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Botelho, Anthony; Baral, Sami; Erickson, John A.; Benachamardi, Priyanka; Heffernan, Neil T. – Journal of Computer Assisted Learning, 2023
Background: Teachers often rely on the use of open-ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving mathematical problems beyond what is possible through…
Descriptors: Natural Language Processing, Artificial Intelligence, Computer Assisted Testing, Mathematics Tests
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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Gombert, Sebastian; Di Mitri, Daniele; Karademir, Onur; Kubsch, Marcus; Kolbe, Hannah; Tautz, Simon; Grimm, Adrian; Bohm, Isabell; Neumann, Knut; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2023
Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free-text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task…
Descriptors: Coding, Energy, Scientific Concepts, Formative Evaluation