This theme explores the potential of technology and learning analytics for enhancing teaching and learning practices.

Learning analytics

Learning analytics aims to analyse data on students for the purpose of understanding and improving student learning, taking into consideration the diverse needs of the student population. Within learning analytics, the development and evaluation of learning analytics dashboards have received significant attention.

The ITaLI Learning Analytics team has developed a course-level tool called Course Insights that empowers educators to gain insights and act on student data to enhance student learning and experience across the course life-cycle at scale. In particular, Course Insights enables instructors to reach out to students to provide rich, personalised and actionable student feedback tailored to their learning needs. A key feature of Course Insights is that it incorporates pedagogical and data-driven approaches to assist educators in identifying students in need of attention. A recent paper presenting this approach received the Best Short Paper Award at the 10th International Conference on Learning Analytics and Knowledge (LAK20).

If you are interested in research in learning analytics, or would like further information about the presented work, please contact Dr Aneesha Bakharia or Dr Hassan Khosravi.

Top of page

Artificial intelligence in education

At a time of heightened interest in online learning and Artificial Intelligence (AI), there is a growing consensus that applications of AI in education have a transformational impact on the educational landscape.

Our research focus and strengths are in the design, implementation, validation and delivery of technological solutions that use AI in enhancing student learning and experience at scale. The team has developed an adaptive learning platform called RiPPLE where partners academics and students can create and evaluate high-quality learning resources. Using explainable AI algorithms, the platform can also recommend personalised activities to students based on their mastery level. Demonstrated to improve learning, RiPPLE has been used in more than 100 course offerings, reaching over 20,000 students. To date, over 20 peer-reviewed articles have been published on various aspects of RiPPLE, advancing knowledge on ethical use of AI in education, learner models, adaptive learning, feedback literacy, learnersourcing, educational recommender systems, explainable and interpretable use of AI in education and peer learning.

If you are interested in research in AI in education, or would like further information about the presented work, please contact Dr Hassan Khosravi.

Top of page

AI assisted peer learning

A rich body of literature in psychology and education increasingly recognises peer learning as an important form of learning, feedback and assessment. While the benefits of peer and social learning have been well established and widely accepted, methods for their effective facilitation among large communities of diverse learners remains a challenge.

Our research in the field of peer learning has focused on the use of educational technologies to:

  1. help students identify and connect with like-minded peers that have the same availability and learning preferences (see example paper)
  2. engage students in peer feedback and assessment to help them develop evaluative judgement, the capability to make decisions about the quality of work of oneself and others (see example paper)
  3. create novel approaches to identify the reliability of peer assessments provided by individuals (see example paper).

If you are interested in research incorporating educational technologies to support peer learning, or would like further information about the presented work please, contact Dr Hassan Khosravi.

Top of page

Online and blended learning

The COVID-19 pandemic and associated requirements for social distancing created a watershed moment for online learning. UQ had been heavily investing in blended learning prior to the pandemic, with its effects leading to a marked acceleration of digital innovation. ITaLI, in collaboration with colleagues across UQ, is continuing to investigate evidence-informed approaches to high-impact learning experiences for students in online and blended modes. This research provides a foundation for UQ’s shift to more digitally-enhanced learning experiences for students and contributes to the international discussion about the future of higher education.

If you are interested in research in blended and online learning and/or would like further information about this research please contact A/Prof Jason Lodge.

Top of page