Providing equivalent learning activities with software-based remote access laboratories

Laboratory-based learning activities are important components of engineering and surveying education and it is difficult to offering practical activities to distance education students. Remote Access Laboratory (RAL) systems are widely discussed as learning tools to offer students remote access to rigs or hardware. In some disciplines laboratory activities are purely software based and RAL systems can be used to provide access to software. As part of a larger study into the transferability of the remote laboratory concept to non-engineering disciplines this project evaluates the effectiveness of RAL based software activities in supporting student learning is investigated. In the discipline of Surveying and Spatial Science, RAL technology is used to provide Geographic Information System software access to distance students. The key research question discussed in this paper is whether RALbased software activities can address the same learning outcomes as face-to-face practical classes for software activities. Data was collected from students' discussion forums, teaching staff diaries and teaching staff interviews. The project demonstrates that students undertaking learning activities remotely achieve similar learning outcomes than student in practice classes using the same software. Ease of system access and usability are critical and the learning activity needs to be supported by comprehensive learning materials. This research provides a clear case in which the use of RAL technology has provided inclusive educational opportunities more efficiently and these general results are also applicable to experiments that involve physical hardware

Cognitive dissonance in student self-assessment

The student self-assessment of assignment study was conducted in a first year course in 2010, 2011 and 2012. The purpose of this paper is to provide an understanding of students' response patterns while seeking cognitive consonance. The general strategy followed by students in an attempt to remove or reduce cognitive dissonance (i.e. reaching consonance) seemed to fall into one of the following three broad categories: Modify cognition to cope with new facts (i.e. change one or more of the beliefs, opinions, or behaviours involved in the dissonance) - 'An instance of acceptance'; Integrate new facts to preserve an 'own self' by reducing the importance of conflicting instance - 'An instance of avoidance or deviation'; Forget, ignore, overlook, or bypass those cognitions that are in a dissonant relationship - 'An instance of ignorance'

Mapping of peanut crops in Queensland, Australia using time-series PROBA-V 100-m normalized difference vegetation index imagery

Mapping of peanut crops is essential in supporting peanut production, yield prediction, and commodity forecasting. While ground-based surveys can be used over small areas, the development of remote-sensing technologies could provide rapid and inexpensive crop area estimates with high accuracy over large regions. Some of these recent earth observation satellite systems, such as the Project for On-Board Autonomy Vegetation (PROBA-V), have the advantage of increased spatial and temporal resolution. With a study area located in the South Burnett region, Queensland, Australia, the primary aim of this study was to assess the ability of time-series PROBA-V 100-m normalized difference vegetation index (NDVI) for peanut crop mapping. Two datasets, i.e., PROBA-V NDVI time-series imagery and the corresponding phenological parameters generated from TIMESAT data analysis technique, were classified using maximum likelihood classification, spectral angle mapper, and minimum distance classification algorithms. The results show that among all methods used, the application of MLC in PROBA-V NDVI time series produced very good overall accuracy, i.e., 92.75%, with producer and user accuracy of each class ≥78.79  %  . For all algorithms tested, the mapping of peanut cropping areas produced satisfactory classification results, i.e., 75.95% to 100%. Our study confirmed that the use of finer resolution 100 m of PROBA-V imagery (i.e., relative to MODIS 250-m data) has contributed to the success of mapping peanut and other crops in the study area

Relating satellite imagery with grain protein content

Satellite images, captured during the growing seasons of barley, sorghum and wheat were analysed to establish a relationship between the spectral response and the harvested grain protein content. This study was conducted near Jimbour (approx. 151°10’E and 27°05’S) in southern Queensland. Grain protein contents of the geo-referenced samples, collected manually during the harvest, were determined using a laboratory-based near-infrared spectrophotometer. Grain protein contents in grain varied between 7.4–15.2% in barley, 6.2– 10.6% in sorghum and 13.1–15.6% in wheat. The Landsat images of 18 September 1999 (a week after barley flowering), 5 March 2000 (three weeks before sorghum harvest), and 15 August 2001 (two weeks before wheat flowering) were analysed. Additionally, an ASTER image of 24 September 2001 (three weeks after wheat flowering) was also examined. Digital numbers, extracted from raw image bands and derived indices, were correlated with grain protein contents. The grain protein content in barley was correlated strongly (r>0.80) with bands 2, 4 and 5 of the Landsat scene, first principal component, and the tasselled cap brightness and greenness indices. Similarly, wheat protein content was well correlated (r>0.75) with the near infrared band (band 4) of the Landsat scene, first principal component, and the tasselled cap brightness, greenness and wetness indices. The band 3 (near infrared band) of the ASTER image, captured well after flowering, was moderately correlated (r<0.5) with the protein content of the wheat. However, the grain protein content in sorghum was found poorly correlated (r<0.20) with Landsat image bands and indices. Results indicate that it may be possible to use certain bands and indices of the satellite images, captured around the time of flowering, to predict grain protein content of barley and wheat crops

Delineation of Management Zones using Multiple Crop Yield Data

Most agricultural fields naturally have within-field variations that may require site-specific attention for optimum crop performance. These variations are often contiguous, extensive and not easy to manage since every spot in a paddock is unique. Delineating a paddock into a few management zones is therefore a practical management approach. In this study, yield maps of various crops and seasons were used to delineate management zones. Map standardisation and the application of geographic information systems (GIS) were necessary to combine various yield maps for management zones delineation. A user-defined fuzzy set membership function was employed to standardise yield maps. The membership function used control points derived from the percentile calculation to rescale yield data continuously between 0 and 1. Map standardization and processing was performed within Idrisi-32 GIS and image processing software program. Standardised maps were combined within raster GIS to identify areas of low, medium and high yield performances. The classified areas were identified as management zones requiring different level of management attention. It was found that the continuous rescaling of yield data, using percentile based control points, was suitable to standardise yield maps. This process derived control points from within the yield data and minimized the influences of extreme yield values. Overlaying standardised yield maps to identify areas of low, medium and high yield potential was a straightforward process within GIS. The investigation revealed that most area performed moderately and the areas requiring highest management attention were around the periphery of the investigated paddock

Relating Satellite Imagery with Grain Protein Content

Satellite images, captured during the growing seasons of barley, sorghum and wheat were analysed to establish a relationship between the spectral response and the harvested grain protein content. This study was conducted near Jimbour (approx. 151 degrees 10'E and 27 degrees 05'S) in southern Queensland. Grain protein contents of the geo-referenced samples, collected manually during the harvest, were determined using a laboratory-based near-infrared spectrophotometer. Grain protein contents in grain varied between 7.4 - 15.2% in barley, 6.2 - 10.6% in sorghum and 13.1 - 15.6% in wheat. The Landsat images of 18 September 1999 (a week after barley flowering), 5 March 2000 (three weeks before sorghum harvest), and 15 August 2001 (two weeks before wheat flowering) were analysed. Additionally, an ASTER image of 24 September 2001 (three weeks after wheat flowering) was also examined. Digital numbers, extracted from raw image bands and derived indices, were correlated with grain protein contents. The grain protein content in barley was correlated strongly (r>0.80) with bands 2, 4 and 5 of the Landsat scene, first principal component, and the tasselled cap brightness and greenness indices. Similarly, wheat protein content was well correlated (r>0.75) with the near infrared band (band 4) of the Landsat scene, first principal component, and the tasselled cap brightness, greenness and wetness indices. The band 3 (near infrared band) of the ASTER image, captured well after flowering, was moderately correlated (

Degree of site suitability measurement in a GIS: the effect of various standardization methods

Suitability analysis is performed to identify sites (usually grid cells or pixels) suitable for a specific purpose so that management decisions can be made in a site-specific manner. However, sites identified as suitable are rarely equally suitable in the real world. Measurement of the degree of site suitability (DoSS) is therefore crucial to be able to manage sites in a truly site-specific manner. Conventionally, site suitability analysis is performed using weighted linear combination (WLC) of standardized input factors within Geographic Information Systems (GIS). Input factors used in such analysis can be standardized in a number of different ways. The method of standardization used in the analysis could have varying effects on the DoSS measurement. However, it is yet to be assessed and quantified. Therefore, the objective of this study was to quantify the effect of various standardization methods on the DoSS measurement. In this study, the DoSS of agricultural field was measured for site-specific application of animal waste as fertilizer. Seven input factors were used in the analysis. They were standardized using a) Boolean logic, b) discrete classification, and c) continuous rescaling methods. The Boolean logic method of standardization classified factor attributes as either ‘suitable (with class weight of 100)’ or ‘unsuitable (with a class weight of zero)’. The discrete classification method of standardization grouped attributes in up to five classes of approximately equal class size. These classes were weighted with equally-incremented class weights that added up to 100. The continuous rescaling method of standardization rescaled the range of attributes in a suitability value of 0 to 100. Standardized input factors were combined respectively using a WLC model to produce composite suitability maps. The DoSS of the composite maps were assessed using weighted average (WA), coefficient of variation (CV), and value range (VR) parameters. Standardization using Boolean logic method was of no consequence since it did not produce different degrees of site suitability. All suitable grid cells were equally suitable (i.e. WA= 700, CV=0 and VR=0). The discrete classification method of standardization produced diverse suitability values with weighted average ranging between 221.9 (CV=6.3 & VR=100) and 700 (CV=0 & VR=0) depending on the number of classes. This has highlighted the measurement inconsistencies of this method of standardization. Further investigation is therefore essential to quantify the effect of discrete classification method of standardization on the DoSS measurement. The continuous rescaling method produced a DoSS map with a WA of 419.05 (CV=8.04 & VR=332). This method of standardization is more consistent in the DoSS measurement and hence potentially useful for future DoSS assessment. However, there is a need to further assess the effect of rescaling using different attribute endpoint values on the DoSS measurement

Enabling effective and inclusive learning opportunities with software-based remote access laboratories

Practical or laboratory-based learning activities are an important part of engineering and surveying education. Offering such activities to distance education students is both difficult and expensive. Remote Access Laboratory (RAL) systems are gaining popularity to provide students with access to on-campus rigs or hardware. Such RAL systems are equally versatile in providing on-campus software access to distance students. In the discipline of Surveying and Spatial Science, the RAL system is being used as an avenue for providing Geographic Information System (GIS) software access to distance students. In this study, the effectiveness of RAL based software activities in supporting student learning is investigated as part of a larger study involving its general use. This project investigates the research question whether RAL-based software activities can address the same learning outcomes as face-to-face practical classes. Data collected from students' discussion forum and via interviews with teaching staff members were analysed. This project provides a clear case in which the use of RAL technology has provided inclusive educational opportunities more efficiently. The key outcomes that students can achieve similar learning outcomes undertaking the activities remotely, system access and usability are critical, the learning activity needs to be supported by comprehensive learning materials and the staff effort to develop such an activity is considerable. These general results are also applicable to experiments that involve physical hardware

Peer assessment of assignment

We have appraised the effectiveness of peer assessment of assignments in aiding student learning at the University of Southern Queensland. Each student was randomly allocated two peers’ assignments for double-blind assessment. A marking rubric was provided. More than 95% of the class participated in the process. Students’ peer-assessment work was evaluated by the instructor. Over 80% of the students assessed their peers satisfactorily. Students' learning experiences, attitudes and behavior towards the peer assessment system was surveyed. More than 60% of the students considered peer assessment a useful learning tool. However 25% remained unconvinced. Most of these students either fully or partially subscribed to William Perry's position of 'dualism'. About 55% found the feedback from their peer's useful. Surprisingly, >69% of the students believed that the peer assessment had nothing to contribute towards a students' community of practice

Enhanced feedback - does peer assessment achieve this goal?

The students’ responses towards peer assessment of assignments system and their acceptance of peers’ assessment feedback were evaluated at the University of Southern Queensland (USQ). More than 95% of a class of 165 students participated in the peer assessment process. However, only eighty-five students responded to the voluntary survey questions. Most respondents (>60%) found the peer assessment of assignment system useful as a learning tool. Many of them (>57%) also found feedback from their peers helpful. A significant minority (~25%) remained sceptical of the peer assessment of assignment system and they did not readily accept peers' feedback. This paper analyses students' responses and concludes that the peer assessment of assignment system had no comprehensive benefit to this cohort of students. However, the analysis revealed a wider scope of the system in enhancing student learning if it is implemented correctly and if peers provided feedback considerately