M-learning in agriculture: possibilities and barriers J.P. Hansen and N. Fog Hansen Danish Agricultural Advisory Service, Udkaersvej 15, 8200 Aarhus, Denmark; [email protected] Abstract To work in agriculture means to work out of the reach of a traditional computer. This, along with the fact that farmers typically have an activity based learning style, indicates that there is a potential in introducing mobile learning. The above was the background for a project running in 2007-2008 where we investigated the potential for the use of m-learning in agriculture. In the project, different learning objects using text, pictures, video, audio, test, quizzes and simple games were developed. By using authoring software, it was an uncomplicated task to produce and administrate the learning objects. Primarily mobile phones, but also MP3 players and internet radios were tested as devices for delivering learning objects to the user. Insurmountable barriers were found in bringing learning objects into the reach of the farmer. The barriers consist of demands for downloading, installing, synchronising or similar technical manoeuvres. Given these barriers – that eventually will be overcome by technological development – no testing in practice was carried out. Keywords: learning styles, mobile learning, podcast Background New knowledge is produced at an ever increasing pace, while at the same time the number of Danish farmers participating in ordinary courses and seminars has shown a steady decline. To some extent, the farmers get their information over the internet instead, however, working in agriculture means working out of the reach of a traditional computer. This background, and the fact that farmers typically have an activity based learning style, indicates that there is a potential for the introduction of mobile learning. That was the background for a project running in 2007-2008, supported by The Ministry of Science, Technology and Innovation, in which we investigated the potential for the use of m-learning in agriculture. Before starting the project, we ran a survey that among other things told us that: • 98.5% of farmers use a mobile phone; • 96% read and 73% write SMS messages; • 73% would like to be able to get a local weather forecast on their mobile phone – 2% do this on a regular basis; • 63% expressed interest in receiving news; • 55% expressed interest in receiving market information; • 17% have a PDA but one out of three of these are not used because of problems with usability and lack of sturdiness. The project’s goal was to develop a number of digital based prototypes, supporting m-learning in the workplace with farmers and farm employees as the target group. Focus was on utilizing the mobile phone as a technical platform, as the mobile phone, popularly speaking, is the most important tool for the modern farmer.

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Furthermore, the project should give the Danish Agricultural Advisory Service hands-on experience with developing and distributing information for mobile platforms and also integrating this information with existing web based platforms. M-learning O’Connell and John Smith (2007) defined the term ‘m-learning’ as referring specifically to learning that is facilitated and enhanced by the use of digital mobile devices, which can be carried and used anywhere and anytime such as mobile phones, PDAs and MP3 players. Generally, this is a valid definition. This definition, however, misses the main strength of m-learning: It is not about learning as learning is traditionally understood, but about supporting performance. The strength of m-learning is that it has the potential for delivering information at the right time. Learning is a fundamental cognitive process of mental and social change over an entire lifetime. M-learning technology can enhance motivation, which is a vital aspect of learning, deliver information when needed, and encourage the solving of problems and satisfying curiosity. Most of all, m-learning technologies also offer the possibility to bring learners through an extended process of capturing and organizing situated activities. Learning styles Before engaging in developing m-learning objects, one should consider the learning styles of the target group. Learning styles were developed by Honey and Mumford (1982), based upon the work of Kolb, and they identified four distinct learning styles or preferences: Activist, Theorist; Pragmatist and Reflector: • Activists are those people who learn by doing. Activists need to get their hands dirty, to dive in with both feet first. Have an open-minded approach to learning, involving themselves fully and without bias in new experiences. • Theorists like to understand the theory behind the actions. They need models, concepts and facts in order to engage in the learning process. They prefer to analyse and synthesise, drawing new information into a systematic and logical ‘theory’. • Pragmatists need to be able to see how to put the learning into practice in the real world. Abstract concepts and games are of limited use unless they can see a way to put the ideas into action in their lives. Experimenters, trying out new ideas, theories and techniques to see if they work. • Reflectors learn by observing and thinking about what happened. They may avoid leaping in and prefer to watch from the sidelines. They prefer to stand back and view experiences from a number of different perspectives, collecting data and taking the time to work towards an appropriate conclusion. Farm work is characterised by a large amount of physical activity; you use your whole body doing practical things. People attracted to the farming life will, besides valuing working with the land and animals, prefer action and doing to analysis and theory. This indicates that m-learning should aim at fulfilling the needs of the Activists and the Pragmatists. In support of this, Johnson et al. (2008) using Gregorc’s (2005) Mind Styles™ approach to examine learning styles, found that the learning style of the majority of Maine potato farmers was concrete sequential and random. Learning context As stated earlier, the strength of m-learning is that it has the potential for delivering information at the right time – it is accessible and, as such, can create conditions for situated learning.

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During a situated learning setting, the mental representation of a concept occurs not in an abstract or isolated form, but in connection with the social and material context of a specific learning situation. Technological development will further improve the situated learning conditions. Barcodes or QR Codes enable linking situated learning opportunities with instructional and interactive learning opportunities. Use of RFID, Bluetooth or GPS can be used to initiate a learning session based upon location awareness. Type of content Diving into m-learning, you will soon meet the concept of learning objects. Currently, many definitions of learning objects exist – amongst them this praxis-oriented definition by Rodin (2005) defining learning objects as ‘Discrete elements of learning content that meet a defined learning objective, and are possibly independently assessable, which may take the form of text, graphics, video, stills, animations, diagrams or audio’. In our project, we developed learning objects using text, graphics, video, stills and audio. Here are some examples: Bluetongue FAQ Following a Bluetongue outbreak in 2007, the Danish Cattle Federation decided together with Danish authorities to implement a number of measures including restriction zones and a vaccination campaign including more than 1.5 million animals. These measures involved a lot of personnel working in the field, and to support them and farmers, an m-learning object was produced. It is a simple object, primarily using text and a bit of graphics re-using an existing web-based Bluetongue FAQ. The object holds more than fifty questions/ answers divided into three sections. It offers a simple navigation in the form of a table of contents. The castration of piglets It is difficult for Danish pig producers to get sufficient labour, so more than half of the employees in Danish pig production are foreigners. Many of these are farm students in the beginning of their curriculum, and they need to be instructed – but language difficulties will often be a problem. M-learning comes in handy in such situations. When the farmer gives a task to such an employee, he can at the same time, require that the employee updates his knowledge by using a provided learning object. As an example, a learning object covering the castration of piglets was produced. This object includes a general introduction to the subject followed by a 2 minute video explaining how and why. To check that the employee understands, the video is followed by a multiple choice test with 4-6 choices per question and one or several correct answers. After finishing the test the result is presented and there is an option for submitting the result to a web based administration system. The sow after farrowing With the same general objective as above, a quiz covering how to take care of sows after farrowing, was constructed. In this quiz, the user is presented with the correct answer and an explanation after each question. As a supplement to reading, the user has an option for also hearing the question, which can be an advantage in strong light (sunshine) and it enables the user to start reading the options, while listing to the question.

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Weed recognition As a farmer, if you see weeds in their full grown stage, it is often an indication that you didn’t notice that weed as a seedling and therefore did not choose the right preventive spraying. To train recognition of weed seedlings, a small game was developed. In the upper part of the screen, the user is presented with a picture of some weed in their full grown stage. In the lower part, the user can look through pictures of weed seedlings until he finds the correct match. If he chooses a wrong match, he can try again – if the match is correct, the name of the weed will be shown and his score increased. Listen to agriculture Working on a farm, you will often have opportunities for receiving information through your ears while working, or while on the move. Furthermore, a number of people working in farming are weak readers. So serving information as podcasts is an essential part of mobile learning (Schooley, 2007). A number of podcasts covering subjects such as market information, organic farming, tax legislation and different aspects of plant production were produced. These podcasts, had a duration from one to seven minutes, and they could be accessed through the portal www.landmand.dk or the information database www.landbrugsinfo.dk. Harvesting time for maize On most dairy farms, maize silage constitutes an important part of the fodder ration for dairy cows. Selecting the correct time for harvesting is crucial for obtaining the optimal combination of quality and quantity. This is a yearly decision, which means that most farmers need to brush up on their knowledge of the subject or seek assistance. Practically speaking, the famer has to inspect his maize crops and have a close look and feel on some cobs. An intelligent and location aware learning object could be created. In Denmark, most fields and crops are registered in a central database. During the growing season, weather conditions are monitored and data is fed into models built for the forecasting of the best harvesting time for maize. Given this, it would be possible to develop a learning object, which would only be activated when these conditions were present: The growth model estimates that it is time to inspect the maize. The mobile phone has registered its location as close to the maize field. Given these conditions, the phone could start buzzing in the farmer’s pocket and offer instructions on how to inspect the maize. The production of learning objects With the exception of the podcasts, the contents for the learning objects were a complete re-use of content pulled from web pages, e-learning systems and other sources. Therefore, the primary task was to transform content into suitable learning objects. For this purpose, two different authoring systems were used to gain experience. The systems were Learning Mobile Author 4.3 from HotLava Software and Mylearning Author from Tribal. MyLearning Author is a PC-based, wizard-driven tool that helps create a learning object by combining a series of different activities together, i.e. text, pictures, video, audio, quizzes and simple games. A number of learning objects can be packaged for delivery to handheld devices or the web. MyLearning is easy to use; it has a professional interface and produces professional looking results. The drawback with this tool is that its focus and philosophy is on traditional educational settings and that customisation to non-English is not possible – it was not even possible to use our special Danish letters.

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Learning Mobile Author is a PC-based tool with a simple but effective interface. A template is your starting point, and you can create your own templates. It is possible to use text, pictures, video, Flash, audio, test and quizzes and to communicate results to a central management system. A learning object can be generated for Palm, WAP, Java, PocketPC or the web. HotLava delivered an excellent service including localisation of a web-based administration and distribution site. Compared to MyLearning Author, the philosophy in Learning Mobile Author is more suited for non-formal learning as is the case in farming. No matter which system, the technical production of learning objects was very easy. With content at hand and a clear idea about the objective of the learning object, production time was normally counted in hours and not days. With respect to podcasts, these were produced using an Edirol R-09 recorder, simply using its build in microphone. Recordings were edited and trimmed using Audacity - a free, open source software for recording and editing sounds. Recording settings included interviews, telephone interviews and reading of short articles. Delivery devices Since the mobile phone is the most important tool of the modern farmer, these devices should be the primary platform for delivering learning objects. The results from our survey showed that there is no reason to consider PDA’s as such. There is a wide selection of phones in use and many of the older models (small screens, no colour) are not suitable for m-learning. This is not an important issue – time will quickly solve this. The market is flooded with new models; a mobile phone of a farmer has a short life in a harsh environment and if it takes a new mobile to give him access to something valuable, he will buy it. What matters to the farmer is the phone’s ability to survive in a dirt filled pocket; handle sunshine and to be operated by big dirty fingers. Concerning the latter, the impact of the iPhone pushes development in the right direction and software producers as Spb Software (2009) have developed shells making even Windows Mobile devices user friendly. MP3 players can be an option for farmers, who wish to provide learning objects to employees. Nowadays, even cheap MP3 players are able to deliver text, Flash and video as well as audio. In our project, we used an iRiver Clix model (iRiver, 2009), as this model can easily be controlled even by big dirty fingers – one navigates by pressing the edges of the player. When it comes to audio alone (podcasts), these are several options for utilising familiar devices. Using an FM transmitter together with a mobile phone or MP3 player, a farmer can listen to podcasts through his radio in his car or tractor, or if he is working in the pig barn wearing headphones listening to the radio, he can hear useful information instead of just music. Internet radio is another interesting alternative. Most dairy farmers have a radio installed in their milking parlour so they can listen to music while milking. Why not give them the possibility to listen to agricultural information? It is possible and relatively simple by using internet radio. For the farmer, an internet radio looks like a traditional radio and is operated in a similar way. The only tricky part is to set up ones favourite stations and podcasts. By using an internet radio equipped with a Reciva chipset, a specific radio can be paired with a profile maintained on the Reciva web site (Reciva, 2009). In that way, the radio will have something similar to preset stations – now it is just presets to favourite podcast feeds or an internet based radio station (playing podcasts). For the provider, a broadcasting service can be installed on their servers or internet based services as e.g. Live365.com can be used. Regarding content, the simple approach is just to play the newest podcasts in a loop.

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Discussion As already stated, the strength of m-learning is that it has the potential for delivering information at the right time. This is very suitable for people working in farming, since their learning styles favour praxis and action instead of studying in formal settings. The Danish Agricultural Advisory Service has worked with the possibilities for providing m-learning and has gained these valuable experiences: • Content should not be a problem. If an organisation wishes to provide m-learning, it should, by itself or through cooperation, have a steady production of content (created in advance) for other media. • Content has to be selected and transformed for use in so-called learning objects. Here it is necessary to have a clear understanding of how and in which context, the learning object will be used in practise. • Technically speaking, there are existing authoring tools that can smooth out the process of building and administrating learning objects. • Insurmountable barriers exist in bringing learning objects within reach of the farmer. These barriers consist of demands for downloading, installing, synchronising or similar technical processes. This is not a problem for teenagers or people used to working with ICT devices – farmers, however, do not belong to these groups. These barriers explain why this project did not test the different learning objects in practice. Of course we could have helped the involved farmers along, but it would be useless as long as there is no easy solution for the majority. Solutions will come. In Denmark, even the outermost farm will within the next 18 months be able to connect to the internet using cheap WiMax, and technology will provide us with WiMax enabled devices. Having removed bandwidth as an obstacle, we will see devices, which silently synchronise with central servers. To promote the uptake of m-learning, organisations could consider cooperating with companies selling mobile devices. Where the mobile phone was once marketed as a high-tech device, a tool packed with ingenious features, the trend is now for fashion phones. Why not go a step further and produce personalised farmer phones installed with just these services and applications that the specific farmer find useful. References Gregorc, A. F. (2005). Mind styles. Available at: http://facultyweb.cortland.edu/andersmd/learning/Gregorc. htm. Accessed 27 February 2009. Honey, P. & Mumford, A. (1982) Manual of Learning Styles London: P Honey. IRiver, 2009. iRiver Clix. Available at http://www.iriverinc.com/prod/ultra/index.aspx. Accessed 28 February 2009. Johnson, S. B., Carter H. S., Kaufman, E. K., 2008. Learning styles of farmers and others involved with the Maine potato industry. Journal of Extension, 46 (4). Available at http://www.joe.org/joe/2008august/rb7. php. Accessed 27 February 2009. O’Connell, M., Smith, J., 2007. A guide to working with m-learning standards. A manual for teachers, trainers and developers. Version 1.0. Available at: http://e-standards.flexiblelearning.net.au/docs/m-standardsguide-v1-0.pdf. Accessed 27 February 2009. Reciva, 2009. Reciva internet radio. Available at https://www.reciva.com. Accessed 28 Februry.

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Rodin, L. 2005. E-learning to m-learning: An investigation into the potential for content conversion. In: Attewell, J. and Savill-Smith, C. (eds.), Mobile learning anytime everywhere. A book of papers from MLEARN 2004. Learning and Skills Development Agency, London. pp. 171-175. Schooley, C., 2007. Podcasting: An essential part of mobile learning. Forrester Research. Available at http:// www.forrester.com/rb/download?t=1&&c=nch&o=1988&ft=1. Accessed 27 February. Spb Software, 2009. Spb Mobile Shell. Available at http://www.spbsoftwarehouse.com/pocketpc-software/ mobileshell/. Accessed 28 February 2009.

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