This workshop will be a three hour tutorial on the powers and perils of using eye tracking methodologies to study language processing.  The advent of inexpensive and easy-to-use trackers had led to a rapid expansion of users, some of whom may not have the requisite training in the appropriate experimental and data-analytic techniques.  After a brief review of the history eye-tracking research, Dr. Kaakinen will provide an overview of eye tracking best practices, common pitfalls, along with the latest techniques to help users get the most out of this powerful instrument.  The workshop will be hands-off, though we will consider and compare the latest trackers along with their strengths and weaknesses.  This workshop will be of interest to those relatively new to eye tracking, those who have been tracking for years, as well as scholars who would like to consume and appreciate eye-tracking research at a deeper level of sophistication.

This workshop will review FAST as a cloud-based assessment and data system that was developed at the University of Minnesota with funding from IES (2009 to present). Those who attend will learn about FAST and its potential to support a variety of basic and applied research and development. This includes the use of current measures and the development of new measures, which might be shared and distributed widely. A variety of performance data are recorded in the database, which includes accuracy, response choices, and response times (in milliseconds) on an item-by-item basis. Much of the reporting is automated, immediate and exportable in csv files. As an applied research team, we are interested to support basic science, theory development, and their implications for practice. The current domains of assessment span reading, mathematics, and social-emotional behavior. This workshop will be of interest to those who might (a) use FAST to support data collection, (b) explore extant data from large multi-state samples, or (c) use FAST to develop and refine new measures.

Presidential Remarks: Danielle McNamara

Program Chairs’ Welcome: Panayiota Kendeou and Sashank Varma

Awards & Special Recognitions

• Recognitions: Danielle McNamara
• Tom Trabasso Young Investigator Award Presentation: David Rapp
• Jason Albrecht Outstanding Young Scientist Award Presentation: Johanna Kaakinen
• Outstanding Student Paper Award Presentation: Johanna Kaakinen
• FABBS Presentation: Art Graesser

Distinguished Scientific Contribution Award Address:

Mapping Validation Processes onto Memory-based Text Processing

Edward J. O’Brien, University of New Hampshire
Jerome L. Myers, University of Massachusetts – Amherst

Introductory Remarks: Jane Oakhill

The last thirty years, the combined research from our labs has focused on the extent to which passive activation processes (i.e., resonance) play a role in the process of comprehending text. Most current models of reading now take as a basic assumption that the initial activation of information that contributes to comprehension occurs through this passive resonance process. This information is then used during integration. However, recent findings have shown that integration is not the end-stage of processing; readers must validate the linkages formed during integration against information in memory. The goal of this talk is to: give an overview of resonance and its assumptions; explore the role of validation from a memory-based perspective; to further establish how the role of standards of coherence can be mapped onto a memory-based view of text processing; and to outline future steps for research in this area.

Defining and Investigating Automaticity in Text Comprehension

Katherine A. Rawson, Kent State University

Introductory Remarks: Jennifer Wiley

In the literature on text comprehension, automaticity has traditionally been defined in terms of properties of performance (e.g., speed, effort).  A more powerful approach based on contemporary theories of automaticity involves conceptualizing automaticity in terms of underlying cognitive mechanisms that give rise to properties of interest.  To illustrate the utility of automaticity theories for understanding text comprehension, the bulk of my talk will focus on one particular kind of automaticity theory, which states that practice leads to decreasing involvement of algorithmic processing and increasing involvement of memory-based processing.  I will present evidence from studies specifically designed to diagnose the involvement of memory-based automaticity in syntactic and semantic processes during text comprehension, and I will also review findings from earlier studies that provide indirect evidence for this account. Finally, I will consider directions for future research and theory development to address outstanding issues concerning the nature of automaticity in text comprehension.

Must have purchased ticket during registration. Meet in Hotel Lobby at 6:15 PM; Game starts at 7:10. http://minnesota.twins.mlb.com/

Making Learning Stick: Equipping Students to Learn Smarter and Forget Less

Mark McDaniel, Washington University

Introductory Remarks: Brooke Lea

Many students’ typical study activities such as rereading text and lecture notes may heavily engage repetitive recycling of target information.  One implication for education from basic memory research is that typical student study activities just mentioned may not be effective for learning and retention.  I present results supporting this implication. Memory and comprehension research favor study activities that promote elaborative processing and enhance construction of mental models. I present experiments that illuminate a relatively new technique for effectively promoting such processing.  I also discuss concrete techniques to stimulate elaborative learning in the classroom. Another learning principle is that retention and transfer are promoted by spacing study. I present evidence showing gains in learning produced by spaced (practice) relative to massed instruction.  Finally, I present classroom experiments revealing test-enhanced learning: Quizzing results in improvement on exam performances relative to target content that is not quizzed or that is presented for restudy.