Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges-Reference-Cited by-同舟云学术

Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges

Published:2023 Issue: Volume:11 Page:22513-22525
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Pereira Filipe Dwan¹^ORCID,Fonseca Samuel C.²,Wiktor Sandra³,Oliveira David B. F.²,Cristea Alexandra I.⁴^ORCID,Benedict Aileen³,Fallahian Mohammadali³^ORCID,Dorodchi Mohsen³,Carvalho Leandro S. G.²^ORCID,Mello Rafael Ferreira⁵^ORCID,Oliveira Elaine H. T.²^ORCID

Affiliation:

1. Department of Computer Science, Federal University of Roraima, Boa Vista, Brazil

2. Institute of Computing, Federal University of Amazonas, Manaus, Brazil

3. Department of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, USA

4. Department of Computer Science, Durham University, Durham, U.K

5. CESAR School, Centro de Estudos e Sistemas Avançados do Recife, Recife, Brazil

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico–Brazil–Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundaç ao de Amparoà Pesquisa do Estado do Amazonas

Coordenaç ao de Aperfeiçoamento de Pessoal de Nível Superior–Brazil

Acuity Insights

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10049440.pdf?arnumber=10049440

Reference45 articles.

1. Weekly Programs in a CS1 Class: Experiences with Auto-graded Many-small Programs (MSP)

2. A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 Learning

3. A survey of deep learning for scientific discovery;raghu;arXiv 2003 11755,2020

4. Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming

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