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.

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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