Undergraduate learning & Memory

I do not currently run a research lab. However, I do have side projects and data that I analyze. That being said, this page serves as a broad descriptor of my research interests and projects I am in the process of writing up (when I have time!).
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I primarily investigate several cognitive and behavioral variables in lecture settings. Specifically, I focus on natural/uninstructed behaviors in which undergraduates engage during webinar-type neuroscience video lectures. Second, I examine whether these factors change based on lecture structure, "active" learning strategies, and additional manipulations with the goal to enhance content comprehension and retention.

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notetaking

Students' natural notetaking strategies, methods, and constituents.

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metacognition & Individual differences

Judgments of memory, comprehension, content/task difficulty, mental effort, fluency, and other subjective measures.

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Interactive>Constructive>
​Active>Passive (ICAP) Taxonomy

Methods to evaluate the alignment of educational objectives, implementation, and assessments. Similar to Bloom's Taxonomy, but more focus on cognitive contributions (application of depth-of-processing theory).​

Right: Model extracted from Chi & Wylie, 2014.

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Active learning strategies

Retrieval-based learning, note revision, perceived peer dependence, self-explanation, teaching expectancy, summarization, distributed practice, segmented/flipped lectures, digital concept-mapping

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automated text analysis

Expository text analysis using:
Meaning Extraction Helper, LIWC, Semantic Network Modeling, Propositional Networks, Latent Semantic Analysis, and (soon) WordStat and LDA.

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