Much has been written and said about the
importance of quantitative skills in the science curriculum. Science students
need to be able to understand the growing relevance of quantitative science in
addressing the critical challenges we face. Science students and graduates need to be competent in applying
mathematical and statistical reasoning when collecting, working with, and
drawing conclusions from scientific data. This was agreed nationally by
academics and relevant bodies, and articulated in the Threshold Learning Outcomes for the sciences.

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Science students need to be competent in applying mathematical and statistical reasoning when collecting, working with, and drawing conclusions from scientific data |

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**Student views of quantitative skills**

The good news is that science students also
see the importance of quantitative skills. Students told us so in a recent survey involving 400 graduating science students. When asked about various skills in the
science curriculum, 89% agreed that quantitative skills were important, but only 67%
thought they improved them over the 3 years of their science studies.

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**Mathematics under preparedness**

The biggest challenge faced by science
faculties is that we are taking in less mathematically literate students. The
issue is complex. Very often the blame is put on the school system and their
teachers. But universities are partly to be blamed for this. By removing or
lowering the mathematics prerequisites for science courses, we have sent the message that maths is not really
needed. Consequently less students take maths at school, and those who do take the
easier maths that will get them a higher ATAR.

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**The place of quantitative skills in the
curriculum – reality check**

So, how do students develop the necessary
quantitative skills in a science curriculum? What is the minimum they should
know to succeed in their studies? What teaching and assessment opportunities
are they given to catch up on what they missed out at school and further
develop their skills to reach that threshold?

These were the questions asked of academics
as part of an extension to the QS in science OLT funded project. They were work
shopped at three large universities, focusing on a number of selected life
sciences programs. We got around the table academics teaching the discipline as
well as academics teaching first year units relevant to the programs, including
mathematics, statistics and chemistry.

We mapped out the presence of quantitative skills in the curriculum.
Most importantly, we engaged in a frank conversation. Here is what we found – most of it applicable
beyond the life sciences:

The quantitative skills expected of students to undertake higher year
life science units of study are much simpler than what is taught in a typical first
year introductory-level statistics unit.

Quantitative skills are widely present and assessed in majors. We had no
difficulties in ticking the boxes to indicate their presence across units at
all year levels. The mapping of quantitative skills looked healthy!

But this does not mean that all students learn and develop these skills
to meet the desired threshold. Learning
is only superficial for many students.

Assessment structures are such that students can avoid learning
quantitative skills. These skills are largely present in lab activities and
reports, and the weaker students can rely on their peers. Students can still pass their assessment
tasks even if the application of quantitative skills is not present or
incorrect.

Completion of first year quantitative unit prerequisites are generally
not required for higher year science units, even when that is an option
available within the course structure.
Fear that such prerequisites would attract less students (and hence have
an impact on resources) seems to be the driver of these choices.

Teaching staff put student mathematical under preparedness in the too
hard basket. They give up on the students who “cannot handle maths” and turn a
blind eye on the issue. And so the avoidance of maths continues at university
level.

The mathematical language used by mathematicians (who normally teach
foundation maths/stats units) and discipline academics. This creates confusion
in the weaker students who find it even more difficult to use quantitative
skills in a different context. Conversation between the service departments and
the serviced disciplines could easily solve this.

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**Where to from here?**

There is much to be
done to equip our science graduates with the quantitative skills we all agreed
they should have. Of course, life would be much simpler if our students came to
university with a sound mathematical skill base.

We can work on that
front to make it happen. But each of us with responsibility of teaching science
students should put in practice what we preach, in our own classrooms.

Our Chief Scientist has warned repeatedly that we need to change the attitude to mathematics in the
education system—if the trend is not turned around Australia faces a bleak
future. We as science educators all share the responsibility to address this
problem.

*Cristina Varsavsky is the Deputy Dean in the Science Faculty @CVarsarvsky*