Data Analysis Fundamentals

What Are
Factor Loadings?

Understanding the hidden magnetic forces between your questions and the underlying concepts they measure.

The Core Definition

Factor loadings are essentially correlation coefficients between observed items (the specific questions you asked) and the underlying latent factors (the abstract concept).

Range
-1 to +1
Closer to ±1
Strong Relationship
Closer to 0
Weak Relationship
Interactive Simulation

The Magnet Metaphor

Adjust the slider to see how "Loading Strength" affects the relationship.

Factor
Q1
Question Item
0.0 (Weak) 0.5 (Moderate) 1.0 (Strong)
Loading: 0.10

Very weak connection.

Real-World Example

Rotated Factor Matrix

Item Content Factor 1
(Engagement)
Factor 2
(Confidence)
I enjoy online lessons 0.72 0.12
I feel anxious using EdTech 0.10 0.65
I find Zoom effective 0.68 0.18
I feel confident with LMS 0.15 0.70

Factor 1

Items 1 & 3 load strongly here.

Theme: Engagement & Effectiveness

Factor 2

Items 2 & 4 load strongly here.

Theme: Confidence & Anxiety

Interpretation Guidelines

How strong is "strong"? Use these rule-of-thumb thresholds.

≥ 0.70
Very Strong

The item is a quintessential measure of the factor.

0.50 – 0.69
Strong

Solid relationship. Most researchers are happy with this.

0.30 – 0.49
Moderate

Acceptable minimum is often 0.40. Anything lower is questionable.

< 0.30
Weak

Usually ignored or removed from the analysis.

Problematic Items to Watch For

Cross-loading

When an item has high loadings (e.g., > 0.4) on two or more factors. It interprets ambiguously.

Low loading

When an item doesn't reach 0.30 or 0.40 on any factor. It contributes nothing to the solution.

Finding Loadings in SPSS

1
Navigate
Analyze → Dimension Reduction → Factor
2
Configure
Check 'Extraction' and 'Rotation' tabs
3
Locate Output
Look for Rotated Component Matrix

Reporting (APA Style)

"A principal axis factoring with Promax rotation revealed a two-factor solution. Items loaded on factors based on a criterion of ≥ 0.40, with no significant cross-loadings. Factor 1 reflected 'Digital Engagement' and Factor 2 reflected 'Confidence with Technology.'"