Generalisation Driven Design Science Research

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Research Methodology

Good design is a renaissance attitude that combines technology, cognitive science, human need, and beauty to produce something the world didn’t know it was missing. – Paola Antonelli The primary aim of this research is to design and implement a system that addresses the problems and fulfils the requirements identified in the previous chapter (Section 2.6). For this study, Nunamaker Jr et al’s (1991) multi-methodological design science approach for information systems research will be adapted to propose and develop various artefacts. Additionally, the principles and criteria for design science artefacts will be used as guiding and evaluative principles throughout the study (R. Baskerville, 2008; Hevner et al., 2004; Nunamaker Jr & Chen, 1990; Nunamaker Jr et al., 1991).
This chapter presents the research problems and objectives followed by a discussion on multi-paradigmatic multi-methodological information systems research. Subsequently we discuss and examine various design science research methodologies. A generalisation driven design science research methodology is then presented as the most appropriate methodology to address the aforementioned problems, achieve the research objectives, and create the research artefacts. The chapter closes with the steps that need to be taken for the creation, refinement, evaluation and generalisation of these research artefacts.

Research Problems and Objectives

The review and analysis of literature and existing systems helped unearth the research problems that we aim to address with this research. There are limited concepts, models, and processes, and workflows available to support holistic and integrated language preservation and learning. Most of the language revitalisation models emphasise on anguage learning, and not preservation (Grenoble & Whaley, 2005; Hinton & Hale, 2001). There is also limited research on models, frameworks, and/or architectures for the design and implementation of an integrated language preservation and learning system.
Current systems support different aspects of language revitalisation in a siloed manner with isolated repositories of words, poetry, imagery that does not lend itself to holistic governance, discovery and usage. This lack of integration leads ultimately to the death of the language since there is no context to understand, discover and learn the language. Coincidentally, there is limited research on holistic approaches for language capturing, curating, discovering and learning. This motivates us to develop conceptual and system artefacts to help address the above research problems.
When we look at the dimensions of these research problems, we identified four dimensions namely (1) context in which the user is operating and the spatio-temporal aspects of their engagement; (2) heterogeneity of the knowledge artefacts, languages and dialects, modalities engagement, and pedagogies; (3) User who engage in language revitalisation efforts; and (4) Systems that are used for preservation and learning activities. These research dimensions are illustrated in .
Research in the past (inner circle) has focused predominantly on the design and implementation of traditional systems to capture and curate languages by experts in limited contexts focused on standard vocabulary (words and phrases) and media (audio and images) of single languages using simple pedagogies and modalities. This research (outer grey circle) tries to address these research problems by exploring a crowd sourced approach to harness linguistic diversity and richness (words, phrases, poetry, stories, audio, images and videos) using exponential technologies to capture, curate, discover and learn multiple languages using various modalities and pedagogies anytime anywhere.

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Multi-paradigmatic Multi-Methodological

Information Systems Research

Information Systems and many other disciplines that leverage Information and Communication Technologies (ICT) are currently multi-paradigmatic (Vaishnavi & Kuechler, 2015). They adopt research questions, methodologies, and conceptual philosophies from multiple fields to better understand the phenomena of interest (i.e. how systems are developed, how information is produced and processed, and how the organisation is influenced). More than a decade ago, Baskerville & Myers (2002) illustrated (Figure 8.) the multi-paradigmatic roots of IS disciple.
Information Systems Research is an artefact-oriented discipline that requires multiple research methods to understand scientific, technological, organisational, managerial, and societal aspects of the research (Cronholm, Göbel, Lind, & Rudmark, 2013). ISR is an applied discipline more than a pure discipline as it has two aims: (i) theoretical, to gain new and improved knowledge and (ii) practical, to improve practical concepts and processes for humans, organisations, and communities through the use of Information Technology (IT) (Adams & Courtney, 2004; Iivari, 2007; Jr.ad, Ahmed, & Sundaram, 2014). Information Systems discipline is one of applied research, where we frequently apply theory from other fields, such as economics, social sciences, and computer science to solve problems at the intersection of information technology (IT) and organisations (Peffers et al., 2007). Hence the use of a multi-methodological approach is eminently applicable in Information Systems research (Peffers et al., 2007). However these methods require suitable mapping and integration between the different research methodologies (Bai, White, & Sundaram, 2013). This is a challenging task as linking research methods belonging to other research paradigms may cause problems. Mingers (2001) identified four levels of problems: (1) philosophical — issue of paradigm incommensurability; (2) cultural — the extent to which organisational and academic cultures influence against multimethod research; (3) psychological — the problems of individual researchers who are comfortable with a particular type of method; and (4) practical. The author further elaborates, debates, and explains how each of these problems can be mitigated (Mingers, 2001; Mingers & Brocklesby, 1997).
In recent years, it has become increasingly common to adopt multi-methodological approaches that integrate multiple research methods in a single study (Bryman, 2006; Creswell, 2008; Creswell & Clark, 2007; A Tashakkori & Teddlie, 1998). Mixed-methods or Multi-methodological research design embraces multiple methods (i.e. quantitative, qualitative, and design science approaches) to overcome the inherent limitations in a single method design, and is thus expected to produce richer and more holistic findings (Peng, Nunes, & Annansingh, 2011; Venkatesh, Brown, & Bala, 2013). Tashakkori & Teddlie (2003) classify two major types of multiple-methods research: (1) mixed methods research; and (2) multi-method research. The terms mixed methods and multi-method have been used interchangeably in behavioural and social sciences including Information Systems (IS), but there are conceptual differences between the two terms (Venkatesh et al., 2013). Multi-method research uses two or more research methods, but may (or may not) restrict the research to a single worldview (e.g., quantitative or qualitative). In contrast, mixed-methods research combines various methodologies (i.e., a combination of qualitative and quantitative research methods), either concurrently or sequentially, in multiple worldviews (Mingers & Brocklesby, 1997; Abbas Tashakkori & Teddlie, 2003; Teddlie & Tashakkori, 2009).
A considerable number of studies have been published in leading IS journals that provide guidelines for conducting and evaluating research in areas that are uncommon in the IS literature (Venkatesh et al., 2013). Some of the methodologies include, but are not limited to: (1) Interpretive research in IS (Klein & Myers, 1999);

  • Multi-method research in IS (Mingers, 2001); (3) Case studies in IS (Lee, 1989);
  • Positivist case studies in IS (Dubé & Paré, 2003); (5) Generalizability in IS research (Lee & Baskerville, 2003); (6) Design science research in IS (Hevner et al., 2004; Nunamaker Jr. et al., 1991); and (7) Action research in IS (R. L. Baskerville & Wood-Harper, 1996). The proposed guidelines enable researchers to design, conduct, evaluate, report, and obtain greater insights regarding their phenomena of interest. Furthermore, the guidelines provide reviewers and editors with a mechanism with which to assess research artefacts and help to make informed decisions about a paper. Consequently, these IS oriented methodologies have become prevalent in IS research. The afore-mentioned research objectives demand a multi-methodological design science artefact centric approach hence we discuss design science research in the following section.Design Science ResearchOver the last few decades, there has been an increasing amount of interest (Cronholm et al., 2013) in design science research (DSR). The design, creation, and development of information systems or IT artefacts is a significant stream of IS research (Goes, 2014). Design is central to information systems development (R. L. Baskerville, Kaul, & Storey, 2015). In his paper, Baskerville (2008) discusses what “design science research is not” (i.e. it is not: design, design theory, IT artefact, or methodology). For purposes of this discussion, DSR can be defined as a multi-methodology approach that is focused towards the creation, refinement, and validation of artefacts intended to solve identified organisational problems (Hevner et al., 2004; Peffers et al., 2007).
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1 Introduction
1.1 Language Revitalisation
1.2 Practical and Research Problems
1.3 Research Objectives
1.4 Research Methodology
1.5 Research Contributions
1.6 Organisation of Thesis
2 Literature Review 
2.1 Languages
2.2 Endangered Languages
2.3 Language Revitalisation
2.4 Traditional Information Systems
2.5 Exponential Information Systems and Technologies
2.6 Problems and Requirements
2.7 Summary
3 Research Methodology 
3.1 Research Problems and Objectives
3.2 Multi-paradigmatic Multi-Methodological Information Systems Research
3.3 Design Science Research
3.4 Generalisation Driven Design Science Research
3.5 Creation, Refinement, Evaluation and Generalisation of Research Artefacts
4 Conceptual Foundations
4.1 Concepts
4.2 Models
5 Processes
5.1 Capture Process
5.2 Curate Process
5.3 Discover Process
5.4 Learn Processes
6 Workflows
6.1 Capture Workflow
6.2 Curate Workflow
6.3 Discover Workflow
6.4 Learn Workflows
7 Frameworks 
7.1 Concept Driven Framework
7.2 Artefact Driven Framework
8 Architectures
8.1 High Level Architecture
8.2 Detailed Architecture
9 Implementations 
9.1 Instantiated Framework
9.2 Instantiated Architecture
9.3 Representative Scenarios and Workflows
9.4 Generalisation of Implementation
10 Evaluation 
10.1 Concepts and Models
10.2 Processes and Workflows
10.3 Frameworks and Architectures .
10.4 Implementations
11 Conclusion 
11.1 Research Summary
11.2 Contributions
11.3 Limitations and Future Research
Appendices
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Design and Implementation of Social Persuasive Ubiquitous Knowledge Systems to Revitalise Endangered Languages

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