TU Darmstadt / ULB / TUprints

Educational Automatic Question Generation Improves Reading Comprehension in Non-native Speakers: A Learner-Centric Case Study

Steuer, Tim ; Filighera, Anna ; Tregel, Thomas ; Miede, André (2022):
Educational Automatic Question Generation Improves Reading Comprehension in Non-native Speakers: A Learner-Centric Case Study. (Publisher's Version)
In: Frontiers in Artificial Intelligence, 5, Frontiers, e-ISSN 2624-8212,
DOI: 10.26083/tuprints-00021507,
[Article]

[img] Text
frai-05-900304.pdf
Available under: CC BY 4.0 International - Creative Commons, Attribution.

Download (882kB)
Item Type: Article
Origin: Secondary publication via sponsored Golden Open Access
Status: Publisher's Version
Title: Educational Automatic Question Generation Improves Reading Comprehension in Non-native Speakers: A Learner-Centric Case Study
Language: English
Abstract:

Background: Asking learners manually authored questions about their readings improves their text comprehension. Yet, not all reading materials comprise sufficiently many questions and many informal reading materials do not contain any. Therefore, automatic question generation has great potential in education as it may alleviate the lack of questions. However, currently, there is insufficient evidence on whether or not those automatically generated questions are beneficial for learners' understanding in reading comprehension scenarios.

Objectives: We investigate the positive and negative effects of automatically generated short-answer questions on learning outcomes in a reading comprehension scenario.

Methods: A learner-centric, in between-groups, quasi-experimental reading comprehension case study with 48 college students is conducted. We test two hypotheses concerning positive and negative effects on learning outcomes during the text comprehension of science texts and descriptively explore how the generated questions influenced learners.

Results: The results show a positive effect of the generated questions on the participants learning outcomes. However, we cannot entirely exclude question-induced adverse side effects on learning of non-questioned information. Interestingly, questions identified as computer-generated by learners nevertheless seemed to benefit their understanding.

Take Away: Automatic question generation positively impacts reading comprehension in the given scenario. In the reported case study, even questions recognized as computer-generated supported reading comprehension.

Journal or Publication Title: Frontiers in Artificial Intelligence
Volume of the journal: 5
Publisher: Frontiers
Collation: 14 Seiten
Classification DDC: 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Multimedia Communications
Date Deposited: 10 Jun 2022 11:09
Last Modified: 10 Jun 2022 11:10
DOI: 10.26083/tuprints-00021507
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-215072
Additional Information:

Keywords: automatic question generation, self-assessment, natural language processing, reading comprehension, education

URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21507
PPN:
Export:
Actions (login required)
View Item View Item