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Video: Instructional strategies are techniques instructors use to assist students in becoming independent, strategic learners. In this video , I review some of my Innovative Authentic Assessment Strategies which I use for effective teaching.
See my Effective Teaching Strategies for more on this.
Research - Action and Impact!
Research - Action and Impact!
My teaching philosophy has always been student-centred, recognising my role as a facilitator and mentor, while catering to the needs of my students. I promote student autonomy where they actively participate in life-long learning, create an interactive environment for collaboration and foster engagement. I always ask myself ‘How can I be more effective in my teaching practice?’
In courses which require statistical applications, using data to tell a story, I believe it is critical for students to develop a sense of appreciation for data analysis. Inquiry is essential in this process. My focus is to develop the students’ skills needed to advance into the working world, particularly where business intelligence is crucial in the age of Data Science.
I use innovative teaching strategies to prepare students for the real world. More recently, I have explored application-based learning, with digital tools, to optimize the learning experience. I have designed my courses to incorporate instructional approaches in two main ways:
Read on to learn more about my innovative approaches:
Research in Action – where critical reflection is used to bridge the gap between theory and practice.
For instance, students would have the opportunity to participate in a forum discussion on Statistical applications in their field. This opens the conversation to understand three central questions: What? Why? How? which gives them a perspective of working in the field as a statistician. I am also very aware of the feelings of anxiety some students feel toward Statistics and this guides me in providing additional support.
Some of the other techniques I incorporate include collaborative activities and the Flipped approach. These work quite well, particularly with graduate students and has drastically improved student engagement and performance.
Research for Impact – using application-based learning for data exploration and statistical analysis, supported by statistical software
My students, benefit from inquiry-based learning, particularly in the applications of statistical theory to real-life scenarios. I integrate weekly interactive tutorials and demonstrations to show them how to analyse statistical results for interpretation. In this way, they can make the connection between theory and research practice.
One major assessment I employ is the use of guided projects, similar to Capstone projects, where students:
investigate a problem using a data set,
develop simple statistical models,
evaluate their results with a structured critique
and discuss findings, applying key 21st. Century skills.
As a fun element, I incorporate a Mini-Research Conference Session for presentations. This mimics the style of international conferences. This creates excitement as the students experience a professional research setting. By the end of the semester, students have greater confidence when exploring data, using statistical programmes to generate results, interpreting the statistical output and discussing them in a practical way for important insights.
Basically, these instructional techniques for statistics in research, connect theory to real-world practice, and provide my students with 21st century skills which prepare them for the world of work.
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