Charles Sturt University makes its underpinning technical curriculum available to its students using an on-demand online system they call their Topic Tree. The tree is a directed acyclic graph where nodes represent topics to be learned, and edges represent the prerequisite relationships that exist between the topics. Branches on the topic tree represent concentrations in an area of knowledge, sub-branches (water quality, fluid mechanics, etc.) represent distinct subsets of knowledge - specialty. Delivery of the technical content is in three-hour modules, and students are free to choose the order in which they engage with these topics.
Previous work has identified that students engage with the on-demand curriculum much as they engage with on-demand entertainment platforms such as Netflix, completing long sequences of topics with short time periods between them – the traditional “binge” model of consumption.
This paper presents a more fine grained analysis of students’ pathways through the topic tree, focusing on the distance between successive topics completed by the students. Students’ progress is characterised in a three dimensional framework – forward distance, backward distance and time.
In general, pathways through the tree fall into one of four patterns:
• Forward movement along a branch or sub-branch of the tree, either sequentially (distance = 1) or skipping over topics (distance > 1)
• Revision of prior topics along a branch or sub-branch of the tree (backward distance of N)
• Revision of the same topic on a branch or sub-branch (both distances = 0)
• Switching to a different branch of the tree (backward distance to the junction of the branches combined with a forward distance along the new branch)
These pathways are also coupled with the time elapsed between the two consecutive topics.
Different students engage with the topic tree using different combinations of these approaches. This paper will identify these different combinations, and show how these approaches correlate with success and progression throughout the course.
Jim Morgan is the father of two daughters and the spouse of an engineer. Before joining Charles Sturt University as Professor of Engineering and Inaugural Course Director in 2015, he was on the faculty in civil engineering at Texas A&M for over 30 years. Jim has been active in the freshman engineering program at A&M for nearly 20 years; was an active participant in the NSF Foundation Coalition from 1993 to 2003; also has received funding for his engineering education research from the Department of Education FIPSE program and from the National Science Foundation CCLI program.
He is active in the American Society for Engineering Education, is past chair of the Freshman Programs Division, and has served on the FIE steering committee. In addition to his teaching in engineering, Jim served several years as Co-Director of the Eisenhower Leadership Development Program in the Center for Public Leadership at the George Bush School of Government and Public Service; and also served as director of Aggie STEM with funding from the Texas Education Agency and the Texas Higher Education Coordinating Board.
Professor Euan Lindsay is a Mechatronic engineer, a discipline that integrates computers, electronics and physical hardware. Prof Lindsay’s background is in Remote laboratories, investigating whether remote and simulated access alternatives to the traditional in-person laboratory experience can provide the high quality learning outcomes for students.
Prof Lindsay’s work in Remote and Virtual laboratory classes has shown that there are significant differences not only in students’ learning outcomes but also in their perceptions of these outcomes, when they are exposed to the different access modes. These differences have powerful implications for the design of remote and virtual laboratory classes in the future, and also provide an opportunity to match alternative access modes to the intended learning outcomes that they enhance.
Prof Lindsay is the Foundation Professor of Engineering at Charles Sturt University. His research interests centre largely around online learning – the use of remote and virtual laboratories, MOOCs and other methods for making learning asynchronous, and data analytics for promoting student learning.
Prof Lindsay was the 2010 President of the Australasian Association for Engineering Education. He is a Fellow of Engineers Australia, and a Fellow of the UK Higher Education Academy. Prof Lindsay was the recipient of a 2007 Carrick Award for Australian University Teaching. In 2005 he was named as one of the 30 Most Inspirational Young Engineers in Australia.
Dr. Colm Howlin is the principal researcher at Realizeit and leads the research and analytics team. He has been with the company since it was founded over 10 years ago. He is responsible for the development of the Adaptive Learning Engine within Realizeit and the Learning and Academic Analytics derived from learner data. Colm has a background in applied mathematics, earning his B.Sc. and Ph.D. in applied mathematics from the University of Limerick. He was a Research Fellow at Loughborough University in the UK. Colm has over 10 years’ experience working on research, educational data, analytics, and statistical analysis, including spending time as a consultant statistician before joining Realizeit.
http://orcid.org/0000-0002-2267-3674
Delft University of Technology
[biography]
Dr Van den Bogaard is director of studies and assistant professor of Science Education and Communication at Delft University of Technology, the Netherlands.
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