Final unit synthesis assessment and cumulative benchmark test.

Full unit review connecting molecular structures to observable pedigree patterns.

Constructing a family pedigree from a written narrative, including generation and genotype labels.

Determining dominant vs. recessive inheritance patterns from multi-generational family charts.

Identifying relationships and trait status using standardized pedigree symbols.

Final mastery benchmark for monohybrid crosses and probability scenarios.

Calculating carrier ratios and solving advanced genetic inheritance scenarios.

Probability lab using beans to compare experimental results with theoretical Punnett Square predictions.

Decoding complex monohybrid cross word problems to identify parent genotypes.

Calculating genotype and phenotype ratios and percentages from Punnett Square results.

Formative assessment on basic inheritance vocabulary and simple Punnett Square setup.

Introduction to setting up and filling in monohybrid Punnett Squares.

Simulation of random inheritance using coin flips to determine genotypes and phenotypes for a critter.

Mastering the distinction between genotype and phenotype and using homo/heterozygous prefixes.

Introduction to alleles and the history of Gregor Mendel's pea plant experiments.

Summative assessment on the differences between asexual/sexual reproduction and genetic diversity.

Comparing mitosis and meiosis, focusing on daughter cell counts and chromosome distributions.

Simulation activity comparing population growth and survival of asexual vs. sexual species during environmental crises.

Introduction to sexual reproduction, gametes, and the role of fertilization in creating genetic diversity.

Introduction to asexual reproduction, identifying organisms that use budding, fission, and fragmentation.

Summative assessment covering DNA function, genetic hierarchy, and inheritability.

Synthesis of DNA, genes, and chromosomes through vocabulary application and conceptual modeling.

Hands-on extraction of DNA from strawberries to visualize the physical substance of genetic code.

Exploration of how DNA is organized into genes and chromosomes, focusing on the hierarchy of genetic information.

Students identify the nucleus as the site of genetic material and describe the basic function of DNA as the cell's blueprint.

Students act as the final editorial team for their digital magazine, performing rigorous quality control checks on layout, links, and media to ensure the publication is ready for its public launch. This lesson concludes the magazine project with a focus on professional standards and technical accuracy.

A hands-on investigation into the global journey of microplastics through ocean currents, where students simulate marine gyres and design localized reduction strategies.

In this lesson, students are introduced to the concept of decomposition by tackling a 'Messy Mountain' of unsorted books. They work in collaborative 'Sorting Squads' to break the big problem into smaller tasks: categorizing, shelf-finding, and alphabetizing.

An introductory lesson on evolution covering natural selection, adaptations, fossils, and genetic mutations using visual and accessible formats.

Master the art of resolving conflict with educational stakeholders through structured case study analysis frameworks.

Explore Mendelian inheritance and master Punnett squares through interactive reference guides and practice problems.

Une leçon d'introduction à la puberté pour les élèves de 4ème, se concentrant sur les transformations physiques et le passage de l'enfance à l'âge adulte.

Une leçon complète sur les transformations physiques, physiologiques et hormonales lors de la puberté, adaptée au programme de SVT en 4ème.

Students culminate their AI literacy journey by designing an AI solution for a real-world problem. They focus on responsible design, identifying potential biases, and ensuring societal benefit.

Students analyze the ethical implications of AI on privacy and identity. They explore deepfakes, facial recognition, and the balance between security and personal freedom.

Middle school students dive into the mechanics of Large Language Models (LLMs). They learn about tokenization, probability, and how AI "predicts" the next word in a sequence.

Students explore the "ingredients" of AI: datasets. They learn how biased or incomplete data can lead to unfair or inaccurate AI systems and practice creating a balanced dataset.