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Alrashidi, Huda; Joy, Mike; Ullmann, Thomas and Almujally, Nouf
(2020).
DOI: https://doi.org/10.1007/978-3-030-49663-0_38
Abstract
The accuracy of a framework for annotating reflective writing can be increased through the evaluation and revision of the annotation scheme to ensure the reliability and validity of the framework. To our knowledge, there is a lack of literature related to the accuracy of any reflective writing framework in Computer Science (CS) education. This paper describes a manual annotation scheme, applied during four pilot studies, to validate the authors’ novel Reflective Writing Framework (RWF) for CS education. The results show, through the pilot studies, that the accuracy of Inter-Rater Reliability (IRR) increases from 0.5 to 0.8, which was substantial and close to an almost perfect agreement. This paper contributes to CS education through the reliability and validity of the RWF that can be potentially used for generating an Intelligent Tutoring Systems (ITS) using machine learning algorithms.
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About
- Item ORO ID
- 70725
- Item Type
- Conference or Workshop Item
- ISBN
- 3-030-49663-5, 978-3-030-49663-0
- Project Funding Details
-
Funded Project Name Project ID Funding Body Not Set CB19-68SM-01 Kuwait Foundation for the Advancement of Sciences (KFAS) - Extra Information
- Also part of the Programming and Software Engineering book sub series (LNPSE, volume 12149)
- Keywords
- reflection; reflective writing; computer science education; assessment; manual annotation; framework; intelligent tutoring systems
- Academic Unit or School
- Institute of Educational Technology (IET)
- Research Group
-
Centre for Research in Education and Educational Technology (CREET)
OpenTEL - Copyright Holders
- © 2020 Springer Nature Switzerland AG
- Related URLs
- Depositing User
- Thomas Ullmann