we design and use the technologies; and for what purposes.

This research area will critically explore conceptualisations of digital futures, in relation to

issues such as speed of innovation, hyper-connectivity, and co-evolution of technology and

humans within the socio-biological technical system. The research area will contribute to our

knowledge base of how digitalisation is impacting every aspect of life, posing pertinent

questions about optimising human potential. Having a good grasp of digital futures will help

us make more resilient choices to support the flourishing of human and human capabilities.

The study of the future role and relevance of human capabilities will be undertaken alongside

the prospects of digital innovation, drawing important connections with the global geopolitical,

economic, and social state of affairs. In particular, there are three highly relevant focus areas:

Future of work: Examine the impact of digitalisation on the economy and the future of work.

How should jobs be re-designed and job roles re-organised to optimise the role of humans

alongside machines? What are the skills and capabilities required by humans to flourish in

these job roles, and how can we anticipate these future labour market needs?

Future of learning: Examine the impact of digitalisation on the future of education and

learning. What new education and learning models and approaches are required to support

the development of human capabilities in the digital futures? What are ‘digital skills’?

Future of living: Examine the impact of digitalisation on society and the individual, through a

whole of life perspective. What are the set of ethics, values, and legalities required for society

and individuals to function alongside machines? How can we leverage on technologies to help

empower and enable individuals to lead meaningful and fulfilling lives?

Future of co-creation of knowledge in practice: Examine how the recent paradigm shift in

pedagogical concepts of knowledge-building and knowledge-creation can be applied to adult

learning, especially in generating knowledge from practices and use-inspired knowledge.

27

Figure 4. Mind-map of the Digital Futures and Human Capabilities Research Area



including: workforce development research, computer science and AI research, and

supporting SkillsFuture’s Job-Skills Insights and Infocomm and Media Development

Authority’s goal of a digitally-inclusive society. As a Global-Asia hub, Singapore is a critical

player in the global node for shaping digital futures.


What are possible conceptualisations of the Digital Futures, and what is the role of

digital technologies as embedded within the global geo-political, economic, and social

state of affairs?

What are the new conceptualisation of human capabilities that complements the digital

futures? How do we identify and develop these capabilities?

What are the impact of digital technologies on the labour market and employment, and

what are the factors that encourage the creation of quality jobs in the digital economy?

What are the challenges to well-being and life in a digital society? What potential risks

does technological advances bring to individuals, groups, and communities? How can

we improve inclusiveness and equity and mitigate against possible social polarisation

and fragmentation in a digital society?

Whose ethics or values should the AI system be embracing in decision-making and in

taking on human responsibilities as part of the autonomous or automated process?


28

D. Recommendation 2 – Shared Data Infrastructure to

Support Adult Learning Research, Policy Evaluation

and Practice

As adult and lifelong learning assumes a new strategic role in society, the Taskforce is of the

view that it is timely for Singapore to invest in an integrated, shared data infrastructure to

support adult and lifelong learning research, policy evaluation and data-driven practices over

the long-term. Table 3 summarises the objectives of the shared data infrastructure.

Table 3: Objectives of a shared data infrastructure on adult and lifelong learning

Sh

are

d d

ata

in

fra

str

uc

ture

on

ad

ult

an

d

life

lon

g l

earn

ing

Enable open

research

Singapore researchers will benefit from access to a shared

data infrastructure on adult and lifelong learning. All four

priority areas proposed under Recommendation 1 can

contribute to and will benefit from the open access and

shared data. New research questions and interesting

analysis may also emerge from it.

Support policy

evaluation and

measurement

The shared data infrastructure will be built upon strong

theoretical foundations that will allow for scientifically-

informed policy evaluation and measurement.

Build data-

driven

capabilities in

research, policy

and practice

As people analytics such as HR analytics and L&D analytics

gain greater take-up in organisations, there is an opportunity

to tap on such data while also proliferating data analytics

approaches that are theoretically-grounded in adult and

lifelong learning.

A robust data infrastructure should rely on a range of methods and data sources, including

exploiting digital technologies. Methodological diversity and plurality will minimise the limits of

any one approach to offer complementary perspectives.17 For example, while big data mined

from digital learning platforms (e.g. massive open online courses [MOOCs], learning

management systems) provide immediate feedback on learners’ response in authentic

learning environments, longitudinal data allows for analysis of the learning trajectory across

the life-course taking into account employment changes and life events. When integrated and

used together, different types of data will allow researchers to validate and triangulate findings.

The shared data infrastructure should have a strong core of Singapore data, augmented by

data from other countries for comparative investigation. Below, we outline three key data

approaches that are particularly useful for adult and lifelong learning studies.

17 For a comparison between survey and big data methods, refer to Callegaro and Yang (2017).

29

Open Data Lake on Adult Learning

Currently, there is a wealth of data sets from public and private sources that adult

learning research can tap on, to support research and policy objectives. Public

agencies such as MOE and SSG have a plethora of administrative and publicly-

collected datasets on education, learning, and employment that can be mined to study

a range of issues related to adult learning. Institutes of Higher Learning and training

institutions likewise are collecting abundant data about their learners. With the growth

of in-house HR and L&D analytics, there is a growing practitioner community that is

keen to share their organisational data, and tap on the domain expertise of researchers

to enhance their organisational learning and people development processes and

programmes.

Therefore, as proposed under Priority Research Area 3, Singapore should explore the

creation of an open data lake on adult learning so that relevant data sets could be

made available to researchers, policy-makers and practitioners. The data lake will be

an integrated data resource that researchers and users can draw from and contribute

to, including conducting joint research. The open data lake will contribute to a more

responsive research agenda, break down research silos, and foster stronger

collaboration amongst researchers, policy-makers and practitioners, as well as support

Smart Nation’s push for digital innovation and inclusion. To push the development of

the data lake, it will be important to identify potential public and private contributors to

the data lake, put in place mechanisms to incentivise contribution to and usage of the

data lake, address data privacy issues, as well as build analytics capabilities.

Novel Big Data Approaches to Augment Data Sources Accumulated Through

Established Research Methodologies

Novel big data approaches can augment established data sources, and provide

quicker and personalised feedback to stakeholders such as learners, practitioners, and

policy makers. Digital learning platforms and online job and career portals are some of

the key sources of big data that are relevant to adult and lifelong learning research.

Most of these big international datasets are privatised, making access to them costly.

A shared data infrastructure will allow Singapore to negotiate win-win strategic

collaborations with established and emerging players 18 by involving them as data

partners to achieve economies of scale, as well as shape the kinds of big data to be

collected.

University of Glasgow’s Urban Big Data Centre also provides an interesting example

of how adult learning research can be enhanced and enriched by drawing from open

and big data sources. Building on the Key Features of Learning Cities framework by

UNESCO, and applying novel big data approaches, the research team was able to

harness existing city data (e.g. Global Positioning System [GPS]) to study learning

18 There is a thriving private sector community of big data providers opening their data for research (e.g. Burning Glass), as well as local analytics firms and start-ups who may be willing to collaborate on a shared data infrastructure as part of their product roadmap development.

30

engagement within the urban context, and generate important discussions on learning

inequalities, lifelong and life-wide literacies, and active citizenry19.

Long Range Data to Support Trends and Developmental Analyses

Many of the outcomes and impact of adult and lifelong learning are long-term, evolving

throughout the life course. Data from long range studies are necessary to enable

robust trends and developmental analysis. Singapore has given strong support to two

key international cross-sectional studies in learning, namely Programme for the

International Assessment of Adult Competencies (PIAAC) and Programme for

International Student Assessment (PISA). Both have been extremely valuable in

contributing to trends analysis, and can contribute to the shared data infrastructure.

Although comparing the two datasets will offer developmental insights, longitudinal

studies such as panel studies and birth cohort studies remain the best means for

understanding changes over the life course between predictors and the shape of

learners' trajectory. It is therefore recommended that Singapore considers launching

new longitudinal studies on adult and lifelong learning to support robust developmental

analysis. Technological innovations as well as socio-technical readiness in engaging

with digital platforms can enable accelerated, efficient and cost-effective longitudinal

studies. Two types of longitudinal studies are proposed below:

Panel studies on adult and lifelong learning: An example is the German National

Educational Panel Study (NEPS) 20 that provides longitudinal data on educational

processes and competence development across the life course. A fit-for-purpose

approach could be taken for Singapore. Although the unit of analysis in panel studies

is typically the individual, it is recommended to also include firms, community settings

or other units of analysis to capture the evolution of social ecologies of learning in

Singapore. A digital platform would lower the costs of collecting data substantially,

enable more frequent data collection, and be easily integrated into the proposed

shared data infrastructure.

Birth cohort studies on education and lifelong learning: The 1970 British cohort

study21 and its follow-up, the Millennium Cohort Study22, have been phenomenal in

enabling researchers to analyse a range of key social topics such as child development,

social stratification and economic returns to education. Given the focus of lifelong

learning in Singapore from cradle to grave, the launch of a birth cohort study on

education and lifelong learning will be timely.

19 Refer to Lido, Reid and Osborne (2019).

20 For information on the German National Education Panel Study, refer to https://www.neps-data.de/Mainpage

21 For information on the 1970 British Cohort Study, refer to https://cls.ucl.ac.uk/cls-studies/1970-british-cohort-study/

22 For information on the UK Millennium Cohort Study, refer to https://cls.ucl.ac.uk/cls-studies/millennium-cohort-study/

https://www.neps-data.de/Mainpage


https://cls.ucl.ac.uk/cls-studies/1970-british-cohort-study/


https://cls.ucl.ac.uk/cls-studies/millennium-cohort-study/


31

The building of a theoretically-informed shared, integrated data infrastructure is complex. The

Taskforce therefore proposes the formation of a transdisciplinary workgroup to look into the

range of interests, approaches, methodologies and operational issues for building such a data

infrastructure.

32

E. Recommendation 3 – Research Collaboratories to

Enable Large-Scale Research-Practice Collaborations

Building upon global research trends towards non-linear approaches of scientific knowledge

production and research translation, the Taskforce proposes for the setting up of research

collaboratories as novel platforms for large-scale research-practice collaborations to augment

the adult learning research landscape in Singapore, with the four priority research areas as

constituent themes.

Augmenting the adult learning research landscape Research collaboratories could be the new mechanism that will bring together the research,

policy and practice communities to jointly engage in research and translation activities. They

will augment existing institution-led research activities23 as well as grant-based investigator-

led research24.

The novelty of research collaboratories lies in their ability to facilitate a concentration of

expertise with common purpose across research institutions and user communities. Research

collaboratories challenge conventional thinking that the best research is possible only when

free from contemplation of potential uses. They also challenge the linear concept of translation,

recognising that researchers, policy-makers and practitioners have unique expertise that

needs to be brought together to develop solutions to a real-world problem. Importantly,

research collaboratories shift away from the challenges of conducting multi- and inter-

disciplinary research by using a common goal to facilitate research that transcends disciplines

i.e. transdisciplinary research.

As a collaboration-based and iterative research model, the goal of research collaboratories is

to draw committed and like-minded researchers and end-users as strategic stakeholders and

co-creators to tackle a broad challenge, thereby injecting new dynamism to the research

landscape.

Table 4 summarises the specific contributions of research collaboratories to the research and

translation processes.

23 A non-exhaustive list of research institutes with current and potential contributions to adult learning research include Agency for Science, Technology and Research (A*STAR), Centre for Ageing Research and Education (Duke-NUS), Centre for Research and Development in Learning (NTU), Centre for Research on Economics and Ageing (SMU), Institute for Adult Learning (SUSS), Institute for Applied Learning Sciences and Educational Technologies (NUS), Lee Kuan Yew Centre for Innovative Cities (SUTD), and National Institute of Education (NTU).

24 The research grants include the National Research Foundation’s Science of Learning, SkillsFuture Singapore’s Workforce Development Applied Research Fund, MOE’s Academic Research Fund and Social Science Thematic Research Grant.

33

Table 4: Contributions of a research collaboratory to research and translation process C

on

trib

uti

on

s o

f a

Rese

arc

h

Co

lla

bo

rato

ry

Use as

inspiration for

good science

The consideration of use is a means for researchers to derive

good, basic research problems, and to anchor research that will

address real world challenges and issues.

Dialogic

knowledge

exchange

Dialogic interactions between diverse research disciplines and

practice enables new solutions to be co-created using the

expertise of researchers and users, thereby improving

prospects for adoption and scalability in the real-world.

Removing

institutional

barriers to

collaboration

By design, a research collaboratory provides a framework,

purpose and space for researchers from multiple disciplines and

stakeholders to work together.

Key working concepts for setting-up research collaboratories

National research collaboratories are almost impossible in other countries because their size

pose significant geographical constraints. This is different in Singapore where researchers

from all autonomous universities have expressed interest in working together to develop a

transdisciplinary adult learning research ecosystem. Research collaboratories thus will be an

important augmentation to the adult learning research landscape in Singapore by creating

common spaces for horizontal and vertical dialogues, knowledge exchange and collaborations.

As the concept of research collaboratories is still at the embryonic stage, further work will be

required to develop it for Singapore’s context 25 . If approved in principle by the funding

agencies, the research and user communities can jointly work out a plan to set up the research

collaboratories, including their scope, how they are organised, mechanisms for working

together, the goals and impact to be achieved, and more. The following parameters could be

used to guide the setting up of research collaboratories:

Strengthening the Concept: To take the idea of research collaboratories forward, a

Workgroup involving researchers from the four Subgroups, policy-makers, practitioners and

funding agencies should be set up, to further develop the broad principles on the purpose(s)

and objectives of research collaboratories, as well as how they can be operationalised.

25 The concept of a research collaboratory proposed in this Report has been formulated for Singapore’s adult learning research context. The term collaboratory has its origins in the US as a digital library for research collaboration, but its use has since become widened to encompass activities such as climate change research, translation and action research. In countries like the Netherlands and Switzerland, the term ‘transdisciplinary’ is preferred.

34

Scale and Funding: The process of setting up collaboratories across research institutes and

user groups is a complex and difficult activity. Examples of challenges cited from experiences

in other countries include obstructive institutional structures, epistemological and ontological

differences, trust issues including credit allocation, and securing strong commitment from

participants given that outcomes depend on the synergy of group discovery26. There must thus

be a strong signal to both researchers and end-users of a long-haul collaboration, who

otherwise might not be willing to work through the issues. For these reasons, a 5-year initial

block grant is proposed to provide certainty in supporting a number of research projects, proof-

of-concepts, demonstration projects, intervention research etc. With the strong use-inspired

and use-applied focus, the research collaboratories may eventually be able to secure a steady

stream of industry funding that could address the more intractable learning challenges of these

industries.

Leadership Models: To raise the level of coordination to the national level, an overarching

body comprising representation from all the AUs may be set up to oversee all adult learning

research collaboratories. This body will develop and oversee a portfolio of use-inspired and

demonstration projects, drawing from the expertise in the wider research and non-research

communities. At the individual collaboratory level, one possible leadership model is for each

research collaboratory to be led by a cross-institutional governing body with relevant subject

matter expertise. For instance, the Science of Adult Learning Research Collaboratory might

be jointly led by the Institute for Adult Learning (SUSS), Centre for Research and Development

in Learning (NTU), and Institute for Applied Learning Sciences and Educational Technology

(NUS). The Learning Cultures × Smart Cities Research Collaboratory could be jointly led by

the Lee Kuan Yew Centre for Innovative Cities (SUTD), Institute for Applied Learning Sciences

and Educational Technology (NUS), and Institute for Adult Learning (SUSS). Alternatively, a

single institute could drive the collaboratory with expert members drawn from autonomous

universities (AUs). A third leadership model could be a governing body drawn from research

and non-research stakeholders. The pros and cons of each leadership model will need to be

examined.

Themes and Scope: The research collaboratories can be set up around the four priority

research areas identified in Recommendation 1. All four priority areas are highly complex,

requiring approaches from a range of disciplines and stakeholder needs. To facilitate buy-in

of researchers and stakeholders, a series of workshops can be set up for the purposes of

enabling a ground-up approach to inclusive idea-generation and network-building sessions.

Each of the four Subgroups that developed the four priority areas could form the nucleus to

engage the policy and practice communities with the aim of jointly scoping up the research

collaboratories and deciding on common objectives/goals for their respective research areas.

The research questions identified in each of the priority research areas could act as starting

points for the discussion.

26 Refer to Gaziulusoy et al. (2016)

35

Collaboratory Project Design: A one-size-fits-all model for research collaboratories is

undesirable. Each of the four priority research areas may attract different sets of researchers

and stakeholders, thereby requiring flexibility in the design of its membership, priorities and

processes. It is sufficient to set minimum requirements, which should include:

Use-inspired science with research that specifically has a dual focus of producing

high-quality scientific work that will also illuminate or help solve real world problems27.

Transdisciplinary research integrating multiple disciplines and the active inclusion

and participation of stakeholders representing different societal sectors in the research

processes28.

Built-in pathways to impact such as demonstration projects drawing from research

findings.

A systematic study of the experiences of other countries that are advancing use-inspired and

transdisciplinary research should be undertaken to further strengthen the concept of

collaboratories before they are actually set up. For instance, it has been found that research

utilisation was highest when a limited number of actors was involved. However, there was a

trade-off in terms of subsequent utilisation by third parties. Informal participation of non-

research stakeholders (consulting transdisciplinary research) was associated positively with

implementation of results, in contrast to their formal participation (participatory

transdisciplinary research), thus suggesting that the involvement of non-research

stakeholders at strategic points is more useful. The academic requirement to publish has been

found to thwart research participation in transdisciplinary research as the best academic

journals tend to be monodisciplinary. This highlights the need to open up the academic

incentive and reward system to accommodate non-academic outputs29. The challenges of

setting up collaboratories may well go beyond the interests of researchers and stakeholders

in working together and realising use-inspired, transdisciplinary research.

27 First identified by Stokes (1997), use-inspired research has been defined as “scientific investigation whose rationale, conceptualisation, and research directions are driven by the potential use to which the knowledge will be put”. The Swiss National Science Foundation provides more elaboration of use-inspired basic research at http://www.snf.ch/en/theSNSF/research-policies/use-inspired-basic-research/Pages/default.aspx.

28 A definition of transdisciplinary research provided is “integration of multiple disciplines and the active inclusion and participation of stakeholders representing different societal sectors in the processes of problem formulation, knowledge production, and learning” (Angelstam et al., 2013).

29 Challenges of transdisciplinary research are highlighted by Angelstam (2013), Brien, Marzano and White (2013), de Jong, Wardenaar and Horlings (2016), and Gaziulusoy et al. (2016), among others.

http://www.snf.ch/en/theSNSF/research-policies/use-inspired-basic-research/Pages/default.aspx


36

International examples of research collaboratories or equivalent

Re

se

arc

h C

olla

bo

rato

rie

s

NIH Healthcare

Systems

Research

Collaboratory

(US)30

Results from conventional clinical trials performed in controlled

settings on a tightly defined group of individuals have limited

relevance in real-world health care settings. This collaboratory

supports implementation of ‘pragmatic clinical trials’ that are

conducted at the site of care with healthcare delivery

organisations actively participating in the research.

MIT Media Lab

(US)31

Positioned as ‘antidisciplinary’, the lab draws from a range of

disciplines including technology, media, science, art

and design. Research programs include iterative development

of prototypes which are tested and displayed for visitors.

Specific projects and researchers are government funded,

while corporations are invited to sponsor general themes for

which they have royalty-free IP access.

USYS

Transdiscipli-

narity Lab

(Switzerland)32

Transdisciplinarity (Td) Lab focuses on sustainable

development through an approach to scientific inquiry that

deals with complex, real-world problems. It places an

emphasis on joint problem framing between people inside and

outside of academia, with the aim of developing possible

solutions.

30 For more information on the NIH Research Collaboratory, refer to http://commonfund.nih.gov/hcscollaboratory/.

31 For more information on the MIT Media Lab, refer to https://www.media.mit.edu/

32 For more information on the USYS Transdisciplinarity Lab, refer to https://usys.ethz.ch/en/research/TdLab.html

https://en.wikipedia.org/wiki/Technology

https://en.wikipedia.org/wiki/Multimedia

https://en.wikipedia.org/wiki/Sciences

https://en.wikipedia.org/wiki/Art

https://en.wikipedia.org/wiki/Design

http://commonfund.nih.gov/hcscollaboratory/

https://www.media.mit.edu/

https://usys.ethz.ch/en/research/TdLab.html

37

F. Recommendation 4 – Flagship Platforms for a Leading

Research-User Community in Singapore

Finally, the Taskforce proposes creating flagship platforms that signal the building of a leading

research-user community in Singapore towards transdisciplinary and use-inspired research.

International researchers have observed that Singapore is leading in terms of its dedicated

push for adult learning, which should be built on to signal our intent to be a leader in adult

learning research. Throughout the process of engagement, the Taskforce received numerous

suggestions for platforms that bring researchers and research-users together. The Future of

Adult Learning Research Symposium was very well-received by Singapore and international

researchers alike for bringing together diverse expertise. It was regarded as a signature

conference for adult learning for its function as a platform for dialogue and discourse among

experts from different disciplines who were interested in adult learning. There should also be

concerted efforts to create showcase labs as well as living labs or sandbox environments in

authentic settings to facilitate top-down and bottom-up investigations and applications of

research. It has also been observed that there is no professorship and investigator-ships in

adult learning in Singapore’s autonomous universities, which is a gap in terms of building long-

term research capabilities. Therefore, to build a leading research-user community in

Singapore, the following ideas are proposed:

Signature international researcher-user conference on adult learning

Interdisciplinary peer-reviewed journal

on adult learning

Showcase labs where researchers and users dialogue and generate ideas, utilising emerging research

Living labs / sandbox environments at workplaces & other communities to

support the development and piloting of research-informed practice

Professorships & investigatorships on adult learning

38

G. Concluding Remarks

In this Report, we highlight new perspectives, directions and approaches for the future of adult

learning research agenda in Singapore. Based on the review of the global trends, we call for

an expanded role for adult learning research in Singapore. The table below summarises the

key recommendations from the Taskforce on the Future of Adult Learning Research Agenda

for Singapore:

Table 5: Summary of key recommendations for the future of adult learning research

for Singapore

Fu

ture

of

Ad

ult

Lea

rnin

g R

es

ea

rch

fo

r S

ing

ap

ore

: S

um

mary

Outcomes and

Impact of Adult

Learning

Personal, economic and social well-being

Recommendation

1

Four priority research areas to advance adult learning research in Singapore in the next 5-10 years with high potential for academic excellence and significant contributions to Singapore’s national priorities:

Science of Adult Learning


Learning Cultures × Smart Cities

Digital Futures and Human Capabilities

Recommendation

2

Shared data infrastructure to support adult learning research, policy evaluation and data-driven practices, through the following key approaches:

Public-private data lake

Big data streams

Long-range studies, including panel and cohort studies

Recommendation

3

Research collaboratories as a new mechanism to facilitate large-scale research-practice collaborations, driven by use-inspired, transdisciplinary research, supported by initial 5-year block grants

Recommendation

4

Flagship platforms that signal the building of a leading

research-user adult learning community in Singapore

Signature international research-user conference

Interdisciplinary peer-reviewed journal on adult learning

Showcase labs

Living labs / sandbox environments

Professorships and investigatorships in adult learning

39

To take the recommendations forward, we recommend the setting up of the following

Workgroups:

Transdisciplinary Workgroup on a shared data infrastructure: To look into the range

of interests, approaches, methodologies, priorities and operational issues for setting up

a shared data infrastructure

Transdisciplinary Workgroup on research collaboratories: To involve researchers,

practitioners and funding agencies to further develop the concept of a research

collaboratory for operationalisation, with the four priority research areas as possible

themes

Cross-institutional Workgroup on building a leading research-user community:

Cross-institutional workgroup across Autonomous Universities to discuss mechanisms

for creating flagship research-user platforms in adult learning, including involving

stakeholders

The key impact envisaged from the new adult learning agenda is wide-ranging. The new

agenda will support the building up of Singapore’s thought leadership in formulating research

and policy in adult and lifelong learning internationally in four high-impact areas. It will also

provide the foundations for a unique research-practice nexus and culture of collaboration in

adult learning where research contributes strategically to policy-making and practices, and

vice-versa. It will also build a learning culture in the adult population, develop new cutting-

edge capabilities and talent among adult learners, and sustain adult and lifelong learning as a

key socio-economic strategy for Singapore over the long-term.

40

References

Online Resources

1970 British Cohort Study. (2020). https://cls.ucl.ac.uk/cls-studies/1970-british-cohort-study/

Committee on the Future Economy, Singapore. (2017). Report of the Committee on the Future

Economy: Pioneer of the Next Generation. Singapore. Available at

https://www.mti.gov.sg/Resources/publications/Report-of-the-Committee-on-the-

Future-Economy.

German National Education Panel Study. (2020). https://www.neps-data.de/Mainpage

MIT Media Lab. (2020). https://www.media.mit.edu/

NIH Healthcare Systems Research Collaboratory. (2020).


SkillsFuture Singapore Agency. (2020). https://www.skillsfuture.sg/

Smart Nation Office. (2019). https://www.smartnation.sg.

Singapore Life Panel. (2020). https://crea.smu.edu.sg/singapore-monthly-panel

Singapore Panel Studies on Social Dynamics. (2020).

https://lkyspp.nus.edu.sg/ips/research/ips-social-lab/singapore-panel-study-on-social-

dynamics

Singapore Population Health Studies. (2020). https://blog.nus.edu.sg/sphs/

Swiss National Science Foundation. (2020). http://www.snf.ch/en/theSNSF/research-

policies/use-inspired-basic-research/Pages/default.aspx.

National Science Foundation. (2020). The Science of Learning and Augmented Intelligence

Program. https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505731

UK Millennium Cohort Study. (2020). https://cls.ucl.ac.uk/cls-studies/millennium-cohort-study/

USYS Transdisciplinarity Lab. (2020). https://usys.ethz.ch/en/research/TdLab.html





https://www.media.mit.edu/


https://www.skillsfuture.sg/

https://www.smartnation.sg/

https://crea.smu.edu.sg/singapore-monthly-panel

https://lkyspp.nus.edu.sg/ips/research/ips-social-lab/singapore-panel-study-on-social-dynamics

https://lkyspp.nus.edu.sg/ips/research/ips-social-lab/singapore-panel-study-on-social-dynamics

https://blog.nus.edu.sg/sphs/



https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505731


https://usys.ethz.ch/en/research/TdLab.html

41

Selected Academic Publications*

Angelstam, P., Andersson, K., Annerstedt, M. et al. (2013). Solving problems in social–

ecological systems: definition, practice and barriers of transdisciplinary

research. AMBIO, 42, 254–265.

Buizer, M., Ruthrof, K., Moore, S.A., Veneklaas, E.J., Hardy, G. & Baudains, C. (2015). A

critical evaluation of interventions to progress transdisciplinary research, Society &

Natural Resources, 28:6, 670-681

Callegaro, M., & Yang, Y. (2017). The Role of Surveys in the Era of “Big Data”. In D. L.

Vannette, & J. A. Krosnick, The Palgrave Handbook of Survey Research (pp. 175-192).

Open online access at https://link.springer.com/content/pdf/10.1007%2F978-3-319-

54395-6_23.pdf

Cooper, A. & Levin, B. (2010). Some Canadian contributions to understanding knowledge

mobilisation. Evidence & Policy, 6:3, 351-369

de Jong, S.P.L., Wardenaar, T. and Horlings, E. (2016). Exploring the promises of

transdisciplinary research: a quantitative study of two climate research programmes.

Research Policy, 45: 1397-1409.

Evans, K., Waite, E., & Kersh, N. (2011). Towards a social ecology of adult learning in and

through the workplace. In M. Malloch, L. Cairns, K. Evans, & B. N. O’Connor (Eds.), The

SAGE Handbook of Workplace Learning (pp. 456–465). London: Sage.

Gaziulusoy, AI., Ryan, C., McGrail, S., Chandler, P., and Twomey, P. (2016). Identifying and

addressing challenges faced by transdisciplinary research teams in climate change

research. Journal of Cleaner Production, 123: 55-64.

Knowland, V.C.P., and Thomas, M.S.C. (2014). Educating the adult brain: how the

neuroscience of learning can inform educational policy. International Review Education,

60:99–122.

Letaifa, S.B. (2015). How to strategize smart cities: revealing the SMART model. Journal of

Business Research, 68: 1414-1419.

Lido, C., Reid, K., and Osborne, M. (2019). Lifewide learning in the city: novel big data

approaches to exploring learning with large-scale surveys, GPS, and social media.

Oxford Review of Education, 45:2, 279-295.

Miller, S.M. (2018). AI: Augmentation, more so than automation. Asian Management Insights,

5:1, 1-20.

https://link.springer.com/content/pdf/10.1007%2F978-3-319-54395-6_23.pdf

https://link.springer.com/content/pdf/10.1007%2F978-3-319-54395-6_23.pdf

42

O’Brien, L., Marzano, M., and White, R.M. (2013). Participatory interdisciplinarity: towards the

integration of disciplinary diversity with stakeholder engagement for new models of

knowledge production. Science and Public Policy, 40: 51-61

Stokes, D. (1997). Pasteur’s Quadrant: Basic Science and Technological Innovation.

Washington: The Brookings Institution.

*Full lists of academic publications are in the Subgroup Reports at Annexes 2-5.

charting the future of adult learning research in

Documents