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Graduates of the Faculty of Science will be able to create new knowledge and understanding through the process of research and inquiry.

Critical Thinking
Critical thinking is accepting nothing at face value, but rather examining the truth and validity of arguments and evaluating the relative importance of ideas. Critical thinking includes evaluating and weighing different sides of an argument, applying reason and logic to determine the merits of arguments, and drawing and evaluating conclusions from logical arguments and data analysis. Critical thinking requires background skills such as imagination and creativity, logic and reasoning, conceptual thinking, reflection and feedback.

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Problem Solving
Problem solving is the ability to identify, define and analyze problems, to create solutions and evaluate them, and to choose the best solution for a particular context. It requires imaginative and innovative thinking to find new ways to approach a problem, analytical skills to examine the consequences of a particular solution, and reasoning skills to weigh one solution against another. A common form of problem solving in science is experimentation. Problem solving involves the background skills of imagination and creativity, logic and reasoning, data collection, conceptual thinking, reflection and feedback, and scientific experimentation.

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Analysis
Analysis is the ability to gather relevant data and information and apply methods of synthesis, critical thinking and data reduction to locate and understand patterns or connections in that information. Scientific analysis often requires mathematical techniques to manipulate data, such as graphing experimental results or using statistical tests to examine differences between sets of data. Analysis requires the background skills of data collection, data
analysis
, reflection and feedback, scientific experimentation.

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Dissemination
Dissemination is communicating to others the purpose and outcomes of research. It requires the ability to summarise information, explain the aims, motives, results and conclusions of the research, and tailor the communication to the needs and knowledge level of a particular audience. Dissemination requires the background skills of imagination and creativity, logic and reasoning, conceptual thinking, reflection and feedback.

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Background Skills

Imagination and Creativity is:

  • searching for different approaches to a problem or situation (such as adapting technology for a novel purpose like using medical technology on plants)
  • looking for alternatives to common or accepted methods and solutions.
  • trying to examine issues from a different point of view (such as seeing an argument from another person's perspective).

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Logic and reasoning is:

  • understanding the structure of logical arguments, including deductive and inductive reasoning
  • assessing the logical basis for scientific claims and conclusions (such as deciding whether you agree with the conclusions drawn in a scientific paper, based on the evidence given)
  • drawing conclusions from scientific arguments or analyses (for example, making valid generalisations or predictions from experimental data).

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Data collection is:

  • gathering data (for example through carrying out experiments, surveys, focus groups, interviews, literature reviews)
  • designing a data collection tool (for example, planning an experiment or constructing a survey).

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Data Analysis is:

  • identifying an appropriate method (mathematical or otherwise) for interpreting and manipulating data.
  • applying techniques of statistical analysis, including using statistics in research and the statistical analysis of surveys (such as identifying and applying an appropriate statistical test of significance)
  • awareness of the limitations of analysis techniques (for example, understanding the assumptions behind a statistical analysis, and examining whether your data fit these assumptions)
  • forming appropriate conclusions from results of analysis.

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Conceptual thinking is:

  • breaking a big issue into smaller, manageable parts (for example, breaking an experimental investigation into a series of smaller measurements)
  • identifying concepts and ideas relevant to a problem, synthesizing concepts and available data to construct a solution
  • making judgements about the value and relevance of ideas and information (for example, deciding to ignore a particular factor because it contributes only a small amount to the overall problem).

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Reflection and feedback is:

  • thinking about what you have done, what you might have done differently, how you feel about it, and how you might change it to improve your learning (for example, reflecting on the outcomes of a research project and deciding on a different course of action for next time)
  • using insight gained through reflection to improve your own or others' work or situation (for example, watching others perform and offering feedback on the way they are tackling a problem).

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Scientific Experimentation is:

  • identifying and designing an appropriate experimental procedure understanding the limitations and scope of an experimental design (for example, sample sizes and measurement uncertainties).

 

 
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