Design and Implementation of Socially Driven ...

Design and Implementation of Socially Driven Knowledge Management Systems for Revitalizing Endangered Languages Asfahaan Mirza and David Sundaram

1

Background

Many linguists estimate that, if nothing is done, half of the 7000 plus languages spoken today could disappear by the end of this century (Romaine, 2007). Krauss (1992) suggests that only 600 or so languages may survive because they have relatively large numbers of speakers (more than 100,000). Currently, languages are disappearing at an alarming rate; Crystal (2002) estimated that an average of one language every 2 weeks may disappear over the next 100 years. Harmon and Loh (2010) suggest that many estimates for language endangerment are influenced by Michael E. Krauss’s seminal 1992 language paper, as he estimated that 90% of the worlds’ languages would disappear or become irreversibly moribund by 2100 (Krauss, 1992). Moribund languages are those languages that are spoken only by adults who do not teach them to the next generation. However, Nettle and Romaine (2000) and Crystal (2002) have a more optimistic estimate, that only 50% will be extinct. Revitalization of an endangered language first and foremost involves capturing, curating and storing various language artifacts such as words, phrases, songs, idioms, stories and dialects for future retrieval. This is followed by internalization through dissemination and learning of the language. Two approaches that have the potential to address these requirements in a complementary manner are knowledge management (KM) and social media. Knowledge management systems (KMS) facilitate key processes: creating, retrieving, transferring, and applying knowledge (Alavi & Leidner, 2001). In the past decade, significant developments in information technology have given birth to social media platforms that allow one person to communicate with hundreds or even thousands at a A. Mirza • D. Sundaram (*) Department of Information Systems and Operations Management, University of Auckland, Auckland, New Zealand e-mail: [email protected]; [email protected] # Springer International Publishing AG 2017 R. Helms et al. (eds.), Social Knowledge Management in Action, Knowledge Management and Organizational Learning 3, DOI 10.1007/978-3-319-45133-6_8

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time (Mangold & Faulds, 2009). A robust KMS is vital for the storage of the above mentioned language artifacts and social networks are essential for capturing, curating and disseminating the knowledge artifacts. Thus leveraging social media with KMS (SKMS) would significantly assist in designing and implementing a system to help revitalize endangered languages. The following sections introduce the key areas of interest: language revitalization, social media and knowledge management.

1.1

Language Revitalization

In the linguistic community, the term dead or extinct language is commonly used to refer to languages that have no living speakers. Leonard (2008) argues that the use of this word is incorrect. Once a biological species becomes extinct it cannot return. But for extinct languages, there is still hope that they can be revived. Leonard (2008) calls them sleeping languages, as they can be awakened if some part of the population relearns the language from documentation. Language revitalization is also referred to as Reversing Language Shift (RLS) (Fishman, 1991). Language shift is the process by which an individual or community language shifts from one language (generally their indigenous language) to another language. Taking essential measures to counter language shift is known as fostering language maintenance and/or language revitalization (Dwyer, 2011). The linguistic diversity is an important part of human diversity. Language defines a culture, through which people communicate. It is something which cannot be translated or replaced by another language. Many endangered languages are oral cultures with stories, songs, and histories passed on to younger generations without any written forms (National Geographic, 2013). The loss of a language is a loss of a whole culture and knowledge system including environmental, philosophical, music, oral literacy, medical, cultural practices and artistic skills (Hinton & Hale, 2001). Davenport and Prusak (1998) state that knowledge exists within people, as part and parcel of human complexity and unpredictability. In the subsequent section we explore the fundamentals of social media and knowledge management systems.

1.2

Social Media

Social media refers to an interaction among individuals and groups where the participants are involved in the creation, sharing and exchange of information, ideas and data in a virtual community as well as networks. The role played by individuals communicating in the past was not dynamic; the consumer audience and communicator were distinct groups. At present the consumers actively create, publish, produce and broadcast in the autonomous form that a platform facilitates (Lewis, 2010). Social media relies on defining characteristics of interactions mediated by online channels that have become a key tool to reach individuals and masses separated by geographical and ideological divides (Kaplan & Haenlein, 2010; Matthews, 2010). Consequently, social media is profiled as the optimal tool to apply in modern

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communications and interactions where private characteristics are used as critical variables. Conversely, social media can be a source of miscommunication that may hurt the society or individuals. Slander, for instance, is potentially harmful; a common feature that impinges on the democratization and uncensored nature of social media communication (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011). The key strength of social media is in its interactivity and simplicity to generate content. Having defined social media, we will now move on to discuss the key aspects of knowledge management.

1.3

Knowledge Management

Knowledge consists of the tacit and explicit actionable capabilities required to reason and deal intelligently and effectively with situations (Wiig, 2006). Knowledge can be: personal, shared among people, embedded in artifacts, or be part of an organization’s or society’s makeup and culture. Information is converted to knowledge once it is processed by people in their minds, and knowledge becomes information once it is stored in the form of text, graphics, words, or other symbolic forms (Alavi & Leidner, 2001). People are society’s basic knowledge agents. Knowledge Management (KM) is defined as creating value by leveraging intangible assets (Setiawan Assegaff & Dahlan, 2013). KM is underpinned by the management of interaction among knowledge agents and information (Hansen, Nohria, & Tierney, 1999). Knowledge is incremental upon usage, is virtually inexhaustible and is acquired through social means by leveraging the management process through information technology (Sharratt & Usoro, 2003). Knowledge Management Systems (KMS) are used to support the creation, transfer, and application of knowledge in organizations and communities (Alavi & Leidner, 2001). Moreover, according to Qwaider (2011), KMS facilitate key processes and paradigms that collude towards creating, acquiring, capturing, sharing and utilizing of knowledge, skills or expertise. While social media is used to create content, it is rarely integrated into the different facets of KMS. In the following section, we discuss the advantages of applying social media through KMS at a societal level.

1.4

Leveraging Social Media for Knowledge Management

The core purpose of integrating social media with KMS (SKMS) is to leverage active audiences (communities/society) which create, publish, produce and broadcast content (knowledge in this regard) over a platform. Nonaka and Takeuchi (1995) proposed the SECI process of creating knowledge through the conversion of tacit into explicit knowledge. The four distinct modes of knowledge conversion and the evolving spiral movement of knowledge through the SECI process are Socialization, Externalization, Combination and Internalization. Information technology frameworks aid in the capture, refinement, retrieval and distribution of knowledge by employing the SECI model as an optimized protocol (Nonaka, Takeuchi, & Umemoto, 1996). SKMS can facilitate

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connectivity of communities beyond geographical and cultural barriers, as well as presentation of knowledge in an understandable way bound by timeliness, security and integrity (Alavi & Leidner, 2001; Hansen et al., 1999). Communities geared for leveraging SKMS are segmented based on purpose and type of knowledge to be created and subsequently shared. Societal integration is developed through the commonality of ideas and proponents made possible by superseding geographical and ideological barriers in a social media environment (Ellison, Lampe, & Steinfield, 2009). Consequently, ideas can be pooled together for the common good of society. Moreover information disbursement to the masses is made easier and more effective (Baruah, 2012). Furthermore, the orientation of social media platforms according to type of content (knowledge) complements such user-specific sharing practices by availing the community of knowledge circumventing specific knowledge areas (Lewis, 2010; Matthews, 2010). For example, Delicious and Digg are bookmark-oriented while Vimeo and YouTube are video based, and Facebook and Twitter are post oriented. This aggregation of community and platform orientation within social media plays a central role in knowledge management. While social media is used to exchange information and ideas in virtual communities and networks, KMS in the past have predominately been used in an organizational context. The focus of this research is on leveraging the strengths of social media and KMS to preserve, curate, transmit, discover and revitalize endangered languages at a societal level (Fig. 1). During the project we included endangered language stakeholders and native language speakers as advisors. Further to our discussion on the potential of SKMS for endangered languages, the rest of the chapter develops as follows: In Sect. 2 we explore strengths and weaknesses of existing approaches and systems for revitalizing endangered languages. Subsequently, Sect. 3 discusses the design artifacts of SKMS to preserve and revitalize endangered languages. Section 4 explains the implementation of SKMS to revitalize, use, develop, and transmit the indigenous language of Te Reo Ma¯ori for future generations, followed by conclusion.

Fig. 1 Research focus— SKMS for endangered languages

Social Media

SKMS for Endangered Languages

Knowledge Management Systems

Endangered Languages

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Existing Systems for Revitalizing Endangered Languages

To revitalize a language, mere knowledge documentation is not sufficient. It is necessary to adopt or develop techniques for disseminating it to the community (Goodfellow, 2009). Doing this is highly dependent on teaching and facilitating the usage of the language, especially among digital natives (Yang & Rau, 2005). However, if a language has potential to disappear (i.e. when few children and young adults speak the language), it is critical to create a knowledge repository. Today the world is witnessing a tremendous increase in the adoption of social media and ubiquitous devices (UD). These devices include advanced functionality beyond making phone calls and sending text messages. Most UD have basic functionality like: high quality image capture, audio-video recording and streaming, e-mail, and Internet access. These capabilities can be exploited to capture knowledge snippets as close to the source as possible. For example, users can be empowered to capture and share their high-quality audio video recording of their endangered language within a system. If a holistic socially driven approach is employed among the indigenous population, then the workload of language revitalization is distributed. There are two foundational streams of research that underpin this work, namely knowledge management and language revitalization. To support these two streams, we have used the seminal articles by Alavi and Leidner (2001) and Hinton and Hale (2001) respectively. Qwaider (2011) demonstrates how ubiquitous technology can be leveraged for language preservation and learning. Figure 2 illustrates the synthesized model of socially driven KMS processes for language revitalization that leverages concepts from Alavi and Leidner (2001), Hinton and Hale (2001) and Qwaider (2011). The key processes for socially driven KMS for language revitalization include: (1) Capture anytime anywhere in multiple formats including text, image, audio, and video; (2) Curate information by distributed content governance to ensure knowledge integrity; (3) Access knowledge base without any geographical boundaries; (4) Share information instantly and remotely; (5) Collaborate with the wider society to engage in common objectives, and (6) Apply by learning and using the knowledge. Most endangered languages currently lack presence in digital and social spaces. Currently there are limited endangered language revitalization systems available. Fig. 2 Socially driven KMS processes for language revitalization

Access

Share

Curate

Capture

Collaborate

Language Revitalization

Apply

N

N

Y

Spanish!

myLanguage Pro

Tusaalanga

N

Ma Iwaidja

Touch Trainer

Y

MindSnacks

N

N

iPhraseBook

N

N

Hika Explorer

Spanish 24/7

N

Go Vocab

Memo Cards

Y

N

Duolingo

N

Capture audio

DIXEL Mobile

Systems

Functionality

N

N

N

N

N

N

N

N

N

N

N

N

N

Capture video

N

N

N

N

N

N

Y

N

N

N

N

N

N

Capture images

N

N

N

N

N

N

N

N

N

N

N

N

N

Curation process

N

Y

N

N

N

N

Y

N

N

N

Y

Y

N

User feedback

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Audio playback

Y

N

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

Learning

Table 1 Existing systems available for revitalizing endangered languages

Y

N

Y

Y

Y

Y

Y

N

N

N

Y

N

Y

Dictionary

N

Y

N

N

N

N

N

N

Y

Y

Y

N

N

Translator

Y

Y

N

N

N

N

N

N

N

N

N

N

N

Dialect support

Y

N

Y

Y

Y

Y

N

Y

Y

Y

Y

Y

N

Progress tracking

N

N

Y

Y

Y

Y

N

Y

N

Y

Y

Y

Y

Assessments

N

N

Y

Y

Y

Y

N

Y

N

Y

Y

Y

Y

Gamification

N

N

N

N

N

Y

N

Y

N

N

Y

Y

N

Leader board

N

N

N

N

N

Y

N

N

N

N

Y

Y

N

Social media

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These systems do not allow individuals or communities to holistically carry out key SKMS processes such as capturing, sharing, accessing and multiple user collaboration. Table 1 synthesizes the existing systems available for language preservation and learning. It is evident that none of the systems support a holistic knowledge capture and refinement process. The systems are mainly focused on language learning of documented words and phrases with audio playback (e.g. Go Vocab, Hika Explorer, Duo Lingo). Only two systems allow data capture but do not facilitate any form of curation (e.g. Ma!iwaidja, Duo Lingo). Few systems support limited social media integration or user interaction. Additionally, none of the systems facilitate support for multiple dialects and socially driven curation processes for user-documented information (e.g. Google Endangered Voices). Moreover, current systems do not allow seamless integration between one another. Hence, we propose designing an integrated system that supports key processes of language revitalization. In summary, current systems support different aspects of language revitalization in a siloed manner, with isolated repositories of words, poetry, and imagery, that does not lend itself to holistic governance, discovery and usage. This lack of integration could contribute ultimately to the death of a language since there is no context to understand, discover and learn the endangered language. Consequently, in the next section we propose the design of SKMS that provides a socially driven approach to knowledge acquisition/capture, knowledge refinement/curating, sharing and retrieval of an endangered language by its speakers.

3

Design of SKMS for Endangered Languages

Language plays an important role in every aspect and interaction in our everyday lives. It is the primary root that allows communication among people in various forms such as in person, writing, over the phone, chatting on the Internet, Facebook, etc. McCarthy (1933) defines language as a medium by which higher intellectual processes are revealed. It is an essential means of social communication and is one of the outstanding systems of habits which distinguish man from animals. Languages are very complex as they employ grammatical and semantic groupings, such as noun and verb, present and past tense, which are used to express complex meanings (Deacon, 1998). The proposed design of SKMS for Endangered Languages focuses on the key aspects related to saving endangered languages rather than focusing on the richness and complexity of ‘knowledge’ associated within a language. Nevertheless, the system will cater for words, phrases, poems, idioms, and stories; including synonyms and multiple dialects. Design science research (DSR) methodology and guidelines are adopted to develop concepts, models, processes, framework and architecture of SKMS for revitalizing endangered languages (Baskerville, 2008; Hevner, March, Park, & Ram, 2004; Nunamaker & Chen, 1990; Nunamaker, Chen, & Purdin, 1990). The guidelines assist in the iterative process of designing various artifacts to address practical problems (Hevner et al., 2004; Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007).

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CREATE

Capture words, phrases, idioms, stories and songs as text, audio, image or video in different dialects

REFINE

Curate captured records – approve, reject or modify

RETRIEVE

Discover and learn words, phrases, idioms, stories and songs

SHARE

Share knowledge through social networks to prompt use of language

Fig. 3 Holistic SKMS approach for endangered language revitalization

The SKMS for endangered languages will support three crucial processes: (1) Knowledge acquisition/capture—to capture words, phrases, poems, idioms, and stories as text, audio, images, and video in multiple dialects through crowd-sourcing mechanisms; (2) Knowledge refinement/curation—to filter and approve captured content through leveraging the wisdom of the crowd, and (3) Sharing and retrieval of knowledge contextually using ubiquitous smart devices—to encourage the use of endangered languages in daily life.

3.1

Concept

This research employs a model of holistic, socially driven KMS to revitalize endangered languages, as illustrated in Fig. 3. This model is a synthesis of concepts from knowledge management and language revitalization literature (Alavi & Leidner, 2001; Hinton & Hale, 2001; Nonaka et al., 1996; Romaine, 2007). It has four key stages: create, refine, retrieve and share. The create stage involves allowing communities to create/capture words, phrases, idioms, stories and songs in multiple formats including text, image and video. The refine stage involves a crowd-sourced panel of language experts moderating and refining the captured data. The retrieve stage will facilitate the wider society to retrieve knowledge from the dynamic repository. Lastly, the share stage enables knowledge to be disseminated through social media among the community to help promote the use of language.

3.2

Use Case

To help design SKMS for endangered languages, a high-level use case model shown in Fig. 4 presents a graphical overview of the key functions (use cases) provided by each of the systems (SKMS mobile application, SKMS web server and Google Play). It also describes the relationships/interdependencies between the actors and the proposed system. Each user of the proposed SKMS mobile application will have role-based access (standard user, expert and editor/moderator).

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Fig. 4 Use case models of the SKMS

3.3

Framework

The generic design elements that make up the Framework of SKMS for endangered languages are depicted in Fig. 5. These elements will help promote reuse of artifacts for multiple endangered languages. The artifacts are key outputs of design science research (Hevner et al., 2004; Nunamaker et al., 1990). The first six layers of the SKMS framework are generic and well understood in research. However, applying this to language revitalization is novel. Ninety percent of the artifacts, including concepts, models, processes, framework, architecture and system, are independent of the language. This will reduce overheads and time taken to implement a similar instance for other endangered languages. Only language specific changes will be required for the system user interfaces. Implementing and validating the system in multiple languages will assist in identifying any implications associated with cross-language implementation. This will be an iterative process to refine the artifacts.

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Fig. 5 SKMS Framework for revitalizing endangered languages

Fig. 6 Governance process

3.4

Process

The key asset of the SKMS is the knowledge it contains. To maintain the data quality of the SKMS, we need to maintain the state of each record. Each record within the system has multiple states, depicted as rectangles in Fig. 6. The initial state of a record is Captured. The record is considered Curated when two or more experts approve it. Until the second expert validates it, the record is still private to the contributor and available to the expert for curation. Once approved it becomes Discoverable to the wider audience, or it is defined as a Rejected record. In the subsequent section, we will discuss the implementation of the SKMS concepts, use cases, framework, and process proposed herein.

4

Implementation of SKMS for Endangered Languages

In this section we will describe the prototypical implementation of a socially driven KMS to revitalize Te Reo Ma¯ori.

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The SKMS is built for mobile devices and we have named it as “Save Lingo”. Save Lingo extends upon fundamentals from Social Media (Kaplan & Haenlein, 2010; Kietzmann et al., 2011) and KMS (Alavi & Leidner, 2001) to create a highly interactive platform through which individuals and communities share, co-create, and modify user-generated content. Save Lingo will help increase societal engagement to give birth to a living knowledge base for the dissemination and revitalization of indigenous knowledge, values and culture. Te Reo Ma¯ori (Ma¯ori language) is the native language of the Ma¯ori population in New Zealand. Before the European settlers arrived (1800s), Ma¯ori was the only spoken language of New Zealand. The dramatic decline of Ma¯ori speakers was observed in the 1980s, when less than 20% of Ma¯ori population were fluent enough to be classified as native speakers (Ministry for Culture and Heritage, 2012). Since 1987 Te Reo has been an official language of New Zealand. Despite 30 years of Ma¯ori language revitalization initiatives, the language continues to be in an endangered state (Rewi & Rawinia, 2011) and English continues to be the default language for many Ma¯ori. This is confirmed by a recent census: the number of Ma¯ori speakers has declined further since 2003 (Statistics New Zealand, 2013). Language revitalization efforts are focused on introducing the language into everyday situations and broadening the cultural base of speakers. Hence, the proposed SKMS (Save Lingo) could play a vital role in revitalizing endangered languages. The implementation is built on the design artifacts described in the previous section. The SKMS is built explicitly using a hands-off architecture that simultaneously empowers the community to adapt and configure the system to their requirements. This section describes and discusses key areas of the SKMS, which are (1) Knowledge Worker/ User personalization and registration, (2) Knowledge Acquisition/Capture to facilitate creating content in various formats, (3) Knowledge Refinement/Curation for content governance to support and administer the growth and evolution of their knowledge repository, (4) Knowledge Retrieval/Discovery by the wider community to retrieve data from the repository, (5) Knowledge Sharing/Transmission to encourage use of language within the society, (6) Social Gamification to enhance user engagement and competition for the benefit of the language and lastly (7) Adoption Challenges that could be encountered when implementing SKMS for revitalizing endangered languages.

4.1

Knowledge Worker/User Personalization

Social media has become a trusted platform for maintaining relationships between friends, family, colleagues and communities at large. Each person creates their personalized digital identities to communicate their views with freedom on a social media platform (Begay, 2013). The Save Lingo app builds on social media fundamentals (Kaplan & Haenlein, 2010), offering users the chance to upload their own photo/avatar, select their tribe and dialect, location, and/or link their account with their Google+ profile. The viral nature of social networks will help promote the endangered language within the networks. The registration process and personalization workflow is discussed below.

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When a user first opens Save Lingo app, he/she will be prompted with a login screen, as shown in Fig. 7: [1]. The user has the ability to seamlessly authenticate and sign in using their Google+ username and password as shown in Fig. 7: [2], instead of creating a new username and password. This also allows users to control the information they want to share with Save Lingo app and control what activities should be shared among their Google+ social networks. Once the user is authenticated they will be taken to Fig. 7: [3] Register New User screen, which will be prepopulated with information retrieved from their Google+ profile (First Name, Last Name, Profile Image, and Location) to minimize data entry. If the user does not have an existing Google+ account, they will select “Register User”, which will open Fig. 7: [3] Register New User screen. Figure 7: [3] Register New User screen gathers information about the user including first name, last name, profile image, tribe (Fig. 7: [4]), email, nearest location (Fig. 7: [5]), role, and password. The user will select Submit Now to register their account. Once the user successfully logs into the system, the user views the logged in view as shown in Fig. 7: [6]. The main menu shown in Fig. 7:

Fig. 7 User registration and personalization workflow

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[6] provides easy navigation to key modules including discover, capture, curate, my records, my bookmarks, my profile, leaderboard, achievements, sync and logout. The user personalization aspects within Save Lingo app will enable knowledge workers to personalize their identity, growing relationships and reputation within the community. We will now discuss the workflow of knowledge acquisition in multiple formats, including text, image, audio, and video using Save Lingo app.

4.2

Knowledge Acquisition/Capture

Documenting and translating a language can be challenging and expensive (Gippert, Himmelmann, & Mosel, 2006). The approach taken complements the language documentation techniques and formats described by Johnson (2004) and Gippert et al. (2006). The deployment of Save Lingo app on ubiquitous devices enables data capture anytime anywhere, not only reducing costs but also empowering people of different tribes, dialects ages and gender to collectively contribute towards preserving their language. The internalization of newly captured explicit knowledge into the wider community’s tacit knowledge can be difficult. However, creating necessary learning components will enable individuals to learn by using the language in daily life. Knowledge acquisition initiates the holistic socially driven approach towards revitalizing endangered languages as illustrated in Fig. 3. In the “Capture” area as shown in Fig. 8, the user will have the ability to capture knowledge about their language and culture as words, phrases, idioms, stories and songs in multiple formats including text, image and video. Firstly, the user selects the type of content they want to capture: word, phrase, story, song or idiom; for example “Word” as shown in Fig. 8: [1]. Once the selection is made, the category list is displayed as shown in Fig. 8: [2]. Selecting the most appropriate category is important to ensure easy retrieval of records. The

Fig. 8 Knowledge acquisition/capture workflow

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Capture Word screen (Fig. 8: [3]) allows the user to enter the Ma¯ori word and English word as textual inputs and select an appropriate Dialect. Similar input fields are displayed for entering phrases and idioms. However, for story and song, additional input fields are displayed to allow the user to add larger amounts of textual content. Save Lingo app facilitates knowledge acquisition in multimedia formats, leveraging media capabilities of ubiquitous devices. For instance, the user can attach an image (see: Fig. 8: [4]) using their camera or select an existing image from their device gallery. The user has the ability to record their voice or an existing audio file on their device. The Play button allows the user to review their content prior to submission. Furthermore, the user has the facility to capture video or provide a direct URL (Uniform Resource Locator) of the video. Once the data has been captured, the user can either select Submit Now for immediate submission or Submit Later to locally store the record. In summary, knowledge acquisition is not merely for the sake of preserving a language, but also to help empower and educate the language users. Prior to disseminating the knowledge, we need to ensure knowledge is curated. This is discussed in the next section.

4.3

Knowledge Refinement/Curation

Content governance is vital in the context of endangered languages, to ensure the authenticity of the knowledge repository. The implemented governance structure aims to tackle issues related to KMS maintenance: balancing additional workload and ensuring accurate content Hahn and Subramani (2000). The governance is facilitated in the “Curate” area as shown in Fig. 9. The users with expert or editor role will have the ability to moderate words, phrases, idioms, stories and songs, including image, audio and video created by standard users. The Curate tab in Fig. 9: [1] displays the number of records that need to be curated. Firstly, the moderator has to select the type of record they want to curate, for example Phrases in the examples shown in Fig. 9: [1]. On selection, the list of records pending moderation is displayed (Fig. 9: [2]). Below each record, icons (audio, image, video, synonyms) are displayed to indicate the related records that need to be curated. Once the record is selected, the detailed view of the captured content is displayed, as shown in Fig. 9: [3]. The moderator can approve, reject or modify each record. If Modify is selected, Modify popup appears (Fig. 9: [4]), allowing the user to refine the record prior to approving it. If Reject is selected, Reject Confirmation as shown in Fig. 9: [5] appears, prompting the user to enter the reason for rejecting the record. If Approve is selected, Approval Confirmation popup (Fig. 9: [6]) appears to ensure the record is accurate. The business rules for dissemination of records are based on the Fig. 6 state transitions of records within SKMS. The process of content governance is an ongoing effort to ensure authenticity of the knowledge captured. Save Lingo app enables this task to be distributed among

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Fig. 9 Knowledge/refinement/curation workflow

language experts in the society. We will now explore how the wider community accesses the curated records from Save Lingo app.

4.4

Knowledge Retrieval/Discovery

Knowledge captured and curated socially can be retrieved using the Discover tab as shown in Fig. 10: [1]. Save Lingo app facilitates the wider community to access and learn their language anytime anywhere. This complements the existing knowledge retrieval process described by Alavi and Leidner (2001). The user can choose the type of content (e.g. “Phrases” as shown in Fig. 10: [1]) followed by the category that they want to explore (Fig. 10: [2]). On selection, lists of phrases are displayed as shown in Fig. 10: [3]. Below each record, a number of associated synonyms, audio, images, videos and likes are displayed to indicate social activity. Once the record is selected, the detailed view is shown (Fig. 10: [4]). The action bar highlighted in Fig. 10: [5] allows user to Bookmark, Share, Like or Play the record. Numbers of likes indicate the popularity and quality of the record based on social feedback. Moreover, it is a method to acknowledge the contributor’s effort to help revitalize the language. The textual content appears in Ma¯ori first, followed by English translation as shown in Fig. 10: [6]. Images are a powerful means of expression and communication. Languages are not just the words that are spoken but are also the cultural heritage embedded within. Curated images are displayed in a slideshow control as shown in Fig. 10: [7], adding context to the textual information.

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Fig. 10 Knowledge retrieval/discovery workflow

The knowledge contributor’s authorship is acknowledged by displaying their profile (name, avatar, tribe, region and dialect) below each record they contributed as shown in Fig. 10: [8]. The associated records such as synonyms, audio recordings, images, and videos are accessible by their respective tabs as shown in Fig. 10: [9–12]. Additionally, the user has the ability to capture related content within the detailed view. Subsequent to knowledge retrieval; the user has the ability to share knowledge among the society.

4.5

Knowledge Sharing/Transmission

One of the fundamental processes in knowledge management is to share/transfer knowledge among the network of users. This is built on knowledge sharing fundamentals highlighted by Sharratt and Usoro (2003). Save Lingo app enables users to share via popular social media platforms including Facebook and Twitter or other compatible 3rd party applications as shown in Fig. 11. Sharing knowledge among the community helps promote the use of language. Sharing knowledge via mainstream social media platforms will help promote awareness of the language and the Save Lingo app within the wider social network. However, not all audiences may be interested, which is generally the case for

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Fig. 11 Knowledge sharing/transmission workflow

content available on social media platforms. Wider social network users can sign up and contribute to the language by accessing the Save Lingo app.

4.6

Knowledge Management Through Social Gamification

One might have the most beautiful and functional system in the world but it is totally useless if it doesn’t get used, doesn’t engage with users, or if it is not usable. We believe that gamification is a way to attract people, especially digital natives, to start using the system. Of even more importance is to hold their engagement so that they continue to use the system. Gamification is defined as “the process of game-thinking and game mechanics to engage users and solve problems” (Zichermann & Cunningham, 2011). In contrast to traditional language revitalization systems, we have taken a different approach by weaving gamification throughout all processes of Save Lingo app: capture, curate, discover and share. The gamification features will help improve social engagement among users. Moreover, this addresses the problems raised by Hahn and Subramani (2000) of providing motivation and incentives for users to continue maintaining the SKMS. Gamification features are implemented using Google Play Game Services (Google, 2015). The user receives points when they contribute towards the knowledge management of the system. These points are totaled to calculate their leaderboard score and award achievement badges.

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Fig. 12 Leaderboard and achievements

If new record submitted ¼ 5 points If synonym or image or audio or video added ¼ 2 points If content is approved or rejected ¼ 2 points If content is modified/corrected ¼ 5 points The leaderboard shown in Fig. 12: [2], helps drive user engagement by allowing users to compare their scores (contributions) with their social network. Moreover, it allows them to see their public ranking among the wider community. The users are awarded achievement badges on reaching a certain milestone as shown in Fig. 12: [3]. The achievements can be configured in the Google Play Developer console panel. Achievements are created to encourage users to experiment with key features of the app, for example, capturing a word or an image. Incremental achievements are given when the user makes gradual progress towards earning the achievement over a longer period of time; for example, capturing 20 records into the repository.

4.7

Adoption Challenges

There are practical challenges to implementing SKMS for revitalizing endangered languages. A key challenge could be the demographics associated with endangered

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languages, which tend to be statistically skewed towards older adults. However for Te Reo Ma¯ori, 49.6% who could hold a conversation in Te Reo Ma¯ori are below 30 years and 50.4% are over 30 years (Statistics New Zealand, 2013). Balanced distribution between the various age groups can support the uptake of SKMS for Te Reo Ma¯ori. On the other hand, for many other endangered languages, the group that is most knowledgeable about the language may be the same group that is less likely to use social media. This could potentially lead to an adoption problem, if not used by elderly knowledgeable speakers. In summary, we have discussed the key areas within the implementation of socially driven KMS for revitalizing endangered languages. The prototype, Save Lingo app was implemented to help revitalize Te Reo Ma¯ori. The solution enables communities to take advantage of social media and KMS to preserve, curate, discover, transmit and revitalize endangered languages.

5

Conclusion

In conclusion, the rapid disappearance of vital knowledge and culture embedded within each language, as well as the limitation of current systems and approaches, motivated the primary objective to design and implement a SKMS for endangered languages. We propose a new type of knowledge management system that is driven and supported by social media. We apply the concept of SKMS for the capturing, curating, accessing, sharing, collaborating and ultimately revitalizing of endangered languages. We delve into such SKMS and show how social media can be used to support key facets and processes of knowledge management. The three crucial processes that are supported include: (1) Knowledge acquisition/capture through crowd-sourcing mechanisms; (2) Knowledge refinement/curation through leveraging the wisdom of the crowd; (3) Sharing and retrieval of knowledge contextually using ubiquitous smart devices, and (4) Knowledge management through social gamification. More specifically, we began by looking at the strengths of social media and knowledge management systems. Subsequently we reviewed representative language preservation and learning systems. Based on these we proposed socially driven knowledge management concepts, models, processes and frameworks to help preserve and revitalize endangered languages. We further go on to describe the implementation of the proposed concepts, models, processes and frameworks in the context of Te Reo Ma¯ori, an endangered language. We have included endangered language stakeholders and native language speakers as advisors. Moreover, we have presented this research to the Ma¯ori Language Commission of New Zealand with positive and useful feedback. Initial pilot testing of functionality, usability, response, performance and supportability, has been conducted through a number of iterations. We are in the process of conducting wider evaluation to gather empirical evidence for the effectiveness of SKMS for Te Reo Ma¯ori and other endangered languages. Save Lingo’s framework, architecture, functionality and implementation is easily portable and can support the revitalization of other endangered languages. Indeed,

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the system can also support the cultural preservation of mainstream languages. These conceptual and system artifacts could potentially lead to a fundamental shift in how communities could use socially driven knowledge management systems to revitalize, use, develop, and transmit their native language to future generations. Nevertheless, we believe that this is just the tip of the iceberg and that SKMS has the potential to transform the way we work, play and live.

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