Hello! I’m Shibani, a Doctoral Researcher in Learning Analytics at the Connected Intelligence Centre, University of Technology Sydney, Australia. As modern computing technologies progress towards automation and improved efficiency, there is increasing opportunity to harness them for social good. A computer science engineer by training, I like to develop applied technologies that can transform real-life practices. My research is in the field of ‘Learning Analytics’ where we apply analytic techniques to understand and improve educational practice. In my work cutting across the fields of data science and education, I build computational systems making use of data analytics, (text analytics in particular) to improve teaching and learning contexts. I study how these technologies are integrated in the classroom to examine their potential impact on students. This is because I believe that the technical advancement by itself is not of immense value for learning, until and unless, its actual usage is studied in the educational context.
My doctoral research (ongoing) under the supervision of Simon Buckinghum Shum and Simon Knight is on ‘Writing Analytics’ which makes use of analytic techniques to improve student writing. This includes developing user-centered tools that can provide automated feedback on students’ writing at scale, and making use of analytics techniques to study the process of writing. I work on finding effective forms of such formative feedback and developing learning designs that integrate these automated feedback tools into the curriculum. I’m also studying ways in which human intelligence can augment machine intelligence, and vice versa. I’m exploring the combination of peer feedback and automated feedback in the learning design, hoping that it bridges the human context gap in automated feedback and enables peer learning where students simultaneously learn and contribute to other students’ learning with the help of automated tools.
In my previous work at the National Institute of Education, Nanyang Technological University, Singapore, I worked with Dr. Elizabeth Koh to explore teamwork, which is an essential skill for a 21st century learner. This led us to a better understanding of teamwork in a collaborative problem-solving context, with interventions designed for school students to improve their teamwork and collaboration. During this work, I explored computational approaches to study teamwork, and made use of text mining and machine learning techniques to automatically identify teamwork dimensions from online chat logs of students.
A list of publications from my work can be found in the Research section of this blog.