The use of a decision support program to facilitate the teaching of biological principles in the context of agricultural systems

H.G. Daily, G.N. Hinch, J.M. Scott & J.V. Nolan
School of Rural Science and Natural Resources
University of New England Armidale NSW 2351

Abstract

The effective teaching of agricultural science requires the development of an appreciation and understanding of the complex interactions that occur within agricultural ecosystems. These interactions cover a diversity of disciplinary areas including climate, soils, plants, animals, markets and risk assessment and optimisation. As these disciplines are commonly taught as separate entities, there is often a lack of co-ordination of curriculum development and delivery with the result that students may not link biological principles across specialist boundaries.

This paper reports an attempt to use a decision support system (DSS) software package (GrassGro, developed by CSIRO and licensed to Horizon Technology Pty. Ltd.) to provide a 'backbone' throughout an agricultural science degree. The DSS provides a common interface between disciplines allowing students to examine a wide range of biological principles and to develop an appreciation of the inter-relationships that exist between components of a complex system, e.g. soils, pasture growth and animal production.

To date the program has been used in 9 semester units (mostly but not exclusively as practical components) ranging from first to fourth year of the Rural Science undergraduate degree program at the University of New England. Specialist areas include climatic variability, environmental physiology, plant ecology, crop and pasture management, grazing animal nutrition, problem solving in farm systems, animal production management scenarios and issues relating to resource sustainability. The objectives have been to teach either key principles or to demonstrate scenarios that might assist decision making within complex agricultural or natural ecosystems.

Introduction

An understanding and appreciation of the complex interactions among climate, soils, plants, livestock, markets and risk is important in today's world where decisions about natural resource management and agricultural production are increasingly intertwined and mis-management can result in a loss of sustainable resources or decreased production. At the University of New England (UNE), we have argued that professionals and academics need to take a 'systems' view of the world and teach applied science and management students in a context that helps them to relate their specialist training to the holistic systems in which they will operate after graduation. Accordingly, to foster these attributes in our Rural Science graduates we have seen a need for a major focus on field studies and problem solving across the specialist disciplines, and for our students to be given the opportunity to use theory in a practical context. Although teaching in this way is very effective in focusing on key concepts, it is often limited in terms of flexibility (season, year and environment) and does not allow students to develop their own interests and learn independently at their own pace.

Practical sessions used in the past have often considered only one climatic event from the historic record whereas an understanding of risk management associated with the uncertainties of climate is only possible if students have access to and appreciation of long-term climatic records.

Computer software packages that can simulate real life situations provide an alternative to the 'one afternoon' field practical session. Computer simulation of cattle production, for example, over several seasons in different locations enables students to apply scientific principles in a 'real life' context. Such simulations can also add flexibility to teaching in terms of context and scenario choice, as they allow complex biophysical interactions to be examined in daily time steps. Simulation also allows teachers to demonstrate, in a credible way, the importance of interactions between a large array of factors associated with the management of natural and managed ecosystems and the importance of understanding simple biological relationships. Simulations of agricultural production using GrassGro have given our students the opportunity to explore climatic risk in a way that we have not previously found to be possible using traditional practicals.

When considering the incorporation of computer simulations into the teaching of agricultural units, Bellotti et al. (1998) imply that students using computer simulations can learn by:

• applying theory to practice,
• testing hypotheses or experimenting with choices in real time, and
• developing decision making skills by tackling problem scenarios.

In units where the application of theory is an important objective of teaching, such learning attributes are very desirable. However, problems that arise when simulation programs are used for teaching include the availability of time and resources to familiarise students with software packages to a point where self-discovery and interpretation of senarios are possible. For applied science courses such as agriculture, the rapidly growing knowledge base has generated curricula that are already 'overflowing' so that the time available for students to process and make use of information is often a limiting factor. This issue is critical in the final years when integration and systems concepts need to be developed. Thus, for software packages are to be successfully used for teaching in the latter years of a degree, strategies must be put in place to allow the students to develop adequate competency for this purpose. This can be achieved by reducing the number of software packages students need to become familiar with, and at the same time increasing their frequency of exposure to these software packages. Ideally this familiarity can be developed gradually throughout a degree program by using any one software package initially in 'demonstration mode', with subsequent practical sessions gradually requiring students to answer increasingly complex questions. Eventually, the students should be able to tap the full potential of the software to simulate complex interrelationships.

This paper examines the use of a computer decision support system (DSS) as a platform for students at different levels and stages in their undergraduate degrees and providing natural conceptual links between disciplinary units. We believe the use of DSS software, such as the use of GrassGro at UNE, provides teachers with opportunities to illustrate theory and key concepts with greater clarity and ultimately facilitates more effective learning about agricultural systems. This is evidenced by the potential afforded by exercises that use a DSS to engage students at their current level of knowledge, by active learning inside and outside the classroom setting, and by giving teachers increased flexibility to choose scenarios of immediate interest to students. This mode of engagement of students allows learning to occur at both an individual and group level.

Background

As in many other tertiary institutions, applied science and management curricula at UNE introduce students to the basic science and management theory and detailed mechanisms of plant, animal and ecosystem function and management in the first two years. As students proceed through their degree, units become increasingly complex until, in the final year, students are expected to develop and draw on an overall 'systems' perspective. To achieve this goal, they need a common platform on which to base this part of their learning. McClymont (1968) developed a conceptual model that has traditionally been that platform at UNE. However the complexity of the interrelationships has made the effective teaching of agricultural systems concepts around that platform difficult. In the last decade, however, teaching has focused largely on problem solving approaches (Hinch 2000) with the McClymont platform as the focus.

Currently, individual academics throughout our School use a wide range of computer models and DSS to enhance students' learning. Typically, these models have been locally produced or are relatively inexpensive and have been used to reinforce specific theoretical principles in structured practical classes. Alternatively, to demonstrate principles teachers have used more complex and expensive commercial software, but usually, for economic reasons, a single licensed copy. This has meant that students have rarely had the opportunity to 'experiment' with complex models and hence develop an understanding of the interrelationships that can come from simulation senarios.

The software package GrassGro is an example of one of the complex models that are now commercially available to assist extension staff and farmers. This DSS package has been developed by CSIRO scientists over the last decade and is now distributed under licence by Horizon Technology Pty Ltd. The program provides predictive outcomes (both biological and economic) for agricultural systems in a diversity of climatic environments throughout temperate Australia and provides a wide range of management options for grazing animals. It incorporates a comprehensive scientific knowledge base with over 250 scientific papers used to define specific biological relationships (Moore et al. 1997). Development is on-going with additional or more comprehensive modules for cropping and soil fertility to be included.

With funding from a Committee for University Teaching and Development (CUTSD) - Organisational grant, and the collaboration of CSIRO and Horizon Technology, a fully implemented version of GrassGro has been adapted to run on a central campus server and distributed using Citrix Metaframe, so that students can gain access to the DSS from computers on the campus network (ultimately through the Internet). In setting up a teaching scenario, a lecturer has control over what menu choices within GrassGro will be available to the students: the lecturer simply alters an initialisation file within the set-up of the program to disable parts of the DSS so that they are not accessible to the students. Students can then view but not change the contents of the disabled dialogs. This maximises the control and specificity of use of the DSS by lecturers allowing them to focus on particular disciplinary areas. Lecturers can also construct a GrassGro input file to describe the system the students are to use for simulations: for instance, the details of soil characteristics, pastures and animal types can be either be set for the particular practical session. Alternatively, a simulation can be run before the practical session and only the output files made available. There are numerous combinations of options available in the DSS to describe an agricultural system and the interactions between climate (long-term records can be used), soils, plants, animals and economics. Consequently this DSS can be used from the view point of a grazier or farm consultant to undertake experimentation that will generate realistic outcomes.

Creating the platform

Table 1 summarises the UNE units presently using GrassGro in practical classes or in a broader framework of tutorials and practicals. The activity column indicates the areas of expertise that are addressed in the use of the DSS and the 'approach' column the main objective for the use of the program.

The combination of units described in Table 1 is the end result of 2 years of development to integrate the use of the DSS across a number of core units in the Rural Science degree. In all cases the computer package is used as a component (10-15%) of the practical teaching of the units and in a few cases has also been used to demonstrate principles in lectures. In most cases the program is used to demonstrate or reinforce core concepts of the unit (Table 1) in the same way as laboratory exercises or field trips would be used - but with the added advantage of flexibility in terms of climatic, soil, pasture, animal and time parameters.

The objectives set for practical classes become progressively more ambitious, commencing in first year with generation of graphical or tabular summaries or demonstration of simple relationships. By third year the students are expected to be familiar enough with the DSS to be able to experiment and to identify key factors influencing plant and animal production parameters. To date a complete cohort of students has not completed 4 years of exposure to GrassGro and consequently the success or otherwise of the strategy of staged development of familiarity with the DSS and skills in its use has not been assessed. However present indications are that students become familiar with the program relatively quickly and need little rehearsal before using the program on subsequent occasions. Therefore the greatest challenge appears to be to design tasks that will achieve specific objective, stimulate on-going interest and allow students to use different learning styles. Another significant challenge is to get lecturers to 'own' the DSS core and co-ordinate teaching activities between themselves.

Table 1 Discipline areas, learning activities and objectives presently addressed using GrassGro

First Year Teaching

At the first year level, GrassGro has been used to demonstrate climatic characteristics of various southern Australian environments and to give students (about 170 in 2000) an appreciation of interactions between management decisions and sustainability of different soil types. The large number of students has inevitably meant that they have had to cooperate in the learning experience as they shared computer facilities. This has been encouraged and observation of learning activities, and subsequent discussion with students, suggests that the shared learning-experience has generally been positive. The climatic data practical was, in previous years, undertaken using alternative software but the use of GrassGro has achieved the same objectives. This practical session also facilitated the familiarisation of students with the program. This was their first exposure to GrassGro as they investigated the basic climatic characteristics of various sites throughout Australia. The second practical assumed some familiarity with the DSS and required students to think through sustainability issues before accessing information from the simulation that would confirm or negate their hypotheses.

The effectiveness of teaching achieved when using GrassGro at first year level appears to be highly dependent on the provision of a structure that will require all students to interpret the information they collect in terms of core concepts. This is far from being a simple task and a number of years of refinement of the structure will probably be necessary. Our initial approach has been to ensure that students can relate to the information and scenarios being used. To achieve this, we have used scenarios based on previous/concurrent field-site visits and glasshouse experiments so that the students are able to link the simulation to a real-world context. This approach appears to have been an effective way of initiating interest in the use of the program and facilitating the development of hypotheses, sometimes beyond those that are specifically part of the practical objectives. We hope that the link in the students' minds between the simulation output and reality will to some extent 'validate' the use of the program for further simulations in later years.

Second-year teaching

GrassGro has been used in the teaching of basic ruminant nutrition (ANUT221) to second-year students who had previous exposure to the DSS in first year. A simulation of a Merino sheep enterprise on the northern tablelands on NSW uses historic climate data to generate pasture availability and quality in the period 1977-1982. 'Potential pasture intake' is generated by the DSS, and students examine how factors such as pasture availability and quality in good and bad seasons determine actual feed intake, metabolisable energy and protein intake and thus animal growth or wool production. Each student fills in a question sheet recording their responses to a series of questions to which they seek answers as they are guided through the process of running a simulation and graphically displaying the output. The questions require cross-disciplinary thinking.

Third-year Teaching

The approach taken in 2000 with 3rd year students who had had only one prior exposure to GrassGro in 1999 (a demonstration only) was for each student to explore the variations in growth rates of three contrasting pasture species over time at two climatically different locations. To do this, they needed to use the detailed graphical and tabular output to determine historic wet and dry years and to understand the factors limiting the growth of pastures in those years. They were also made aware of differences in seasonal reliability between different geographical regions, seasonal patterns of feed availability at the different locations and the frequency with which animals required supplementary feeding. For those who completed the exercises in time, further extension work was encouraged to explore simulations of various feeding strategies.

Assessment involved marking the students' answers to a range of questions, most of which required them to run the simulation and then to generate a graph or table of simulation outputs. Some questions required students to search the comprehensive help files that are supplied with the software. It is noteworthy that, after a brief introduction, students were keen to commence their own simulations within 20 minutes.

Fourth-year Teaching

As indicated earlier one of the main reasons for attempting to integrate the use of GrassGro into the teaching of Rural Science units was to facilitate more effective teaching of interrelationships between disciplinary areas and systems concepts. A number of computer models had been used in previous years in the unit AGSY410 to illustrate interrelationships between plants and animals, or animal and economic systems. However, the lack of flexibility of these teaching aids had meant that our aim to have students develop an appreciation of the complex interactions that occur in agricultural systems had not been achieved.

In the last two years we have used GrassGro as the basis of exercises designed to assist students to realise the complexity of interrelationships between climate, pasture growth and animal production that underpin correct management decisions. Our 4th year students were somewhat disadvantaged by their limited exposure to GrassGro, but we have found that the DSS does reinforce concepts taught in earlier years and provide an environment for students to test their own attempts to make long-term management decisions. To date we do not appear to have been successful in extending the learning opportunities outside the classroom setting, probably because of technical limitations associated with ease of access to the software.

The introduction of GrassGro as a teaching aid has been very effective in providing an opportunity for students to actively experiment with management choices and to develop problem solving methodologies. However, a proportion of students (about 25%) seem hesitant to use the DSS and lecturers may need to develop more flexible approaches that take better account of differences between students in learning styles and motivation.

Effective teaching and learning?

In a recent paper Terenzini (2000) argued that new learning environments need to be introduced into university teaching. He suggests that these environments should provide opportunities for students actively 'to apply and test what they are learning in real and meaningful settings..... They should require analysis of what is known, and adaptation and application of what is known to the new. ......The learning environment should involve collaborative learning activities, be largely multi-disciplinary and accommodate different learning styles, and if possible to extend outside the normal classroom setting'.

The question of whether the use of this DSS will generated more effective learning outcomes within the Rural Science degree program has still to be fully answered, but our experiences in the first 3 years suggest that our teaching has indeed been more effective with the introduction of this software. However, further improvements in teaching outcomes will, to a large degree, depend on the coordination of its use across disciplinary units and between the undergraduate years. Consequently, there must continue to be a team approach involving lecturers from the different disciplines if the potential advantages of this relatively complex DSS are going to be realised, and if the outcomes are to be superior to those previously obtained from simpler, 'one principle' models that have been and still are currently used as teaching aids.

Our first impressions are that, by using GrassGro as a cross-disciplinary teaching aid, we have begun to create a superior environment for students to learn the complexities of agricultural systems within the Rural Science degree.

Acknowledgments

The adoption and development of this teaching project would not have been possible without funding from the CUTSD Organisational grant and the cooperation of the 15 teaching and general staff at UNE who have participated to date. Specific thanks go Jim Reid and Noni Wells (UNE) for their excellent technical support, to Rob McCook of Horizon Technology Pty Ltd and John Donnelly, Libby Salmon and Andrew Moore of CSIRO Plant Industry.

References

Bellotti, W., Daily, H., Kiley, M., Mullins, G., Peterson, R. and Tivey, D. (1998). Integrating a computer simulation into the curriculum: a teachers guide. The Advisory Centre for University Education, The University of Adelaide.

Hinch, G.N. (2000). Social Components of Agricultural Systems. In: Skills for the Future ed. R Muldoon Teaching and Learning Centre, University of New England, pp. 105-107

McClymont, G.L. (1968). The contribution of Universities to Agricultural Education - Past, Present and Future. Training for Rural Industries - a review of agricultural education in NSW, Sydney University Extension Board.

Moore, A.D., Donnelly, J.R. and Freer, M. (1997). "GRAZPLAN: Decision Support Systems for Australian Grazing Enterprises. III. Growth and Soil Moisture Submodels, and the GrassGro DSS" Agricultural Systems 55, 535-582.

Terenzini, P.T. (2000). Research and practice in undergraduate education: and never the twain shall meet? Higher Education 38, 33-48.