“The state of the mathematical sciences and related quantitative disciplines in Australia has deteriorated to a dangerous level, and continues to deteriorate.” - Professor Gavin Brown, 2009
Simply stated, quantitative skills relate to numbers and how they are used for measuring, recording and analysing data for instances, or performing mathematical or statistical calculations. Quantitative skills (QS) provide an important foundation in many areas of higher education including Science (ie Physics, Chemistry, Biology), Engineering and Mathematics.
Quantitative skills (QS) are essential in science
Recent research suggests that the level of QS in science need to be significantly improved. As a starting point, the QS in Science project will collaborate with Australian and international universities, looking for science programs that produce better skilled science graduates.
The QS in Science project will promote and support strategic change in higher education via the enhancement of learning and teaching in science and mathematics. This will be achieved by articulating contemporary undergraduate curriculum models that are innovative and future-looking, and which meet the needs of students, industry and society. The movement to transform science education, to better reflect the interdisciplinary and quantitative nature of modern science, requires a ‘whole of program’ approach with QS as an essential component. However, institutions continue to struggle to understand how to better integrate QS across the undergraduate science curriculum.
Funding and support
Recent reviews have highlighted the ubiquitous nature of the problem of integrating quantitative skills into undergraduate science. Finding a solution will require wide-ranging involvement of industry, professional bodies and universities from the mathematics, science and education communities. The QS in Science project has the support and involvement of the:
- Australian Council of Deans of Science
- Federation of Australian Scientific and Technological Societies (FASTS)
- Higher Education Research and Development Society Australasia (HERDSA)
- International Commission on Mathematical Instruction (ICMI)
- Mathematics Education and Research Group Australasia (MERGA)
- International Association of Statistics Education (IASE)
- Research Corporation for the Advancement of Science
The QS in Science project was funded by Australian Learning and Teaching Council from 2010-2012.
The QS in Science project was organised around four key outcomes:
Outcome 1: Curriculum Structures
“Whilst the quantitative skills deficit of many students embarking upon university science programmes is well-recognised and is an international problem, institutions have struggled with how best to integrate quantitative skills into science curricula.” – Professor Vicki Tariq, University of Central Lancashire, UK
International benchmarking of undergraduate science curriculum structures which effectively integrate quantitative skills.
Timeframe: late 2010 through mid 2011. Completed: See Case Studies
Outcome 2: Model for Curricula Change in Higher Education
” Many groups, nationally and internationally, are struggling to come up with a model for increasing and reinforcing the quantitative and mathematical skills of students in a range of areas, including science.” – Professor Peter Adams and Professor Phil Poronnik, ALTC Joint Fellowship (2007-2009)
Understanding how effective educational change occurs in science higher education is crucial. Institutional curricula change processes can be complex. Our conceptual framework is based on the work of Fullan (2007), as illustrated below.
Timeframe: early 2011 through mid 2011. Completed: See Case Studies
Outcome 3: Framework for Academic Change
“ Amid the myriad of ‘calls for action’, it is clear that science and mathematics departments will need to work across traditional disciplinary boundaries to address this issue.” – Dr. Shaun Belward, Senior Lecturer of Mathematics, James Cook University, 2009
Implementing any form of organisational change is a potentially challenging task. In this phase, we plan to develop a framework for cross-disciplinary academic collaboration, supporting adaption, adoption and evaluation of educational approaches/resources.
A template will be developed based on Rogers’ (1995) conceptual framework, as illustrated below:
Timeframe: mid 2011 through mid 2012. Completed: See Project Report
Outcome 4: Dissemination
The QS in Science International Symposium is being planned for late 2012 at the University of Queensland, and will bring together leaders and practitioners from the disciplines of science, mathematics, statistics and education around common goals of improving undergraduate science curricula and enhancing science students’ quantitative skills.
The forum will provide opportunities for science program leaders to gain valuable insight into models for curricular change across science programs as well as opportunities for practitioners to share subject-specific innovations around the implementation of new resources.
Timeframe: 2012. Completed: See Forum Website, Project Report presented to Australian Council of Deans of Science (ADCS), and presentation video from ACDS Forum and Australian Conference on Science and Mathematics Education (ACSME) conference.
Special Edition dedicated to QS in Science
While implementing the activities related to curriculum structures and models for curriculum change, the project team will identify exemplar case studies that could become scholarly academic articles. The International Journal for Mathematical Education in Science and Technology, a highly rated journal, dedicated a series of articles to QS in Science in later 2013.
Timeframe: 2012. Forthcoming: (September 2013) at IJMEST
A highlight of QS in Science International Symposium will be the launch of QS in Science Network, an initiative designed to strengthen and expand relationships and to sustain momentum of the QS in Science project beyond 2012. While there are strong networks in mathematics, statistics and sciences, these networks are firmly based in their respective disciplines – we seek to create a cross-disciplinary network dedicated to the enhancement of QS in Science.