While developing and promoting MobLab has been an exciting process, I have always felt something critical was missing. That something became more evident in a recent discussion I had with Albert Wenger from Union Square Ventures, when the conversation turned to student operated experiments in social science classrooms.
In Biology (the natural science field that I am most familiar with), students are often asked to design, conduct and analyze their own experiments. This is a necessary step in the mastery of crucial concepts, such as mutagenesis, cloning, or gene amplification. Students, as I recall from my own experiences, learn from experiments with great curiosity and engagement. There is no reason that the same level of experimental and immersive training can’t be expected from social science, especially with the right technology and content support.
The core mission of MobLab is to disrupt the ‘chalk and talk’ norm of teaching and learning. However, so far our focus has been rather instructor-centric. Despite the fact that students are encouraged to actively participate in games and experiments, they are not the experiment designers - at least not yet. Intuitively, some key differences between participating and conducting experiments come to mind:
Experiment Formulation
This is arguably the most crucial and rewarding step in exploratory learning. Until students take ownership of their experiments and games, they will not get the full benefits of identifying a problem, formulating a hypothesis, and subsequently designing experiments to test their hypotheses.
Repeatability and Failure
A powerful way to learn is through (repeated) failures. Experiments offer a natural and inexpensive way to learn through repeated actions. Students gain firsthand appreciation on the importance of instructions, the impact of various interfaces or procedures, the effects of parameters, and how context can change behavior, all through repeated, carefully designed experiments. This can happen much more effectively though, if students are not mere subjects in the experiments.
Data Collection
Careful data collection lays foundation for interpretation and future experiments. Sometimes attributes, especially those indirect ones, may not become crucial to analysis only when it’s too late. Does the order of actions submitted by subjects matter? How long does it take for subjects to make their decisions? How about the format of the data? It’s both an art and discipline and something students can acquire only through practice.
Interpretation
Being able to give precise and concise interpretation is just as important as conducting experiments from which the results are being derived. A 2009 report from the National Assessment of Educational Progress showed that, “[K-12] Students were asked to explain what they had observed by interpreting data or drawing conclusions. Across all grade levels, a majority of students could observe, but far fewer could predict or explain.” The ability to explain and interpret evolves over time through practices. Empowering students to take on an active role through the entire lifecycle of experiments would be a great place to start.
It’s only a matter of time until we put experiments in the hands of students.
With the MobLab solution, students will be able to modify game configurations easily in our instructor console, recruit participants from a list of their classmates, friends or even online subjects (subjects from Amazon Mechanical Turk - imagine that!), execute games seamlessly with real-time monitoring, and collect data in a standardized format. Whether it be conducting a vote, emulating a panicked bank run, or observing the difficulty of coordination among a group of workers, MobLab is there to help students learn complex and abstract concepts through the power of experiments.