A Tool for Automatic Question Generation for Teaching English to Beginner Students

Moron, Martin; Scocozza, Joaquin; Chiruzzo, Luis; Rosá, Aiala

doi:10.1109/sccc54552.2021.9650423

Cited by 5 publications

(3 citation statements)

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“…Moron et al [29] have utilized linguistic information such as POS, semantic role labeling (SRL), and NER to design the rules. After pre-processing the input text, rules were used to replace the part of the text having a particular semantic role and the named entity with a question word.…”

Section: Literature Reviewmentioning

confidence: 99%

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Bloom’s Taxonomy based automatic Marathi question generation

2024

IJATEE

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In the current era of automation, various fields, including education, are undergoing transformations to enhance their existing processes. One crucial aspect in the field of education is examination management. Automatic question generation (AQG) for creating evaluation systems and question papers represents a significant transformation that schools, colleges, and universities are experiencing. Although significant research has been conducted in AQG for foreign languages, there is a scarcity of such work in Indian regional languages. Considering this, a novel working model for AQG for Marathi language texts was presented. The proposed research generates a diverse set of questions automatically through various natural language processing (NLP) pipeline activities, including tokenization, parts of speech (POS) tagging, stemming, named entity recognition (NER), shallow parsing, and dependency parsing. The generated questions fall into the categories of context-based and grammar-based questions, each elaborated in detail with scientific interpretation. This process contributes to the validation and refinement of our question generation methodology. A benchmarking approach using Bloom's Taxonomy was employed to validate the accuracy of the generated questions, ensuring they were aligned with educational objectives and targeted the desired levels of cognitive complexity. The empirical evaluation of the proposed methodology is conducted using the bilingual evaluation understudy (BLEU) score and manual scoring. The accuracy achieved using the BLEU score is 90.37% for the 'wh' questions, based on the corpus created from the sixth standard science textbook published by the Maharashtra State Board, Maharashtra, India. A diverse set of high-quality Marathi language questions has been successfully curated, suitable for compiling question papers aligned with Bloom's taxonomy levels.

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Section: Literature Reviewmentioning

confidence: 99%

“…Throughout the literature survey of AQG, a divergence in question generation for different natural languages, approaches, datasets used, and evaluation techniques was observed. The reported works employ neural network-based [18,19,22,25], template-based [26,34], and rule-based [3,12,13,29] approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

Bloom’s Taxonomy based automatic Marathi question generation

2024

IJATEE

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“…Although a certain correlation between teachers' questions and students' responses has been recognized in previous studies, current research methods have some obvious limitations [15][16][17][18][19]. For example, most studies focus on the quantity of questions and responses, but do not consider the quality aspect, which cannot fully grasp their depth and complexity.…”

Section: Introductionmentioning

confidence: 99%

Correlation Between Cognitive Levels of Teachers’ Questions and Response Enthusiasm of Students

Yang

2023

Int. J. Emerg. Technol. Learn.

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Teachers’ questions and students’ responses are important interactive links in the educational process. In recent years, with the deepening of research on educational psychology, more and more studies have begun to pay attention to the influence of cognitive levels of teachers’ questions on students’ responses. However, although some studies have shown that the way teachers ask questions has a significant impact on the learning outcomes of students, there is no clear answer to the precise relationship between cognitive levels of teachers’ questions and response enthusiasm of students. In addition, existing research methods often rely too much on descriptive statistics and lack a deep understanding and exploration of correlation. This study aimed to explore the correlation between cognitive levels of teachers’ questions and response enthusiasm of students. A new method was first introduced to measure the response enthusiasm of students. Taking English teaching as an example, an evaluation model was constructed through factor analysis, and the evaluation results were analyzed through Kaiser-Meyer-Olkin (KMO) test and Bartlett’s Test of Sphericity. Then grey relational analysis was used to measure the correlation between cognitive levels of teachers’ questions and response enthusiasm of students. The results revealed that cognitive levels had a significant impact on the response enthusiasm. The findings of this study not only provide teachers with an effective strategy to enhance the learning participation of students, but also bring new theoretical knowledge and practical experience to the field of educational psychology.

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