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Jescovitch, Lauren N.; Scott, Emily E.; Cerchiara, Jack A.; Merrill, John; Urban-Lurain, Mark; Doherty, Jennifer H.; Haudek, Kevin C. – Journal of Science Education and Technology, 2021
We systematically compared two coding approaches to generate training datasets for machine learning (ML): (1) a holistic approach based on learning progression levels; and (2) a dichotomous, analytic approach of multiple concepts in student reasoning, deconstructed from holistic rubrics. We evaluated four constructed response assessment items for…
Descriptors: Science Instruction, Coding, Artificial Intelligence, Man Machine Systems
Prevost, Luanna B.; Smith, Michelle K.; Knight, Jennifer K. – CBE - Life Sciences Education, 2016
Previous work has shown that students have persistent difficulties in understanding how central dogma processes can be affected by a stop codon mutation. To explore these difficulties, we modified two multiple-choice questions from the Genetics Concept Assessment into three open-ended questions that asked students to write about how a stop codon…
Descriptors: Science Instruction, Genetics, Scientific Concepts, Scoring
Chambers, Jemma C.; Ward, Tony; Eccleston, Lynne; Brown, Mark – Journal of Interpersonal Violence, 2009
Research on offending behavior rehabilitation suggests that offenders would gain the maximum benefit from programs that reflect the individual needs of different types of offender. Multivariate theories of offending behavior are thus required to inform individualized rehabilitation. The aim of the current study was to construct a multivariate…
Descriptors: Violence, Correctional Rehabilitation, Criminals, Rehabilitation Programs