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Lecture

Understanding Cohen's d Effect Size

In course

HUM-432: How people learn: Designing Learning Tools I

The students will understand the cognitive and social factors which affect learning - particularly in science and engineering. They will be able to use social research techniques as part of the design process to understand end users. ...

Description

This lecture covers the interpretation of Cohen's d effect size in research studies, including how to calculate and understand the values, as well as its significance in comparing control and treatment groups. It also addresses the importance of effect size in meta-analyses and its implications for educational research.

Instructors (2)

Nihat Kotluk

Dr. Kotluk is currently a post-doc at the EPFL. He focuses mainly on emotions in the decision-making process, moral reasoning, and ethics in Engineering Education. He also works on equality and diversity issues. He has an academic background in both STEM and social sciences. Dr. Kotluk has acquired advanced skills in education, inclusive pedagogy, and science teachers' training. He has 14 years of teaching experience and has trained high school students in physics and teachers in pedagogy and research methods, among others. Dr. Kotluk has strong teaching and learning communication skills. He holds a Ph.D. in Educational Science, Curriculum, and Instruction. In his thesis, he studied the perceptions and practices of educators in culturally relevant pedagogy and developed recommendations to put more emphasis on inclusion in pre-service teacher education. With his research, he opened a new discussion in the academic community in Turkey and internationally. In his recent work, he analyzes the educational challenges facing refugee communities and other marginalized groups. In the study, he focused on whether and how teachers implemented the principles of culturally relevant and sustaining pedagogies and the challenges teachers faced while trying to implement these principles with Syrian students in Turkey. In his more recent work, he has studied moral emotions, moral reasoning in engineering ethics, and equality and diversity issues in engineering education. His teaching and research interests include emotions in engineering education, culturally responsive STEM education, equity and diversity in education, and multicultural education.

Roland John Tormey

I am a sociologist and learning scientist researching and teaching on engineering education. I'm particularly focused on the roles of emotion and self-regulation in engineering teaching and learning. My profile is accessible here.

Official source

Related concepts (15)

Meta-analysis

A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. It is thus a basic methodology of Metascience.

Effect size

In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of a parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size value. Examples of effect sizes include the correlation between two variables, the regression coefficient in a regression, the mean difference, or the risk of a particular event (such as a heart attack) happening.

Treatment and control groups

In the design of experiments, hypotheses are applied to experimental units in a treatment group. In comparative experiments, members of a control group receive a standard treatment, a placebo, or no treatment at all. There may be more than one treatment group, more than one control group, or both. A placebo control group can be used to support a double-blind study, in which some subjects are given an ineffective treatment (in medical studies typically a sugar pill) to minimize differences in the experiences of subjects in the different groups; this is done in a way that ensures no participant in the experiment (subject or experimenter) knows to which group each subject belongs.

Scientific control

Informal improvements in any process or enquiry have been made by comparison between what was done previously and the new method for thousands of years. A scientific control is a modern formal experiment or observation designed to minimize the effects of variables other than the independent variable (i.e. confounding variables). This increases the reliability of the results, often through a comparison between control measurements and the other measurements. Scientific controls are a part of the scientific method.

Metascience

Metascience (also known as meta-research) is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing inefficiency. It is also known as "research on research" and "the science of science", as it uses research methods to study how research is done and find where improvements can be made. Metascience concerns itself with all fields of research and has been described as "a bird's eye view of science".

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