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Innovative Social
Sciences Teaching
and Learning
Facilitating Students’ Personal
Growth and Career Success
Katharina Rietig
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Innovative Social Sciences Teaching and Learning
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Katharina Rietig
Innovative Social
Sciences Teaching and
Learning
Facilitating Students’ Personal Growth
and Career Success
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Contents
1 Introduction 1
Artificial Intelligence and Shifting Roles for Social Sciences
Graduates 1
The Changing World of Work 4
Changing Expectations of and Requirements for Graduates 6
Who Is This Book For? 9
Chapter Overview 10
References 13
Part I The Big Picture of Learning Theories and Course
Design 17
2 Learning
Theory: The Power of Yet and Dreaming Big 19
What Is Learning? 20
How Do We Learn? Insights from Social Psychology and
Organizational Studies 22
The Linear Cognitive Learning Process 22
Experiential Learning 23
Single- and Double-Loop and Deutero Learning 25
The Complete Cycle of Choice 27
Non-learning: Defensive Avoidance, Unlearning, and
Muddling Through 28
The Learning in Governance Framework 29
v
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vi
Contents
The Growth Mindset, Grit, Perseverance, and Try: Attributes
of Policy Entrepreneurs as Agents of Change 32
The Personal Growth Mindset: Framework for Analysis 36
Conclusion 38
References 39
3 Constructive
Alignment in Course and Degree Design 43
The Personal Growth Mindset and Constructive Alignment 44
Constructive Alignment in Degree Programs 46
Constructive Alignment Within Courses 49
Conclusion 66
References 67
Part II Teaching Activities to Develop a Growth Mindset
in Students 71
4 Lectures 73
Lectures, Lecturers, and the Personal Growth Mindset 74
In-person Lectures, Online Lectures, and Blended Approaches 76
Preparing the Lecture 83
Delivering the Lecture 86
Conclusion 88
References 89
5 Seminars 91
The Growth Mindset and Seminar Design 92
Face-to-Face Seminars Versus Online Seminars, and Hybrid
Approaches 93
Seminar Preparation 96
Running the Seminar 97
Seminar Activities 99
Student Presentations 99
Answering Sample Exam Questions 100
Working Through Math Problems and Quantitative Methods
Training 102
Discussing Questions and Case Studies 103
Debates 105
Conclusion 107
References 107
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Contents vii
6 Study Groups109
How Can Study Groups Help Develop/Embed a Growth Mindset? 110
Study Group Examples and Typology 112
Study Group 1: The Friendship and Peer Group 112
Study Group 2: The Social Club 113
Study Group 3: The Student-Led Exam Prep Course 114
Study Group 4: The Incentivized Group 115
Study Group 5: The Never Have-Beens 117
Integrating Study Groups into the Course 117
Advantages of Study Groups 120
Addressing Challenges 122
Conclusion 123
References 124
7 Simulations127
Benefits and Challenges of Simulations 129
Planning, Preparation, Running the Simulation, and Reflection 131
Negotiation Venue 131
Country/Role Assignments 132
Position Paper 132
Training and ‘Working Up’ to Larger MUNs 133
During the Simulation 134
Element of Reflection 135
The Simulation Itself 135
MUNs and Other Simulations in 1–2-Hour Seminars 135
Half-Day up to 2 Day MUNs as Part of a Course 137
MUNs as Week-Long Championship in Diplomacy and
Debating 142
Conclusion 143
References 144
8 Supervising Dissertations147
Developing a Supervisor-Supervisee Relationship 148
Identifying the Research Question: Or Seeing the Trees in the
Forest 150
Typical Dissertation Structure 152
Addressing Common Challenges Faced by Students 155
Procrastination and Writer’s Block 155
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viii
Contents
Getting Lost in the Woods During the Literature Review 157
Data Availability and Analysis 159
Too Exhausted for a Clear, Concise Discussion Section 161
Confusing a Dissertation with an Essay or Including Too
Much Personal Opinion 163
Conclusion 164
References 164
9 Conclusion167
Constructively Aligning Degrees and Courses with the Personal
Growth Framework 168
Mainstreaming Major Societal Challenges 171
The Personal Growth Framework and the World of Work 172
References 173
References175
Index189
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List of Figures
Fig. 2.1
Fig. 2.2
Fig. 2.3
Fig. 2.4
Fig. 2.5
Cognitive learning process. Source: Adapted by author from
Swann, 1999: 266
Simple model of individual learning/the learning cycle. Source:
Kim, 1993: 40 based on Argyris, 1976
Kolb’s experiential learning cycle. Kolb & Kolb, 2005
Complete cycle of choice. Source: March & Olsen, 1975: 150
Personal growth mindset framework
23
24
25
28
37
ix
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CHAPTER 1
Introduction
This book offers novel insights into how students can develop a personal
growth mindset during their degree programs that allows them to view
new challenges as opportunity to grow personally, reflect on the new
knowledge and experience, and subsequently improve their skills to critically examine and evaluate information on a journey of personal growth.
It provides a novel framework that allows university teachers to constructively align learning objectives and assessments with crucial transferable
skill development and fostering a mindset for personal growth among students with a focus on continuously improving and reflecting on feedback.
The objective is to empower academics to develop and deliver courses and
degree programs that are ‘fit for purpose’ by equipping social science students with the skills and mindsets that will benefit them throughout their
careers in ever-changing and newly emerging jobs.
Artificial Intelligence and Shifting Roles for Social
Sciences Graduates
Studying Social Sciences at university or small liberal arts colleges offers
the unique opportunity to deeply engage with literature, world-changing
ideas, new concepts, and to critically evaluate what these mean in any
given social, economic, and political context. These three to four years in
student’s lives are also a formative phase before entering the workplace
1
K. Rietig, Innovative Social Sciences Teaching and Learning,
https://doi.org/10.1007/978-3-031-41452-7_1
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2
K. RIETIG
and starting their careers. For many, these years mark the transition into
adulthood and discovering one’s purpose in life (Heckhausen et al., 2019).
It also means a considerable financial investment either through tuition
fees in most countries or at least through the years of income forgone
compared to vocational training. At the same time, most students are concerned about their employability prospects. This means that students are
increasingly asking how what they learn in their degree programs will be
relevant for achieving their career and professional aspirations.
At the same time, artificial intelligence (AI) applications in the form of
large language models and machine learning such as ChatGPT, the Google
chatbot Bard, Microsoft’s Windows 11 Copilot, and others enter education in formal and informal ways through facilitating time-consuming
tasks. This means that students are getting increasingly familiar with the
opportunities offered by virtual personal assistants and that educational
providers need to both address the associated ethical challenges such as
plagiarism, as well as explore ways of embedding AI applications into educational practice (Popenci, 2022). At the same time, it requires strengthening and maintaining a focus on student’s cognitive and social
development, and in particular their ability to adapt to the fast-paced technological changes that continue to emerge over the next decades.
Education providers are adapting and integrating into teaching practices
such technologies, which also increasingly include virtual reality applications (for more details, see, e.g., Araya & Marber, 2023; Viegas & Correia,
2022). They are thus reacting to the increasing importance of technology
in the classroom (see Jaafar & Pedersen, 2021; Khadimally, 2022; Wang
et al., 2021).
While integrating such new and emerging technologies into teaching is
important and increasingly happening across higher education providers
as well as secondary schools, this book takes a long-term perspective by
focusing on the mindset that students need to develop to keep up with
future technological developments that we can currently only glimpse the
early beginnings of. Most of the integration of AI technologies into teaching and learning practices of the early 2020s will be outdated in the 2030s
much like computers, tablets, and digital learning resources have replaced
pen, paper, and print books in the 2000s and 2010s.
This book is less about the means and tools, i.e., the technologies and
their uses themselves, than about innovative approaches to allow students keep up with whatever changes in technologies and the workplace
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1
INTRODUCTION
3
they encounter during their careers. This is why the mindset that students develop during their studies is crucial. If they were to take away
only one attitude and related skill from their education, then it should
be having learned how to learn and how to deal with new challenges in
a way that allows them to live fulfilled lives no matter what the technological, economic, and social framework conditions they find themselves in.
Consequently, the question is how can Social Sciences degree programs
in, e.g., Business, Communication Sciences, Environmental Studies,
Economics, Geography, Law, Political Science, or Sociology prepare students for the changing world of work, especially the rise of artificial intelligence applications in white-collar jobs? This is highly relevant given the
increasing professionalization of degree programs that react to the calls for
including internships, simulations, research projects, and other skill-­
development into their elective and/or core curriculum to improve
employability (Szymaniak, 2022). Social sciences departments across
North America, the United Kingdom, Europe, Asia, and beyond are revising their curriculums to react to challenges such as declining enrolment
and to integrate best practices, including developing teamwork skills
through capstone projects (Bayer et al., 2022).
My central argument is that although these experience-based curriculum revisions are important, they need to be combined with encouraging
a personal growth mindset in students that prepares them not only for
current careers, but for the future of work. Student’s career destinations
are undergoing fundamental and rapid changes, which make it even more
important to equip students with a mindset that makes them highly adaptive to new technologies, opportunities, and increased awareness of cross-­
cutting challenges such as on sustainability, equality, diversity, and inclusion
(Queshi et al., 2020; Vos et al., 2016). Most students will enter jobs and
careers that do not yet exist. This means that they require the skills for
self-directed learning and teamwork (Bayer et al., 2022) to be creative,
confidently deal with challenges and changing environments, as well as
develop a mindset that focuses on continued growth and personal
development.
This chapter examines the fundamental changes to white-collar jobs
brought on and expected by AI applications and assesses how a personal
growth mindset, perseverance, and not giving up in the face of challenges
(Dweck, 2017) can equip students to rise to future challenges in their
professional careers. It concludes that degree programs need to
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constructively align their teaching and learning offerings to support students in developing a mindset and skill set aimed at being able to better
adapt to future challenges and engage in lifelong learning. This is particularly important for the increasing group of first-generation students who
depend on their experience at university within the curriculum, extracurricular activities and accessing the hidden curriculum (Gable, 2021) to
develop the growth mindset and skills to succeed once they graduate.
The Changing World of Work
The world of work that graduates enter is constantly changing. In most
subject disciplines, some of the jobs and career paths graduates will eventually pursue have not yet existed when they started their studies (Cameron,
2017). Who has heard of a social media manager, artificial intelligence
specialist, or big data analyst in 2005 (Reese, 2018)? Or a web developer
in 1990? At the same time, what happened to the typist pools of secretaries that occupied most open plan office floors in the 1970s and 1980s? Or
the stock market exchange traders of Wall Street? Where did all the bank
staff go when bank branches closed or consolidated with the rise of online
banking? As new jobs, and with them career pathways, emerge, others
encounter diminishing opportunities and fundamental changes (Sumantran
et al., 2017; Zuboff, 2019), including the emergence of automation and
algorithms in management either through augmented approaches or even
AI applications taking over direct management and decision-making functions as ‘boss’ (Aloisi & DeStefano, 2022). This is not only restricted to
the gig economy (Moore & Woodcock, 2021) or autocratic regimes
(Zeng, 2022) but increasingly mainstreamed in sectors such as banking,
insurance, and finance across the global north and global south (Nir,
2023). Earlier, industrial revolutions, automation advances, and waves of
outsourcing to countries with lower wages were focused on blue-collar
jobs, but increasingly typical entry positions for graduates of Social
Sciences degree programs are also affected. The rise of narrow artificial
intelligence means that also typical office-based white-collar jobs with
career pathways and professional accreditations are changing rapidly
(Moore & Woodcock, 2021). This impacts on the key sectors and employers where Social Science graduates will work, ranging from non-profit and
civil society organizations such as NGOs to the government sector/civil
service and small/medium sized as well as multinational companies within
the private sector as the largest employer.
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INTRODUCTION
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The increased level of automation will result in large numbers of jobs
disappearing in highly qualified areas such as law, public relations, and
government administration in addition to lower qualified areas such as
logistics or driving of vehicles (Vaidhyanathan, 2011, 2018). At the same
time, decarbonization of industries also means job losses in carbon intensive and fossil fuel extraction sectors, including office administration.
Studies that analyzed what percentage of jobs could be automated on the
basis of the tasks performed by these jobs and any computerization bottlenecks (Davenport, 2018) found that by 2033, 47% of jobs in the US were
likely to be automated and that 35% of jobs in the UK could be automated
within 10–20 years. Other studies argued that the actual level of automation potential is likely closer to 5–10% as jobs also contain other tasks that
cannot be automated. However, it is important to keep in mind that any
estimates cannot foresee future developments and impacts such as
Covid-19 measures or the arrival and mainstreaming of large language
models. Covid-19 measures, including a shift toward home office, remote
working, and video conferencing solutions (Yarberry & Sims, 2021) have
accelerated this trend. It is being solidified by a culture shift among many
companies and employees who expect hybrid working and fewer days at
the office to become the norm, not the exception.
There are two likely outcomes: large-scale automation and marginal
automation/augmentation of human employees by artificial intelligence
and vice versa (Davenport, 2018). The level of large-scale automation is
expected to be around 5–10% due to associated high costs. Whether a job
becomes automated also depends on benefits beyond replacing labor
costs, the availability and scarcity of skilled labor, considerations around
regulation/legal frameworks, and level of social acceptance. Augmentation
of human workers and artificial intelligence applications is more likely as
few jobs contain sufficiently high shares of tasks that could be fully automated. Experience from earlier technological advances suggests that the
new technologies supplement existing jobs (Broussard, 2018). As some
tasks get automated, new tasks and entirely new jobs are likely to emerge,
amounting to a net-increase overall (Dougherty & Wilson, 2018).
Automating certain tasks results in increased demand for addressing new
follow-on problems or new tasks (Ross, 2017) such as training cognitive
technologies in capabilities like empathy, sustaining the performance of
cognitive systems over time with regard to ethical compliance and task
performance, and explaining the processes and results of recommendations made with artificial intelligence-involvement to senior
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decision-makers (Davenport, 2018). This implies a shift in employment
and a high need for investment in education, both the ‘classic’ route of
entering higher education after secondary school and an increasing importance of life-long learning that allows for the updating of existing skills and
learning of new skills to keep pace with the ever-evolving technological
capabilities.
Consequently, technological developments such as artificial intelligence
and related societal shifts impact on graduate’s jobs and careers, with new
opportunities and increased convenience (Moring, 2022; Nir, 2023), as
well as new challenges such as ingrained inequalities, surveillance, and loss
of autonomy (Chun & Barnett, 2021; Verdegem, 2021). Knowledge of
facts gets increasingly outdated as new scientific findings emerge and new
technological developments take hold. This includes supporting technologies such as the widespread uptake of communication applications like
Slack and Microsoft Teams, virtual personal assistants and video conferencing software such as Zoom. However, it also impacts upon ‘know-­
how’ and the time intensity of finding information. Gone are the days of
pouring over library catalogues on index cards, ordering books, or searching for journal articles on dusty shelves. Today’s students can write entire
dissertations based on a much wider range and higher quality of academic
sources without ever setting foot into the library building—an Internet
connection anywhere in the world suffices.
Changing Expectations of and Requirements
for Graduates
All these developments mean that knowing facts, which are increasingly
outdated and replaced by new scientific findings, becomes less important
in many disciplines than embedding the ability to find, synthesize, analyze,
and especially to critically evaluate new knowledge as well as determine its
relevance to one’s current needs. Skills such as information literacy, i.e.,
the ability to find and synthesize, are crucial for research and writing, yet
only 8.8% of university teachers consider their arriving Social Science students as having sufficient information literacy to succeed (Thornton &
Atkinson, 2022). There is also a whole array of skills and tasks that will be
increasingly needed as much of the ‘groundwork’ of finding information
and analyzing data gets automated similar to the secretarial and typist
pools before the arrival of the photocopier and personal computer. By the
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INTRODUCTION
7
2020s, personal electronic assistants, like Apple’s SIRI, Google’s Echo,
and Amazon’s Alexa, among others, facilitate and replace tasks that were
once carried out by personal assistants and office support staff. All these
technological developments free up time for other tasks and activities.
Many of these new tasks and activities will be in the area of creativity and
innovation (Bessen, 2015) with regard to generating new ideas, identifying new opportunities for offering services and products, research and
development of such new services and products, and in particular social
networking and interpersonal communication skills, which is mirrored by
employer’s expectations communicated in job advertisements (Rios et al.,
2020). As more information and data become available in pre-analyzed or
synthesized form thanks to big data, it will be ever more important to be
able to identify the relevant information and especially critically evaluate it
for its implications and set it into the relevant context.
Social Science graduates will need to be able to identify new opportunities, convincingly present their ideas to colleagues and stakeholders,
collaborate, use critical thinking skills as well as work in an international
context and within virtual teams to implement these ideas to ultimately
solve problems and address key societal and economic challenges (Rios
et al., 2020). In many professions, there is a ‘hidden curriculum’ of, in
the case of academia, networking, grant writing, and publication skills
that new entrants need to be aware of and familiar with if they are to
succeed in their careers (Windsor & Kronsted, 2022). Being aware of
and mastering professions’ hidden curricula is an important skill students need to develop independently of their existing social capital,
especially in the interest of equality, diversity, and inclusion (Papa,
2020). Graduates also need to be able to differentiate between knowledge based on scientific research and ‘post-truth’ fake news (Chinn
et al., 2021). Furthermore, they are likely to change employers or even
careers several times during their working life, which further increases
the importance of adaptability and flexibility, as well as motivation
(Latham & Pinder, 2005).
All these skills and abilities that will determine success could be summarized within a mindset for personal growth. Especially Social Science
graduates with no set professional career pathway such as accountants or
lawyers contribute their soft skills, adaptability, and creativity for problem
solving as key characteristics in their jobs. Specializations and internships/
work placements are a crucial step (Lester & Costley, 2010; Szymaniak,
2022) with potential to widen participation and close achievement gaps
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8
K. RIETIG
between ethnic minority students/students of color and white students
(Moores et al., 2017; Tate, 2020). So ideally, their time at university
allows students to develop such skills and more importantly a mindset for
personal growth that helps them to seek out new knowledge and skills, use
their creativity, and to deal with the changing world of work.
Drawing on research in social and cognitive psychology, this book’s
central argument is that student’s mindsets play a crucial role at determining how they develop the key attributes of successful graduates that have
the necessary skills to succeed in their later careers and achieve their professional goals. Students with a fixed mindset believe that abilities are
born, they are either smart or they are not. They focus on current performance and not ‘looking bad’, resulting in behavior that discounts effort
and avoids challenges, getting discouraged by mistakes and defensive
when receiving feedback. In short, students shy away from opportunities
to grow personally and professionally. However, university teachers can
change student’s mindsets with our teaching and course design by constructively aligning the course content with opportunities to develop a
‘growth mindset’ (Dweck, 2017).
This book demonstrates how the personal growth mindset can be integrated into the undergraduate and master’s degree curriculum. It examines how teaching activities such as lectures and seminars can be modified
and aligned with assessments to allow for feedback loops and encourage
students to approach their performance as ‘not yet’, leading to reflection
on how they can further improve. This means praising students for the
process they engage in. Instead of rewarding right answers, a growth
mindset-focused course rewards the learning process. Focusing feedback
on ‘not yet’ creates greater confidence and persistence as well as encourages students to improve. Pushing students out of their comfort zone to
work hard helps to increase academic performance and enables students to
grow with the challenges they will encounter in their later careers (Dweck,
2017). This book contributes to the education literature with a theoretical
framework on learning based on reflection on input resulting in factual,
experiential, and constructivist learning that allows to conceptualize learning and teaching strategies aimed at developing a growth mindset among
students. It also contributes to academics’ understanding how they can
have a positive impact on their student’s employability, problem-solving,
public speaking, and advanced research skills, in addition to fact-based
degree program-specific knowledge.
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INTRODUCTION
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Who Is This Book For?
This book is particularly useful for three groups. First, scholars in the fields
of education, psychology, public policy, and management studies who are
interested in how individuals learn in educational settings and in the wider
workplace, e.g., in policymaking or large bureaucracies, and how their
learning influences decision-making.
Second, this book has a very high relevance for the wider academic
audience of scholars who teach as part of their academic appointment. It
speaks to mid-career and senior scholars who reflect on their teaching
practices with regard to the relevance and usefulness of their teaching
methods and who are open to innovative approaches that equip students
with the skills to succeed in any professional career of the twenty-first century that requires life-long learning, creativity, resourcefulness, and perseverance. It is primarily written with early career scholars (PhD candidates,
postdocs, teaching fellows/lecturers on the teaching and scholarship track,
as well as lecturers/assistant professors on the research and teaching career
track) in mind who are in their early years of teaching and actively developing their teaching philosophy and practice.
Third, this book is aimed at academics and teaching professionals who
are involved in designing and delivering professional development programs
for teaching in higher education. These programs are offered by all UK
universities and increasingly across continental Europe, the United States,
and Asia. They are optional for PhD candidates, postdocs, and teaching fellows, but their successful completion tends to be mandatory for lecturers/
assistant professors to pass their probation phase/tenure review to be
appointed on a permanent research and teaching contract. One common
criticism of these teaching certificate programs across UK post-1992,
research intensive and Russell Group universities (or the equivalent of Small
Liberal Arts Colleges, R2 and R1 universities in the United States) is that
they are little more than ‘box ticking’ exercises that require ‘jumping
through hoops’. This book hopes to contribute to reading lists of teaching
certificate programs as it allows teachers, mentors, and participants, including those from professional services career paths involved in delivering training programs, to make use of the unique opportunity for early career
academics to genuinely reflect on their teaching, how it can be better aligned
with the skill development and personal growth of their students, and thus
go beyond the communication of facts toward student-focused learning
that includes experiential learning and a growth mindset.
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Chapter Overview
Part I: ‘The Big Picture of Learning Theories and Course Design’. The
first part introduces a theoretical framework for conceptualizing and analyzing learning in higher education. This ‘Personal Growth Framework’
draws on latest advances in psychology, education, management studies,
and public policy. Chapter 2 introduces this framework following a review
of the related literatures. Chapter 3 addresses the central research question
how learning theories can support teaching and learning in higher education settings with regard to designing degree programs in the social sciences and constructively aligning learning activities with assessments and
professional skill development.
Chapter 2. ‘Learning Theory: The Power of Yet and Dreaming Big’.
This chapter offers an introduction to and overview of central learning
theories from the fields of education, psychology, public policy, and management studies, and reflects on their applicability in higher education
settings. For example, it draws on ‘classic’ approaches such as Bloom’s
Taxonomy of lower and higher level cognition, single- and double-loop
learning based on Argyris and Schön, as well as the further development
into Kolb’s Learning Cycle. It discusses recent advancements from the
field of psychology into social sciences teaching in higher education, especially with regard to moving from fixed mindsets to growth mindsets and
‘the power of yet’, developed by Professor Carol Dweck (Stanford
University), and the related concept of ‘grit’ with a focus on perseverance
and policy entrepreneurial drive put forward by Professor Andrea
Duckworth (University of Pennsylvania). Drawing on my own research on
learning theories, in particular the ‘Learning in Governance Framework’
(Rietig, 2021), this chapter makes a novel contribution by presenting the
‘Personal Growth Framework’ (PGF) that helps to constructively align
career-relevant skill development with teaching and learning activities.
Chapter 3. ‘Constructive Alignment in Course and Degree Design’.
Chapter 3 links the previous chapter on learning theories and the theoretical framework with teaching practice in higher education. It starts with the
big picture of degree program development at both the undergraduate
and master’s levels. It examines constructive alignment of learning objectives with developing skills for a successful career, including in jobs that do
not yet exist. It then zooms in on course-specific learning objectives and
links the learning theories, in particular the Personal Growth Framework,
with the constructive alignment of teaching and learning activities. It first
explains what constructive alignment means and why it is important in
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1 INTRODUCTION
11
higher education, i.e., how close and obvious links between the learning
objectives, teaching/learning activities, and assessment (Biggs, 1996) can
increase and maintain student motivation and strengthen the development
of a growth mindset and skills. The third section provides an example of a
course that integrated elements supporting a personal growth framework
within the UK educational context.
Part II: ‘Teaching Activities to Develop a Growth Mindset Among
Students’. The second part of the book examines distinct approaches,
techniques, and learning activities. It addresses the question to what extent
and how these activities can help to develop a growth mindset both within
the ‘traditional’ face-to-face setting in the lecture hall, seminar room, and
supervision meetings, as well as in synchronous and asynchronous online/
distance teaching through Teams, Zoom, or similar platforms that allow
communicating independently of the teacher’s/student’s location and/or
at the student’s individual pace.
Chapter 4. ‘Lectures’. Chapter 4 reflects on how a lecture can be set
up and delivered to keep students engaged. It discusses advantages and
challenges with regard to delivering the lecture in-person/face-to-face or
online. It examines planning the lecture, taking into account pre-existing
knowledge of the students, and discusses activities during the lecture such
as integrating polls and small group discussions in break-out groups with
subsequent reporting back to the larger group.
Chapter 5. ‘Seminars’. Chapter 5 examines how seminars can be constructively aligned with the learning objectives and developing a personal
growth mindset. It examines different aims of a seminar and reflects on
seminar preparation as well as the actual running of the seminar. This
includes the opening of the seminar by presenting the structure and activities, guiding the seminar discussion as moderator, posing and discussing
reading-related questions and seminar activities that are focused on
student-­centered activities. These include student presentations (individually or by a study group), mini-debates, and answering previous year’s
sample exam questions through small group discussions/group work. The
final five minutes of the seminar are focused on summarizing key points
and reinforcing ‘takeaways’ by linking them to the learning objectives. It
also offers scope for asking students for feedback, especially if the seminar
included new activities. The chapter also provides insights into integrating
the personal growth framework in teaching and learning settings that
require problem solving such as quantitative methods and math exercises/
problem sets and computer-based experiments.
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12
K. RIETIG
Chapter 6. ‘Study Groups’. Chapter 6 examines the advantages and
challenges of integrating study groups into courses. This can happen voluntarily by encouraging students to form study groups and offering advice
on how this can be done most effectively. Alternatively, study groups can
be included into the assessment by, for example, offering a small percentage of the course mark for completed group assignments such as summaries of the core readings/literature and answering related questions in a
study group meeting, including a subsequent report that summarizes the
discussion. The chapter outlines advantages and discusses challenges
around study groups. The chapter then proceeds to reflecting on how
these challenges could be addressed.
Chapter 7. ‘Simulations’ are role-playing exercises where students take
on the roles of diplomats, government representatives, managers, consultants, lawyers, judges, civil society actors, and others in an experiential
learning-focused exercise that seeks to reconstruct professional settings as
realistically as possible. The purpose of these simulations is to allow students to develop relevant skills such as debating, public speaking, working
in teams, targeted research, thinking on ‘their feet’ and through experience, gain a deeper appreciation for the dynamics of, e.g., international
negotiations, stakeholder dialogues, management board decision-making,
and law trials. This chapter first explores the benefits and challenges of
simulations and why they can be a useful learning tool in the curriculum.
It offers insights into the conceptual and practical considerations of running simulations on the small and larger scale within a course. Small-scale
simulations could be part of 1-hour seminars or stand-alone workshops
over 2–5 hours and offer a good first insight for students, but require careful planning and chairing by the teacher. Large-scale simulations can be an
advanced version in the form of external conferences such as the Harvard
World Model United Nations (WorldMUN) or the National Model
United Nations (NMUN) conference. A central element of this experiential learning approach is to provide students with feedback cycles in which
they can reflect on their experience and draw lessons for their next participation in a simulation and for transferring their acquired skills to similar
professional settings that require negotiation acumen, debating skills,
public speaking, research skills, and the ability to develop solutions to
specific and complex problems.
Chapter 8. ‘Supervising Dissertations’. Dissertation supervision at the
undergraduate, master’s, and PhD levels includes a close mentoring relationship between the student and supervisor. Developing the research
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1 INTRODUCTION
13
project and providing feedback in several rounds is at the core of this relationship, with broad scope for supporting students in developing their
personal growth mindset and fostering a positive experience. To achieve
this, Chap. 8 discusses central elements and steps in the research supervision process. It opens with setting the ground rules and developing a
professional supervisor-supervisee relationship, focusing on the level of
guidance, and treating students similar despite differences in the supervisor’s topic expertise. The chapter proceeds to explore the key steps in the
supervision process such as finding and specifying/narrowing down the
topic, identifying the research question and contribution, discussing the
research strategy and methods, the literature review, identifying and selecting theoretical frameworks and theories, and subsequently proceeding to
the case study/empirical part of the dissertation. It reflects on different
approaches and strategies around collecting primary data through interviews, field work, and participant observation, complying with risk assessment and research ethics in the process, and then proceeds to the analysis
of quantitative/qualitative data. It closes with key considerations around
writing the central discussion section/chapter that links the theoretical
framework/theory to the empirical findings and discusses how these sit
with the broader academic literature on the topic, before moving to the
conclusion chapter that summarizes the contribution and offers broader
implications for theory and policy/practice.
Chapter 9. ‘Conclusion’. The conclusion chapter draws together the
central findings and take-aways on the personal growth mindset and how
courses/modules and degree programs can be constructively aligned to
support students in their personal development journey and improving
their career skills. It closes with an outlook into the 2020s and 2030s,
which are likely to see a continuing trend toward blended (online/face to
face) teaching approaches and life-long learning as societies and with them
career pathways change given the uptake of new technologies and the rise
of automation in highly skilled white-collar jobs.
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PART I
The Big Picture of Learning Theories
and Course Design
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