# The effects of note-taking methods on lasting learning: the role of motivation and cognitive load

## TL;DR

This study compared note-taking methods and found that the Cornell method improved long-term learning more than others, with motivation being a key factor.

## Contribution

The study provides new insights into how note-taking methods and motivation influence long-term learning retention in teacher candidates.

## Key findings

- The Cornell note-taking method showed significantly higher retention scores compared to the Sentence method.
- Learning motivation increased significantly in the Cornell and Parallel groups but not in the Digital or Sentence groups.
- Digital note-taking was associated with lower cognitive load compared to Parallel and Sentence methods.

## Abstract

This randomized controlled experimental study examined the effects of four note-taking methods (Cornell, Parallel, Digital, and Sentence) on lasting learning (retention) in primary-level teacher candidates, while also exploring the roles of learning motivation and cognitive load.

A total of 134 participants were randomly assigned to three experimental groups (Cornell, Parallel, Digital) and one control group (Sentence). Following a one-session orientation, the intervention spanned 5 weeks (2 h/week). Measures included a researcher-developed Academic Achievement Test (pre-, post-, retention), a validated Learning Motivation Scale (pre-, post-), and a single-item cognitive load rating collected after each lesson. Analyses used mixed ANCOVA with Bonferroni-corrected post-hoc tests and regression analyses.

Mixed ANCOVA revealed significant main effects of time and group, whereas the time × group interaction was not significant. Post-hoc tests showed no significant pairwise differences at post-test; at retention, only the Cornell group scored significantly higher than the Sentence group. Motivation increased significantly in the Cornell and Parallel groups, while Digital and Sentence showed no significant pre–post change. Cognitive load differed by method, with Digital reporting significantly lower load than Parallel and Sentence. Regression analyses indicated that motivation was significantly associated with retention, whereas cognitive load was not.

Overall, retention differences were limited and observed only for the Cornell–Sentence comparison. Learning motivation showed the most consistent association with retention scores, whereas cognitive load showed no significant association with retention in the regression analyses.