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Resilience and Effective Learning in First-Year Undergraduate Computer Science

Tom Prickett, Julie Walters, Longzhi Yang, Morgan Harvey, Tom Crick Orcid Logo

Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, Pages: 19 - 25

Swansea University Author: Tom Crick Orcid Logo

DOI (Published version): 10.1145/3341525.3387372

Abstract

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...

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Published in: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education
ISBN: 9781450368742
Published: New York, NY, USA ACM 2020
URI: https://cronfa.swan.ac.uk/Record/cronfa55022
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spelling 2020-09-26T17:36:23.2706114 v2 55022 2020-08-19 Resilience and Effective Learning in First-Year Undergraduate Computer Science 200c66ef0fc55391f736f6e926fb4b99 0000-0001-5196-9389 Tom Crick Tom Crick true false 2020-08-19 EDUC 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. Conference Paper/Proceeding/Abstract Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education 19 25 ACM New York, NY, USA 9781450368742 Resilience, Effective Learning, Progression, Success, Learning Analytics 15 6 2020 2020-06-15 10.1145/3341525.3387372 COLLEGE NANME Education COLLEGE CODE EDUC Swansea University 2020-09-26T17:36:23.2706114 2020-08-19T09:31:12.2342862 Faculty of Humanities and Social Sciences School of Social Sciences - Education and Childhood Studies Tom Prickett 1 Julie Walters 2 Longzhi Yang 3 Morgan Harvey 4 Tom Crick 0000-0001-5196-9389 5 55022__17986__8966728d54cb43a99cf3a217784aecac.pdf ITiCSE2020.pdf 2020-08-19T09:33:54.5196183 Output 528030 application/pdf Accepted Manuscript true true English
title Resilience and Effective Learning in First-Year Undergraduate Computer Science
spellingShingle Resilience and Effective Learning in First-Year Undergraduate Computer Science
Tom Crick
title_short Resilience and Effective Learning in First-Year Undergraduate Computer Science
title_full Resilience and Effective Learning in First-Year Undergraduate Computer Science
title_fullStr Resilience and Effective Learning in First-Year Undergraduate Computer Science
title_full_unstemmed Resilience and Effective Learning in First-Year Undergraduate Computer Science
title_sort Resilience and Effective Learning in First-Year Undergraduate Computer Science
author_id_str_mv 200c66ef0fc55391f736f6e926fb4b99
author_id_fullname_str_mv 200c66ef0fc55391f736f6e926fb4b99_***_Tom Crick
author Tom Crick
author2 Tom Prickett
Julie Walters
Longzhi Yang
Morgan Harvey
Tom Crick
format Conference Paper/Proceeding/Abstract
container_title Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education
container_start_page 19
publishDate 2020
institution Swansea University
isbn 9781450368742
doi_str_mv 10.1145/3341525.3387372
publisher ACM
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Social Sciences - Education and Childhood Studies{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Social Sciences - Education and Childhood Studies
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description 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.
published_date 2020-06-15T04:08:57Z
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score 11.037603

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