Improving students' learning approaches through intervention in an information systems learning environment

Dados Bibliográficos

ID4098797
AutoresChris Cope (Latrobe Regional Hospital, autor correspondente), Lorraine Staehr (La Trobe University)
Ano2005
Volume30
Fascículo2
Páginas181-197
Data de publicação2005-04-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoStudies in Higher Education (JOURNAL)
Identificadores do periódicoISSN: 0307-5079 • E-ISSN: 1470-174X
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/03075070500043275
OpenAlexW2113070009
IdiomaEN
Citações recebidas11
Referências citadas22

A study is reported which aimed to improve the proportion of students using aspects of deep learning approaches in an undergraduate information systems (IS) subject. Underlying the study was relational learning research, which identified learning environment factors more likely to be perceived by students who adopted deep learning approaches. These factors were used to design, and refine over five years, small‐scale interventions to the IS subject’s learning environment. To investigate the impact of the interventions students’ learning approaches were evaluated each year on the basis of responses to short written answer and Likert‐scale questionnaire items. In the fifth year of the study a statistically significant increase in the proportion of students using aspects of deep learning approaches was identified. Among a number of important learning environment factors, perception of workload appeared to be a key to encouraging the use of deep learning approaches. Through gradually decreasing the workload in the subject each year, a point was reached where enough educationally critical content was covered to satisfy the subject aims, but significantly more students perceived they had enough time to apply deep learning approaches

Cooperative learning · Deep learning · Developmental psychology · Educational technology · Learning environment · Likert scale · Mathematics education · Perception · Psychological intervention · Teaching method · Workload · Computer Science · Evaluation of Teaching Practices · Online and Blended Learning · Online Learning and Analytics · Psychology · Artificial Intelligence