A Method Comparison on Multi-Label Questions Classification for Assessment-Based Personalised Scaffolding Adaptive Learning Path

Wahyuningsih, Yulia and Djunaidy, Arif and Siahaan, Daniel Oranova (2022) A Method Comparison on Multi-Label Questions Classification for Assessment-Based Personalised Scaffolding Adaptive Learning Path. In: Proceeding 2022 International Conference on Electrical Engineering and Informatics. ICon EEI 19-20 Oct. 2022, 3rd . Institute Electrical and Electronics Engineers (IEEE), Pekanbaru, Indonesia, pp. 162-167.

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Abstract

Classification of the topic of a question item is one of the fundamental problems in e-learning systems. Unlike single-label classification, the multi-label classification method simultaneously predicts more than one-class label. This research is a series of process development for a Personal Diagnostic system based on assessment. This system needs an annotated question bank because multi-label question items can be used to build a Concept Effect Relationship (CER). The purpose of building CER is to track the failed concept of students who fail the formative tests. Hence, there is necessary in looking for a multi-label question classification method. Therefore, this paper compares several multi-label classification methods in determining subject topics associated with questions in a formative test question bank. This study investigates the non neural-based and neural-based multi-label classification. The test results for the non-neural show that Term Frequency Inverse Document Frequency (TF-IDF) with Random Forest classifier produces the best hamming loss value (16,3%) while on neural, TF-IDF with convolutional neural network (CNN) produces a hamming loss value (21,2%) that is better than Long Short Term Memory (LSTM).

Item Type:	Book Section
Uncontrolled Keywords:	multilabel, Indonesian questions classification, personal diagnostic system, formative test, concept effect relationship
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Prodi Ilmu Informatika
Depositing User:	Yulia Wahyuningsih
Date Deposited:	13 Mar 2025 03:01
Last Modified:	13 Mar 2025 03:02
URI:	http://repositori.ukdc.ac.id/id/eprint/1801

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