Cognitive processes in university learning: a developmental framework using structural equation modelling.

Area of Science:

• Educational Psychology
• Academic Performance Research
• Student Motivation Studies

Background:

• Achievement goal theories and study processing strategies are key predictors of academic performance.
• Existing research links these theories to effort and motivation, but longitudinal studies are scarce.
• Few studies have explored the dynamic relationships between achievement goals, processing strategies, effort, and performance over time.

Purpose of the Study:

• To investigate the longitudinal relationships between performance-approach goals, mastery goals, deep processing strategies, effort, and academic performance.
• To test an empirical model examining these constructs across six data collection points over two years.
• To understand the interplay of goal orientations and cognitive strategies in predicting student success.

Main Methods:

• A longitudinal study involving 281 university students (161 female, 120 male).
• Data collected across six time points over a 2-year period.
• Utilized Likert-scale inventories and academic records (course marks, final exams) as performance measures. Structural equation modeling was employed for analysis.

Main Results:

• Performance-approach goals predicted deep processing strategies and mastery goals over time.
• Mastery goals predicted effort, and deep processing strategies influenced mastery goals.
• The model highlighted the mediating roles of deep processing and effort in the performance-approach goals-mastery goals-academic performance pathway.

Conclusions:

• Findings offer theoretical insights into the performance-approach and mastery goals relationship.
• Practical implications suggest using goal structures and adaptive strategies like deep processing to enhance academic learning.
• The study underscores the importance of a longitudinal perspective in understanding student academic trajectories.