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Revisiting the relationship between constructive alignment and learning approaches: A perceived alignment perspective
Christian Stamov Roßnagel1, Katrin Lo Baido2, Noleine Fitzallen3
1Department Psychology & Methods, Jacobs University Bremen, Bremen, Germany.
Clear learning outcomes and effective feedback in university teaching significantly boost deep learning approaches. This adaptation enhances student motivation and perceived competence, though it may increase stress.
Area of Science:
- Educational Psychology
- Higher Education Pedagogy
- Learning Sciences
Background:
- Constructive alignment (CA) aims to foster deep learning but evidence on its effectiveness is mixed.
- Students may adopt surface learning approaches despite teaching strategies promoting deep learning.
Purpose of the Study:
- To investigate if students' perceptions of CA predict adaptation towards a deep learning approach.
- To explore the relationships between deep approach adaptation, learning motivation, and perceived mental workload.
Main Methods:
- Quantitative study involving 56 second-year university students across two courses.
- Learning approach questionnaires administered at three time points (T1, T2, T3).
- Student ratings of CA, learning motivation, and mental workload collected at T2 and T3.
Main Results:
- Clarity of intended learning outcomes (ILOs) and effective feedback significantly predicted an increase in deep approach scores.
- Deep approach adaptation positively correlated with learning motivation (competence, performance importance, usefulness).
- Deep approach adaptation was associated with higher goal accomplishment satisfaction but also increased insecurity and stress.
Conclusions:
- Students' perceptions of CA are significant predictors of learning approach adaptation.
- CA implementation effectiveness can potentially be indicated by students' deep approach adaptation.
- Further research can refine CA strategies to optimize deep learning and manage student workload.
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