This article was downloaded by: [McMaster University]On: 25 November 2014, At: 09:51Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Geography in HigherEducationPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/cjgh20

Interactive online tools for enhancingstudent learning experiences in remotesensingKaren E. Joyceab, Bopelo Boitshwarelob, Stuart R. Phinnc, GregJ.E. Hilld & Gail D. Kellye

a Research Institute for the Environment and Livelihoods, CharlesDarwin University, Casuarina Campus, Darwin, NT 0810, Australiab Office of Learning and Teaching, Charles Darwin University,Casuarina Campus, Darwin, NT 0810, Australiac School of Geography, Planning, and Environmental Management,University of Queensland, St Lucia, QLD 4072, Australiad University of the Sunshine Coast, Maroochydore, Darwin, QLD4558, Australiae AAM Pty Ltd, Level 1 Leichhardt Court, 55 Little Edward Street,Spring Hill, QLD 4004, AustraliaPublished online: 01 Jul 2014.

To cite this article: Karen E. Joyce, Bopelo Boitshwarelo, Stuart R. Phinn, Greg J.E. Hill & Gail D.Kelly (2014) Interactive online tools for enhancing student learning experiences in remote sensing,Journal of Geography in Higher Education, 38:3, 431-439, DOI: 10.1080/03098265.2014.933404

To link to this article: http://dx.doi.org/10.1080/03098265.2014.933404

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever

or howsoever caused arising directly or indirectly in connection with, in relation to orarising out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

Interactive online tools for enhancing student learning experiences inremote sensing

Karen E. Joycea,b*, Bopelo Boitshwarelob, Stuart R. Phinnc, Greg J.E. Hilld and

Gail D. Kellye

aResearch Institute for the Environment and Livelihoods, Charles Darwin University, CasuarinaCampus, Darwin, NT 0810, Australia; bOffice of Learning and Teaching, Charles DarwinUniversity, Casuarina Campus, Darwin, NT 0810, Australia; cSchool of Geography, Planning, andEnvironmental Management, University of Queensland, St Lucia, QLD 4072, Australia; dUniversityof the Sunshine Coast, Maroochydore, Darwin, QLD 4558, Australia; eAAM Pty Ltd, Level 1Leichhardt Court, 55 Little Edward Street, Spring Hill, QLD 4004, Australia

(Received 11 December 2013; final version received 26 April 2014)

The rapid growth in Information and Communications Technologies usage in highereducation has provided immense opportunities to foster effective student learningexperiences in geography. In particular, remote sensing lends itself to the creativeutilization of multimedia technologies. This paper presents a case study of a remotesensing computer aided learning (RSCAL) program, which was developed in Australiato facilitate student active engagement with foundational knowledge and skills.We demonstrate how RSCAL has evolved to become scalable and responsive to newerpedagogical perspectives and emerging learner needs. It has become a recommendedkey resource in contemporary remote sensing education and training.

Keywords: remote sensing; multimedia; pedagogy; online learning; higher education

Introduction

The rapid growth of Information and Communications Technologies (ICTs) undoubtedly

provides immense potential in the teaching and learning of geography in higher education

(Lemke & Ritter, 2000; Ritter, 2012). For remote sensing specifically, the key role of the

Internet was already evident as far back as the 1990s (Stubkjær, 1997). The nature of

remote sensing lends itself particularly to multimedia technologies and as the years have

passed, it is clear that remote sensing education without these tools is fundamentally

limited.

Some of the early attempts at using ICTs within the remote sensing discipline included

collating educational resources by links through a single web page to provide a “one stop

shop” for educators and students to search for materials (Sivaprakash, Ng, Teo, Khoo, &

Liew, 1997). Recognizing the value of interactivity in education, Koenig (2000)

progressed the online materials with the development of a website that contained a number

q 2014 Taylor & Francis

*Corresponding author. Email: karen.joyce@cdu.edu.au

Journal of Geography in Higher Education, 2014

Vol. 38, No. 3, 431–439, http://dx.doi.org/10.1080/03098265.2014.933404

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

of basic animations, as well as some java scripting to allow students to select and view a

variety of spectral reflectance signature graphs. Aspects of this historic work are still

valuable today, though their presentation needs to be updated and integrated into a more

consolidated framework of learning materials.

In more recent work, there is evidence of an increasing focus on quality of the

multimedia products developed (Konig, 2009). It would appear that earlier products were

largely deficient in interactivity and didactic strategies (Konig, 2009; Weippert & Fritsch,

2002). This interactivity and the use of didactic strategies in online multimedia has

become immensely important, in part due to an increasing number of learners studying

remote sensing at a distance (Cochrane, 2005). Owing to this trend, there are currently a

number of remote sensing educational resources available online, and several of these

have been developed by government organizations. One such resource is the Canadian

Government Fundamentals of Remote Sensing Tutorial (http://www.nrcan.gc.ca/earth-

sciences/geography-boundary/remote-sensing/fundamentals/1430). While far more com-

prehensive than many other online resources, this remains a static source of information.

It requires the student to read large amounts of text with very little interactivity or

engagement, thus being more in line with a soft-copy text.

Against this backdrop, this paper presents an online multimedia resource known as the

remote sensing computer-aided learning (RSCAL, accessed via http://www.kejoyce.com/

education.html). It was developed in Australia to facilitate student active engagement with

foundational remote sensing knowledge and skills. The paper will demonstrate how

RSCAL has evolved over time to meet students’ emerging needs. In addition to being

cohesive, interactive and comprehensive, RSCAL is freely accessible. The paper is

motivated by the need to demonstrate good pedagogies, and at the same time openly share

educational products to advance remote sensing education globally.

Taking a descriptive case study approach, this paper will start by providing a

contextual background to RSCAL, in terms of its history and also the specific context of its

recent implementation at Charles Darwin University (CDU). Next, analysis of the design

and development of the product will be made, followed by some information on recent

preliminary evaluation thereof. Finally, future prospects, particularly anticipated

developments, will be briefly discussed, followed by a summary.

Contextual background

The RSCAL program was originally developed in the late 1980s as an initiative of the

ARC Key Centre in Land Information Studies (AKCLIS). Headquartered at the University

of Queensland (UQ), AKCLIS was one of the first key centres to be established, and was

charged with undertaking research on the rapidly developing new disciplines of remote

sensing and geographical information systems.

Driven by advances in technology and computing, remote sensing curricula that had

previously been dominated by techniques for interpretation of manual air photographs and

photogrammetric analysis required complete revision. Within the AKCLIS, a decision was

made to harness the potential of the technology itself to inspire students, enhance the

learning experience and provide the educational leadership expected of a key centre.

Consequently, RSCAL, an interactive computer-aided learning program, was created to

assist students in developing a fundamental understanding of remote sensing and the

associated complex technical skills.

Over the past 23 years, more than 1000 undergraduate and postgraduate students have

used the program, primarily at UQ and CDU (previously Northern Territory University),

432

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

where it is now written into the course syllabus of the introductory remote sensing classes.

Here it directly supports understanding of specific topics to provide learning and active

revision of all the major concepts and skills. Recently, RSCAL was revised to make use of

more contemporary software and make it more widely accessible through the web. The

new version was implemented at CDU and UQ in early 2013.

Our context of focus in this paper is primarily on the recent implementation of RSCAL

at CDU, which is a small regional university in the Northern Territory of Australia. A large

proportion of the student cohort study via distance learning for undergraduate and

postgraduate degree qualifications. As such, a considerable amount of effort and attention

is focussed on providing high quality online learning experiences.

Between 2010 and 2013, the proportion of enrolment of external students at CDU

studying remote sensing increased from 27% to 48%. The quality and quantity of online

materials was thus required to increase accordingly. Relying solely on audio and/or video

recordings, static web pages and document download via the Learning Management

System proved insufficient to meet the needs of students who were participating

externally. Further, with many on-campus-based students increasingly relying on, and

expecting, online resources to complement lectures and practicals, it became obvious that

more sophisticated resources were needed.

Provision of online learning is challenging across all disciplines. In some cases, there

may be materials available from other institutions or organizations that can be collated for

the student. Otherwise, it remains the responsibility of the course teacher to develop and

deliver these resources. While the field of remote sensing is driven by science, technology

and visualization, a range of online resources are available, yet are not always presented in

a cohesive, comprehensive and easily digestible format. The RSCAL program forms part

of complete learning materials overhaul for remote sensing to address this requirement at

CDU.

Design and development of RSCAL

Remote sensing requires students to grasp concepts from a variety of disciplines, and to

apply their knowledge in practical settings. Like most other fields, it has traditionally been

taught with a lecture and practical/tutorial format, which is now becoming somewhat

defunct with the high demand for online learning. The rationale for creating RSCAL, and

subsequently revising it, was therefore to provide remote sensing students with a means for

more interactive, engaging and comprehensive learning that is congruent with emerging

best teaching practices. RSCAL leverages the technological developments in terms of

software that are now able to support a variety of learning tools suitable for the technology

demanding and savvy student.

The objective of developing this suite of multimedia learning tools was threefold: to

attract and engage students in the online learning space; to offer tools that break down and

explain some of the key concepts that can be challenging in understanding due either to the

scientific or industry-based terminology and processes and to meet the broad range of

learning preferences of a diverse student cohort (Hammen, 1992).

RSCAL is a program that requires the student to actively engage with the educational

content as they begin to develop basic skills in remote sensing. It presents the foundational

theory and concepts of remote sensing, while assisting students to acquire and apply basic

skills through practical applications. The intent was to move away from text-driven

resources; thus, the program uses an integrated multimedia format including graphics and

animations to scaffold learning. This format has been shown to effectively promote

433

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

student learning (Mayer, 2003). Additionally, graphics are known to support attention,

enhance motivation and minimize cognitive load (Clark & Lyons, 2010). This approach

stimulates curiosity, motivating students to connect to the theory and practice of remote

sensing, and forming a sound basis for more advanced learning. RSCAL uses a

combination of learning tools that incorporate video, animation, narrations that align with

the lecture, interactive “play”, quizzes and encourages exploration and therefore appeals

to different mix of learner styles such as the auditory, visual or verbal styles.

The design and development of instructional multimedia to effectively meet these

multi-fold objectives is a rather complex undertaking because a multiplicity of factors is

involved. Numerous interrelated elements are known to determine the effect of

multimedia on learning and these can be grouped into four broad categories (Hede, 2002):

multimedia inputs, cognitive processes, learner dynamics, and knowledge and learning.

Of these four categories, multimedia inputs (which includes auditory, visual and learner

control inputs) is the one that is under the direct control of designers/developers of

instructional multimedia. The multimedia inputs then influence the other elements in one

way or another, or intervene between them. For example, multimedia inputs, if well

designed and organized, can enhance attention, foster engagement and lead to meaningful

construction of knowledge. An analysis of the RSCALmultimedia inputs reveals that their

design was underpinned by some key instructional media design strategies especially

those discussed by Mayer (2003):

. The multimedia effect principle, where the program uses integrated text, graphics

and sounds/audio to motivate and engage learners and hopefully facilitate deep

learning.

. The coherence effect principle also is evident as only relevant material tended to be

included while extraneous details are excluded to avoid interference with the

learning process and reduce cognitive overload.

. Effectiveness was also achieved through the spatial and temporal contiguity effect,

in which different media are physically integrated together or close to each in time

and space to avoid split attention (Moreno & Mayer, 1999).

. While the personalization effect is mildly used, the material was not too formal

either and is written in simple language, and therefore is still friendly to learners.

The content used originates from various text books, and the combined research of

authors and colleagues. It is structured into four main modules: What is remote sensing;

spectral signatures; aerial photo interpretation and digital image processing. Each module

was then broken down into between six and eight topics (Figure 1). Consistent with

Gagne’s theory around conditions of learning, which is widely used to guide effective

instructional multimedia (Deubel, 2003; Gagne, 1985; Stemler, 1997; Wild & Quinn,

1998), RSCAL facilitates the different events of learning. For example, the attractive

graphics on the front page of every module and/or topic helps to gain attention of the

students while the specific learning objectives and a list of topics used to introduce the

module creates expectancy. The way the material is chunked and structured and the use of

strategies described earlier to organize different media aid the cognitive processes such as

semantic encoding (meaning-making). Students can also choose which topic to access and

can navigate the program according to their areas of interest. This promotes inclusivity for

students with diverse needs. To elicit performance, provide feedback and assess

performance, questions are embedded within the modules which give many opportunities

for formative feedback, while each module concludes with a summative assessment,

assisting with retrieval, reinforcement and knowledge transfer.

434

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

Themost recent version of RSCAL released in early 2014 encompasses amajor upgrade

of the software, including changing the operating platform from the original 1990s MS-

DOS to a web-based platform. In addition, some of the materials were outdated, as were

some of the learning techniques. The program therefore needed to be revised to be platform

independent, and to embrace contemporary learning styles. The current edition was

developed using primarily Adobe Captivate and Adobe Illustrator, in addition to the

Goanimate animation tools available online. It was designed to be flexible in that the content

within the modules can be easily updated, and additional modules can also be added.

When entering RSCAL, users initially select from the available learning modules, or

the optional “Games” or “Scenarios” (Figure 2(a)). Within a module, the topic selection is

then made (Figure 2(b)). The user progresses through the materials by clicking on various

links to allow new content to appear (Figure 2(c)). Within topic navigation is performed

using an expandable table of contents, or the forward and back arrows at the bottom of

each slide. A number of different styles of questions are offered as formative feedback to

the student (e.g. Figure 2(d)), and the final score is presented at the end of the module.

This, however, is not recorded in any way.

RSCAL has many advantages for educators and students in the discipline of remote

sensing. For example, course coordinators can link this resource to the main topics in any

textbooks on introductory remote sensing, as is currently done at CDU and UQ. In addition,

specific examples in the modules can be used in conventional lectures, practicals and

tutorial discussions to reinforce learning of concepts and skills. Also, if individual students

experience difficulties, they can be directed to particular modules or topics for revision and

practice. Furthermore, the program has been designed with careful attention to the

foundational concepts and skills required to understand and use remote sensing

Figure 1. The modular structure and topics of the remote sensing computer-aided learning program.

435

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

technologies in a variety of professional applications. This critical feature extends the

program’s “shelf life” indefinitely and ensures sound learning of the basics in diverse

student cohorts and in individuals with differing abilities and preferred learning modes.

A critical aspect of the online resources is the active link between content-based learning

and direct application of fundamental concepts to image processing and interpretation at the

same time, along with the ability to obtain immediate feedback on work completed. Given

the interactive nature of image processing and understanding digital images and how they

measure and represent the environment, this use of online tools for this approach is essential.

The multimedia learning materials have also been designed to improve the learning

experience for external students who have historically had limited access to resources

beyond lecture slides and audio recordings (of variable quality) and standard text books.

The materials satisfy the broad range of learning needs and preferences that are found

within a diverse cohort of students. The range covers domestic and international students,

those with varying levels of educational, science and professional experience, and those

studying either on-campus or externally.

Evaluation

Over the past 23 years, more than one thousand undergraduate and postgraduate students

have used the program, primarily at UQ and CDU. The students’ disciplines span Arts,

Science, Planning, Geophysics, IT, Environmental Science and Management, Engineer-

ing, Marine Science and Agricultural Science. In the first semester of 2014, approximately

150 students from UQ and CDU were actively encouraged to use the program and provide

Figure 2. Example components of RSCAL: (a) module selection; (b) topic selection; (c) contentpresentation and (d) formative assessment.

436

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

feedback. Data from Google Analytics, which was used to track usage, demonstrates the

high degree of uptake of this program. During March 2014, which represents the first

month of teaching in Australian universities, 349 unique visitors were recorded to visit

RSCAL. While the vast majority of the total 868 hits registered during this period were

from Australia, this also represented users in the USA, Algeria, Indonesia, Bahrain, Spain,

New Zealand, Turkey, Belgium and Bhutan.

In addition to acquiring usage information, an online feedback surveywas incorporated.

Thus far, the survey has been completed by a variety of people of all ages with differing

levels of experience (n¼17). This includes undergraduate and postgraduate students, as

well as industry and government employees. Those completing the survey were required to

rate their experience of the program on a scale of one to five. Most responses showed that

users were extremely likely to recommend the product to a peer or colleague (score ¼ 4.8),

and also considered that it facilitated their learning of the topic extremely well

(score ¼ 4.7). Students were equally happy with their level of engagement in the materials

(score ¼ 4.8), and experienced a high level of enjoyment in using it (score ¼ 4.6). With

only one exception, all users chose this program as their first choice for learning materials

when rated against textbooks, lecture notes and other online resources.

In addition to the numerical ratings, respondents had the opportunity to provide a

feedback comment. Figure 3 shows a selection of some of the responses, and also

demonstrates the international testing of the program.

Future directions

This current version is presented in a somewhat linear fashion that promotes self-paced

learning, but the student is somewhat limited in their direction or pathway choice. We

Figure 3. Feedback from users of RSCAL.

437

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

would like to see further editions of the product follow more of a spider web type or mind

map structure, which would further promote student exploration into topics of interest.

However, this will require significantly more programming and design development. The

most recent release (April 2014) of the Scenarios module starts to head in the direction of

more exploratory learning.

To complement RSCAL, we have more recently created an additional tool that is

specifically focussed on addressing the types of skills that are used in a field or laboratory

situation. The new virtual lab includes considerably more interactivity, and features field

spectrometer use, visualizing colour using multi-band image displays, and experimen-

tation associated with spatial extent and resolution trade-offs. It is optimized for tablet use,

taking advantage of touch and gestures in addition to audio-visual cues. It is now available

via http://remotesensinglab.com and is receiving positive feedback from initial testing.

In a recent survey of 130 Canadian and US universities and colleges involved in

teaching remote sensing, Sader and Mueller (2012) found that only 5.6% of courses were

taught online. It will be interesting to see if this increases in the future, though one can only

expect this to be the case if the momentum of MOOCs (massive online open courses) is

indicative of this trend and students increasingly demand online education. As such, the

continued development of engaging and contemporary online resources will be critical to

recruiting and retaining students.

We will continue to collect data to ensure that the success of the past 23 years is

maintained, and will modify the program in response to feedback and our further critical

reflection. Consequently, RSCAL’s relevance and currency for higher education in

introductory remote sensing, both nationally and internationally – and for continuing

education in a variety of workplaces – will not only be maintained but will also be further

increased.

Summary

This paper has presented the developmental history and use of RSCAL, originally

designed in the late 1980s, but re-released in 2013. To our knowledge, it is the most

cohesive, comprehensive, and interactive learning tool within our discipline. RSCAL is

freely available online and targeted towards learning the fundamental principles of remote

sensing. Grounded in what is known to be effective pedagogy, it engages the student

through a range of multi-media tools including visualization, animation, and audio, in

addition to providing opportunities for both formative and summative assessments.

We encourage other educators to use the tool within their teaching programs, and

acknowledge that the proliferation of online learning opportunities can only continue to

enhance the development of similar products.

Acknowledgements

The authors wish to thank Sushana Karki for her assistance in transcribing the previous edition ofRSCAL into the current format; Leigh Findlay, Tania Stevenson and Darin Ritchie for editorialassistance; and the many people who have taken the time to provide us feedback on the program.RSCAL can be accessed here: www.kejoyce.com/education.html

References

Clark, R. C., & Lyons, C. (2010). Graphics for learning: Proven guidelines for planning, designing,and evaluating visuals in training materials. Chichester: Wiley.

438

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014

Cochrane, T. (2005). Interactive QuickTime: Developing and evaluating multimedia learningobjects to enhance both face-to-face and distance e-learning environments. InterdisciplinaryJournal of E-Learning and Learning Objects, 1, 33–54.

Deubel, P. (2003). An investigation of behaviorist and cognitive approaches to instructionalmultimedia design. Journal of Educational Multimedia and hypermedia, 12, 63–90.

Gagne, R. M. (1985). The conditions of learning (4th ed.). New York: Holt, Rinehart and Winston.Hammen, J. L. (1992). Accommodating student diversity in remote sensing instruction. Journal of

Geography, 91, 28–31.Hede, A. (2002). Integrated model of multimedia effects on learning. Journal of Educational

Multimedia and hypermedia, 11, 177–191.Koenig, G. (2000). Interacive education on the web – Experiences in development and application

of a computer assisted training course for remote sensing. In International archives ofphotogrammetry and remote sensing, Amsterdam.

Konig, G. (2009). Best practice in e-learning: Applications in photogrammetry, remote sensing andGIS. ISPRS proceedings, e-learning tools, techniques and applications. Retrieved from http://www.isprs.org/proceedings/xxxviii/6-w7/paper/01_koenig.pdf

Lemke, K. A., & Ritter, M. E. (2000). Virtual geographies and the use of the Internet for learning andteaching geography in higher education. Journal of Geography in Higher Education, 24, 87–91.

Mayer, R. E. (2003). The promise of multimedia learning: Using the same instructional designmethods across different media. Learning and Instruction, 13, 125–139.

Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role ofmodality and contiguity. Journal of Educational Psychology, 91, 358–368.

Ritter, M. (2012). Barriers to teaching introductory physical geography online. Review ofInternational Geography Education Online, 2, 61–77.

Sader, S. A., & Mueller, T. (2012). Survey on remote sensing and geospatial technologies training inUS and Canadian colleges and universities. Photogrammetric Engineering and Remote Sensing,78, 1193–1198.

Sivaprakash, S., Ng, J., Teo, N. L., Khoo, V. H. S., & Liew, S. C. (1997). Remote sensing educationresources on the World Wide Web. In Geoscience and Remote Sensing, 1997. IGARSS’97.Remote Sensing-A Scientific Vision for Sustainable Development, 1997 IEEE International(Vol. 2, pp. 848–849).

Stemler, L. K. (1997). Educational characteristics of multimedia: A literature review. Journal ofEducational Multimedia and hypermedia, 6, 339–360.

Stubkjær, E. (1997). The world wide web and university education in remote sensing. ISPRS Journalof Photogrammetry and Remote Sensing, 52, 281–293.

Weippert, H., & Fritsch, D. (2002). Development of a GIS supported interactive “remote sensing”learning module. International Archives of Photogrammetry Remote Sensing and SpatialInformation Sciences, 34, 125–130.

Wild, M., & Quinn, C. (1998). Implications of educational theory for the design of instructionalmultimedia. British Journal of Educational Technology, 29, 73–82.

439

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

09:

51 2

5 N

ovem

ber

2014