Journal Articles

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Author: search.filters.author.Mwendia, Simon N.End date: 2019

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    Ambient learning conceptual framework for bridging digital divide in higher education
    (IGI Global, 2014) Mwendia, Simon N.; Wagacha, Peter W.; Oboko, Robert
    According to ITU (2012), digital divide is the difference between countries in terms of levels of ICT development. This difference remains significant. In 2011, the ICT Development Index (IDI) value of developed countries (6.52) was twice as high as that of developing countries (3.24). The need to link the digital divide for universal broadband Internet access is within the key international development goals, which include World Summit on the Information Society (WSIS) goals and Millennium Development Goals (MDGs). Ambient learning is the next generation of M-learning (Bick, Kummer, Pawlowski, & Veith, 2007), which allows flexible content access by considering learner's current situation and learning context (Kofod-Petersen, et al., 2008). However, ambient learning has not yet attained a state of common understanding (Winker, Scharf, Hahn, & Herczeg, 2011) and is not widely used or adopted (Bick, et al., 2007). This chapter presents a theoretical conceptual framework to foster creativity for innovative ambient learning applications, which can be used to bridge the digital gap between universities in developed and developing countries.
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    Culture aware M-learning classification framework for African countries
    (IGI Global, 2014) Mwendia, Simon N.; Wagacha, Peter W.; Oboko, Robert
    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 universi- ties, 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.
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    Evaluation model for improving ambient learning systems towards achieving sustainable development goal four
    (2018) Mwendia, Simon N.
    Among the 17 sustainable development goals specified by United Nations organization in 2015, goal four is the key for progress towards the achievement of all the other goals. However, studies show that this goal is yet to be achieved among African universities in terms of supervision due to inadequate availability of supervisors to their research students. Ambient learning approach promises to address the problem by allowing access to education services like research supervision at anytime, anywhere and anyhow. Nevertheless, little research has been conducted to assess its effectiveness towards achieving sustainable development goal four. The aim of this paper is to describe a model that illustrates how ambient learning systems can be combined with decision support tools to support evaluation of its effectiveness.
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    Ambient learning - knowledge as a service model: towards the achievement of sustainable development goal four
    (IEEE, 2018) Mwendia, Simon N.; Karanja, Richard G.
    Studies show that United Nations Sustainable Development Goal Four is yet to be achieved. This paper presents an artefact named “Ambient learning- Knowledge as a Service model” for describing how actionable knowledge can be extracted from ambient learning systems to support improvement and consequently facilitate the achievement of Sustainable Development Goal Four. A creative process was adopted to guide the development of the model. The process involved carrying out problem analysis through literature review, designing the model by combining ambient learning and Knowledge as a Service concept and demonstrating its application by developing a prototype. Evaluation results revealed that C4.5 algorithm that is implemented in Waikato Environment for Knowledge Analysis (WEKA) software is suitable for extracting knowledge from ambient learning systems while Swi-prolog software can be applied to create a tool for knowledge delivery.
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    Dynamic heuristics greedy search: a mobile information retrieval algorithm for ambient learning systems
    (ACM Digital Library, 2016) Mwendia, Simon N.; Oboko, Robert; Wagacha, Peter Waiganjo
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    Open mobile ambient learning(OMAL): The next generation of mobile learning for 'mobile-rich' but 'computer-poor' contexts
    (DAAD, 2014) Mwendia, Simon N.; Buchem, Ilona
    By the end of year 2011, Africa had over 620 million mobile connections, overtaking Latin America to become second largest mobile market after Asia. According to Ilona Buchem in 2012, since mobile devices and applications are used every day in order to interact, plan, work, play and orientate, mobile pedagogies in context of HE in Africa should focus more on ambient assisted learning to facilitate greater independence and improve quality of life, which is especially beneficial to learners with special needs (e.g. disabled people and people living in remote locations). African universities face challenges in their attempts to offer quality educations, including the lack of access to university educational facilities and scientific information, poor access to computers, scarce availability of qualified teachers and the irrelevance of formal education to African needs, according to research conducted in 2008 and 2009. This removes flexibility that is needed in personalized learning, according to a 2010 study. This calls for innovative learning approaches that facilitate flexible access of open education resources (OER) in settings with high prevalence of mobile devices (such as mobile phones) but poor prevalence of location dependent devices (such as computers) as it is the case in Africa. Current forms of mobile learning aim at enabling context-sensitive learning, e.g. interacting with learners by considering learner’s current context (e.g. location, activity, social relations), mixed reality learning, for example, enhancing the meaning of learning content by allowing learners to participate in a media-rich environment, as well as ambient learning, for example, delivering learning content at anytime, anywhere and anyhow by placing digital artefacts within the environment of the learner, according to a 2006 report. However, a number of European projects in this area assume availability of adequate infrastructures, such as location dependent devices, which are hard to implement in setting such as African based universities, given the lack of sophisticated technological infrastructures. This presentation focuses on mobile learning as a means for supporting advancement in the quality of education by addressing mobile pedagogies that provide flexible access to learning through consideration of learner’s current context. Based on the Mobile Interface Ambient Learning (MIAL) framework, according to a 2013 report, designed for contexts with high penetration of mobile devices (mobile rich) but low prevalence of location dependent devices (computer poor), we propose Open Mobile Ambient Learning (OMAL) as an approach to enhance adoption of ambient learning by integrating Open Educational Resources (OER) into Personal Learning Environments (PLE), e.g. individual collocations of distributed applications, services and resources, according to a 2011 study, in context of HE in Africa. OMAL targets to benefit university students with special needs (e.g. disabled, elderly) by improving their learning independence and digital marginalization (e.g. own phones but have poor access to computers) through enhancing access flexibility. OMAL combines mechanisms of embedding intelligent interface in mobile devices to monitor special learning needs and contexts (Mobile Ambient Intelligence), with mechanism of appropriating adaptable learning tools and services by learner through mobile devices Adaptable Mobile Personal Learning Environment (AMPLE) and mechanisms of dynamically discovering Personal Learning Networks (PLN) in OER driven environments.
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    3-Category pedagogical framework for context based ambient learning
    (IEEE, 2013) Mwendia, Simon N.; Waiganjo, Peter; Oboko, Robert
    Mobile phones have taken centre stage in transforming people’s lives in all sectors of African economies. With regard to Education sector, studies show that, there is high prevalence of mobile phones among learners in African universities but no computer prevalence. However, E-learning technologies are not readily available among learners. Learners are therefore forced to access content from few fixed locations with internet connectivity such as cyber cafes and workplace, eliminating access flexibility in learning. The ‘Mobile phone rich’ but ‘computer poor’ context prevailing in African universities presents an opportunity to establish an appropriate type of learning that utilizes mobile phones rather than computers. This paper explores existing categories of m-learning projects and proposes a 3-category framework to provide better understanding of ambient learning and allow integration of future ambient learning projects situated in different learning environments.