Experimental Between-Subjects Design - Research Methods in Psychology/Social Sciences

Summary

This lecture delves into the between-subjects design in experimental research, highlighting its importance and application in various psychological subfields. It contrasts hard copy and soft copy study materials, emphasizing the former's superiority in student performance. The lecture outlines the design's characteristics, such as comparing multiple groups and its requirement for a large, balanced participant pool. It also addresses challenges like individual differences and participant mortality, and discusses strategies to mitigate these issues. The discussion concludes with the statistical implications of the design, transitioning to the next topic: within-subjects design.

Takeaways

• 📚 The lecture discusses the 'between subjects design', a research strategy used in experiments to compare different groups.
• 🧪 A sample study is presented suggesting that studying from printed text is more effective than from a computer screen.
• 📊 The lecture explains that in a between subjects design, participants are randomly assigned to different treatment conditions and then compared.
• 🔍 The goal of a between subjects experiment is to determine if differences exist between two or more treatment conditions.
• 👥 The design involves multiple groups of participants, each experiencing a different condition, rather than using the same group repeatedly.
• 🚫 A key characteristic is that each participant provides only one score, meaning they can only be in one group and not participate multiple times.
• 🔄 The lecture highlights the advantages of between subjects design, such as reducing the influence of extraneous variables by ensuring each participant is only measured once.
• 📉 It also discusses the disadvantages, including the need for a large number of participants and the potential influence of individual differences.
• 🎯 Strategies to limit confounding by individual differences include randomization, matching, and holding variables constant.
• ⚖️ The lecture emphasizes the importance of group equivalence to reduce bias and ensure that any observed effects are due to the treatment and not individual differences.
• 📈 Statistically, the between subjects design allows for the use of ANOVA (Analysis of Variance) when comparing three or more groups, as opposed to t-tests for two groups.

Q & A

What is the main topic of the lecture?

The main topic of the lecture is the experimental research strategy, specifically focusing on the between subjects design.

Why might studying from a printed hard copy be more effective than from a computer screen?

Research suggests that studying from a printed hard copy might be more effective because it reduces distractions from apps and other digital elements that can be found on computer screens.

What are the two treatment conditions mentioned in the sample study about studying text?

The two treatment conditions mentioned are the hard copy version and the soft copy version of the text.

What is the general goal of a between subjects experiment?

The general goal of a between subjects experiment is to determine whether differences exist between two or more treatment conditions.

What is a characteristic of a between groups or a between subjects design?

A characteristic of a between groups or a between subjects design is that it compares different groups of individuals, such as Group A versus Group B, and each participant can only be in one group.

Why is a between subjects design also known as an independent measures experimental design?

A between subjects design is known as an independent measures experimental design because each group is independent of the others, and the measurements are not contaminated by other treatment factors.

What is one downside of using a between subjects design?

One downside of using a between subjects design is the need for a relatively large number of participants to ensure fair comparison between groups.

How can individual differences become a confounding variable in a between subjects experiment?

Individual differences can become confounding variables if they influence the results more than the treatment itself, such as a participant's pre-existing knowledge or conditions affecting their performance.

What are some strategies to limit confounding by individual differences in a between subjects design?

Strategies to limit confounding by individual differences include randomization, matching, holding variables constant, and ensuring that groups are created and treated equally.

What are the two types of variance discussed in the lecture, and how do they relate to experimental design?

The two types of variance discussed are variance between, which refers to differences between groups, and variance within, which refers to differences within a group. High variance between with low variance within is desirable in experimental design to ensure that differences are due to the treatment and not individual variations.

What are some threats to validity in a between subjects design?

Some threats to validity in a between subjects design include participant mortality, communication between groups, diffusion of treatment, and phenomena like compensatory rivalry and resentful demoralization.