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Evaluating an automated analysis using machine learning and natural language processing approaches to classify computer science students’ reflective writing
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Alrashidi, Huda, Almujally, Nouf, Kadhum, Methaq, Daniel Ullmann, Thomas and Joy, Mike (2023) Evaluating an automated analysis using machine learning and natural language processing approaches to classify computer science students’ reflective writing. In: 2nd International Conference on Pervasive Computing and Social Networking (ICPCSN 2022), Online, 03-04 Mar 2022. Published in: Pervasive Computing and Social Networking Proceedings of ICPCSN 2022, 475 pp. 463-477. ISBN 9789811928390. doi:10.1007/978-981-19-2840-6_36 ISSN 2367-3370.
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Official URL: http://dx.doi.org/10.1007/978-981-19-2840-6_36
Abstract
Reflection writing is a common practice in higher education. However, manual analysis of written reflections is time-consuming. This study presents an automated analysis of reflective writing to analyze reflective writing in CS education based on conceptual Reflective Writing Framework (RWF) and application of natural language processing and machine learning algorithm. This paper investigates two groups of features extraction (n-grams and PoS n-grams) and random forest (RF) algorithm that utilize such features to detect the presence or absence of the seven indicators (description of an experience, understandings, feelings, reasoning, perspective, new learning, and future action). The automated analysis of reflective writing is evaluated based on 74 CS student essays (1113 sentences) that are from the final year project reports in CS’s students. Results showed the seven indicators can be reliably distinguished by their features and these indicators can be used in an automated reflective writing analysis for determining the level of students’ reflective writing. Finally, we consider the implications of how the conceptualization of providing individualized learning support to students in order to help them develop reflective skills.
| Item Type: | Conference Item (Paper) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||
| Series Name: | Lecture Notes in Networks and Systems | ||||||||
| Journal or Publication Title: | Pervasive Computing and Social Networking Proceedings of ICPCSN 2022 | ||||||||
| Publisher: | Springer | ||||||||
| ISBN: | 9789811928390 | ||||||||
| ISSN: | 2367-3370 | ||||||||
| Book Title: | Pervasive Computing and Social Networking | ||||||||
| Official Date: | 2023 | ||||||||
| Dates: |
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| Volume: | 475 | ||||||||
| Page Range: | pp. 463-477 | ||||||||
| DOI: | 10.1007/978-981-19-2840-6_36 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Conference Paper Type: | Paper | ||||||||
| Title of Event: | 2nd International Conference on Pervasive Computing and Social Networking (ICPCSN 2022) | ||||||||
| Type of Event: | Conference | ||||||||
| Location of Event: | Online | ||||||||
| Date(s) of Event: | 03-04 Mar 2022 | ||||||||
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