AI-Assisted Assessment of Inquiry Skills in Socioscientific Issue Contexts

被引:1
作者
Zhang, Wen Xin [1 ]
Lin, John J. H. [1 ]
Hsu, Ying-Shao [1 ]
机构
[1] Natl Taiwan Normal Univ, Grad Inst Sci Educ, Taipei, Taiwan
关键词
auto scoring; inquiry-based learning; learning assessment; socioscientific issues; NEURAL-NETWORKS; SUSTAINABILITY SCIENCE; LSTM; VALIDATION; CHALLENGES; EDUCATION; FUTURE;
D O I
10.1111/jcal.13102
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Background StudyAssessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education.ObjectivesThe present study evaluated the SSI inquiry skills of students in an AI-enabled scoring environment. An AI model for socioscientific issues that can assess students' inquiry skills was developed. Responses to a learning module were collected from 1250 participants, and the open-ended responses were rated by humans in accordance with a designed rubric. The collected data were then preprocessed and used to train an AI rater that can process natural language. The effects of two hyperparameters, the dropout rate and complexity of the AI neural network, were evaluated.Results and ConclusionThe results suggested neither of the two hyperparameters was found to strongly affect the accuracy of the AI rater. In general, the human and AI raters exhibited certain levels of agreement; however, agreement varied among rubric categories. Discrepancies were identified and are discussed both quantitatively and qualitatively.
引用
收藏
页数:18
相关论文
共 111 条
[1]   A Deep Learning Model to Predict Student Learning Outcomes in LMS Using CNN and LSTM [J].
Aljaloud, Abdulaziz Salamah ;
Uliyan, Diaa Mohammed ;
Alkhalil, Adel ;
Abd Elrhman, Magdy ;
Alogali, Azizah Fhad Mohammed ;
Altameemi, Yaser Mohammed ;
Altamimi, Mohammed ;
Kwan, Paul .
IEEE ACCESS, 2022, 10 :85255-85265
[2]   Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis [J].
Alwosheel, Ahmad ;
van Cranenburgh, Sander ;
Chorus, Caspar G. .
JOURNAL OF CHOICE MODELLING, 2018, 28 :167-182
[3]  
Amos R., 2020, Science Teacher Education for Responsible Citizenship. Contemporary Trends and Issues in Science Education, V52, DOI [10.1007/978-3-030-40229-7_4, DOI 10.1007/978-3-030-40229-7_4]
[4]  
[Anonymous], 1996, NATL SCI ED STANDARD
[5]  
[Anonymous], 2018, Curriculum Guidelines of 12-Year Basic Education for Elementary School, Junior High and General Senior High Schools, Subject of English in the Domain of Language
[6]  
Arifi SM, 2015, PROCEEDINGS OF 2015 THIRD IEEE WORLD CONFERENCE ON COMPLEX SYSTEMS (WCCS)
[7]   Socio-Scientific Inquiry-Based Learning as a Means toward Environmental Citizenship [J].
Ariza, Marta R. ;
Christodoulou, Andri ;
van Harskamp, Michiel ;
Knippels, Marie-Christine P. J. ;
Kyza, Eleni A. ;
Levinson, Ralph ;
Agesilaou, Andria .
SUSTAINABILITY, 2021, 13 (20)
[8]   Understanding Students' Experiments-What kind of support do they need in inquiry tasks? [J].
Arnold, Julia Caroline ;
Kremer, Kerstin ;
Mayer, Juergen .
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION, 2014, 36 (16) :2719-2749
[9]  
Arras L., 2019, Lecture Notes in Computer Science, P211, DOI DOI 10.1007/978-3-030-28954-6_11
[10]  
Balasubramaniam N, 2022, Paper presented at the Requirements Engineering: Foundation for Software Quality