The types of intrinsic motivation as predictors of academic achievement: the mediating role of deep learning strategy

The purpose of this study is to explore the relationship between types of intrinsic motivation and academic achievement through a deep learning strategy. Specifically, the study focused on the intrinsic motivation to know, the intrinsic motivation to experience stimulation, and the intrinsic motivation toward accomplishment. Participants were 310 randomly sampled university students. The descriptive, correlational, and mediation analyses were applied to the data. Results show that the intrinsic motivation to know was positively and directly related to academic achievement. However, the intrinsic motivation to experience stimulation and the intrinsic motivation toward accomplishment were not directly related to academic achievement. Regarding mediation effects, the deep strategy of learning mediated the relationship between the intrinsic motivation to know and academic achievement, as well as between the intrinsic motivation to experience stimulation and academic achievement. These results show that intrinsic motivation to know was positively and directly related to academic achievement, while the link between intrinsic motivation to experience stimulation and academic achievement was significant only indirectly via deep learning strategy. This study emphasizes awareness-raising interventions for the academic community about the effects that types of intrinsic motivation may have in relation to learning strategies in academic achievements.

Authors

Institutions

Publication Details

Journal
Cogent Education
Published
2025-03-24
DOI
https://doi.org/10.1080/2331186x.2025.2482482
Citations
20
Primary Topic
Motivation and Self-Concept in Sports
Type
article
Field-Weighted Citation Impact
48.77
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The types of intrinsic motivation as predictors of academic achievement: the mediating role of deep learning strategy

Mimoza Kamberi
20 citations
Cogent Education
Motivation and Self-Concept in Sports
48.77
article

The types of intrinsic motivation as predictors of academic achievement: the mediating role of deep learning strategy

Mimoza Kamberi
article en
20 citations

Abstract

The purpose of this study is to explore the relationship between types of intrinsic motivation and academic achievement through a deep learning strategy. Specifically, the study focused on the intrinsic motivation to know, the intrinsic motivation to experience stimulation, and the intrinsic motivation toward accomplishment. Participants were 310 randomly sampled university students. The descriptive, correlational, and mediation analyses were applied to the data. Results show that the intrinsic motivation to know was positively and directly related to academic achievement. However, the intrinsic motivation to experience stimulation and the intrinsic motivation toward accomplishment were not directly related to academic achievement. Regarding mediation effects, the deep strategy of learning mediated the relationship between the intrinsic motivation to know and academic achievement, as well as between the intrinsic motivation to experience stimulation and academic achievement. These results show that intrinsic motivation to know was positively and directly related to academic achievement, while the link between intrinsic motivation to experience stimulation and academic achievement was significant only indirectly via deep learning strategy. This study emphasizes awareness-raising interventions for the academic community about the effects that types of intrinsic motivation may have in relation to learning strategies in academic achievements.

Cogent EducationVol. 12(1)
AAB College (XK)
Quality Education
Openalex Percentile: Top 0%
Motivation and Self-Concept in Sports
48.77
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.