Conference Paper/Proceeding/Abstract 135 views 112 downloads
Resilience and Effective Learning in First-Year Undergraduate Computer Science / Tom Prickett, Julie Walters, Longzhi Yang, Morgan Harvey, Tom Crick
Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, Pages: 19 - 25
Swansea University Author: Tom Crick
PDF | Accepted ManuscriptDownload (515.65KB)
DOI (Published version): 10.1145/3341525.3387372
Many factors have been shown to be important for supporting effective learning and teaching — and thus progression and success — in higher education. While factors such as key introductory-level (CS1) knowledge and skills, as well as pre-university learning and qualifications, have been extensively...
|Published in:||Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education|
New York, NY, USA
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Many factors have been shown to be important for supporting effective learning and teaching — and thus progression and success — in higher education. While factors such as key introductory-level (CS1) knowledge and skills, as well as pre-university learning and qualifications, have been extensively explored, the impact of measures of positive psychology are less well understood for the discipline of computer science. University study can be a period of significant transition for many students; therefore an individual’s positive psychology may have considerable impact upon their response to these challenges. This work investigates the relationships between effective learning and success (first-year performance and attendance) and two measures of positive psychology: Grit and the Nicolson McBride Resilience Quotient (NMRQ).Data was captured by integrating Grit (N=58) and Resilience (N=50) questionnaires and related coaching into the first-year of the undergraduate computer science programme at a single UK university. Analyses demonstrate that NMRQ is significantly linked to attendance and performance for individual subjects and year average marks; however, this was not the case for Grit. This suggests that development of targeted interventions to support students in further developing their resilience could support their learning, as well as progression and retention. Resilience could be used, in concert with other factors such as learning analytics, to augment a range of existing models to predict future student success, allowing targeted academic and pastoral support.
Resilience, Effective Learning, Progression, Success, Learning Analytics
College of Arts and Humanities