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Benmesbah, Ouissem; Lamia, Mahnane; Hafidi, Mohamed – Interactive Learning Environments, 2023
Adaptive learning has garnered researchers' interest. The main issue within this field is how to select appropriate learning objects (LOs) based on learners' requirements and context, and how to combine the selected LOs to form what is known as an adaptive learning path. Heuristic and metaheuristic approaches have achieved significant progress on…
Descriptors: Algorithms, Teaching Methods, Educational Innovation, Genetics
Laurel Raffington – npj Science of Learning, 2024
Recently, biological aging has been quantified in DNA-methylation samples of older adults and applied as so-called "methylation profile scores" (MPSs) in separate target samples, including samples of children. This nascent research indicates that (1) biological aging can be quantified early in the life course, decades before the onset of…
Descriptors: Genetics, Aging (Individuals), Older Adults, Scores
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

Tamine, Lynda; Chrisment, Claude; Boughanem, Mohand – Information Processing & Management, 2003
Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…
Descriptors: Algorithms, Comparative Analysis, Evolution, Genetics

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