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Zong, Zheng; Schunn, Christian D. – International Journal of Computer-Supported Collaborative Learning, 2023
Online peer feedback has proven to be practically useful for instructors and to be useful for learning, especially for the feedback provider. Because students can vary widely in skill level, some research has explored matching reviewer and author by performance level. However, past research on the impacts of reviewer matching has found little…
Descriptors: Computer Mediated Communication, Feedback (Response), Peer Evaluation, Biology
Line Have Musaeus; Deborah Tatar; Peter Musaeus – Journal of Biological Education, 2024
Computational modelling is widely used in biological science. Therefore, biology students need to learn computational modelling. However, there is a lack of evidence about how to teach computational modelling in biology and what the effects are on student learning. The purpose of this intervention-control study was to investigate how knowledge in…
Descriptors: Computation, Models, High School Students, Biology
Ariely, Moriah; Nazaretsky, Tanya; Alexandron, Giora – International Journal of Artificial Intelligence in Education, 2023
Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…
Descriptors: Artificial Intelligence, Algorithms, Natural Language Processing, Hebrew
Sung, Rou-Jia; Swarat, Su L.; Lo, Stanley M. – Journal of Biological Education, 2022
Exams constitute the predominant form of summative assessment in undergraduate biology education, with the assumption that exam performance should reflect student conceptual understanding. Previous work highlights multiple examples in which students can answer exam problems correctly without the corresponding conceptual understanding. This…
Descriptors: Biology, Problem Solving, Undergraduate Students, Scientific Concepts

Stewart, Jim; Dale, Michael – Science Education, 1989
Investigates high school students' understanding of the physical relationship of chromosomes and genes as expressed in their conceptual models and in their ability to manipulate the models to explain solutions to dihybrid cross problems. Describes three typical models and three students' reasoning processes. Discusses four implications. (YP)
Descriptors: Algorithms, Biology, Concept Formation, Fundamental Concepts
Zuckerman, June T. – 1992
Various researchers have associated meaningful problem solving with methods guided directly by a conceptual knowledge base. By contast, a meaningless solving course, or sequence of operations, is essentially independent of the solver's conceptual understanding of the problem under consideration. This paper is the first to document a meaningless,…
Descriptors: Algorithms, Biology, Cognitive Processes, Conceptual Tempo