I have a keen interest in maximising opportunities for student learning in higher education. In addition to my undergraduate teaching at the University of Melbourne, I am the lead investigator on a grant from the Office of Learning and Teaching (OLT) which aims to encourage widespread adoption of student peer review in tertiary programs. Together with my colleague Mark Elgar, I am also preparing a massively open online course (MOOC) on Animal Behaviour, which will be taught through the Coursera platform.
Undergraduate teaching at the University of Melbourne
Promoting student peer review in tertiary education
Student peer review is a process whereby students review each others’ work with an aim to improving it before submitting for assessment. It is widely recognised as an effective component of learning to promote active student learning and increase satisfaction with feedback.Together with colleagues Jon Pearce and Chi Baik, I also hold a large grant from the Office for Learning and Teaching (OLT) which has as its aim to encourage the widespread implementation of student peer review through the production of resources and advice about peer review, and the availability of a nationally available online peer review tool known as PRAZE. For more information about this project, please visit the Student Peer Review website.
PRAZE is an intuitive anonymous web-based peer review system which automates and flexibly manages the entire peer assessment process. Developed in 2008 by a group of academics (including myself), PRAZE promotes effective learning by providing students with prompt and diverse feedback, engaging them in critical analysis and self-reflection. The versatility of the software allows it to be used across a wide range of disciplines for the peer-review of almost any document type. To register to use PRAZE, please visit the PRAZE website.
Animal Behaviour MOOC
Coursera is a provider of Massively Open Online Courses (MOOCs), which are free online courses that are available to anyone, in collaboration with universities and organisations from around the world. In collaboration with Professor Mark Elgar, I teach an Animal Behaviour course on Coursera. Our course explores how scientists study animal behaviour, and in particular how behaviour is shaped by the evolutionary forces of natural and sexual selection. For more information, or to enrol in the course, please visit the Coursera website.
Mulder, RA, Pearce, JP & Baik, C (2014). Peer review in higher education: student perceptions before and after participation. Active Learning in Higher Education. Full Text
Mulder, RA, Baik, C, Naylor, R & Pearce, J (2014). How does student peer review influence perceptions, engagement and academic outcomes? A case study. Assessment & Evaluation in Higher Education. Full Text
Søndergaard, H & Mulder, RA (2012). Collaborative learning through formative peer review: pedagogy, programs and potential.Computer Science Education 22: 343-367. Full text
Pearce, J, Mulder, RA & Baik, C (2009). Involving students in peer review: case studies and practical strategies for university teaching. Centre for the Study of Higher Education, University of Melbourne. Full text
Mulder, RA & Pearce, JM (2007). PRAZE: innovating teaching through online peer review. ICT: Providing choices for learners and learning. Proceedings of the 24th Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education, pp. 727-736. Singapore. Full text
Mulder, RA, Elgar, MA & Brady, D (2005). APRES: electronically managed student feedback via peer review. Proceedings of the Blended Learning in Science Teaching and Learning Symposium, 30 Sep 2005. pp 2-6. Pearson Science Teaching Award Invited Paper [peer reviewed]. Full text
Centre for the Study of Higher Education (CSHE) video resources: Engaging students in authentic peer review processes.
I have contributed several resources to the website Enhancing assessment in the Bioloigical Sciences which acts as a repository for ideas and resources for university educators:
– Peer review of research reports
– Deep learning in exams
– Temporal separation of feedback from grades
– Use of a scoring matrix to provide detailed feedback on performance