Abstract
Mobile learning (m-learning) environments open a wide range of new and exciting learning opportunities, and envision students who are continually on the move, learn across space and time, and move from topic to topic and in and out of interaction with technology. In this article we present findings from a study of how students manoeuvre and study within an m-learning environment. The students in the study were enthusiastic about the new learning options provided by the mobile technologies, and they reported that the learning environment offered new study opportunities. One major asset was the flexibility of being able to study at any time and any place. The students engaged in learning activities within three learning spaces: attending lectures, on-campus activities and off-campus activities. Each learning space had different features when it came to how the students worked with the course material. Interactions between the participants, how they used the mobile technologies and their perceptions of the student role also differed across the learning spaces. To realize the valuable affordances provided by m-learning environments, educators will need to undertake complex pedagogical reasoning in their planning and teaching and must take into account how students act within various learning spaces.
Keywords
M-learning
Institutions of higher education are always looking for effective teaching methods that place the student at the centre of learning. Bearing this in mind, universities are increasingly exploiting technology in the teaching they provide. The use of technology in higher education is based on the interrelationships amongst at least three areas: technology, theories of learning and issues of educational practice. This interrelatedness implies dynamic relationships where the changes in one area make other areas change. For example, developments in technologies call for the re-conceptualization of learning theories and changes in the designs of educational practices. The challenge for teaching in higher education is to ensure that the learning environment we provide is that which best helps our learners to learn. Recent technology developments have yielded a new generation of computer-based learning environments. These are to a large extent characterized and conditioned by such mobile and portable devices as smartphones, laptops and tablet personal computers with wireless broadband access. Evidently, there is a need for educational approaches to teaching and learning in higher education that take into account this technological development (Laouris and Eteokleous, 2005; Rajasingham, 2011; Rismark et al., 2007; Sølvberg and Rismark, 2009). With developments in mobile technology, an increasing proportion of the learning activities may take place outside the confines of a controlled classroom, and the teacher role may be challenged accordingly. Taking an environmentalist view of education, education is seen as the type of communication where the teacher facilitates student learning (Bruner, 1984; Tharp and Galimore, 1988; Vygotsky, 1978). To facilitate student learning when mobile technology is used for learning purposes, teachers need knowledge of how students manoeuvre and study within these environments. One important concern is to understand how students interact with their surroundings to create learning sites. Such insights may allow teachers to rearrange and redesign educational practices to better address the needs of their students.
To design educational practices we need to clarify what characterizes mobile learning. There are varied, overlapping and still evolving definitions of m-learning. Many see m-learning as a natural evolution of e-learning or as a new stage of distance learning and e-learning (Georgiev et al., 2004; Rajasingham, 2011). Some define mobile learning in the context of devices, as they emphasize the mobility aspects of the devices used. Quinn (2000), for example, defines mobile learning as learning that takes place with the help of mobile devices. On the other hand, Laouris and Eteokleous (2005) suggest taking a broader view that involves a shift of focus from device to human, thus defining mobile learning in the context of the learning environment and learning experiences. Within the m-learning field, such terms as mobile, spontaneous, intimate, situated, connected, informal, realistic situation and collaboration are used to characterize these learning environments (Laouris and Eteokleous, 2005). Mobile learning also envisions learners who are continually on the move and learn across space and time, move from topic to topic and in and out of interaction with technology (Sharples et al., 2005). An environment- and time-independent pedagogy may thus be needed.
Educators find it challenging to implement technology in ways that enhance student learning in m-learning environments (Sølvberg et al., 2009). Students never learn in a vacuum, whatever the learning environment. They interact with fellow students, teachers, learning aids and technologies. Students in m-learning environments make choices as to when they want to access the resources for learning purposes, where they will learn and how they will use the learning materials (Sølvberg et al., 2007). The concepts ‘complexity’ and ‘contingency’ (Luhmann, 2000) may shed light on the challenges of manoeuvring within an m-learning environment. Complexity is a term that has traditions in several sciences, for example organizational theory and the natural sciences, and has also recently been discussed in learning theories (Edwards, 2009; Van Lier, 2000; Larsen-Freeman, 1997; Waldrop, 1992). The term complexity refers to the manifold learning opportunities within a social communication system (Edwards, 2009). Contingency means that ‘something else may well be equally possible’ (Luhmann, 2000). The term describes the choice or choices that need to be made from amongst the abundance of opportunities and possibilities. In their study situation, students need to choose (contingency) from the many opportunities and possibilities (complexity) within a situation.
More knowledge about how students manoeuvre and the choices they make within m-learning environments may be of help to teachers in their efforts to design educational practices in m-learning environments. The purpose of this article is to explore this, and especially to look into new learning sites that arise within an m-learning environment. Insights into how students interact with their learning surroundings may provide a platform for designing an environment- and time-independent pedagogy for m-learning practices.
Research methodology
Fourteen randomly selected students in a sociology course that is part of a Bachelor’s degree programme at the Norwegian University of Science and Technology (NTNU) were selected. The selection procedure involved putting the names of all the 32 attending students into a hat and then drawing 14 names. All 14 students consented to participate in the study.
The course consisted of lectures, reading from a list of literature on the topic areas in the course and two written assignments. The subject matter in the course was ‘digital competence and organizational challenges’. Students were to work on problem analysis related to such areas as: the use of ICT in organizations; new opportunities and challenges for customers and competitors; and new challenges to traditional organizational theory. The students were to analyse problems arising from the interrelationship between technology development and enterprises. The aim of the course was to focus on problem analysis more than memorize facts and details. This is the type of subject where students may draw from a well of equally acknowledged theories when they are to analyse the constantly shifting human realities in question. The lectures were given by professors and invited speakers from outside the university campus and also outside Norway.
In previous semesters, the students could watch the lectures as multimedia presentations delivered on the internet as streaming video. In the present project, we took this concept one step further; the lectures were made available to the students, regardless of time and place, and on any kind of terminal and network available. The scheduled lectures were given in real time and the students could view the lecture on a screen in the classroom. Students had the opportunity to ask questions and interact with the lecturer. All lectures in the course took place in a ‘multimedia enabled’ classroom.
Each lecture was encoded to suit three different bandwidths so that when accessing the lectures on a mobile terminal, the lecture would be available regardless of which bandwidth was accessible (Wi-Fi, 3G, EDGE, GPRS). The mobile recordings were made available through a website, parallel to the course’s own website.
The students had free access to wireless networks within the university campus, within student dorms and in the downtown areas of the city. The city of Trondheim has created a full-scale field laboratory for mobile information services, ‘Wireless Trondheim’ (WT). This laboratory aims to establish a wireless network infrastructure within the city. In August 2006, the network was officially opened, providing mobile information services in parts of the downtown areas for a student population of 30,000, of a total of 160,000 inhabitants in the city. The status in 2011 is that WT’s network covers large parts of the downtown and surrounding areas of the city. The network uses wireless technology, often referred to as ‘Wi-Fi’ or ‘WLAN’, which makes it possible to use portable devices such as laptops, smartphones or tablet personal computers to gain access to the internet anywhere in the area covered.
To ensure that students had the appropriate equipment to act within the m-learning environment, the selected students were equipped with smartphones and laptops that could access the internet, either through wireless networks or other types of network. The students were encouraged to use this equipment for educational purposes over a period of 12 weeks. For research purposes, Hine (2004) claims that the researcher needs first-hand experiences with the technology under study. Bearing this in mind, the researchers used the same equipment as the students during the project period.
Data collection and analysis
Group interviews were used. Students were divided into three groups and interviewed on two occasions. The first interview took place when the students had used the equipment for about four weeks. The second interview took place when the 12-week period came to an end. Group interviews were used because the informants were relatively ‘similar’ and cooperative with each other (Creswell, 1998). Moreover, the communication between students on the use of the equipment was the aspect that would yield the most relevant information.
The interviews were guided by themes developed prior to the interviews. We encouraged the students to provide rich descriptions and examples of how the technology at hand had influenced their study and learning situation. Assumptions as to how topics and suppositions could be presented to the students could thus be verified or rejected continuously. The format of short questions and long answers, a quality criterion of interviews (Kvale and Brinkmann, 2009), was strived for. The interviews were recorded and transcribed.
Two researchers cooperated throughout the data collection processes, analysis and development of the text. During the analysis, the researchers continuously read and coded small extracts of data individually before mutually developing preliminary categories of students’ experiences. The analysis involved the interplay between the researchers, transcribed data material and theory. The researchers functioned as peer de-briefers as they engaged in ‘critical and sustained discussions’ (Rossman and Rallis, 2003) with each other. The categories developed through the analysis naturally emerged from the data material. As such, our research approach was inspired by grounded theory, which involves the generation of innovative theory derived from data collected in an investigation of ‘real-life’ situations relevant to the research problem (Gasson, 2004).
The data analysis revealed three distinct learning spaces in the learning environment, each with unique features that made it possible to explore how students manoeuvred and studied within the m-learning environment: (1) attending lectures, (2) on-campus activities, (3) off-campus activities. Each learning space has different features when it comes to how students work with the course material. Interactions between the participants, how they used the mobile technologies, and their perceptions of the student role also differed across the learning spaces. Even though the three learning spaces cater to learning under different environments, they also provide a variety of frames for discussing issues about how students act within m-learning environments. Thus, the issues discussed within one learning space may also be relevant to other spaces.
Results and discussion
Learning space 1: Attending lectures
Learning space 1 describes the situation where students are assembled in the classroom during video-transmitted lectures. These scheduled lectures took place in real time. The students could view the lecture on a screen in the classroom and had the opportunity to ask questions and interact with the lecturer during the session. During the project period, only five to ten students (out of a total of 32) chose to view the scheduled video-transmitted lectures in the classroom. One student explained his attendance at the scheduled lectures in this way:
There are few people attending lectures now. I myself have maybe been present at 30% of the lectures.
Turney et al. (2009) found that student attendance decreases with increased availability of online courses. Throughout the term the students in our study had a choice of whether to attend the lectures in the classroom or not. They made their choices based on how the announced topic matched their own interests. They also attended the classroom session if they had matters to discuss or questions to ask. As one student put it – ‘I can’t ask questions from home’. On the other hand, there seemed to be little communication during the classroom sessions, both with respect to student-to-student and lecturer-to-student interaction. The students told us that they were reluctant to ask questions because they felt uncomfortable in front of the video cameras and microphones. It seems as though the technologies, as used here, actually added stress to the learning situation. McLoughlin and Luca (2006) found that students can have poor experiences of online learning and communication if there is little direct contact between students and their teachers. In extreme cases, attendance can drop off (Saunders and Klemming, 2003).
In general discussions on effective learning environments, the interrelationship between people and the dialogical activities in which they take part are suggested learning assets (Gergen, 1995; Shotter, 1995; Sølvberg, 2004; Vygotsky, 1978). Research also demonstrates the value of human interaction in technology-rich learning environments. For example, technology can promote learning when students are active participants, interact and obtain feedback (Rismark et. al., 2007; Mason and Weller, 2000; Rochelle et al., 2000; Treleaven, 2003). Thus, in an educational sense, our findings suggest that this learning space involves unused learning potential; the students are gathered together, the lecturer is online and the technology actually allows for activity, interaction and dialogue. There was clearly an educational challenge in how to adjust the use of technology to pedagogical considerations so that the students could really participate and not just listen passively.
Even though there was limited interaction, the students reported that attending the scheduled classes provided ‘a good feeling’. For some students this was a feeling of belonging to a social community that arose from time to time during classroom sessions. For other students, the positive sensation was the opportunity to fully concentrate on the person speaking, without having to take notes. If necessary, they could always go back at a later stage and fill in any missing details by watching the video-recorded lessons. The students described attendance during lectures as closely connected to their perception of being a ‘good student’. Following the scheduled lecture in the assigned room gave the attending students a notion of an overall outline of the subject matter. The students told us that attending lectures gave them a feeling of confidence and a better overview.
In this sense, attending the lectures in real time may have given the attending students a feeling of being ‘a good student’ based on the fact that ‘I was there’:
I get another type of feeling when I’m present during class. But I think that’s a feeling that sticks to the tradition that we have to be at school to learn. But maybe this feeling will fade away in the future.
Although the professor in charge of the course in fact underlined that there was no need for the students always to attend lectures because these were all video-recorded and streamed, the students still had a good feeling when they attended the class setting. It is interesting to link the students’ conception of being ‘a good student’ to a traditional anticipation of the classroom as the officially acknowledged learning space. One phenomenon in the students’ prior educational career is that scheduled classes always were a major feature in a pre-structured school day. Such timetables may still communicate either an open or a hidden expectation of student presence.
Learning space 2: On-campus activities
The m-learning environment opened up a wide range of study possibilities. As mentioned above, few students attended the lectures. This implied that many learning activities were located outside the regular classroom and at other times. The students reported that the learning environments offered new study opportunities. One major asset was the flexibility to study at any time and in any place. Use of technology offers greater flexibility in relation to time, place, pace, entry and exit (Inglis et al., 2002). Several students repeatedly praised the opportunity and the freedom to choose a time convenient for themselves to watch the lectures:
If you don’t feel like getting up at seven a.m. to be at school eight sharp to attend the class, this is much more convenient. You can do it whenever you like and stagger your work time . . . in fact you could watch the lecture while having breakfast.
This is a characteristic trait in distance learning and by no means surprising. It frees learners in the learning group from having to learn at a fixed time, at a fixed place and for a fixed period of time (Keegan, 2005). However, the flexibilities raise some educational dilemmas when it comes to how the learners deal with the complexity in technology-rich learning environments. One general dilemma is about individual freedom and individual responsibility. Several students pointed out the increased need to be a ‘self-regulated learner’ (Zimmerman, 1986, 1989) within this type of learning environment. To be self-regulated learners within these technological environments, the students had to manage their ‘freedom’ in ways that supported their learning responsibilities. For example, they had to structure their own work in terms of deciding where, when and how to work with the subject in general and the different themes in particular.
Another dilemma was related to the social and individual references for learning, in other words, whether students search for learning opportunities in learning spaces that enhance learning as socially anchored and learning as individual effort. The students expressed a wish and need to belong to a social community. At the same time, the students appreciated the opportunity to work individually within the m-learning environment. Balancing the social and individual references for learning was a salient phenomenon among the students. The students were constantly interacting with their surroundings to create impromptu sites for learning. For example, a group of students sometimes gathered in a student office during lectures to create their own private learning space. In the office they viewed a lecture together in real time. The students found it convenient to sit together in the office to view the lecture. During subsequent interviews, the students looked back and provided various arguments for choosing this private learning space:
– I have all my stuff in the office. – I can make a cup of coffee. – I’m more concentrated when I sit in front of my own computer, compared to when I sit in class. I use ear plugs so I only hear the speaker. It’s easier to be involved in the situation in front of my PC as opposed to the classroom situation. When I sit in the office, I only watch the screen. In class there are lots of other distractions.
The students withdrew from the regular classroom and pointed out why they preferred this group arrangement over the classroom situation. Their arguments embraced the flexibility that the private learning space can open up; they chose to watch the lecture together as a group at the same time as their arguments for doing this pointed to individual learning aspects. For one student, having access to his ‘stuff’ was important. This made it possible for him to refer to other learning materials if necessary. For another student, the office environment provided a good learning situation because it offered better concentration. In this way, individual preferences for learning were enhanced within the private learning space, which offered more flexibility in relation to place, pace, entry and exit, as opposed to attending the lectures.
Learning space 3: Off-campus activities
For various reasons, attending the lectures provided a good feeling and also supported the notion of being a good student. Evidently, the private learning space in the student office accommodated a range of individual priorities for what makes an agreeable learning environment. However, technology-based learning activities also took place off campus. It proved to be challenging to embrace the considerable learning opportunities that the mobile-learning-based course makes available outside the classroom setting.
All in all, the students were enthusiastic about the new learning options provided by the mobile technologies. They mentioned the bus and train as possible places for using the mobile devices. However, in fact, the students hardly used the mobile devices during bus or train rides. While this low degree of use is in one way surprising, results from another project, the MOBIlearn project on everyday adult learning, show that only 1% of self-reported learning occurred during transport (Sharples et al., 2005). The low use during transport may indicate that the students did not necessarily associate the designed m-learning opportunities with physical movement. However, the students also maintained that, because of the length of the video sequences, the local bus rides were too short: the video sequences would last longer than the ride. They suggested that the videos were better suited for longer trips and weekend excursions.
When students used the mobile technology off campus, this by and large took place in their home environments. This shows that the students used the wireless network access they all had in their home environments for learning purposes. There was an overall positive attitude to video-streamed lectures, and the students expressed the wish that all courses could be organized in this way. One general impression was, however, that the students did not use the mobile devices to watch an entire lecture. They watched bits and pieces, either for orientation or as a repetition of various themes. More importantly, working off campus was regarded as an activity that demanded extra effort:
We can always catch up at another time, but it requires extra initiative to get started. When you’re attending the lectures, you’re there during the whole session, but if you’re catching up at a later point, you’re also easily interrupted.
When the students used mobile technologies off campus, they not only encountered learning challenges, they also had to find new ways to work within their private sphere with the technology at hand. One learning related challenge was to link ‘bits and pieces’ of the subject matter into an overall understanding of the subject when working off campus. ‘Cut-offs’ may be a suitable concept to describe the student’s off campus work with mobile devices, as fragmented work was a prevailing theme when the students described how they used the mobile technologies outside the university campus. Generally, they used the devices for short periods of time to watch limited sections of video material at the same time as they were engaged in home activities:
I have been watching video-taped lectures on Sunday mornings and then I do the dishes at the same time.
This shows that the home as a learning environment is quite different from the university facilities when it comes to maintaining focus on subject matter. While the home sphere might be a relaxed learning area, it also introduces complexity into the learning situation as regular home activities may easily come into focus. Within this learning space students had to choose the study activity from among a multitude of activities and impulses that were salient within the home environment. This is a well-known challenge for distance-learning students who are confronted with the need to combine study efforts with various family, work and leisure-time activities (Rønning and Grepperud, 2006). In this learning space, the students commuted ‘in and out’ of technology and ‘in and out’ of home-based activities. This left the students with a learning puzzle: which are the more and which are the less salient pieces of the learning material? If we are to help our learners with their learning, it is essential that the study situation allows for interaction with the study material and for expansion of understanding. Thus, when students commute in and out of technology and home-based activities in the off-campus learning space, deep approaches to learning may be a challenge. Based on these findings, teachers may find it helpful to have the characteristics of the complex home situation in mind when planning educational designs in m-learning environments.
Conclusion
We have discussed how students manoeuvred and studied within an m-learning environment and how the students’ study and learning situation was challenged and supported by the technology described. The students took part in learning activities within three learning spaces during the project period: attending lectures, on-campus activities and off-campus activities. Each learning space has different features when it comes to how students worked with the course material. Moreover, interactions between the participants, how they used the mobile technologies and their perceptions of the student role differed across the learning spaces. The students moved between various times and places, moving from topic to topic, and in and out of technology use in ways that enhanced their learning. Based on our findings, it is evident that new technologies call for ‘new geographies of learning’ (Thackara, 2005) that capture the interrelatedness between student learning, times, places, topics and technologies.
Our study of how students act within m-learning environments has limitations. The findings stem from a small sample of university students. New studies with a wider sample might enable the researchers to search for contrary and parallel cases with reference to broader data material. Another limitation is that the students in our study used the mobile devices for a period of 12 weeks only. Studies over a longer period of time would perhaps reveal other findings. By conducting studies over longer time periods it might also be possible to overcome limitations relating to the possible role of novelty effects. The reported findings are based on students’ self-reported experiences through group interviews. Additional data collecting methods, such as the combination of interviews and observations, would make it possible to find corroboration between the different data sources. The students in our study used mobile devices to access video-streamed lectures. Other arrangements may reveal other findings. Future studies of m-learning environments should look into the use of other types of learning material, for example could short videos and quizzes bring additional learning spaces into focus and reveal other ways of acting?
These limitations notwithstanding, the study provides new insights into how students manoeuvre and study within m-learning environments. These findings may be helpful to educators when they plan student learning and establish teaching practices. The students in this study argued that watching the videos together in the student office offered the flexibility to go in and out of technology and to interact with other learning material. If educators consider these insights into ways of acting and working, they should plan educational designs that accommodate these ways of working. For example, with respect to the learning material to be accessed through mobile devices, educators could provide cues for learning by suggesting how students could combine and alternate the displayed content and other learning aids.
The students argued that learning in home environments involved challenges as the regular home activities easily came into focus. Moreover, the students rarely watched the entire lecture while at home. Going in and out of technology afforded the students bits and pieces of knowledge. Although accessing the material designed to help them in their learning seemed to be a challenge, the students valued these off-campus learning opportunities. Going in and out of technology may have provided the students with ‘surface knowledge’ of the learning material. Such surface knowledge may be a learning asset when students read deeper into the subject. Also, educators may turn such surface knowledge into valuable learning assets during subsequent in-class elaborations (Rismark et al., 2007; Sølvberg et al., 2007). Insights into how students manoeuvre and study within the home environment could be useful to educators when they design learning material that is meant to be accessed in home environments. Bearing this in mind, educators need to take into consideration the fact that students go in and out of their interaction with technology and so design learning material that accommodates this.
The findings show that there is reason to believe that m-learning environments provide new and exciting learning opportunities. Our findings indicate that educators should take the features of various learning spaces into account when they plan student learning and establish teaching practices. To realize the valuable affordances provided by m-learning environments educators, as they have always done, will have to undertake complex pedagogical reasoning in their planning and teaching.