Mobile learning and student engagement in remote field activities
First Monday

Mobile learning and student engagement in remote field activities by Anthony Ralston, Guillermo Hernandez, Miles Dyck, M. Derek MacKenzie, and Sylvie A. Quideau

This research is centred on an investigation of the potential for the use of mobile learning in remote field study locations by university students. The study focused on both geospatial concepts and abilities, instructional design methodologies and the impact of learning through the use of mobile devices and online learning. The study group included a total of 118 students enrolled in the University of Alberta, in the Department of Renewal Resources. The research methodology included mixed method approach that included the dissemination of online surveys, feedback forms completed during field study, and anecdotal data collected by instructors. A major pedagogical change in the course design resulted in students accessing mobile devices in place of traditional hard-copy maps in order to conduct their field studies.


Discussion and conclusion




This paper sets out to draw connections between mobile learning and interactive design processes through the adaption of transformative learning and self-motivational learning related to the curriculum based in geospatial sciences. The objective of this study was to develop mobile learning tools that will improve the teaching of the spatial context of Alberta land resources using digital contents and maps of soils, hydrology, vegetation, geology and climate via user-friendly versions of off-line and online modes. Students need to experience and associate where and how resources such as soils, water and vegetation fit in the landscape. Traditional modes of teaching (didactic lecturing) and outdated approaches to landscape interpretation using paper maps can be pedagogically inflexible and create a disconnect with the curriculum for contemporary students. This research study was based on the Action Research method through qualitative data collection and analysis (Piliouras, et al., 2015). The design methodology for this research is based on utilizing online surveys to collect data.

The DigiMapping project was conceived and produced to offer flexible learning modalities through a mobile application of digital maps, eLearning modules and a Moodle online course to deliver a curriculum that mirrors the needs of professionals working in the natural sciences sector (de Róiste, 2012). The interactive self-paced eLearning modules comprised of narration, animation and assessment questions. Four modules were produced based on course lecture materials and would normally take a student 20 to 30 minutes to complete. Portables devices were used which enabled interactive educational activities conducted by small student groups in remote field locations. This project affected a combined population of 118 students encompassing several university courses. It has the potential to be extended to many audiences across the university campus in different disciplines as well as beyond the campus. From the perspective of the impact of mobile technologies on education, Goff (2015) reinforces the idea that teaching and learning related to global positioning system (GPS) is best delivered in authentic environments rather than just in a classroom, “Teaching GPS by lecturing is far less effective than teaching GPS by allowing students to use the technology to solve real-life problems in real-life situations” [1]. The capacity of mobile technology to deliver synchronous communication and knowledge-sharing can provide numerous benefits. For example, mobile learning encouraged simultaneous personal development, such as networking and socialization, outside of normal working groups. For the purposes on this study, the emphasis of enquiry was placed on the attitudes and learning experiences of students studying in remote field settings. The learning methodologies (transformative and self-motivational learning) integrated into this study are reflected in the use of mobile devices as well as the online course. Through analysis of the student performance and feedback, the results favour the concept of knowledge construction.

Working professionals in agriculture and natural resources are expected to learn and apply geospatial skills (Charles and Kolvoord, 2016; Petras, et al., 2015). Specifically, they are expected to discern where and how key biophysical features such as soils, hydrology and vegetation fit in the landscape. These contextual abilities also involved interpreting how the spatial relationships interrelate. This knowledge is one of the essential foundations for effective assessment and management of our land resources as well as for devising future developments and preservation of our natural assets depending in part on how they are distributed in the landscape (Armstrong and Bennett, 2005). Although this conceptual knowledge and practical skills are critical for future professionals, engaging our current students in active learning of geospatial context using the traditional approach based on paper maps can be very challenging and inherently limited. Therefore, using digital maps on mobile devices is an exceptional opportunity to enhance the experiential learning of students (Hedley, et al., 2013).

Mobile delivery can be applied in remote fields where students participate in learning activities relevant to gaining hands-on expertise in the spatial context of soils, vegetation and hydrology. This approach to teaching and learning place students at the centre of the learning process as they will operate mobile devices to select, access, query and interpret multiple digital maps while following prescribed educational guides, exercises and evaluation. This project has enabled and engages students to follow their own curiosity and inquiries related to conceptual foundations and abilities for mapping and interpretation of landscape processes. This project involved students recording the correlation of their own field observations with multiple georeferenced spatial data layers. Broadly, mobile learning is an activity that depends on handheld technology to deliver content and allow for interaction between an instructor and learner and between learner and learner. These devices may or may not be connected to the Internet and to a wireless signal for uses related to learning and therefore could be used in an off-line capacity for learning activities. Professionals working in the natural resources sector are expected to discern where and how key biophysical features such as soils, hydrology and vegetation fit in the landscape (Rip, et al., 2014; Estaville, 2010). This set of industry competencies relates directly to the pedagogical and delivery methodologies utilized by formal educational institutions.

Based a review of the literature, it is evident that new skills in the field of geospatial technology, global positioning systems (GPS), and geographic information systems (GIS) are required by the labour market can be seen as having an impact on education and student learning. In this field, studies have identified that these related location-based technologies (GIS and GPS) have a positive impact on critical thinking skills, data analysis and locating geographical data (Gerwin, 2004; Hofer, et al., 2014), thus creating new geospatial literacies. Geospatial studies, when combined with mobile learning, can be seen to have applications in the field sciences and therefore provide a student with data analysis directly in remote locations, rather than having to review data in a lab (MaKinster, et al., 2014).

Through mobile devices and applications dedicated to geospatial sciences, the learning environment in field study can be based on active learning, collaborative learning and provide opportunities for students to engage in more complex tasks that mirror those required by employers (Kerski, 2015). From a student and learning perspective, the inclusion of geospatial technology in subjects such as forestry, soil science and agriculture provide skills and competencies that improve their prospects for employment (Price, et al., 2014; Müller, et al., 2013).

In rangeland monitoring it has been noted that: “The second innovation in rangeland monitoring is associated with the vastly increased accessibility, ease of use, and quality of geospatial data and technologies. This allows land managers to leverage field data with geospatial information, improve landowner’s understanding of landscape variability, and take advantage of the increasing amount of knowledge and information available through state-and transition models” [2]. One way in which this learning model can be improved is by adopting the constructivist model in which learning is student-centred and teachers act as expert guides. Global Information Systems (GIS) allow us to visualize, analyze and interpret spatial data and are a ubiquitous tool in geography [3].

Geospatial concepts and abilities are essential to design the management and conservation of natural resources. Universities are expected to educate and build these mapping foundations in new professionals. Students need to experience and associate where and how resources such as soils, water and vegetation fit in the landscape. However, existing approaches to landscape interpretation using paper maps could be considered pedagogically inflexible and disengaging for contemporary students (Petras, et al., 2015; de Róiste, 2012). The use of portable devices used in this project enabled interactive educational activities conducted by small student groups in remote field locations, thus changing the teaching and learning pedagogical approach. The use of mobile devices installed with applications to enhance learning related to geospatial topic areas will:

  • Enable portable off-line learning activities, thus overcoming limitations noted earlier
  • Include necessary curriculum guides, exercises and evaluations in digital content for students to engage in true mobile learning

The research questions were developed based on curricular activities, brainstorming, peer-review and the development of a planning matrix to aid in the final development of questions for this research:

  1. What are the perceptions of students using mobile devices in remote field education?
  2. What direct and indirect evidence is there to show that learning has occurred?
  3. How does transformational and self-motivational learning enhance student learning?
  4. How does the introduction of mobile technology in university courses affect attitudes toward mobile technology and the use of mobile technology in learning?
  5. How does the introduction of mobile technology affect student learning achievements as measured by various tests?




Data was extracted from a learning management system (LMS) which produced reports based on usage of the system. Questionnaires were provided to 33 students on online material. A pre-test was administered at the start of the course and comprised of 15 questions related to key points in the curriculum taught in course modules. A post-test was administered at the end of the course and reflected the same questions as posed in the pre-test. The students had access to the four eLearning modules though the online course.

This research study was a mixed methods design, whereby the approach for collecting data utilizes both quantitative and qualitative data to, therefore, provide the best understanding of the research problem (Creswell, 2003). Data represents both qualitative and quantitative analysis of information gathered from the beginning of the course, field study, post-field, and final examination. The results from the pre-and post-testing in the course were based on two classes totalling 118 students. The pre-course and post-course results represent an average of scores by the students. Notably, the post-course questions were based on four eLearning modules whereby links to the modules were available through the LMS for students to access. Students could access eLearning modules through a personal computer or mobile device, or they could access the LMS site through any mobile device or personal computer.

Data which was based on an anonymous online questionnaire that related to the use of mobile devices and knowledge gained through field study work. Online surveys were available through an online learning management system and students could access surveys two weeks before field study activity, during field study, and two weeks prior to field study completion. Students could complete online surveys by using any Internet browser on any computing device. Course instructors informed the students as to the nature of the study and direct them to the learning management system course to fill out a digital online consent form and the survey should they want to participate in the research.

The participants in this study included students enrolled at the University of Alberta in the Faculty of Agriculture, Life, and Environmental Science and its Department of Renewable Resources. Two courses formed the source of the data, REN R 441 — Soil and Landscape (33 students) and the REN R 299 — Field School course (85 students). In this study, the focus was centred on student coursework in soil sciences and specifically, geospatial soils, vegetation and geological associations; field examination and computer-assisted learning of soils and their landscape relationships; kinds and distribution of soils in Canada; and soil classification. For the purposes of this research study, one course in the Department of Renewable Resources was selected to gather data pertinent to research into mobile learning. Specifically, the participants represented 118 undergraduate students who were divided into 21 subgroups (working as teams). All the subgroups had the opportunity to try and test the Digimapping mobile learning tools in the required field study aspect of the course. Of the 21 subgroups in the course, 18 subgroups completed the test and associated questionnaire. The questionnaire was an option for students and therefore not a requirement in the course. Results shown below are based on the subgroups that took the test and answered the questionnaire.

For the purposes of this study, a combination of online surveys and in-person interviews were administered to gather a mix of qualitative and quantitative information. Qualitative information was collected in online surveys and in-person interviews. In this research project, thematic content analysis was utilized. This method is founded on grounded theory and can be also be utilized in qualitative work, including ethnography and phenomenology. The process of thematic content analysis involves the analysis of transcripts and identifying themes and categories. This open coding process involves a repetitive process whereby themes based on interview transcripts are reviewed to identify further themes and categories (Burnard, et al., 2008).

Students worked together in small groups; mobile devices were necessary to work simultaneously on field trips. In addition, each course involved teaching assistants who were managing and facilitating mobile learning elements of the curriculum for students. Students in these courses had the option to create their own small teams by affinity or in some cases instructors in these courses created teams. These teams consisted of three to five people and none of the students refrained from participating in using portable digital devices to learn about natural resources management. All student teams provided formal written feedback about their experiences when conducting their laboratory activities. All questionnaires were available through a secured online management system only accessible to the course professor and enrolled students. Research questions were made available to students through the online learning system inclusive of the research description and consent form. Students could access research questions through a questionnaire tool which was set for anonymous submissions and identification. In phase one of this project, no control student groups (students not using mobile devices) were included in the field study, due to a lack of resources. However, in future project development and research there will be both a control student group as well as student groups supplied with mobile devices.




Qualitative evaluation of the behaviour and actions of participants in this study revealed insights and an understanding of field mobile learning. The figures and tables included in this section reflect data extracted from a Learning Management System (LMS), producing reports based on usage of the system. For the purposes of this study, students were given the option to take part in the study by submitting responses to online questionnaires, designed to measure behaviour and learning during the course. The set of figures below illustrate attitudes and behaviours of students with respect to learning on mobile devices. The system recorded responses to questionnaires by 33 students to online questionnaire material.

The results show an increase in knowledge related to the topics from the curriculum that were integrated into two tests (Figure 1). The topics covered for the tests were taught through lecture and available as review modules to students during the semester in order to prepare for the second test.


Pre-test and post-test (RENR 441)
Figure 1: Pre-test and post-test (RENR 441).


Based on 33 averaged responses taken from the RENR 441 — Soil and Landscape course, the questionnaire suggests possible uses of mobile devices for students. The results indicate a willingness and interest in mobile technology on the part of students. When compared to results of a questionnaire at the end of the course, it is clear that student willingness and use of mobile devices increased over time (Table 1).


Table 1: Pre-field study questions — Behaviour/attitudes (based on 33 averaged responses and a Likert scale from 1 to 5 in RENR 441).
Mobile device usage 
To use mobile devices for learning purposes would save me a lot of time.Strongly disagree 1 — 2 — 3 — 4 — 5 Strongly agree
I am comfortable using mobile devices and their functions.Strongly disagree 1 — 2 — 3 — 4 — 5 Strongly agree
I would be more encouraged to learn if I could access materials anytime, anywhere via mobile devices.Strongly disagree 1 — 2 — 3 — 4 — 5 Strongly agree
I would like to be able to interact with instructors and classmates via mobile devices.Strongly disagree 1 — 2 — 3 — 4 — 5 Strongly agree
I would feel more interested in taking a course if I could use mobile devices.Strongly disagree 1 — 2 — 3 — 4 — 5 Strongly agree
Allowing me to study anytime, anyplace using mobile devices would be a benefit.Strongly disagree 1 — 2 — 3 — 4 — 5 Strongly agree


When evaluating proficiency in the use of digital maps in the field from the RENR 299 — Field School course, results for correct completion of mapping activities yielded an overall average of 93 percent, ranging from 72 percent to 100 percent (Table 2); moreover, when relating this high performance while using digital maps with favourable feedback by students about DigiMapping (Table 3), this collective evidence becomes a strong argument for the continued use and expansion of mobile learning in this specific context.


Table 2: Field study Part A: Digital maps and mobile devices (RENR 299).
Part A: Using digital maps on mobile devicesCompletion
 Overall ability to use digital maps = 93% proficiency
Briefly comment on: how different or similar is the vegetation you see in your field plot versus the “ABMI Landcover” digital map on the device?100% completion
Compare the parent material(s) (PM) found in your soil pit versus the “Surficial Geology” map?100% completion
Does the “Saturated Soil” map agree in any way with your observations of water seepage, soil mottling or drainage class in your soil pit description?72% completion
Which is the closest (or one of the closest) wetland type to your site location within the “Wetland (North)” digital map on the device?94% completion
What is the approx. distance from your location to this closest wetland?100% completion


These results were taken from the same student groups in the RENR 299 — Field School course, questions related to digital maps and the mobile devices were posed (Table 3). Recommendations made for an improvement of DigiMapping teaching tools can be further explored and applied in the near future.


Table 3: Post-field study part B: Teaching and learning experiences (RENR 299).
Feedback on teaching and learning 
Part B: Teaching and learning experience 
In your opinion, how could the digital maps, software or devices be improved? (adding other maps, excluding some of the maps, changing colors, when switching layers, accessing legends, map visibility, the processing speed of the software & device, GPS signal.
  • A tutorial or demonstration would be useful
  • Format of layers: sort layers alphabetically, reordering the layers, a way to clear and search layers quickly
  • Format of legends: easier legend, more legend information, less confusing coding
  • Labelling main layer menu
  • Ability for adding notes or observations to the maps
  • terrain, elevation, more detail vegetation layer, aerial photo, wildlife habitat
  • Improve GPS signal response
What features were you able to learn about the landscape around you when using the digital maps? (include something that you would not have learned without having the digital maps).
  • Learn about surrounding ecosystems (nine times)
  • Distance to specific features (four times)
  • Learn about geology of the area (three times)
  • Learn about topography and hydrology (three times)
  • Location of pipelines and cut lines in the area
  • Provides a starting point
Was the initial explanation by the TA or instructor enough to start using the digital maps?The answer was “Yes” 89% of the time. The rest of the participants indicated they needed to start using it to be able to feel comfortable with the DigiMapping tool. There were no clear associations between these responses and final ability to access and use the data layers or with comments about the overall learning experience.
What works well when using the digital maps?
  • Switching layers
  • Measuring distance
  • Measuring distance took some time
  • GPS took time to respond
  • Overlapping of layers make it busy
  • Finding locations worked well
  • People with field experience find it easier to use
How was the overall learning experience when using the digital maps on portable devices?
  • Really enjoy using it, explain the general area
  • would use it again
  • A very well thought idea
  • Intuitive, simple, fast, access to critical information
  • Easy, convenient
  • Handy to use it from the beginning
  • Good as supplement, very easy
  • Intuitive, quick respond, provide information, but device can be damaged


Focusing further on the results from the RENR 441 — Soil and Landscape course recorded by LMS for the use of mobile devices, type of content and effectiveness of the curriculum content, we see an overall positive percentage of responses with on the impact mobile learning, including (Figure 2), knowledge attainment (Figure 5) and use of mobile learning content (Figure 3). Moreover, aspects of both transformative learning and self-motivational learning were depicted in these responses. Results have been rounded for simplicity. Students felt that mobile learning could contribute to other university courses (Figure 2), therefore one can deduct from the responses (Strongly agree — Level 5: 18 percent; Agree — Level 4 percent; Agree — Level 3 percent) that students felt that content included in eLearning modules would benefit other courses (Figure 2). This feedback encourages future development of cross-functional curricula by expanding mobile learning.

Our study also revealed student perceptions related to transformative learning (Figures 7 and 8) as students felt that there was an appropriate amount of content from which they gained new knowledge, through mobile learning. Results have been rounded for simplicity. The combined ratings on the scale of 3, 4, and 5 equaling 97 percent and Figure 8 results equaling 96 percent, therefore the value of curriculum content and knowledge attainment was supported (Figure 7). In practical application of knowledge following the course was identified by 14 of 33 respondents on the rating scale of 4 out of 5 (Figure 9).

The level of difficulty of content in the eLearning modules was perceived as appropriate by 42 percent of total respondents (Figure 6). To effectively measure transformational learning the degree of difficulty of the curriculum content should match outcomes required in the course and therefore provide opportunities for knowledge growth by students (Christopher, et al., 2001).

The self-motivational learning from the standpoint of students was also monitored and demonstrated in our study through the frequency of accessing the module as students recognized that they have opportunities to access module information for review and study purposes. Indeed, of the 33 student respondents, 23 students were in favor of utilizing mobile devices to review information (Figure 7).


Mobile modules and course study (RENR 441)
Figure 2: Mobile modules and course study (RENR 441).



Course content (RENR 441)
Figure 3: Course content (RENR 441).



Mobile modules and knowledge (RENR 441)
Figure 4: Mobile modules and knowledge (RENR 441).



Practical application (RENR 441)
Figure 5: Practical application (RENR 441).



Level of difficulty (RENR 441)
Figure 6: Level of difficulty (RENR 441).



Review of content (RENR 441)
Figure 7: Review of content (RENR 441).


In a post-course questionnaire, our study captured how students responded to mobile learning devices as part of their learning experience (Table 4). The overall attitude towards mobile technology was positive. The high percentage of responses related to the use and recommendation of mobile learning to other students correlates well with other feedback and results in the post-course phase (Table 4). There was a 95 percent affirmative response for the use of mobile devices by students.


Table 4: Post-course questionnaire (RENR 441).
Post-course results 
Post-course questionnaireResults
Does the use of a mobile device create an attractive learning experience?Yes: 98%
No: 2%
Would enroll in another mobile learning course?Yes: 95%
No: 5%
Would you recommend mobile learning as a mode of study to your fellow students?Yes: 97%
No: 3%
Did you study the mobile training content at home, at the university, or job, or while traveling?At home: 4 %
At university: 95%
Travelling: 1%
Did you study the content in a variety of locations?Yes: 69%
No: 31%
Do you feel that the course objectives were met using mobile learning?No: 21%
Yes: 79%
Was the design of the course materials such that is was easy to navigate through the course and from module to module of the course?No: 12.12%
Yes: 87.88%


Positive responses were also noted in response to questions posed by instructors, looking for information related to student experiences using mobile technology.

  • Does the idea of using mobile devices for learning to appeal to you? How would you describe your experiences with using mobile devices for learning in this course?
  • “Using mobile devices is appealing, I would say that using them has a time and place. I would say that in a lab setting, it works very well.”
  • “Yes. It was another way of learning the specific material in our course. I especially would like to see more quiz material or a self-test.”
  • “Yes, the mobile learning is convenient and a good review tool.”
  • “Yes, I would learn better if all lectures were taught this way (there would be time to write down notes).”
  • “I prefer printed notes but the mobile learning is useful for supplementing the lecture materials.”

The following set of results were based on questions related to the frequency of use of mobile devices by students. This set of questions was meant to gather information related to frequency of use, accessing mobile devices, and eLearning modules. The four separate eLearning modules were designed so that a student could complete each module in 20 to 30 minutes. The results reveal that 81 percent of the students used mobile devices less than one hour per week and less than one day per week (see Figures 8 and 9). In addition, accessing the eLearning reveals that 63 percent of the students accessed the application once and 30 percent accessed it twice (see Figure 10). In a similar result, 60 percent indicated that they only accessed the Collector mapping application once, but 18 percent accessed it more than three times (see Figure 11). Notably, the short length of each of the four eLearning modules could explain the short duration of access by students. Therefore, students could complete eLearning in one attempt. This could signal that subsequent versions of the eLearning modules could be more complex in nature and provide more rigour in learning.


Hours per week (RENR 441)
Figure 8: Hours per week (RENR 441).



Days a week (RENR 441)
Figure 9: Days a week (RENR 441).



eLearning application access (RENR 441)
Figure 10: eLearning application access (RENR 441).



Accessing collector for ArcGIS (RENR 441)
Figure 11: Accessing collector for ArcGIS (RENR 441).




Discussion and conclusion

This study encourages capacity building in the geospatial industry and the use of mobile technology at the intersection of pedagogy and mobile learning, as well as proving the advantages of blending different learning technologies in geospatial science education (Gewin, 2004; Horák, 2015). Although previous studies have used various types of mobile resources and online applications in education related to geospatial science, this study supports a further expansion in education of mobile learning methodologies.

Previous studies supported implementing mobile applications in geospatial education (Marra, et al., 2017; Price, et al., 2014; Charles and Kolvoord, 2016). In contrast to previous traditional approaches teaching geospatial context using paper maps, our study implemented a blend of interactive eLearning modules and geospatial mapping applications in remote field activities, enhancing the educational experience for students (Figure 4 and Table 4). These results suggest greater flexibility in course content, supporting an escalating rise in mobile technology (Müller, et al., 2013).

The beneficial influence of our mobile learning approaches on self-motivational and transformational learning was evident in the study (Figures 2 and 4 and Table 1). Furthermore, student acceptance of mobile technology added a positive element to mobile learning. As existing literature indicates, the flexibility of learning content gained through eLearning and mobile applications affects self-motivation (Roeser and Peck, 2009). Likewise, transformational learning also occurred through interaction with mobile learning materials (Table 4). Both self-motivational and transformational learning had not been widely included in geospatial mobile learning before; therefore, this study advances education effectiveness by broadening the scope of learning methodology and technology (Boyer, et al., 2006; Cranton, 1994).

In addition, through group interactions with mobile devices, collaborative learning for both teachers and students was bolstered (Roschelle, et al., 2005) (Figures 6, 7 and 11 and Tables 2 and 3). The limitations of this study were bound by financial resources, availability of participants, and time necessary to develop specific technologies. End of article


About the authors

Anthony Ralston is an educational design consultant for AR Educational Technology Inc.
E-mail: aredutech [at] shaw [dot] ca

Guillermo Hernandez is an associate professor in Agricultural Life and Environmental Sciences at the University of Alberta.
E-mail: ghernand [at] ualberta [dot] ca

Miles Dyck is an associate chair of the undergraduate program in Agricultural Life and Environmental Sciences at the University of Alberta.
E-mail: mdyck [at] ualberta [dot] ca

M. Derek MacKenzie is an associate professor in Agricultural Life and Environmental Sciences at the University of Alberta.
E-mail: mdm7 [at] ualberta [dot] ca

Sylvie A. Quideau is a professor in Agricultural Life and Environmental Sciences at the University of Alberta.
E-mail: quideau [at] ualberta [dot] ca



1. Goff, 2015, p. 10.

2. Herrick, et al., 2017, p. 46.

3. Peirce, 2016, p. 2.



M.P. Armstrong and D.A. Bennett, 2005. “A manifesto on mobile computing in geographic education,” Professional Geographer, volume 57, number 4, pp. 506–515.
doi:, accessed 26 October 2019.

N. Boyer, P. Maher and S. Kirkman, 2006. “Transformative learning in online settings: The use of self-direction, metacognition, and collaborative learning,” Journal of Transformative Education, volume 4, number 4, pp. 335–361.
doi:, accessed 26 October 2019.

M.T. Charles and R.A. Kolvoord, 2016. “Geospatial semester: Developing students’ 21st century thinking skills with GIS: A three year study,” Pyrex Journal of Educational Research and Reviews, volume 2, number 6, pp. 67–78, and at, accessed 26 October 2019.

S. Christopher, T. Dunnagan, S.F. Duncan and L. Paul, 2001. “Education for self-support: Evaluating outcomes using transformative learning theory,” Family Relations, volume 50, number 2, pp. 134–142.
doi:, accessed 26 October 2019.

P. Cranton, 1994. “Self-directed and transformative instructional development,” >Journal of Higher Education, volume 65, number 6, pp. 726–744.
doi:, accessed 26 October 2019.

M. de Róiste, 2012. “The geospatial skills shortage in New Zealand,” report commissioned by the New Zealand Geospatial Office and SIBA NZ (Spatial Industries Business Association), at, accessed 26 October 2019.

L.E. Estaville, 2010. “Geospatial workforce trends in the United States,” International Journal of Applied Geospatial Research, volume 1, number 1, pp. 57–66.
doi:, accessed 26 October 2019.

V. Gewin, 2004. “Mapping opportunities,” Nature, volume 427, number 6972 (22 January), pp. 376–377.
doi:, accessed 26 October 2019.

D. Goff, 2015. “Benefits and methods of integrating geospatial technology in both educational and professional realms of STEM education,” Master’s thesis, University of Wyoming, at, accessed 26 October 2019.

M.L. Hedley, M.A. Templin, K. Czajkowski and C. Czerniak, 2013. “The use of geospatial technologies instruction within a student/teacher/scientist partnership: Increasing students’ geospatial skills and atmospheric concept knowledge,” Journal of Geoscience Education, volume 61, number 1, pp. 161–169.
doi:, accessed 26 October 2019.

J.E. Herrick, J.W. Karl, S.E. McCord, M. Buenemann, C. Riginos, E. Courtright, J. Van Zee, A.C. Ganguli, J. Angerer, J.R. Brown, D.W. Kimiti, R. Saltzman, A. Beh and B. Bestelmeyer, 2017. “Two new mobile apps for rangeland inventory and monitoring by landowners and land managers,” Rangelands, volume 39, number 2, pp. 46–55.
doi:, accessed 26 October 2019.

B. Hofer, G. Wallentin, C. Traun and J. Strobl, 2014. “Workforce demand assessment to shape future GI-education — First results of a survey,” Proceedings of the AGILE’2014 International Conference on Geographic Information Science, at, accessed 26 October 2019.

J. Horák, 2015. “The role of certification in GIS&T education,” Procedia — Social and Behavioral Sciences, volume 174, pp. 1,356–1,363.
doi:, accessed 26 October 2019.

J.J. Kerski, 2015. “Opportunities and challenges in using geospatial technologies for education,” In: O. Muñiz Solari, A. Demirci and J. Schee (editors). Geospatial technologies and geography education in a changing world. Toyko: Springer, pp. 183–194.
doi:, accessed 26 October 2019.

J. MaKinster, N. Trautmann and M. Barnett (editors), 2014. Teaching science and investigating environmental issues with geospatial technology: Designing effective professional development for teachers. Dordrecht: Springer.
doi:, accessed 26 October 2019.

W.A. Marra, L. van de Grint, K. Alberti and D. Karssenberg, 2017. “Using GIS in an Earth sciences field course for quantitative exploration, data management and digital mapping,” Journal of Geography in Higher Education, volume 41, number 2, pp. 213–229.
doi:, accessed 26 October 2019.

M.U. Müller, D. Medyckyj-Scott, A. Cowie, T.-H. Heuer and P. Roudier, 2013. “Current status and future directions of mobile GIS,” Proceedings of the SIRC NZ Conference, at, accessed 26 October 2019.

S. Peirce, 2016. “Making learning mobile: Using mobile technologies to bring GIS into the geography classroom,” Teaching Innovation Projects, volume 6, number 1, at, accessed 26 October 2019.

V. Petras, A. Petrasova, B. Harmon, R.K. Meentemeyer and H. Mitasova, 2015. “Integrating free and open source solutions into geospatial science education,” ISPRS International Journal of Geo-Information, volume 4, number 2, pp. 942–956.
doi:, accessed 26 October 2019.

P. Piliouras, D. Lathouris, K., Plakitsi and L. Stylianou, 2015. “Collaborative action research in the context of developmental work research: A methodological approach for science teachers’ professional development,” World Journal of Education, volume 5, number 6, pp. 74–77, and at, accessed 26 October 2019.

S. Price, P. Davies, W. Farr, C. Jewitt, G. Roussos and G. Sin, 2014. “Fostering geospatial thinking in science education through a customisable smartphone application: Mobile application to foster geospatial thinking in science,” British Journal of Educational Technology, volume 45, number 1, pp. 160–170.
doi:, accessed 26 October 2019.

F.I. Rip, G. Wallentin and R.J.A. van Lammeren, 2014. “Integrated analysis of the demand for and supply of geospatial education and training: Results of the GI-N2K surveys,” at, accessed 26 October 2019.

R.W. Roeser and S.C. Peck, 2009. “An education in awareness: Self, motivation, and self-regulated learning in contemplative perspective,” Educational Psychologist, volume 44, number 2, pp. 119–136.
doi:, accessed 26 October 2019.

J. Roschelle, M. Sharples and T.W. Chan, 2005. “Introduction to the special issue on wireless and mobile technologies in education,” Journal of Computer Assisted Learning, volume 21, number 3, pp. 159–161.
doi:, accessed 26 October 2019.


Editorial history

Received 12 April 2019; revised 7 September 2019; revised 12 September 2019; accepted 13 September 2019.

Copyright © 2019, Anthony Ralston, Guillermo Hernandez, Miles Dyck, M. Derek MacKenzie, and Sylvie A. Quideau. All Rights Reserved.

Mobile learning and student engagement in remote field activities
by Anthony Ralston, Guillermo Hernandez, Miles Dyck, M. Derek MacKenzie, and Sylvie A. Quideau.
First Monday, Volume 24, Number 11 - 4 November 2019

A Great Cities Initiative of the University of Illinois at Chicago University Library.

© First Monday, 1995-2020. ISSN 1396-0466.