Life After MOOCs: online science education needs a new revolution

Professor Pavel Pevzner, Department of Computer Science and Engineering, University of California at San Diego

Co-presented by the Education Portfolio and School of Mathematics and Statistics, Faculty of Science

23 March, 2017

Universities continue to pack hundreds of students into a single classroom, despite the fact that this ‘hoarding’ approach has little pedagogical value. Hoarding is particularly objectionable in STEM courses, where learning a complex idea is comparable to navigating a labyrinth. In the large classroom, once a student takes a wrong turn, the student has limited opportunities to ask a question, resulting in a learning breakdown, or the inability to progress further without individualised guidance.

A recent revolution in online education has largely focused on making low-cost equivalents of hoarding classes, as many MOOCs are mirror images of their offline counterparts. This is one of the reasons why prominent computer scientist Moshe Vardi published an editorial in the Communications of the ACM expressing concerns about the pedagogical quality of MOOCs and including the sentiment, “If I had my wish, I would wave a wand and make MOOCs disappear”.

Professor Pavel Pevzner from the University of California, San Diego, shares the concerns about the quality of early, primitive MOOCs, which have been hyped by many as a cure-all for education. At the same time, he believes that much of the criticism of MOOCs stems from the fact that truly disruptive educational resources have not been developed yet. He proposes to transform MOOCs into a more efficient educational product called a Massive Adaptive Interactive Text (MAIT) that can prevent individual learning breakdowns and even outperform a professor in a classroom.

For this special Sydney Ideas event, Pevzner argues that computer science is a unique discipline where this transition is about to happen and describes the first steps towards transforming a MOOC into a MAIT that has already outperformed teachers. He argues further that the future MAIT revolution, in difference from the ongoing MOOC revolution, will profoundly affect the way we all teach.



Professor Pavel Pevzner is Ronald R. Taylor Professor of Computer Science and Engineering and Director of the NIH National Center for Computational Mass Spectrometry at University of California, San Diego.

He was named Howard Hughes Medical Institute Professor in 2006 and was elected the Association for Computing Machinery (ACM) Fellow (2010) for "contribution to algorithms for genome rearrangements, DNA sequencing, and proteomics”, International Society for Computational Biology Fellow (2012), and European Academy of Sciences (Academia Europaea) in 2016. Pevzner has authored textbooks Computational Molecular Biology: An Algorithmic Approach, Introduction to Bioinformatics Algorithms (jointly with Neal Jones) and Bioinformatics Algorithms: an Active Learning Approach (jointly with Phillip Compeau).

In 2015, jointly with Phillip Compeau, he developed a Bioinformatics specialisation on Coursera (a series of 7 courses) that is now being transformed into a MAIT and that has already have over 300,000 enrolments by the end of 2016. In 2016, he co-developed the first Algorithms specialisation on Coursera that had over 100,000 enrolments by the end of the year.