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Lean Six Sigma for reducing student dropouts in higher education – an exploratory study

TL;DR: In this paper, the authors investigated the potential causes behind student dropout in higher education institutions (HEIs), and explored the use of Lean Six Sigma (LSS) tools in reducing dropout rates.
Abstract: This paper investigates the potential causes behind student dropouts in higher education institutions (HEIs), and explores the use of Lean Six Sigma (LSS) tools in reducing dropout rates. This qual...

Summary (5 min read)

Introduction

  • Education provides a wide range of economic and social benefits for individuals and for society (Brennan et al., 2013; Baum et al., 2013) .
  • Though the word 'dropout' in higher education institutions (HEIs) carries various notions like leaving the course or programme or institute, there is absolute consensus that it causes loss in social and economic wellbeing of both individuals (or dropouts) and institutions.
  • This means each student generates £27000 for an HEI over the course of a 3-year bachelor degree programme.

Lean Six Sigma Methodology

  • The evolution of LSS Lean Six Sigma (LSS) is a combined process improvement methodology, which was founded on over sixty years of quality improvement efforts, undertaken by the so-called quality gurus Shewart, Deming, Juran, Crosby, Ishikawa, Taguchi and others (Snee 2010) .
  • Lean Six Sigma is a "business strategy and methodology that increases process performance, resulting in enhanced customer satisfaction and improved bottom-line result" (Snee 2010, 10) .
  • The combined methodology uses a systematic project approach to improving processes, commonly referred to as DMAIC, from the 5 phases of Define, Measure, Analyse, Improve and Control.
  • PUT IN about coming from MOTOROLA ETC Although the Lean Six Sigma methodology has been extensively considered within the literature for over a decade and has been adopted by several manufacturing and service industries with remarkable results (George 2003) , AREAS SUCH AS ……. the Public Sector has been slower in adapting it (Maleyeff 2007) .
  • This applies in particular to the Higher Education setting where its application is of growing importance, but still remains in its embryonic stages (Antony, et al.

Current status of Lean, Six Sigma and LSS in HE

  • Since mid-2000 and as a response to the changed environment, several HEIs have been experimenting with Lean principles and concepts (Waterbury, 2015) .
  • Lean has also proved to be also applicable and beneficial for academic core processes (Balzer, Francis D E, et al. 2016) .
  • Holmes, Jenicke and Hempel (2015) introduced a Six Sigma-based framework for HEIs to select those projects that yield to highest financial performance, growth and customer satisfaction.
  • Other than these examples of the applicability of the LSS methodology in general or administrative HEI processes, practical evidence on the use of LSS on academic core processes is limited (Simons 2013; Antony, 2014) both firmly believed that improvement of the education system can be done in a similar way as any other industry, including academic and non-academic processes.
  • The primary objective of the Define phase is to decide whether the project chosen is the most appropriate one to take on at that moment in time.

Research Methodology

  • The study is based on a qualitative approach, with an in-depth study of the contemporary issue of student dropouts in the higher education complex environment, where the expertise of different stakeholders is sought (LSS experts and university employees).
  • The primary research philosophy of this study is based on an interpretive first understanding of the contexta strategy that meets the need of this research is an exploratory study (Shields and Rangarajan 2013) .

Case selection

  • Convenience sampling technique was applied focused on gaining in-depth and qualitative insights rather than generalizability (Yin 2009 , Powell 1997) .
  • Fricker and Schonlau ( 2002) also suggested convenience sampling might be useful in developing research hypotheses in the early phases of research.
  • For LSS expert selection, five or more years of experience with LSS and possessing a Master Black Belt (MBB) were the minimum requirements for this study.
  • Further, each university was represented by their three employees to discuss the dropout phenomenon and its response mechanism.

Data Collection

  • The small sample size of subjects is justified with the scope of this study, which is concerned with gaining an interpretive first understanding of a contemporary issue (Saunders, Lewis and Thornhill 2009) .
  • Semi-structured interviews allow a free-flowing information exchange through open-ended questions, enabling interviewees to "speak spontaneously and unrestrainedly" (Decorp 1999, 47) around previously defined themes (Ayres 2008, 810) and at the same time allow the researcher better comparison of the interviews afterwards (Patton 2002) .
  • Apart from that, the raw data obtained in form of quotations enriches the data collection.
  • The pilot study was conducted with two academic supervisors along with a MBB and a university employee and they suggested minor amendments in the interview protocol.
  • The corrected interview protocol for university employees dealt mainly with three themes -(1) the awareness of employees regarding the dropout issue and its consequences, (2) the university's current strategy to reduce dropout numbers, (3) the current approaches to evaluate the underlying reasons why students decide to drop out.

Prioritization

  • Interviewing Documentation related to the following themes: (4) how can LSS be applied to students drop out issues, ( 5) what relevant tools of LSS can be utilized to reduce dropout rates and 6) how can LSS contribute positively to student retention and satisfaction in HEIs.
  • Furthermore, it was also highlighted that no right or wrong answers to the questions exists (Polit and Beck 2004) .
  • All interviews followed an interview protocol prepared upfront to enhance analysis of the responses (Yin 2009) .
  • The interviews with the MBBs were conducted face-to-face at their offices and the interviews lasted about 45 minutes.
  • To triangulate data, public and nonpublic documents regarding dropout numbers and dropout definitions were collected from the universities.

Data Analysis

  • The interviews were transcribed and a thematic analysis was performed to codify and analyze responses from the LSS experts and university employees.
  • This research method enables researchers to analyze the vast information of interview-data in a systematic manner (Boyatzis 1998) .
  • Due to the exploratory nature of this research and the lack of previous literature in this area to build up on, an inductive coding approach was applied (Boyatzis 1998) .
  • As suggested by Eisenhardt (1989) and Yin (2003) , data was first analyzed within each MBB and each university along the research questions described above.
  • The analysis of the between-cases followed the themes which were described above.

Analysis of findings

  • Data analysis revealed rich information on the working style of HEIs, dropouts handling approaches and LSS based interventions.
  • The findings are structured around five key emergent themes or issues reflected by university representatives and LSS experts responses on those.

i. Ambiguity on dropout definition

  • A major theme which emerged from interaction with university employees is that there is no standard definition of dropout in their academic guidelines or charter.
  • This theme could be supported with following quotations of employees:.
  • The discussion with LSS experts showed that a university must develop a standardized typology to classify and define various kinds of dropouts.
  • They unanimously emphasized the need for defining the problem or issue in hand, in this case dropout, to successfully implement the quality improvement measures of LSS.

An incomplete or no data set on the reasons why students drop out

  • The interviews of university employees revealed that due to the historically grown differences among Western European HE systems, no standard definition and measurement method exists regarding student dropout.
  • Currently, universities measure dropouts based on different characteristics regarding the (1) student's behavior (different kinds of involuntary dropout and voluntary withdrawals), (2) different institutional levels ranging from abandoning a specific course to leave the HE system level, and (3) the timing a dropout occurs.
  • None of the selected universities had a withdrawal/exit form to capture the reasons behind students' dropout.
  • The LSS experts raised their concern that availability of partial or no data presents a major challenge for LSS projects, as it prevents the detailed analysis of underlying reasons why a student's dropout occurred.
  • In fact, one should take some time to strengthen the available information system.

Reluctance of specific students to provide honest answers on their drop out motivation

  • University employees mentioned that in many cases they do not have a clear understanding why students decided to quit their studies.
  • Students are reluctant to answer frankly to this delicate question, or they refuse to answer at all.
  • LSS experts mentioned that finding the root causes and tackling them consequently is the very core of LSS.
  • The lack of a clear understanding of those reasons is a problem as per MBBs understanding, but they suggested more effort has to be put during the define and measurement phases of DMAIC (Design, Measure, Analyze, Improve and Control) cycle to gain a clear set of data.
  • Additionally, different LSS tools such as cause and effect analysis and root cause analysis, can play a very vital role in understanding the underlying factors influencing students' dropout decision in a HEI.

iv. The employees awareness on impact of a student's dropout decision and their role

  • The researchers recognized that many university employees are not aware of their role on the students' dropout decision and impact of a dropout on the economy of the institute and the society .
  • Four out of nine interviewees believed that their job had no or a low impact on a student's decision-making process.
  • All three MBBs uniformly agree that through applying the LSS methodology this can be overcome.
  • The analyze phase of the Six Sigma methodology helps staff members to understand and evaluate the driving factors behind a student's dropout decision and thus can make the university employees aware of their impact.
  • L1 highlights the point that that the real challenge is to make the result of the analysis phase accessible to university staff so they can understand the impact of their work on a student's decision-making process.

Medium awareness

  • Those services mainly focus on students who were about to drop out and to a lesser extent to reduce factors leading to this point.
  • Therefore, the employees were also not aware or trained in formulating dropout reduction strategies.
  • I don't know such a strategy, if the authors have it it's not communicated (B3) Moreover, the university employees, although chosen based on their impact on a student's dropout decision were not aware of all the services offered by the university, also known as As B3 commented.

I don't know for sure if we have all those services you are asking about, but we have a Student Service Center where they could know that (A2)

  • From the perspective of LSS, MBBs recommended that HEIs can conduct detailed feasibility analysis of impact and effectiveness of their offered services for the students who are about to dropout or prone to dropout.
  • Based on the clearer dataset, the impact of each factor can be assessed and be assigned to the group of malleable or less-malleable factors.
  • LSS can be used to overcome this problem: Understanding the interests and needs of the stakeholders and showing them up what's in for me is a required first step.
  • Demonstrating the management that the current fire-fighting mode is costlier than a continuous improvement approach provides resources which can be used for pilot projects.

Conclusion and agenda for future research

  • This paper has addressed the research question of how LSS can be used as an improvement methodology to reduce dropouts from HEIs.
  • To authors' best knowledge, this is possibly the first study exploring the possibility of using LSS as a methodology to address the dropout rates in HEIs.
  • The findings of the study are based on qualitative analysis of data gathered from interviews with LSS experts and university employees of three different Western-European HEIs.
  • The research findings clearly indicated that LSS has potential to bring systematic improvement in HEIs' dropout reduction approach.

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Gupta, SK, Antony, J, Lacher, F and Douglas, JA
Lean Six Sigma for reducing student dropouts in higher education – an
exploratory study
http://researchonline.ljmu.ac.uk/id/eprint/7880/
Article
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Citation (please note it is advisable to refer to the publisher’s version if you
intend to cite from this work)
Gupta, SK, Antony, J, Lacher, F and Douglas, JA (2018) Lean Six Sigma for
reducing student dropouts in higher education – an exploratory study. Total
Quality Management and Business Excellence. ISSN 1478-3363
LJMU Research Online

Lean Six Sigma for reducing student dropouts in Higher Education an exploratory
study
Fabian Lacher*, Sandeep Kumar Gupta**, Jiju Antony**, Jackie Douglas
***
-----------
* Department of Management, Economics and Industrial Engineering, Politecnico di Milano, P.zza Leonardo
da Vinci 32, 20133 Milano - Italy Italy
** Research Scholar, Department of Business Management, School of Social Sciences, Heriot Watt University,
Edinburgh, Scotland, UK
** Professor of Quality Management, Department of Business Management, School of Social Sciences, Heriot
Watt University, Edinburgh, Scotland, UK
*** Senior Lecturer in Management, Liverpool Business School
Liverpool John Moores University, Liverpool, England, UK
Abstract
This paper investigates the reasons behind student dropouts in higher education institutions
(HEIs) exploring the use of Lean Six Sigma (LSS) tools in reducing dropout rates. This
qualitative study used twelve semi-structured interviews with university employees (nine) and
LSS experts (three), in order to understand the complexity of the dropout phenomenon and the
role of various LSS tools in reducing the dropouts. Analysis revealed that, in order to develop
a typology of student dropouts, maintain detailed records, and sensitize relevant authorities
about the impact of a student’s dropout decision, LSS was an appropriate methodology to use
as a turnaround strategy for HEIs in managing the phenomenon.
Though the small sample size is a limitation of the study, the revelations of HEIs authorities
and LSS experts have given new impetus to look at and take action on the issue of student
dropouts in HEIs.
Key words: Lean, Six Sigma, DMAIC, student dropout rates, Higher Education
Paper type: Research paper

Introduction
Education provides a wide range of economic and social benefits for individuals and for society
(Brennan et al., 2013; Baum et al., 2013). Well-educated individuals have a lower propensity
to commit crime, are less likely to smoke, to drink excessively or to be obese - which all results
in a longer and healthier life (BIS, 2011; Baum et al., 2013). In addition to these physiological
factors, knowledgeable people reportedly have a better mental health and a higher life
satisfaction (Organization for Economic Co-operation and Development [OECD], 2011). What
is beneficial for an individual is also of benefit to society as a whole; there is greater social
cohesion, trust and tolerance and additionally guarantee political stability and economical
welfare (OECD, 2013; Brennan et al., 2013). With these unanimous benefits of education,
specifically higher education, the increasing rate of student dropouts has raised the concerns of
various stakeholders (Balzer, Brodke and Kizhakethalackal 2015, Thomas, et al. 2015,
Waterbury 2015).
Though the word ‘dropout’ in higher education institutions (HEIs) carries various notions like
leaving the course or programme or institute, there is absolute consensus that it causes loss in
social and economic wellbeing of both individuals (or dropouts) and institutions. For instance,
according to the OECD, a tertiary-educated individual, in lieu of his/her investment gets an
average Internal Rate of Return (IRR) of 13.0% and 11.5% for men and women respectively
(OECD 2013, 144f). Moreover, there are other social benefits from investments in HE, namely,
that graduate students ensure higher tax revenues, a faster economic growth, increased
productivity and a higher innovation rate among workers (Brennan, Durazzi and Sene 2013).
Considering all the financial and social benefits that successful participation in tertiary
education provides, it is logical for national governments to want to increase the numbers of
graduates from Higher Education Institutions (HEIs). Therefore, most countries have been
primarily focusing on “widening access to Higher Education” (Trow 2006, Gaebel, et al. 2012),
and not on increasing completion rate. On average, every third student who enters a program
does not finish it, and either moves to another program or leaves HE without graduating
(Vossensteyn, et al. 2015, Quinn 2013). Those students are generally referred somewhat
negatively as dropouts (Larsen, et al. 2013). Dropouts are a “drain on public finance and a
waste of valuable resources” (Quinn 2013), this weighs especially heavy during a financial
crisis (Heublein and Sommer 2003). In England, HE undergraduate students pay £9000 per
annum for their tuition. This means each student generates £27000 for an HEI over the course
of a 3-year bachelor degree programme. Each student who drops out after 1 year means a loss
of income of £18000 or if they last until their 2
nd
year and then drop out, a loss of £9000 for
the institution. If a programme recruits 200 students and only 10% drop out after 1 year then
the cost to the HEI is 20 x £18000 = £360000; the financial numbers start to be significant and
warrant investigation.
There are limited studies within the literature that have analyzed the dropout phenomenon in
the HE context. A plethora of terminology exists to explain the complexity of this phenomenon,
including the ‘withdrawal’ of students from courses in HEIs in the United Kingdom (Aldridge
and Rowley 2001); staff perceptions for ‘non-completion’ in higher education (Taylor and

Bedford 2004). However, there is no standard definition and classification of the student
dropout phenomenon in the extant literature (Larsen, et al. 2013). In general, those who
discontinue their studies from a particular course or programme or institution, for any reason
are termed dropouts. To understand the factors behind dropouts, Forsman, Linder, Moll,
Fraser, & Andersson (2012) advocated the need to apply the theory of complex thinking to
model student retention in HEIs. NEED TO EXPLAIN WHAT THIS MEANS.
To overcome challenges of student retention in HE, Thomas, et al (2015) page 983 suggested
that “HEIs will need to do more with less, develop new teaching and learning strategies,
differentiate by being distinct in the products and services it offers, offer a greater value adding
proposition to the student and continue to be more “customer focused”. “To facilitate these
changes the LSS process improvement methodology may have a role to play (Antony, et al.
2012, 947). Therefore, this study was conceptualized to conduct a systematic inquiry into the
functioning of higher education system, to discuss issues related to dropouts and explore how
Lean Six Sigma as a methodology and strategy can be used to address those issues.
Lean Six Sigma Methodology
The evolution of LSS
Lean Six Sigma (LSS) is a combined process improvement methodology, which was founded
on over sixty years of quality improvement efforts, undertaken by the so-called quality gurus
Shewart, Deming, Juran, Crosby, Ishikawa, Taguchi and others (Snee 2010). As its name
indicates, LSS is based on both Lean and Six Sigma methodologies, and aims to improve both
by combining the individual concepts, methods and tools (George 2002). Lean Six Sigma is a
“business strategy and methodology that increases process performance, resulting in enhanced
customer satisfaction and improved bottom-line result” (Snee 2010, 10). The combined
methodology uses a systematic project approach to improving processes, commonly referred
to as DMAIC, from the 5 phases of Define, Measure, Analyse, Improve and Control.
(Wedgwood, 2016). PUT IN about coming from MOTOROLA ETC
Although the Lean Six Sigma methodology has been extensively considered within the
literature for over a decade and has been adopted by several manufacturing and service
industries with remarkable results (George 2003), AREAS SUCH AS ……. the Public Sector
has been slower in adapting it (Maleyeff 2007). This applies in particular to the Higher
Education setting where its application is of growing importance, but still remains in its
embryonic stages (Antony, et al. 2012, Albliwi, et al. 2014). However, through major changes
in the HE environment it can be witnessed that LSS is growing in importance within HEIs
(Antony 2014). NEED MORE ON THIS HERE. Six Sigma hones in on improving the drivers
of process performance, whilst lean looks to reduce any waste in the process to improve flow.
(Wedgwood, 2016).
Current status of Lean, Six Sigma and LSS in HE
Since mid-2000 and as a response to the changed environment, several HEIs have been
experimenting with Lean principles and concepts (Waterbury, 2015). Among other

universities, St Andrews University and Cardiff University in Europe and Central Connecticut
State University, Winona State University, University of Central Oklahoma, University of
Iowa, University of New Orleans, Bowling Green State University, University of Scranton,
Rensselaer Polytechnic Institute in the U.S. have been applying Lean to their administrative
and core processes (Waterbury 2015). The benefits from the application of Lean thinking in
administration, finance, HR, estates, library and other support services within a HE setting, is
not surprising. Lean has also proved to be also applicable and beneficial for academic core
processes (Balzer, Francis D E, et al. 2016). Douglas, et al. (2015) illustrated that Lean thinking
theories and tools were appropriate to identify waste in both academic and supportive services.
Seminal work on the utilization of Lean for course design, teaching or handling student
feedback was provided by Emiliani (2004) and using the kaizen technique to improve graduate
business school degree programs (Emiliani, 2005). Other researchers focused on applying Lean
thinking on curriculum design (Dey 2007) or student assessment (El-Sayed, et al. 2011).
Svensson et al. (2015) reported improvements made in terms of increased student satisfaction,
identification and reduction of hidden costs and process efficiency. Sinha and Mishra (2013)
successfully applied Lean for a course review process.
There are some successful Six Sigma projects in academia, such as Six Sigma in experimental
learning (Box 2006), a Six Sigma framework for academic institutions (Jenicke, Kumar and
Holmes 2008) or improving self-service at university libraries (Kumi and Morrow 2006).
Holmes, Jenicke and Hempel (2015) introduced a Six Sigma-based framework for HEIs to
select those projects that yield to highest financial performance, growth and customer
satisfaction.
From a practical point of view, a few universities implemented LSS in its processes: Miami
University in the US conducts regularly Lean and Six Sigma programs (Sunder 2016). Kings
College saved over £1million in 2012, using LSS tools to improve college processes around its
infrastructure (Sunder 2016). University of Central Florida improved the speed of the
admission process for qualified students through LSS (Coowar, et al. 2006) and the pharmacy
department at the University of North Carolina illustrated that it could improve employee and
customer satisfaction by applying LSS techniques (Sunder 2016). However, other than these
examples of the applicability of the LSS methodology in general or administrative HEI
processes, practical evidence on the use of LSS on academic core processes is limited (Simons
2013; Antony, 2014) both firmly believed that improvement of the education system can be
done in a similar way as any other industry, including academic and non-academic processes.
Whilst reviewing the literature and reported examples, it would appear that there is a common
thread among the many barriers and challenges LSS faces while implementing it into an
academic setting (Pryor, et al. 2012).
Given that it is commonly agreed that student dropouts represent a “waste of valuable
resources” (Quinn 2013), there is no European-wide overview about the financial impact a
dropout creates for a HEI. Moreover, presently, very limited LSS literature addresses such a
critical issue. This might be surprising, as LSS, being a process improvement methodology
focusing on reducing waste (George 2002) seems to be well suited for effectively reducing
dropout rates. Hence, the purpose of this paper is to examine and explore how the LSS DMAIC

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References
More filters
Book
01 Oct 1984
TL;DR: In this article, buku ini mencakup lebih dari 50 studi kasus, memberikan perhatian untuk analisis kuantitatif, membahas lebah lengkap penggunaan desain metode campuran penelitian, and termasuk wawasan metodologi baru.
Abstract: Buku ini menyediakan sebuah portal lengkap untuk dunia penelitian studi kasus, buku ini menawarkan cakupan yang luas dari desain dan penggunaan metode studi kasus sebagai alat penelitian yang valid. Dalam buku ini mencakup lebih dari 50 studi kasus, memberikan perhatian untuk analisis kuantitatif, membahas lebih lengkap penggunaan desain metode campuran penelitian, dan termasuk wawasan metodologi baru.

78,012 citations

Journal ArticleDOI
01 Feb 2009
TL;DR: In this paper, the authors describe the process of inducting theory using case studies from specifying the research questions to reaching closure, which is a process similar to hypothesis-testing research.
Abstract: Building Theories From Case Study Research - This paper describes the process of inducting theory using case studies from specifying the research questions to reaching closure. Some features of the process, such as problem definition and construct validation, are similar to hypothesis-testing research. Others, such as within-case analysis and replication logic, are unique to the inductive, case-oriented process. Overall, the process described here is highly iterative and tightly linked to data. This research approach is especially appropriate in new topic areas. The resultant theory is often novel, testable, and empirically valid. Finally, framebreaking insights, the tests of good theory (e.g., parsimony, logical coherence), and convincing grounding in the evidence are the key criteria for evaluating this type of research.

40,005 citations

Book
01 Jan 1980

27,598 citations


"Lean Six Sigma for reducing student..." refers background in this paper

  • ...To achieve the research objective, semi-structured interviews are advocated as an appropriate means of data collection (Yin, 2003) which allow insights in the words of respondents themselves (Patton, 2002)....

    [...]

  • ...…a free-flowing information exchange through open-ended questions, enabling interviewees to ‘speak spontaneously and unrestrainedly’ (Decorp, 1999) around previously defined themes (Ayres, 2008) and at the same time allow the researcher better comparison of the interviews afterwards (Patton, 2002)....

    [...]

  • ...Semi-structured interviews allow a free-flowing information exchange through open-ended questions, enabling interviewees to ‘speak spontaneously and unrestrainedly’ (Decorp, 1999) around previously defined themes (Ayres, 2008) and at the same time allow the researcher better comparison of the interviews afterwards (Patton, 2002)....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors define a leadership event as a perceived segment of action whose meaning is created by the interactions of actors involved in producing it, and present a set of innovative methods for capturing and analyzing these contextually driven processes.
Abstract: �Traditional, hierarchical views of leadership are less and less useful given the complexities of our modern world. Leadership theory must transition to new perspectives that account for the complex adaptive needs of organizations. In this paper, we propose that leadership (as opposed to leaders) can be seen as a complex dynamic process that emerges in the interactive “spaces between” people and ideas. That is, leadership is a dynamic that transcends the capabilities of individuals alone; it is the product of interaction, tension, and exchange rules governing changes in perceptions and understanding. We label this a dynamic of adaptive leadership, and we show how this dynamic provides important insights about the nature of leadership and its outcomes in organizational fields. We define a leadership event as a perceived segment of action whose meaning is created by the interactions of actors involved in producing it, and we present a set of innovative methods for capturing and analyzing these contextually driven processes. We provide theoretical and practical implications of these ideas for organizational behavior and organization and management theory.

22,673 citations


"Lean Six Sigma for reducing student..." refers methods in this paper

  • ...As suggested by Eisenhardt (1989) and Yin (2003), data were first analysed for each MBB and for each university employee along with the research questions described above....

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Book
30 Oct 1996
TL;DR: How to use this book Guided tour Preface Contributors The nature of business and management research and structure of this book and the research topic are explained.
Abstract: How to use this book Guided tour Preface Contributors 1 The nature of business and management research and structure of this book 2 Formulating and clarifying the research topic 3 Critically reviewing the literature 4 Understanding research philosophies and approaches 5 Formulating the research design 6 Negotiating access and research ethics 7 Selecting samples 8 Using secondary data 9 Collecting primary data through observation 10 Collecting primary data using semi-structured, in-depth and group interviews 11 Collecting primary data using questionnaires 12 Analysing quantitative data 13 Analysing qualitative data 14 Writing and presenting your project report Appendices Glossary Index

19,739 citations

Frequently Asked Questions (11)
Q1. What are the contributions in this paper?

This paper investigates the reasons behind student dropouts in higher education institutions ( HEIs ) exploring the use of Lean Six Sigma ( LSS ) tools in reducing dropout rates. This qualitative study used twelve semi-structured interviews with university employees ( nine ) and LSS experts ( three ), in order to understand the complexity of the dropout phenomenon and the role of various LSS tools in reducing the dropouts. Though the small sample size is a limitation of the study, the revelations of HEIs authorities and LSS experts have given new impetus to look at and take action on the issue of student 

However, expanding the study ’ s scope and scale, such as focusing exclusively on faculty, including further universities or addressing employees with other job descriptions, would improve the reliability and validity of the findings in future research. `` Qualitative case studies in operations management: Trends, research outcomes, and future research implications. `` Research methodology in management: Current practices, trends, and implications for future research. `` What do the authors know about explanations for drop out/opt among young people from STM higher education programmes ? '' 

For LSS expert selection, five or more years of experience with LSS and possessing a Master Black Belt (MBB) were the minimum requirements for this study. 

The research findings clearly indicated that LSS has potential to bring systematic improvement in HEIs’ dropout reduction approach. 

The corrected interview protocol for university employees dealt mainly with three themes – (1) the awareness of employees regarding the dropout issue and its consequences, (2) the university’s current strategy to reduce dropout numbers, (3) the current approaches to evaluate the underlying reasons why students decide to drop out. 

Fricker and Schonlau (2002) also suggested convenience sampling might be useful in developing research hypotheses in the early phases of research. 

For instance, four out of nine interviewees believed that their job had no or a low impact on a student’s decision-making process. 

University of Central Florida improved the speed of the admission process for qualified students through LSS (Coowar, et al. 2006) and the pharmacy department at the University of North Carolina illustrated that it could improve employee and customer satisfaction by applying LSS techniques (Sunder 2016). 

The findings of this study contribute to the understanding of how the LSS methodology can be a viable approach to reduce dropouts from HEIs. 

This list can be used to reallocate resources to more effectively reduce dropout rates and can be communicated to students to make them aware of the most common causes which led to a dropout among their peers. 

Although an ambiguous dataset represents a problem for a data driven improvement methodology such as LSS, particularly, during for the Define and Measure Phases, HEI authorities need to get sensitized to distinguish dropouts in greater detail and collect numbers on such an event in a consistent way so that they can track the influence of improvement measures.