This is one of the most powerful ideas driving MOOCs; data-driven education. Not for administrators finding out which schools perform better than others, but for course designers, teachers, and developers who continually can improve online lectures, digital content, and facilitation strategies.

We will be doing this with another 8 to 10 MOOCs this year.

via @timokos

nevver:

Land Mammals
A Taxonomy of the Collaborative Economy
— From: Web Strategist

A Taxonomy of the Collaborative Economy

— From: Web Strategist

A/B testing for teachers in edX

Probably this week or the next, edX will roll out a - I think - transformational tool for teachers: A/B testing functionality inside the course development environment. It allows teachers to do - as you might guess - A/B testing, which means testing different ‘versions’ of the course to randomized groups of students. Within one course, teachers can experiment with different types of videos, test out motivational strategies, implement psychological interventions, and see the results in (student) engagement nearly instantly and results in achievement over time. See screenshot below for an impression of the interface.

Why transformational? It enables teachers to better understand what works, how content should be created to have maximum effect, through a rather rigorous process of trying different versions to randomized groups of students. Not just the click-data can be used to determine “the best solution”, but combined with the available student data, analyses can be done to better understand different versions for different subgroups of students. For example, if you want to know the effects of different message strategies on motivating students to do their homework, a result could be that <Imadethisup>a direct call for action is more effective among younger US students, while nudging strategy proved to be effective among Asian student populations.</Imadethisup>

Traditional one-directional lectures are moving online, greater and much more diverse populations of students need to be served (including adults), and these kinds of tools will become invaluable in order to be able to provide a level of personalization and enhance teachers’ capabilities to better understand their product and student population.

I will use this tool in a collaboration with Stanford University Psychology Dept., to design an experiment addressing self-affirmation theory in our upcoming MOOC on Next Generation Infrastructures. We will keep you posted about that.

More info on the A/B testing tool for edX here.

Proportions of a Gerenuk.
{&#8230;and more evolution beauty&#8230;}

Proportions of a Gerenuk.

{…and more evolution beauty…}

Report visit MIT Media Lab

Two weeks ago (8 January 2014), I went to MIT Media Lab for a 2-day workshop about motivation and mindset research and practice in the context of online learning. I say research and practice, because the people participating in the workshop were invited because they were either into research or had access to learning platforms. The meeting (and my trip) was sponsored by the Raikes foundation, and hosted by the Lifelong Kindergarten group at MIT Media Lab. This post describes the setup of the workshop, which worked out very well in getting people to know each other and creating a trusting atmosphere. Workshops and conferences could benefit from such an approach.

Read a nice summary by Vanessa (P2PU) here.

image

The workshop was organized as follows. After inviting about 30 researchers and practicioners involved in open and online education and specifically motivational research, an initial list of readings was shared among participants as a preparation for the workshop. The night before the workshop started, there was an informal dinner to have people get to know each other and already make some connections. The workshop was organized at MIT Media Lab, a place so inspiring that creative ideas and excitement are unavoidable. During the meeting, several activities were organized to stimulate interaction and create a foundation for future collaboration between participants:

  • Day 1: Short intro + objectives → Brainstorm in small groups: mapping challenges and opportunities → Speed-geeking → Creating themes from postits brainstorm → Creating theme-based groups → Short presentations and reflection
  • Day 2: Informal discussions + coffee → Short intro + reflection day 1 → Pitches (optional) to propose research themes to cover in day 2 (to create a group) → Merging / adding themes to the whiteboard → Group formation around themes (extension of day 1) and discussing future collaboration possibilities, experimental setups, shared objectives, etc. → Closing and exchanging contact information.

A more elaborate report of the workshop can be read below.