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Cross-Cultural Online Learning in Higher Education and Corporate Training Jared Keengwe University of North Dakota, USA Gary Schnellert University of North Dakota, USA Kenneth Kungu Tennessee State University, USA

A volume in the Advances in Higher Education and Professional Development (AHEPD) Book Series

Detailed Table of Contents

Foreword . ............................................................................................................................................. xi Preface . ...............................................................................................................................................xiii Acknowledgment . ............................................................................................................................. xvii

Chapter 1 Designing and Delivering Web-Based Instruction to Adult Learners in Higher Education ................... 1 Mabel C. P. O. Okojie, Mississippi State University, USA The essence of this chapter is to discuss theories and practices including approaches that instructional designers consider when designing Web-based instruction for adult learners. The importance of the chapter is to discuss best practice activities and theories as well as technologies that enable adult online learners to be involved in the design of their Web-based instruction. This represents recognition that adults have accumulated a repertoire of knowledge and experiences that inevitably will enrich the course materials. The theories discussed in this chapter are constructivism and connectivism; these theories improve adult involvement and help them to establish learning networks for exchanges of ideas using cultural artifacts and various interactive and video technologies. These technologies include Adobe Connect, Camtasia, Articulate Storyline, SoftChalk, Prezi, Google.docs, and Google Hangout. The idea is to provide rich virtual learning environments to help adult learners explore learning and connect with each other without inhibition. The traditional method of instruction, which is teacher-centered, is considered inadequate for the present digital age with its rapid knowledge transformation. The roles of technology leaders within the institutional leadership and factors that may impact negatively on Web-based instruction for adults are also considered. Chapter 2 Cultural Orientation Differences and their Implications for Online Learning Satisfaction ................. 20 Moussa Tankari, University of Zinder, Niger The purpose of this chapter, which uses sociocultural learning theory as its framework and a mixedmethods study design, is to understand the differences between personal culture orientation and online learning satisfaction by examining culture at the macro and micro level in an online learning environment. More specifically, this chapter examines the cultural orientation differences among graduate students enrolled in at least one online course in the fall of 2011 at a Western institution of higher education and how these cultural differences impact their level of satisfaction with online learning. Both quantitative and qualitative data is collected, respectively, via surveys, and interviews indicate that, although culture does not directly affect satisfaction, there is a need to raise awareness about the critical factors that may

affect online learning experience and to provide guidance for practice and future research. Chapter 3 Adult Millennials: Conceptualizing a Student Subpopulation with Implications for Online Teaching and Learning.......................................................................................................................................... 62 Brian Bourke, Louisiana State University, USA Discussions about students in post-secondary education are often based on divisions of distinct subpopulations, which are in turn often based on demographics or generational status. In the context of adult learners who are also members of the Millennial generation, there exist no discussions of the overlaps between the two groups. In this chapter, the author provides an overview of the characteristics of both adult learners and members of the Millennial generation. Following a comparison of the characteristics of the two groups, the author offers a perspective of a distinct subpopulation: Adult Millennials. After offering strategies for working with Adult Millennials, with attention to online learning environments, the chapter concludes with suggestions for further research addressing Adult Millennials. Chapter 4 Cultural-Pedagogical Norms in Iranian Virtual Higher Education Institutions . .................................. 79 Davoud Masoumi, University of Gothenburg, Sweden Berner Lindström, University of Gothenburg, Sweden By discussing the cultural-pedagogically inscribed norms, this chapter argues that, regarding the design and implementation of e-learning from the perspective of globalization, it is critically important to recognize, understand, and thus take into account cultural situatedness. Such cultural-pedagogical norms are often taken for granted in educational settings. Drawing on the literature, this study presents a model of cultural-pedagogical paradigms in higher education in general and e-learning in particular. The authors use this model to explore cultural-pedagogical orientations in Iranian virtual institutions as an instance of a developing country. This is done from a comparative perspective, looking to the similarities and differences of teachers’ and learners’ points of view. Chapter 5 Culture Aware M-Learning Classification Framework for African Countries . .................................... 98 Simon N. Mwendia, KCA University, Kenya Peter Waiganjo Wagacha, University of Nairobi, Kenya Robert Oboko, University of Nairobi, Kenya African countries are currently experiencing proliferation of mobile phone subscriptions but no prevalence of personal computers or electricity. Although there is a great potential for Mobile Learning (M-Learning) in education, the formal integration of M-Learning in the education systems is in its infancy since there is limited number of M-Learning projects in the region. This is in contrast with the rapid increase and integration of mobile phones in the daily lives of the population in the region. Online learning needs to be culturally aware and investigate the dimensions of cultural variability as well as its influence on learning within global education. In an attempt to address this need, this chapter focuses on the African region in describing dimensions of cultural variability and proposes four categories for M-Learning projects as well as their influences on dimensions of cultural variability.

Chapter 6 Differences in Generational Characteristics and their Implications for Cross-Cultural Online Learning and Knowledge Management ............................................................................................................. 112 Doo Hun Lim, University of Oklahoma, USA Seung Won Yoon, Western Illinois University, USA Ji Hoon Song, University of North Texas, USA This study is an integrative literature review about the distinctive characteristics of multi-generations, their cognitive differences within online learning environments, modern knowledge management theories and frameworks, and the differences of knowledge management practices among multi-generations. Particular attention has been paid to examine distinctive characteristics in the cognitive learning style and knowledge management practices between different cultural settings. Based on the review, the authors propose an integrated approach to comparing the divergent and convergent characteristics of multi-generations and cross-cultural variables in order to design and deliver effective learning solutions and knowledge management systems that will address various organizational and cross-cultural learning and performance issues. Chapter 7 Adult Learners Online: Cultural Capacity Assessment and Application............................................. 134 Adam A. Morris, University of Arkansas, USA Michael T. Miller, University of Arkansas, USA The current chapter describes how adult learners of different cultures experience and respond to online learning, and what different instructional strategies and personnel in higher education can do to develop an appropriately delivered online experience. This foundation has a limited element of cultural differentiation and is complicated by using one-size-fits all online courses. Instructors, administrators, and instructional designers must all collaborate to re-think and re-build the effective online course experience: an experience with a hallmark of flexibility and diversified instructional techniques. Effective cultural responsiveness can greatly improve adult learning and potentially respond to a unique group of learner motivations. Chapter 8 Understanding Online Cultural Learning Styles and Academic Performance of Management Students in an Ethnic Context ........................................................................................................................... 149 Syed Raza Ali Bokhari, Bahria University, Pakistan Iqbal Ahmed Panhwar, Bahria University, Pakistan This study utilizes Structural Equation Modeling with maximum likelihood discrepancy function to examine the relationship among various cultural dimensions and multicultural learning styles, and subsequently the impact thereof on student academic performance. 210 MBA students who enrolled in an online class were examined. The hypothetical model integrated proven learning styles and cultural theories. While Kolb’s Learning Styles Inventory (LSI) version 3.1 captured attributes of learning style preferences, the Cultural Dimensions of Learning Framework questionnaire developed by Parrish and Linder-VanBerschot captured cultural preferences. Three structural models (epistemological beliefs, social beliefs, and temporal perceptions dimension of culture) were analyzed. It was found that epistemological beliefs and temporal perceptions dimensions of culture exhibited a positive relationship with multicultural learning styles; the social relationship dimension showed negative relationship, while total effect on student academic performance across was relatively similar across all models.

Chapter 9 Cross-Cultural Challenges in the Design and Delivery of Online Language Programs . ................... 170 Frederick Kang’ethe Iraki, United States International University, Kenya Whether online, offline, hybrid, distant, or even e-learning, recent developments in technology all over the world have changed the way learning and teaching is designed and delivered. Recently, some university consortia in the US announced that they would be offering large-scale online degree courses, for free. Irrespective of the repercussions of such an initiative, it seems very likely that the future of higher education will be online courses. In recognition of this reality, universities are providing continuous professional development to their faculty, particularly in the area of online teaching and learning. But the challenges are not only technical but cultural too. This chapter discusses the general requirements and challenges (both technical and cultural) that face a designer of an online or hybrid language program that is communicative, interactive, exciting, motivating and engaging for students. More specifically, the chapter details the road travelled by the author in designing and delivering a hybrid Intermediate 2 Swahili program in spring 2013 to American students at American University in Washington DC. The technical, technological, and cultural issues encountered by both the lecturer and the students are reviewed in the chapter. A comparison with regular face-to-face students provides some points for reflection in future designs. Chapter 10 Learning through Immersive Virtual Environments: An Organizational Context............................... 185 Erastus Ndinguri, Framingham State University, USA Krisanna Machtmes, Ohio University, USA John Paul Hatala, George Brown College, Canada Mary Leah Coco, Louisiana Transportation Research Center, USA Changes on how the workforce is learning/training today are evident in many organizations. Discussions about how Immersive Virtual Learning (IVL) is a part of the skill development process and outcomes in the workplace have increased. There is an abundance of literature on the application of virtual and other learning technologies within learning institutions; however, there is a paucity of literature on IVL organization learning. This chapter discusses the existing research and understanding of IVL and the application within an organizational setting. Further, this chapter explores the connection between knowledge transfer and the impact IVL has on the workforce. This exploration attempts to create a link between global connectivity, changing cultures, and changing technologies. In addition, this chapter examines the benefits of IVL in a workplace setting and offers suggestions for future research and practice. Chapter 11 A Place for Culture in Instructional Design . ...................................................................................... 200 Shabana Figueroa, Georgia Institute of Technology, USA Wanjira Kinuthia, Georgia State University, USA The purpose of this chapter is to discuss the macro and micro challenges instructional designers face when designing Web-based instruction for adult learners. Macro level challenges like institutional and infrastructural requirements are those outside the design process that directly affect teaching and learning outcomes. Micro level challenges, on the other hand, are those inside the design process that directly impact teaching and learning outcomes (e.g. cultural biases of the designers and instructors). The authors discuss the effects of these challenges for instructional designers in higher education. Since the population of focus is adult learners, a brief overview of adult learning and characteristics of adult learners is provided. A variety of models and frameworks have been developed within the field, with only a handful that are constructed to explore diverse learners and learning. The chapter also includes introspection of the authors’ experiences as instructors, instructional design professionals, and students in the field. It concludes with strategies instructional designers can use to overcome the challenges discussed.

Chapter 12 Best Practices of Teaching Cross-Cultural Adults in Online Format ................................................. 216 Barbara Hagler, Southern Illinois University – Carbondale, USA Online learning is on the increase, as is the teaching of cross-cultural adults. Best practices of teaching cross-cultural adults in the online format are presented and discussed in this chapter. Online learning benefits are also discussed. Online learning needs to be regularly evaluated to ensure learning is actually taking place. Suggestions relating to the evaluation of online learning are presented. Additional references are included for further reading opportunities related to the best practices of teaching cross-cultural adults in the online format. Chapter 13 Preparing for Online and Distance Learning Courses: Factors Affecting Student Learning and Retention.............................................................................................................................................. 229 Paul A. Asunda, Southern Illinois University – Carbondale, USA Jennifer Calvin, Southern Illinois University – Carbondale, USA Rosalie Johanson, Southern Illinois University – Carbondale, USA The purpose of this descriptive study is to investigate students’ perceptions of online learning courses at a 4 year mid-level mid-western university and whether or not these perceptions influenced their decision to continue taking online courses or not. The findings of this study show that thorough preparation prior to online course work can help to curb dropout rates and can better prepare learners for successful completion of the course. Chapter 14 Social Presence and Student Engagement in Online Learning . ......................................................... 244 Luka Ngoyi, University of Zambia, Zambia L. J. Sandy Malapile, Independent Consultant, South Africa Effective online learning practices should incorporate an active social presence that provides space and technological support for students and instructors to engage in social activities, which are an integral part of the learning process. The focus of this chapter is the description of social presence, the forms in which it occurs, and how social presence enhances student engagement in the learning process, whether online or face-to-face. Based on various studies related to this topic, the authors argue that social presence has a significant impact on student engagement, especially in online classes. Finally, this chapter examines how social presence affects student engagement and offers various strategies for instructors to enhance social presence and student engagement in online learning. Chapter 15 The Role of Social Constructivist Instructional Approaches in Facilitating Cross-Cultural Online Learning in Higher Education . ........................................................................................................... 253 Janella Melius, Winston Salem State University, USA The role of the university is rapidly changing in this new information age, as many courses and programs are using on-line modalities (i.e. live, interactive audio or video or video conferencing, pre-recorded instructional videos, Webcasts, CD-ROMs, DVDs, or computer-based systems accessed over the Internet) as part of their instructional delivery. Online learning education has closed the gap for many learners who would have been unable to attend an institution of higher learning due to family and career obligations; it has also been instrumental with facilitating collaborative learning and teamwork among students in

cross-cultural and cross-national settings. However, due to these geographic variations among online learners from culturally diverse backgrounds, instructors may be faced with challenges hindering their facilitation of online courses and the overall learning outcomes among cross-cultural students. The purpose of this chapter is to discuss aspects of these challenges, provide educators across all discipline with an understanding of the role social constructivist instructional strategies have on facilitating an inclusive online cross-cultural learning environment, and provide recommendations for developing strategies to accommodate these diverse students.

Compilation of References ............................................................................................................... 271 About the Contributors .................................................................................................................... 306 Index.................................................................................................................................................... 313

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Chapter 5

Culture Aware M-Learning Classification Framework for African Countries Simon N. Mwendia KCA University, Kenya Peter Waiganjo Wagacha University of Nairobi, Kenya Robert Oboko University of Nairobi, Kenya

ABSTRACT African countries are currently experiencing proliferation of mobile phone subscriptions but no prevalence of personal computers or electricity (Parker, 2011). It is estimated that, by the end of 2015 in Sub-Saharan Africa, the percentage of people with mobile network access will surpass that of access to electricity in homes (Rao, 2011). This phenomenon is also experienced in learning institutions, particularly universities, where almost every student owns a mobile phone (Kashorda & Waema, 2009). Although there is a great potential for Mobile Learning (M-Learning) in education, the formal integration of M-Learning in the education systems is in its infancy since there is limited number of M-Learning projects in the region. This is in contrast with the rapid increase and integration of mobile phones in the daily lives of the population in the region (Isaacs, 2012). According to Olaniran (2009), online learning needs to be culturally aware and investigate the dimensions of cultural variability as well as its influence on learning within global education. In an attempt to address this need, this chapter focuses on the African region in describing dimensions of cultural variability and proposes four categories for M-Learning projects as well as their influences on dimensions of cultural variability.

DOI: 10.4018/978-1-4666-5023-7.ch005

Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Culture Aware M-Learning Classification Framework for African Countries

INTRODUCTION Society is made up of different sub-cultures that exist among its members. These differences cause many barriers such as communication and due to lack of effective communication there are misunderstandings among people depending on their values, beliefs, backgrounds (Kawar, 2012). The mobile phone technology is the quickest growing technology innovation in history, which can be used to remove such barriers. According to industry estimates, by the end of 2010, there were more than 500 million mobile phone subscribers out of 110 million people in Africa. This was more than 50% of the continent’s population and an increase from 246 million in 2008. The number was expected to surpass 750 million people by the fourth quarter of 2012 and reach one billion before the end of 2015 (Reed, 2012).The fast growing trend of mobile phone technology presents a great potential for delivering learning content on mobile devices especially in Africa where most of the countries are characterized by poor ICT infrastructure (Kashorda & Waema, 2009). Mobile learning (also known as m-learning) has various definitions by researchers in this field. For the purpose of this chapter, we adopt definition proposed by Viberg & Grönlund (2012), who defined m-learning as a process of learning across multiple contexts among people and personal interactive technologies with a focus on contexts. These technologies include any type of handheld devices that can be used when walking around such as mobile phones, personal digital assistants (PDAs), smart phones, Ipads and soon. According to Olaniran (2009), online learning discussion needs to be culture aware and investigate the dimensions of cultural variability and their repercussions on learning within global education. The primary objective of this chapter is to get a better understanding of m-learning applications for multi-cultural context such as African countries while the specific objectives include:

1. To describe cultural variability dimensions that exists in African countries. 2. To establish a classification framework that integrates and provides a theoretical framework for integrating emerging cross-cultural m-learning projects launched in African countries. 3. To identify influences of cross cultural mlearning applications in African countries.

BACKGROUND M-Learning Projects in Africa The rapid growth of mobile phone subscriptions in African countries has triggered interest in how mobile phones might enhance open and distance learning opportunities for the professional development of educators, and support educators in their pedagogical practices and administrative responsibilities. However, the limited but growing number of m-learning projects in the region indicates that the formal integration of m-learning in education systems is in its infancy stage. Majority of m-learning projects in Africa are found in South Africa, Kenya and Uganda with the highest concentration being in South Africa. Mobile phones are the dominant tools for supporting teaching and learning within classrooms or improved learner performance in both formal and informal learning environments with majority focusing on formal education in primary and secondary schools (Isaacs, 2012). Studies show that, there are some researches that contextualize online learning from intercultural perspectives but majority of these researches ignores the multicultural contexts (Thatcher, 2012). This chapter therefore focuses on exploring various categories m-learning applications that target multicultural target users that have been launched in African countries, as a case study of multicultural context.

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Motivation According to Vieira (2009), Mobile phone is now a utility and not just a communication device. Mobile phones capabilities have improved over the years from just communication device for chatting, organizing contacts and diaries to small pocket-sized computers. These devices can now be used to deliver learning objects and provide access to online services, just like other systems (Attewell, 2005). For the last one decade, African countries have been experiencing a high growth of mobile phone penetration and by the year 2011, Mobile phone networks had covered 75% of the population in many African countries (Rao, 2011). Forecast by Informa Telecoms and Media estimated the growth rate of mobile subscriptions in Africa to have reached 17.5% by the end of 2012. This rate was the highest among other major world regions and above the world average of 10.75% (Reed, 2012). In higher learning institution, a study carried out by (Muyinda,, Lubega,, & Lynch, 2008) at Makerere University, indicated that over 96% (n=68) of university students own mobile phones and they use them for research collaboration (93%). This proliferation of mobile phones presents an opportunity to education institutions to use mobile phones for reaching a large number of students (Hellström, 2010). Study carried out by Kashorda & Waema (2009) observed that, approximately 50% of the male students and 47% female students use mobile Internet in East African universities. It was therefore concluded that, active use of mobile phones to access internet rather than using computers is an important indicator of how mobile Internet will play a fundamental role in supporting access to learning resources by learners in East African universities and should therefore be a new domain for research. Mobile devices are progressively used for supporting social interaction, sharing and communication. The use of Media such as mobile devices in everyday life have led to cultural sig100

nificance (Pachler, 2009). This calls for research with a cultural perspective, which focus on use of mobile phones to support learning in ‘mobile rich’ contexts such as learning institutions situated in African countries.

Existing Dimensions of Cultural Variability in African Countries Culture is defined as collective programming of the mind which differentiate the members of one group of people from another (Hofstede, Hofstede,, & Minkov, 2010). According to Olaniran (2009), the objectives of online learning can be realized by paying attention to learners’ cultural learning needs and accommodate them in ways that encourage good outcomes for the learners. Paying attention to learners’ cultures necessitates looking at the dimensions of cultural differences. The most commonly used dimensions of culture variability include; i) Power Distance (PDI), ii) Individualism (IDV), iii) Masculinity (MAS), iv) Uncertainty Avoidance (UAI), v) Long-Term Orientation (LTO) (Hofstede, 2010; Hofstede, 2001; Hofstede,1980). For the purpose of this chapter, we focus on these dimensions of culture variability among African countries. Power Distance (PDI), is the extent of inequality that exists and is accepted among members society with and without power. A high power distance shows that society accepts an uneven distribution of power and people understand their position in that society. In Africa, examples of countries with high PDI include East African countries (e.g. Kenya, Tanzania and Uganda) with a collective PDI of 64% and West African countries (e.g. Nigeria, Ghana and Sierra Leone) with a collective PDI of 77% and North African countries (e.g. Egypt and Libya) with a collective PDI of 80%. On the other hand, Low Power Distance indicates that, power is equally distributed and shared among the people. In such a society, people view themselves as colleagues. South Africa is an example of low PDI country in Africa with low PDI of 49%.


Individualism (IDV) refers to the strength of the dependence members have to others within the society. A high IDV suggests that people are highly independent and have less interpersonal connections. Individual members have few friends and sharing of responsibility is limited. In Africa, South Africa is an example of countries with very high IDV of 65%. Low IDV indicates that, people have strong interpersonal connections and share responsibilities among them selves. Generally, members respect each other with a lot of royalty in low IDV societies as compared to high IDV societies. Countries with low IDV in Africa include; i) Libya and Egypt, with collective IDV of 38%, ii) East Africa countries with IDV of 46% and, iii) West Africa countries (i.e. Ghana, Nigeria and Sierra Leone) with IDV of 20%, which is one of the lowest among African countries. Masculinity (MAS) refers to the extent of how much a community retains its values, traditions and roles. A high score (masculine) indicates that the there a lot of competition among people and achievement is more valued. Men dominates women in decision making, providing, assertiveness, toughness and physically strong. There is a clear separation of roles between men and women. Low MAS (Feminine) indicates that male and female roles are not clearly defined. In such society, men and women can take any role in various professions. Consequently, there are more career women in low MAS as compared to high MAS. Uncertainty Avoidance Index (UAI) describes the extent of anxiety people feel when in unknown or uncertain situations. High UAI suggests that, people attempt to avoid uncertain or unknown state of affairs by formulating rules for governing their activities. Examples of African countries with high UAI include North Africa countries such as Egypt, Morocco and Libya with UAI of 68% collectively. On the other hand, low UAI indicates that people in the society take pleasure in unique situations. Activities are not guided by any rules and members discover their own way of doing things. Examples of African countries with

medium-low UAI include West Africa countries (Ghana, sierra Leone and Nigeria) with UAI of 54% and East African countries with UAI of 52%. Long Term Orientation (LTO) describes the degree of how much people cherish long-term traditions and values as compared to short-term traditions and values. High LTO score indicates that people avoid loss of their traditions and values while Low LTO suggests that people do not cherish their long-term traditions and values. African countries with low LTO include: East African countries (Kenya, Tanzania and Uganda) with collective LTO of 25% and West African countries (Ghana, Nigeria and Sierra Leone) with LTO of 16%, which is one of the lowest globally. There is no available data for African Countries with high LTO.

Existing Classifications of M-Learning Projects Categorization of m-learning applications enables understanding of challenges, specific issues and benefits of mobile devices in education. However, there has been very little progress in attempting to categorize mobile learning. Examples of existing categorization attempts include: Pedagogical Classifications, Contextual Classifications, Blended Classifications, Application-Based Classification and usability-based applications (Deegan & Rothwell, 2010). Pedagogical Classifications categorize mlearning applications according to their dominant pedagogical theory. An example include theory-based classification that was proposed by Naismith, Lonsdale, Vavoula, & Sharples (2004), which described 6 categories of m-learning. These are: Behaviourist, Constructivist, Learning and teaching support, Situated, Informal and lifelong and collaborative category. Pedagogical classifications pursue key pedagogical concepts that explain user activities when interacting with m-learning application. Limitations of these classifications are: i) They do not enlighten the designer in relation

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to design characteristics, especially for usability, ii) Some the categories are overlapping. For instance, an application may be collaborative but also with constructivist elements, iii) the classifications do not offer frameworks that consider variability of cultural dimensions. Contextual Classifications categorize mobile learning applications based on learning environment of the learner (learner’s context). These classifications are based on argument that, all m-learning occurs within a context, thus the need to classify them according to context. An example include classification by Frohberg & Schenk(2008), which describe four categories of m-learning that is; independent, formalized, physical and socializing context. Comparatively, there has been little research that focus on the context attribute in m-learning and only few frameworks for context-aware m-learning exist (Thüs et al., 2012). Application-based Classifications categorize m-learning according to types of application. An example include classification by Roschelle (2003), which described three types of m-learning applications: participatory simulations, collaborative data gathering and computer response systems. According to Deegan & Rothwell (2010), these classifications are useful to designers since they view applications from a usability perspective but incomplete since they do not comprise many types of m-learning application. Blended classifications describe m-learning categories that contribute to more than one classification. An example include classification by De Jong, Specht, & Koper (2008),which suggested five categories. These are: Content, Pedagogical Paradigms, Purpose, Information Flows, and Context. The categories contribute to both application classifications and pedagogical classifications. However, the final Purpose, Information Flows, and Pedagogical Paradigms dimensions offer little support to the designer in developing usable mlearning applications (Deegan & Rothwell 2010).

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A usability-based classification describes set of categories that meets our learner needs with regard to usability issues. An example include classification by Deegan & Rothwell (2010), which describes five distinct categories of m-learning: Learning Management, Supportive, ContentBased, Context-Based and Collaborative.

Evaluation of Existing Classifications From authors’ perspectives, the existing classification of m-learning applications are successful in their goals and objectives (Deegan & Rothwell 2010). However, they are not ideal for achieving our goals of understanding different categories of m-learning applications for multi-cultural context such as African countries.

METHOD Content analysis method was used to explore categories of cross cultural learning projects and potential applications on Dimensions of Cultural Variability that exists in African countries. Data sources included written materials such as conference reports and journal articles. The study applied the following four qualitative data analysis steps recommended by (Mugenda & Mugenda, 1999). They include; 1. Data organization: use of computers to record data derived from the literature. 2. Creating categories: Detect various types of m-learning and their potential applications on dimensions of cultural variability. 3. Analyzing and interpret information: Involves evaluation of m-learning types to determine their applications. 4. Compile report: The book chapter was then compiled to discuss findings of the study.


The explored m-learning projects were selected on the basis of the two criteria. These are:

Figure 1. Classification framework for crosscultural m-learning projects launched in African countries

1. The projects that used mobile technology to support learning and teaching across cultures in one or more African countries. 2. Projects that target students enrolled in formal education institutions such as primary schools, high schools, colleges and universities.

FRAMEWORK Drawing from the literature review explored, it can be observed that people from different countries are associated with different dimensions of cultures. In this chapter, we propose an m-learning classification framework that extend reviewed contextual classifications to categorize m-learning projects across all cultures, based on physical context dimension suggested by Frohberg & Schenk (2008). This classification is differentiated from the rest by considering variability of cultural dimensions and differences of physical contexts in terms of countries. Figure1 illustrates four categories of mlearning projects launched in African countries.

RESULTS: FOUR CATEGORIES OF CROSS CULTURAL M-LEARNING PROJECTS The framework categorizes m-learning projects launched in African countries into four main categories. That is: 1. In-Country m-learning projects. 2. Regional m-learning projects. 3. Continental m-learning projects. 4. Global applications m-learning projects.

Category 1: In-Country M-Learning Projects In-country m-learning projects are adopted by users within a certain country but from, across different cultures. The majority of these projects are based in lower formal education institutions such as primary and secondary schools. Examples include Mprep and Elimu.org in Kenya which target primary school pupils while M4Girls and Dr Math in South Africa targets Secondary schools students. Examples of m-learning applications that target university students include ‘UI initiative’ in the University of Ibadan, Nigeria and ‘Makerere Research supervision initiative’ in Makerere University, Uganda. Comparatively, ‘Dr Math’ project has a wider application than other In-Country m-learning projects explored in this review. For instance, the project has supported over 25,000 registered users since its inception. Dr Math project was therefore sampled as a case study for In-Country applications. South Africa has low PDI and UAI but high MAS and IDV culture. Dr Math is an mlearning tutoring service for Mathematics subject, which was started in 2007 by the CSIR Meraka Institute in South Africa to help both primary secondary school students learn Mathematics.

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Although South Africa has high IDV culture of 65%, Dr Math promotes collective culture since it enables students to send queries through mobile social networking service known ‘MXit’, which are answered by students from the Faculty of Engineering, the Built Environment and Information Technology (EBIT) at the University of Pretoria. The Table 1 describes a list of In-country m-learning projects that are based in African countries.

Lessons Learnt Factors that contribute to success of In-country m-learning projects include: i) Partnership: For instance Dr Math project was a Joint venture of MXit, a chat platform company, Nokia, and local textbook publisher, ii) All inclusive collaboration: Dr Math project allowed learners, teachers, and school management to participate in project activities (Isaacs, Vosloo, & West, 2012). m-learning projects launched for specific country can be transferred to other African countries. According to Adedoja, Botha, & Ogunleye (2012), Dr Math Initiative can be transferred to Nigeria as it uses the available technology, where learners are

allowed to access content with any mobile phone that can access Internet. In addition, it requires low initial and running cost, thus it does not require a huge capital layout. This mobile application can also be transferred to East African countries since their variability of cultural dimensions is similar to that of South Africa. In-country m-learning project can be used to enhance learning across the country irrespective of cultural differences. For example, results obtained from Dr Math project indicated that there was improvement of performance in mathematics in schools where it was based (Isaacs et al., 2012). Dr Math project utilizes MiXit platform and institutionalized community service, which are not used in universities of other African countries. These are some of the challenges that hinder scalability of In-country m-learning projects to other countries (Adedoja et al., 2012).

Category 2: Regional M-Learning Projects Regional m-learning projects category comprises projects with users from different cultures cross several adjacent countries within a continent. For

Table 1. Analysis of in-country m-learning projects in Africa M-Learning Projects

Learner Profile

Focus Area

Dr Math (2007)

Secondary students

Maths

M4Girls (2008)

Technical, high school & college

Maths

ICT bites-2009

Secondary teachers

Mprep -2011, Elim.org 2013

Country

Cultures PDI

IDV

UAI

MAS

LTO

South Africa

49

65

49

63

-

Education

Tanzania

64

27

52

41

25

Primary

All areas

Kenya

M-Research Supervision Initiative-2005

University students

Research

Uganda

UI Initiative

University Students

Science& arts

Nigeria

77

20

54

46

16

Nigeria teachers Project

Primary school teachers

All

(culture dimensions source: Hofstede, 2010)

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example Africa is made up several regions such as East Africa, West Africa and North Africa. The majority of Regional m-learning projects are concentrated in 3 East African Countries (i.e. Kenya, Tanzania and Uganda). Examples include Agakhan and Amref m-learning Projects. According to Onguko (2010), between August and December 2008, Aga Khan University initiated an m-learning project for supporting delivery of certificate course known as Certificate in Education: Educational Leadership and Management (CE:ELM), which targeted primary school teachers in Kisumu and Mombasa, Kenya and Mvomero district of Tanzania. The project encourages collective culture by enabling collaboration through phones between students and instructors. This collaboration reduces time wasted during visits to schools and mitigating cost on the course without lowering quality of learning. The initiative was necessitated by the fact that target students came from both urban and rural settings, where there is no or limited exposure and access to computers thus lacking Internet access and the required basic computing skills. The communication structure was consistent with low power distance index (PDI) culture since there was less power gap between the learners and trainers. Learners were organized into clusters for peer support through SMS conversations such that, text Messages could be sent by learners from the course site or from trainers located either in Dar-es-Salaam or Nairobi. The instructors were expected to provide feedback in one week’s time through SMS while learners were informed of the

need to contact their supporting trainers through SMS at least every fortnight. These messages were then received at a central message centre in Dar-es-Salaam University for storage on the Nokia Blogs software and redirected to the concerned learner or trainer. The project encouraged low uncertainty avoidance culture (UAI) since there were no specific rules to govern content of text messages. Content could be reminders, comments, updates, instructions, enquiries, feedback on progress, issues arising from cluster meetings and soon. Other courses have since been conducted through m-learning support across East Africa including at Mombasa in Kenya and Turiani in Tanzania, thus maintaining long term orientation (LTO) culture, which is relatively low in East African countries. Table 2 shows a list of Regional m-learning projects that target users across all cultures in East Africa countries.

Lessons Learnt Aga Khan University m-learning project has led to acknowledgement of the need to utilize locally available technologies such as mobile phones in delivery of learning programs by the universities. Though at infancy stage, m-learning learning initiatives in Africa, are now being introduced to mainstream education by universities in both health and education programs. This is an important pointer to potential institutionalization

Table 2. Analysis of regional m-learning projects in East Africa M-Learning Projects

Target Profile

Thematic Areas

Aga khan

Primary Teachers

All

Amref

Nurses Midwives

Medical

Region

East Africa

Culture Dimensions Index Values PDI

IDV

UAI

MAS

LTO

64

27

52

41

25

* Key: ‘East Africa’ = Ethiopia, Kenya, Tanzania, Zambia (culture dimensions source: Hofstede, 2010)

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of mobile learning in higher learning institutions (Onguko, 2010) Factors that contribute to success of implementing regional m-learning projects include Understanding fundamentals, formulating implementation strategy, supporting innovation Identifying champions communicating and celebrating success (ibid). Challenges for implementing this category of m-learning project include technical limitations such as posting messages onto E-learning platform for supporting discussion forum (ibid).

Category 3: Continental M-Learning Projects Learners from different cultures adopt Continental m-learning projects across a certain continent. Yoza is a good example of continental m-learning project, which is adopted in South Africa and Kenya. Yoza (previously known as M4lit) was initiated after an observation that South Africa was a ‘bookpoor’ country with only 7% of public schools that had functional libraries and 51% of South African households had no leisure books. The project was launched during the year 2010, following a successful pilot phase of m4Lit that was conducted from August 2009 to January 2010 with an aim of promoting reading and writing among youths in Africa. The initiative is now accessible across African continent through mobisite and on MXit in South Africa and Kenya.

This project is characterized by low uncertainty avoidance culture (UAI), since it does not require formulation of rules to guide learning activities. For example, library content can be m-novels, classic literature, short stories or locally written poetry. The project also demonstrates the possibilities for promoting a reading and writing culture among youth through informal unconventional forms and linguistic styles. Since its inception, Uptake of Yoza Cellphone stories have been growing such that it had produced almost 50 mobile-based novels (m-novels), poems and plays by the end of year 2012 (Isaacs et al., 2012). Looking at Table 3, Yoza is adopted in countries with low UAI cultures of 49% and 52% in South Africa and Kenya respectively.

Lessons Learnt Social networking sites offer an opportunity for scaling m-learning projects to be adopted across countries. For instance, Yoza is now available across African continent through mobisite and accessible via MXit in Kenya and South Africa (Isaacs, 2012). Mobile phones provide a platform for content distribution to readers and enable immediate response from them. This promotes collectivism culture among participants through mobile platform. Adoption of certainty avoidance (UAI) culture in distributing learning content increases the uptake of m-learning projects in a multi cultural context such as African continent. Yoza is an

Table 3. Analysis continental m-learning projects in targeting users across cultures in Africa Ml Project Yoza

Target Profile Young People 14-25yr

Thematic

Literature Stories


106

Continent

Africa

Countries


IDV

UAI

MAS

LTO

Kenya

64

27

52

41

25

South Africa

49

65

49

63

-


example m-learning projects that have thrived across Africa through informal unconventional forms of learning.

debating environment issues or collaboration among students and leading experts from different countries through sending text, images or making phone calls. The project demonstrates low uncertainty avoidance (UAI) by applying a wide variety of strategies and technologies thus proving very costly to implement in a developing or poor countries unless heavily technologically and financially supported (SAIDE, 2008). Table 4 shows a list of Global m-learning projects launched in African countries.

Category 4: Global M-Learning Projects This category comprises of m-learning projects that target users across the world. Dunia Moja is a case of global m-learning projects, which utilizes mobile phones to support learning across all cultures. The project is implemented in Tanzania and Uganda, where there is high power distance, low Individualism and low masculinity culture as well as in USA, where there is low power distance, high individualism and high masculinity culture. The project target is to support learning in both undergraduate and post‐graduate programmes offered at three Universities in Africa, in collaboration with Stanford University-USA. Videos and audio presentations are loaded to smart phones donated by Sony Ericsson to allow watching or listening of audio content at any time and any location. Students can also access learning content on a CD or moblog, which is an online interface that sends postings to mobile phones Dunia Moja project adopts high collectivism culture that allow usage of mobile phones for

Lessons Learnt Global m-learning projects can be used to implement consortia model of distance learning education, where learners consult experts from partner universities situated in different cultural background. This model can also allow learners and faculty from several universities to engage in joint research projects. For instance, Dunia Moja project allowed students to interact with environmental science experts from more other partner universities. The project demonstrates mobile phones’ potential to support collaboration across the globe irrespective of cultural differences.

Table 4. Analysis global m-learning projects targeting users in more than one continent M-learning Project

Learners Profile

Thematic Area

Country


IDV

UAI

MAS

LTO

BridgeIT (2003)

Primary Schools

Maths Science

Philippines

94

32

44

64

19

Tanzania

64

27

52

41

25

MoMath (4k by 2010)

Sec. Schools

Maths

Finland

33

63

59

26

-

Tanzania

64

27

52

41

25

South Africa

49

65

49

63

-

Tanzania Uganda

64

27

52

41

25

USA

40

91

46

62

29

South Africa

49

65

49

63

-

Dunia Moja

Varsity Students

Environmental issues


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CROSS-CATEGORY ANALYSIS Influences of Cross Cultural M-Learning Applications in African Countries M-learning projects have influenced several changes among cultures where such projects are implemented. Some of these influences include the following: Promoting intercultural communications: Implementation of m-learning projects in multicultural context allows intercultural communication among participants (Tibuktu, 2013). For instance, Yoza and Dr Math projects allowed participants from different cultures to interact through sending text messages, making phone calls and accessing social media platforms such as ‘Mixit’. Redesigning instruction methods and resources: According to Olaniran (2009),cultural differences calls for content providers to design learning materials for cross cultural learners rather than designing for a particular culture in order to ensure learners don’t feel like they are lost at anytime. Aga khan project led to redesigning of the course to allow collaboration without face-toface contact via mobile phones between learners and facilitators. This increased access by students and reduced travel for facilitators. Cultural harmonization: This involves standardizing different cultures by removing all or some of the unwanted cultural differences to reduce variations in cultural dimensions across geographical regions(Jaikumar L & Sahay, 2012). Yoza project, which is adopted in South Africa and Kenya, promotes culture harmonization by enabling reading and writing of stories, poems and plays among youths from more than one countries (Isaacs et al., 2012). Promoting Power Distance culture (PDI): M-learning promotes PDI by enabling learners to receive instructions from their teachers per-

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ceived to be in superior positions in comparison to learner positions. BridgeIT project was started in Tanzania during the year 2007, encouraged high power distance (PDI) by allowing teachers to download video content using mobile phones linked to Televisions. Students were then taught by listening to teachers who made references to content displayed on TVs. This created an impression of teachers being in superior position of connecting their phones to TVs and students in a lower position of listening to instruction from teachers, thus fostering high power distance culture (Enge, 2011). Fostering collectivism culture: M-learning projects encouraging collectivism culture by allowing learners to collaborate among themselves. Examples include: i) Dunia moja Project, which allowed students to collaborate with other students and/or leading experts by sending images, text or making phone calls (SAIDE, 2008), and ii) Aga khan Project, where students were organized into clusters to enable peer collaboration through SMS conversations (Onguko, 2010).

FUTURE RESEARCH DIRECTIONS The chapter was limited to classification of Mlearning projects launched in African countries. Further research should be undertaken to establish appropriate criteria for classifying multicultural M-learning projects launched outside African countries. This is particularly important because of differences in availability of mobile devices and computers between Africa and other parts of the world. The next step for our research will involve establishing appropriate framework for adopting multicultural M-learning projects in each of the identified categories. The framework will then be evaluated through development of a prototype and conducting experiments in multicultural contexts


CONCLUSION This chapter presented an overview of digital context in African countries, which indicated that there is there is high prevalence of mobile phones but no prevalence of computers in African universities. Although this trend has contributed to growth of M-learning projects in this region, their number is still limited (Isaacs, 2012). Literature reviewed indicated that, there has been attempts to contextualize online learning from intercultural perspectives but most of these attempts fails to consider multicultural contexts (Thatcher, 2012). The chapter therefore focused on M-learning as branch of online learning that makes use of mobile devices to support learning across cultural variability dimensions within multicultural contexts and aimed at achieving three main objectives, which were all achieved. First objective was to describe dimensions of cultural variability dimensions that exist in African countries. Dimensions of culture variability identified include: 1. 2. 3. 4. 5.

Power Distance (PDI) Individualism (IDV) Masculinity (MAS) Uncertainty Avoidance (UAI) Long-Term Orientation (LTO) (Hofstede, 2010); (Hofstede, 2001); Hofstede,1980).

Second objective was to establish a classification framework that integrates and provides a theoretical framework for integrating emerging cross-cultural m-learning projects launched in African countries. In this regard, classifications described include: Blended Classifications, Pedagogical Classifications, Contextual Classifications, Application-Based Classification and usability-based applications (Deegan & Rothwell, 2010). These classifications were however not ideal for achieving our primary objective of

understanding different categories of m-learning applications for multi-cultural context such as African countries. In an attempt to address this gap, a new framework was therefore proposed, which extended reviewed contextual classifications by identifying categories of multicultural m-learning projects based on physical context dimension suggested by Frohberg & Schenk (2008). Each of these categories was described using cases of m-learning projects launched in African countries. They include: 1. 2. 3. 4.

In-Country m-learning projects. Regional m-learning projects. Continental m-learning projects. Global applications m-learning projects.

The proposed classification considered mlearning projects that utilize mobile phones to support learning and targeting students enrolled in formal education institutions such as primary schools, high schools, colleges and universities. Finally, third objective was to identify influences of cross-cultural m-learning projects launched in African countries. Influences identified include: Promoting intercultural communications, redesigning of instruction methods and resources for cultural contexts, harmonization of culture, fostering collectivism and power distance cultures.

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KEY TERMS AND DEFINITIONS Computer Poor Context: An environment with low prevalence of computers. Continental M-Learning Projects: Projects adopted by users from different cultures within one continent. Dimension of Cultural Variability: Cultural elements that distinguish cultural differences among societies (Hofstede, 2010); (Hofstede, 2001); Hofstede,1980).. Global M-Learning Projects: Projects are adopted by users from different cultures across the world In-Country M-Learning Projects: Projects adopted by users from different cultures within a country. M-Learning: A process of learning across multiple contexts among people and personal interactive technologies with a focus on contexts (Viberg & Grönlund, 2012). M-Learning Projects: Mobile learning initiatives that utilize mobile devices to support learning among learners on the move. Mobile Devices: Personalized device that is wireless, tiny, handheld and portable (Muyinda, Lynch, & van der Weide, 2010). Mobile Rich Context: An environment with high prevalence of mobile devices Regional M-Learning Projects: Projects targeting users from different cultures within a region of more than one country, which are neighbours.

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