Online tools adapted from industry for teaching agricultural science at university

Agricultural professionals with contemporary knowledge and skills are critical to ensuring that new practices are adopted in farm businesses. However, only 8% of the agricultural workforce has a tertiary qualification compared with 25% of the broader population, with an estimated four jobs available for every tertiary agricultural graduate (Pratley and Acuna, 2015). Consequently, this raises two issues. Firstly, that the learning outcomes of graduates from Australian universities reflects the technology and data needs of contemporary farming practice. Secondly, that more students are encouraged to consider a future career in agriculture.

The SMARTfarm Learning Hub ‘the Hub’ aims to address these issues by developing learning module that use authentic farm data in a real industry technology learning system (RITLS) (Trotter et al. 2016). The Hub is a collaboration between seven universities, each with a farm representing a varied range of agricultural enterprises and geographical locations.

Here we report on the development and delivery of an RITLS based on the online decision support platform Pasture.io. Using real-time data from dairy farms in north-west Tasmania, the tool can assist users to understand the complex nature of pasture management and dairy feed rations. The tool allows users to explore both tactical (short-term) and strategic (long-term) on-farm decisions. Supporting resources include a lesson plan, video and notes for both students and teachers for a 3-hour practical session, in the unit KLA211 Pasture and Animal Science to 64 students in semester 2, 2017.

The RITLS module was evaluated as part of an action research cycle (McTaggart, 1991), where most students (75%) regarded the practical to improve their knowledge of contemporary issues in agriculture. Similarly, a high number of respondents (79%) agreed or strongly agreed that the practical helped them to understand how to select and apply an appropriate tool to solve an agricultural problem.

The next steps for the project are to revise the practical for delivery in 2018 and, as appropriate, develop an assessable component aligned with the unit learning outcomes. Project partners have expressed an interest in using the Pasture.io practical in relevant courses.