Michael's Reading Academic Papers Flashcards
(28 cards)
What is the first step before reading an academic paper?
Define a clear research question.
What sections should you read first to decide if a paper is relevant?
Abstract, Introduction, and Literature Review.
What should you do if the paper is relevant after the initial skim?
Read the Discussion, Conclusion, and Methodology sections in detail.
What critical factors should you examine in a study’s methodology?
Sample size, sampling method, and study design.
Why is reading with a research question important?
It focuses your attention and improves information retention.
What is the risk of relying solely on AI summaries?
AI can hallucinate, miss nuance, and does not promote deep learning.
What is a systematic review?
A review that follows a structured process for searching and selecting literature based on specific criteria.
How does theoretical research differ from empirical research?
Theoretical research develops or critiques theories without collecting empirical data.
What is grey literature?
Non-peer-reviewed material like theses, industry reports, and conference proceedings.
What does the mean measure?
The average value in a dataset.
What does standard deviation tell you?
How spread out data is around the mean.
What does a p-value indicate?
The probability that the results occurred by chance.
What p-value is commonly considered statistically significant?
p < .05.
What is the difference between statistical significance and practical significance?
Statistical significance shows a low probability of chance results, while practical significance measures if the effect is meaningful.
What does a correlation (r) of +1 mean?
A perfect positive relationship between two variables.
What does R² tell you in a study?
The percentage of variance explained by the relationship between two variables.
What is Cohen’s d?
A measure of the effect size between two group means.
Why is effect size important?
It indicates the practical significance of a result, beyond statistical significance.
What is the main caution with correlation findings?
Correlation does not imply causation.
What is reliability in a measurement?
The consistency of the measurement across time or raters.
What is validity in a measurement?
Whether the measurement accurately captures what it claims to measure.
Give an example of a reliable but invalid measurement.
Phrenology (measuring skull lumps for personality traits).
What should you critically examine about the sample used in a study?
Whether it is large enough and representative.
What is the danger of relying only on p-values?
Large sample sizes can create statistically significant results for trivial effects.
