Thanks for stopping by! As you surmised, we are very interested in the development in implicit processing which occurs during the course of a learning session and leads to rapid change in the processing of information, which is very similar to the idea of microgenesis.

Some of the analyses that we intend to perform on our dataset include looking at the amount of time that the student is fixating on the particles and seeing if there is a relationship between particle density and fixation time. We also will be looking at the development of strategies: some students may start looking for particles that are on a collision course, which is a great strategy and also demonstrates implicit understanding of Newton's laws. We have many other ideas that we are working on, and we will soon see how  these gaze analyses will align with the existing work on mouse click analysis in Impulse.

Thanks for your question, and please feel free to ask a follow-up question.

 

Thanks for your questions, which are excellent ones.

 

First, let me describe some of the anticipated benefits of a future adaptive version:

 

1) In the current version of the software, the is no "hint" feature to help a student who is stuck. In the adaptive version, the software would analyze the eye movements or other in-game data and detect the ineffective deployment of attentional resources. It would then start providing hints (perhaps with a glowing ring around a particle) that would direct the student's attention to particles that are on a collision course. This would reduce student frustration and enable more efficient learning.

 

2) To help the student assess themselves during play, an adaptive version of this game could give students "brain points" each time they show from their behavior and eye movement that they are attending to the critical items in the game. This would mean that even though the student was not jumping to the next level, they would see that their implicit learning was progressing.

 

To answer your second question, we are hoping that the data we are collecting and analyzing will help other experimenters and learning theorists to better understand the power of implicit learning. We see great potential for non-digital experiences that are similar to our software in their avoidance of textual content and explicit instruction. Mixing digital and non-digital implicit learning may be the most effective method of all, but first more research needs to be done.

I hope I was able to answer your questions. If you have a follow-up question, please ask away!

 

 

Thanks, Jodi! We could not have done it without you and the other folks at TERC and MIT.

Thanks for your comment Chris. Yes we see this work leading to a number of potential research directions. On the one hand we are interested in bringing additional neurocognitive tools online given that we now have the infrastructure to easily do so, but we are hoping to match the highly instrumented patterns with more easily gathered data that can be collected out in the field (e.g. mouse stream, webcam) to allow for the detection of non-productive play patterns and the introduction on non-obtrusive prompts to put the students back on track without explicitly guiding their play behavior.

Thanks for the questions Janet and for your interest in our project. As you know it is hard to provide details in a short three minute clip but I will try to provide a bit more detail for you here. Please let me know if you'd like me to expand on any of my answers below:

1. Implicit learning is similar to tacit learning and often used interchangeably. However there is a distinction between the two: Tacit knowledge is knowledge that is almost impossible to verbalize by its very nature, whereas implicit knowledge is knowledge that a given individual may not yet be able to verbalize but that can with instruction be verbalized.

2. By looking at a learner's game behaviors and eye movements, you can deduce the type of information guiding those events. For example, if a student implicitly understands that a particle will continue along its trajectory unless acted upon by a force, then I would expect to see that student looking along that trajectory for potential collisions. If a student does not understand this at an implicit level then we would not expect them to be able to predict the behavior of particles in the game.

3. The game our students play goes through multiple levels with increasing complexity that help students slowly develop their understanding of particle behavior in a particle simulator. As they interact with different particle types with differences in Mass, their behavior changes. We are interested in seeing if there is a predictable progression in terms of game behaviors and eye movement patterns observed for successful students and if the patterns of students who do not seem to develop behaviors consistent with this implicit knowledge differ in some uniform way.

So at the end of the day we are interested in a paradigm that: 1. allows us to measure whether learners are developing knowledge that is guiding their eyes and game behaviors, and when they are not, 2. intervening to non-intrusively guide their attention to help them develop that knowledge.

Thanks, Ibrahim. Excellent answers -- because they are succinct, because I now understand better what you are doing and why, and because it seems you are on a really good track. Good work! I look forward to hearing more as the project progresses.

Henry, 

Thanks so much for your question. This type of adaptive learning system is where we think the research should be headed. Learning foreign languages is definitely an area where the interaction between implicit and explicit learning is not yet well understood. There has been a deep and broad body of research using eye-tracking to look at how language is learned, and there are some theories that would predict a benefit of providing a "just-in-time" translation. 

From other theoretical perspectives, having the native version of the word appear while reading the foreign language might inhibit learning, possibly due to "blocking" caused by the extremely well-learned native word appearing and preventing learning of the unfamiliar foreign word. See this paper on which I am a co-author for more thoughts on this.

In any case, it would be an idea worth trying out! Thanks for the comment.

I was also thinking learning to read (for those who are having trouble). Jack Mostow (at CMU) used eye tracking and other means to figure out how to help young kids learn to read better; I wonder if your technology would add to what they have been able to do. 

I would actually say that the vast majority of eyetracking research, particularly in the field of cognitive psychology, is on reading and understanding the reading process. Unfortunately, most of the work is on neurotypical readers and there is relatively little work on readers with dyslexia. I certainly believe that more eyetracking work on reading and reading interventions for students with dyslexia is needed.

I'm sure at least some of Mostow's kids were dyslexic, and others, I'm sure, had other learning and reading difficulties. My guess is that a good percentage of them are not neurotypical, but maybe I am wrong.

Good work!!

Thanks for posting Jenna, I'd be happy to share more information if you are interested in learning more about our work.