In learning analytics, we want to take data about our students and teachers and use this to help us understand each other and to make our learning and teaching experiences better. Rather than just collect and focus on some of the measurements that we already know about attendance, grade performance, and so on, analytics research by the CSER group looks for key indicators that we can use to measure the impact of change in pedagogical practice. Analytics is more than simple statistics, because it requires a detailed investigation of qualitative, quantitative and behavioural aspects (such as cognitive biases) to develop truly useful analytical processes.
Work resulting from a CSER student project, led by Daniel La Vista, has been accepted for ITICSE 2017. Daniel La Vista, Nickolas Falkner and Claudia Szabo, Understanding the Effects of Intervention on Computer Science Student Behaviour in On-line Forums. Accepted for ITiCSE 2017.
Work from one of our previous CSER student projects, led by Katrina Le and Hamid Tarmazdi, has been accepted for publication at Latice 2017. This work explores how text processing techniques can be used to assist educators in identifying students who need assistance, by identifying unanswered questions, or questions that are expressing strong emotion, and […]
Early results from our new project exploring discourse analysis in MOOC videos with the aim of improving learner engagement has been accepted for the upcoming LAK conference. This is a great result and one that reflects some of the new directions in learning analytics based on MOOC-level data analysis. Thushari Atapattu and Katrina Falkner, Discourse Analysis […]
We have commenced a new project in the area of learning analytics exploring how we can better understand how students engage in student discussion forums, with the aim of building models that describe and inform educator interventions. Early work in this new project has been accepted as a Work in Progress paper for the upcoming […]
Our work, funded by Google, explores how we can support personalised learning in MOOCS by automatically classifying and labelling discussion forum topics. This work helps learners navigate large amounts of discussion data, by helping them focus on the topics that are of interest to them, and helps academics by allowing them to see those topics that […]
Our first results from our Google Research Grant exploring personalised learning at scale has been accepted as a Work in Progress paper at the upcoming Learning@Scale conference. We are excited to be able to share some of our preliminary results in such a forum, and to be able to share our thoughts on where this […]
An extended version of Thushari Atapattu’s conference paper from CSEDU has recently been published as a chapter in a special edition of the book series Communications in Computer and Information Science. The initial version of this paper was published at CSEDU in 2014, and received a nomination for Best Paper Award! T. Atapattu, K. Falkner and […]
Congratulations to Thushari Atapattu! A paper led by Thushari on her thesis work has been nominated for the Best Paper Award at the AIED 2015 conference. Educational Question Answering Motivated by Question- Specific Concept Maps by Thushari Atapattu, Katrina Falkner, Nickolas Falkner
CSER is pleased to announce that our work on developing a teamwork learning analytics dashboard for analysing and assessment online collaborations for Computer Science and Software Engineering students has been accepted for publication in ACM Transactions on Computing Education. Our Teamwork Analysis Dashboard builds upon earlier work where we developed a qualitative analysis framework for […]
Thushari Atapattu has had some more recent results from her thesis work accepted for publication in the upcoming AIED Conference. Question answering (QA) is the automated process of answering general questions submitted by humans in natural language. QA has previously been explored within the educational context to facilitate learning, however the majority of works have […]