Projects Overview

Check out our current projects in the lab!

 
 

Adjunct questions in video

How do questions help people learn? This project investigates the effect that adjunct questions have on students' learning. We are interested in understanding how question features (such as format, placement, and feedback) influence what students are able to retain and transfer from a lesson, and how those effects differ for people with different amounts of familiarity with the lesson content. Some of our current research questions include:

  • Do students learn more from multiple choice or open response questions?
  • Are questions more effective when they are interspersed throughout the lesson or massed at the beginning/end?
  • Should questions be asked before or after the answer has been presented?
  • Are certain types of questions more effective for students with different levels of prior knowledge?
  • What kinds of feedback makes adjunct questions more effective?
  • What questions better support transfer (vs. retention) of information?

misconceptions & conceptual change

Many of us hold misconceptions about the world: theories and ideas that we believe to be true but which are inconsistent with scientific theories. These misconceptions are often quite resistant to instruction - we persist in believing them even when confronted with contradictory evidence. How can we help students overcome these misconceptions? We are exploring effective teaching techniques and possible mechanisms that support conceptual change. Some questions we are currently interested in include:

  • What makes refutation more effective that exposition?
  • What conditions are most likely to lead to conceptual change?
  • What is the role of surprise, confusion, and confidence in overcoming students misconceptions?
  • How important are errors during learning?

  Recent posters:     Psychonomics 2017    CogSci 2015

Cognitive load & learning from video

Video lessons have exploded online and are found everywhere from YouTube to online courses. Yet videos differ from in-person lessons in important ways and we are just beginning to understand how to optimize video for learning. Building off the Cognitive Theory of Multimedia Learning (Mayer, 2003), we are interested in understanding what features of video lessons lead to greater learning and transfer of information. This work involves considering both the cognitive load of video lessons, as well as the importance of engaging the viewer. Some current and future questions include:

  • Can cognitive load be effectively measured and managed in response to a video lesson?
  • Is learning better predicted by cognitive load (mental effort) or engagement (interest in the lesson)?
  • Are animated visuals more effective than static diagrams?
  • Are on-screen narrators distracting or engaging?
  • What length and pace of lesson is optimal for learning?
  • What role does prior knowledge have on the effectiveness of different video features?

statistics learning

Statistics is often a dreaded topic, but is critically important for understanding scientific research. Although students are fairly competent at memorizing formulas and carrying out calculations, they often struggle when forced to identify appropriate analyses or make sense of statistics in real data analysis situations. The goal of this line of work is to develop more effective instructional exercises and techniques in statistics by applying possible mechanisms from cognitive psychology, including comparison, explanation, and analogical reasoning. Some research questions include:

  • Does side-by-side comparison of example problems in statistics facilitate schema abstraction more than sequential comparison?
  • Is comparison more effective for transfer when surface features of problems are similar or different?
  • Do prompts to explain help students generalize knowledge about appropriate statistical analyses?
  • Do students learn more effectively when they are prevented from calculating?
  • Should statistical concepts be taught before or after calculation/analysis procedures?
  • How much do undergrads, grads, and faculty really retain about statistics?
  Recent posters:    APS 2017

Recent posters:

APS 2017