Keynotes and Speakers for ITx Rutherford
Sunitha Prabhu is a Senior Academic Staff member at the Centre for Information Technology, Waikato Institute of Technology (Wintec).
Sunitha has over 20 years of experience teaching Information Technology in New Zealand. She specialises in teaching Mathematics, Programming, Databases, and supervises IT projects and internships.
This paper outlines the design and implementation of an educational approach to cultivate student leadership in a flipped classroom by facilitating a positive learning relationship between the learner and the facilitator through shared leadership and flexible assessments.
The aim is to enable learners abandon the notion of the teacher being the ‘sage on the stage’ and adapt to learning accomplished through interaction. Such an environment enables learners to actively contribute towards their success by taking ownership of their learning. The paper describes the findings of a learner-centered educational approach implemented for an IT Mathematics module run in the flipped classroom model. Student performance over five consecutive occurrences of the module was compared – the first three were prior to implementing the said approach; and the last two implemented the student leadership approach. Early qualitative and quantitative results of the student leadership approach indicate improved student performance and student satisfaction. Students have requested that this model be implemented in more modules.
In recent years, there has been a push in the Artificial intelligence (AI) field to simplify the application of machine learning so that its use can be more widely adopted. While this reduces barriers to entry for AI and machine learning, they also introduce the risk that persons or organisations with insufficient expertise will have the ability to use these systems to make decisions that have a significant impact on society based on discriminatory factors. Implementers and decision-makers need to have a good understanding of the features that the system might use and infer from to make predictions, and how these can affect their stakeholders.
In this paper, we outline the risks of this phenomena occurring in a specific case – the application of machine learning applied to secondary school student grades. We demonstrate that naïve approaches can have unanticipated consequences and can generate predictions based on discriminatory factors such as gender or race. The impact of the application of such flawed decisions in matters such as awards, scholarships etc. could entrench detrimental bias in the education systems.
Knowledge on Database systems is essential in qualifications related to Information Technology, Information Systems, Computer Science, and Software Engineering.
It is an expectation from the industry that graduates with these qualifications are competent with working on database systems. For learners to be proficient in the concepts of database systems, a good understanding of SQL and PL-SQL is core. However, many learners perceive it to be difficult to grasp even the basic concepts, especially in a flipped classroom model.
In this paper we reflect on the challenges faced in teaching and learning SQL and PL-SQL and we present the factors that contribute to these learning difficulties. We review the literature of teaching methods that can be applied to overcome these perceptions and difficulties. The focus is to enable learners to gain the necessary knowledge and skill to create scripts in a professional manner. We aim to describe a teaching approach to improve student engagement and completion rates while providing a holistic learning experience.