S10 E12: Filling the gaps with inferences, with Kristen McMaster, Ph.D.

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In this episode of Science of Reading: The Podcast, Susan Lambert is joined by Kristen McMaster, Ph.D., Guy Bond Chair in Reading and professor of special education in the Department of Educational Psychology at University of Minnesota. Together, they explore how reading comprehension isn't just about what's on the page—it's also about what's not there—and share practical insights on how to support students in developing inference skills. Susan and Kristen also discuss the dual processes of activation and integration when making inferences; the distinction between teaching students to process text actively versus teaching students to apply comprehension strategies; and different types of inferences, including causal, bridging, and elaborative.

Show notes:

Quotes:

"Inferencing is really central to comprehension. We wouldn't comprehend if we didn't make inferences." —Kristen McMaster

"I would encourage teachers not to underestimate the importance of supporting even the inferences that might seem obvious to us." —Kristen McMaster

"Good comprehenders are often making very automatic inferences that they don't even realize." —Kristen McMaster

"It helps to explicitly teach what an inference is in language that students will understand." —Kristen McMaster

Timestamps*:
00:00 Introduction: Filling in the gaps with inferences, with Kristen McMaster, Ph.D.
05:00 Comprehension is how we make sense of the world around us
09:00 The types of inferences: Causal, bridging, elaborative, and theory of mind
17:00 How teachers can help students develop inference skills
22:00 Creating an effective questioning strategy
27:00 How teachers can preview a text and think about the inferences that might need to be made
31:00 Supporting students who process texts in different ways
37:00 The timing of comprehension questions
40:00 The connection between oral language comprehension and text comprehension
45:00 Final thought: Teacher's shouldn't underestimate the importance of inferences that might seem obvious.
*Timestamps are approximate, rounded to nearest minute