Understanding Interaction Experience in Mobile Learning Fariza Hanis Abdul Razak Computing Department Lancaster University, Lancaster, LA1 4YR United Kingdom
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Abstract. The convergence of mobile technology and e-learning has generated considerable excitement among both practitioners and academics. Mass media continually promotes novel idea about m-learning. Content developers also continue to deliver learning on wireless, mobile learning devices based on their often abstract conceptions of what the ‘generalised’ learners might want to learn. We are now seeing the adoption of e-learning into m-learning without a clear understanding of motivations and circumstances surrounding m-learning and m-learners. This research looks into interaction experience that is believed to play a significant role in the development of usable m-learning. Keywords. M-learning, e-learning, interaction experience, HCI, mobile environment
1 Mobile Learning Context The workforce has become much more mobile than before: about 50% of all employees now spend up to 50% of their time outside the office. In fact, many full time learners (like those in schools and higher learning education) are also very mobile. There is evidence that people would like to make more use of this “empty time” for learning purposes. M-learning (mobile learning) is designed to fit with the unique work style requirements of the mobile workforce. Mobile workers need to continually enhance their knowledge and skills in order to address immediate problems. This new type of learning is to empower people to manage their own learning in a variety of contexts throughout their lifetimes [1]. M-learning doesn’t replace traditional learning; it just represents another way of learning using a new technology. In fact, the fundamentals of learning still don’t change with m-learning: 1. Learning more effective when active. A course built around actively “doing” will be better than passively reading from the screen. 2. Individual learning styles. Some learners prefer reading, others might prefer observing, doing, or being coached, and the preferred method of learning can change depending on the context.
M. Masoodian et al. (Eds.): APCHI 2004, LNCS 3101, pp. 672-674, 2004. Springer-Verlag Berlin Heidelberg 2004
Understanding Interaction Experience in Mobile Learning
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Learner controls learning. Content should be presented in such way that the learner understands and controls the information flow. The Instructor, whether human or computer, is a learning facilitator.
2 Research Problem Although m-learning is a natural evolution of e-learning, to effectively build and deliver m-learning requires rethinking, reinvestigating, and re-evaluating the humancomputer interaction in the m-learning environment. Existing e-learning frameworks may not work very well with m-learning: the interaction experience in m-learning is different from other types of learning. Learning with mobile devices constitutes a new learning-interaction experience: a lot is still unknown about the m-learning experience. Although some research in m-learning has discussed some aspects of mobile experiences [2], the discussion did not really focus on the understanding of what constitutes interaction experiences in the mobile environment. It is believed that interaction experience can be an important, mediating towards the successs of mlearning.
3 My Research My research is aimed at understanding interaction experience in m-learning by examining a broad range of aspects of m-learners, their environments, and relationships. I hope that this research will serve as a base for development of an m-learning experience framework. This research is broken into two main areas: understanding of interaction experience in the mobile environment and the development of m-learning content. 3.1 Understanding of Interaction Experience in the Mobile Environment To understand the interaction experience in the mobile environment, I am investigating three important components: 1. Understanding of the mobile learners – including their characteristics, psychological (affective and cognitive), and physical capability. 2. Understanding of the m-learning environment – the motivations and circumstances surrounding mobile device use and adoption; and how and why people adopt m-learning. 3. Understanding of the mobile experience – completely different from desktop experience as it has specific characteristics that need to be factored into the design of a mobile application. 3.2 Development of M-learning Content When developing m-learning content, it is important to balance effective learning and adoption of mobile and web technology, which has advantages and limitations.
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Fariza Hanis Abdul Razak
Learning Object Methodology will be applied in this development, because it allows a designer to create learning content in chunks. The chunks allow flexibility in terms of how they can be used together and separately [3]. Other key development issues include: 1. User interface – including task flow, predictability and consistency, and ease of use. 2. Battery life – balance between applications and battery consumption. 3. Modality – different devices support multiple kinds of modalities, each behaving differently. 4. Interruption – how well the application handles interruption and resumes interaction later.
4 Conclusion Understanding interaction experience is not an entirely new area in HCI, but there is no agreed framework that can actually guide designers and developers towards the development of usable m-learning systems. There is considerable work to be accomplished on many fronts – HCI, mobile technology, learning communities, and content development – before the potential of m-learning comes to fruition. Although this research may not provide a perfect solution to the current problem, it can at least offer some promise especially to the HCI and learning communities.
References 1. Bentley, T.: Learning Beyond the Classroom. Education For A Changing World. (1998) 177–193 2. Trevor, J., Hilbert, D. M., Schilit, B. N., Tzu, K. K.: From Desktop to Phonetop: An UI For Web Interaction on Very Small Devices. In ACM UIST (2001) 3. IEEE Learning Object Metadata (2002). See http://ltsc.ieee.org/wg12/
