Volume 30, Issue 2 | Journal of Science Education and Technology

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Volume 30, Issue 2

April 2021

Special Issue on Applying Machine Learning in Science Assessment

Issue Editor:

Xiaoming Zhai

13 articles in this issue

Practices and Theories: How Can Machine Learning Assist in Innovative Assessment Practices in Science Education
Xiaoming Zhai
OriginalPaper 10 February 2021 Pages: 139 - 149
Comparison of Machine Learning Performance Using Analytic and Holistic Coding Approaches Across Constructed Response Assessments Aligned to a Science Learning Progression
Lauren N. Jescovitch
Emily E. Scott
Kevin C. Haudek
OriginalPaper Open access 26 September 2020 Pages: 150 - 167
Machine Learning-Enabled Automated Feedback: Supporting Students’ Revision of Scientific Arguments Based on Data Drawn from Simulation
Hee-Sun Lee
Gey-Hong Gweon
Sarah Pryputniewicz
OriginalPaper 04 January 2021 Pages: 168 - 192
Testing the Impact of Novel Assessment Sources and Machine Learning Methods on Predictive Outcome Modeling in Undergraduate Biology
Roberto Bertolini
Stephen J. Finch
Ross H. Nehm
OriginalPaper 04 January 2021 Pages: 193 - 209
How Does Augmented Observation Facilitate Multimodal Representational Thinking? Applying Deep Learning to Decode Complex Student Construct
Shannon H. Sung
Chenglu Li
Ji Shen
OriginalPaper 16 September 2020 Pages: 210 - 226
Relationships between Facial Expressions, Prior Knowledge, and Multiple Representations: a Case of Conceptual Change for Kinematics Instruction
Hongming Liaw
Yuh-Ru Yu
Mei-Hung Chiu
OriginalPaper 12 September 2020 Pages: 227 - 238
Using Machine Learning to Score Multi-Dimensional Assessments of Chemistry and Physics
Sarah Maestrales
Xiaoming Zhai
Joseph Krajcik
OriginalPaper 26 March 2021 Pages: 239 - 254
Combining Machine Learning and Qualitative Methods to Elaborate Students’ Ideas About the Generality of their Model-Based Explanations
Joshua M. Rosenberg
Christina Krist
OriginalPaper 15 September 2020 Pages: 255 - 267
Correction to: Combining Machine Learning and Qualitative Methods to Elaborate Students’ Ideas About the Generality of their Model-Based Explanations
Joshua M. Rosenberg
Christina Krist
Correction 20 November 2020 Pages: 268 - 268
Automated Scoring of Chinese Grades 7–9 Students’ Competence in Interpreting and Arguing from Evidence
Cong Wang
Xiufeng Liu
Hongyan Zhang
OriginalPaper 09 September 2020 Pages: 269 - 282
Computational Modeling of the Effects of the Science Writing Heuristic on Student Critical Thinking in Science Using Machine Learning
Richard Lamb
Brian Hand
Amanda Kavner
OriginalPaper 18 November 2020 Pages: 283 - 297
On the Validity of Machine Learning-based Next Generation Science Assessments: A Validity Inferential Network
Xiaoming Zhai
Joseph Krajcik
James W. Pellegrino
OriginalPaper 12 January 2021 Pages: 298 - 312
Commentary—Applying Machine Learning in Science Assessment: Opportunity and Challenges
Joseph S. Krajcik
Letter 17 February 2021 Pages: 313 - 318