Encouraging students' deep learning through assessment
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BACKGROUND It is important to engage students in deep learning in order to achieve the desired course objectives. Engineering students are required to study a wide range of subjects to develop the skill set required for their chosen career. These include technical skills that are heavily reliant on mathematics and natural sciences while other subjects are more aimed towards developing their soft skills, for example; communications and management skills. Numerical and Data Analysis is often seen and approached as a technical course which requires extensive mathematical and programming skills but is rarely seen as the place to develop the communication skills of engineering students. PURPOSE This paper provides observations on how changing the assessment regime encouraged students' engagement in deep learning. DESIGN/METHOD A new assessment approach was introduced in the 2012 offering of the Numerical and Data Analysis course which favoured formative assessment and placed more emphasis on developing the critical thinking and independent learning skills of students. To assess the performance of the new assessment approach, a comparison of key learning performance indicators is conducted on the 'before' and 'after' the introduction of the new approach. RESULTS Comparing the results obtained from the course offering before and after the introduction of the changes indicates that the approach has enhanced students' satisfaction in the course, increased retention rate and reduced failure rate. CONCLUSIONS Assessment items offer opportunity to link theoretical subjects to more practical engineering skills, hence engaging students in deep learning.
Proceedings of the 2013 Australasian Association of Engineering Education (AAEE) Annual Conference
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