TEACHING BACKCROSS BREEDING WITH AN INTERACTIVE GENETIC SIMULATION: THE INTGENSIM APPROACH
Universitat Jaume I (SPAIN)
About this paper:
Conference name: 20th International Technology, Education and Development Conference
Dates: 2-4 March, 2026
Location: Valencia, Spain
Abstract:
Traditionally, the instruction of breeding methods in genetics has been predominantly theoretical, given the impracticality of demonstrating processes that span several years within a single academic semester. While graphical diagrams are typically employed to outline the principal steps involved, students frequently perceive these representations as insufficient and encounter difficulties in comprehending the rationale behind key decisions throughout the process. To overcome these challenges, we adopted a holistic educational strategy by integrating IntGenSim (Interactive Genetic Simulator) into an undergraduate curriculum applying it on the backcross breeding method. Using this virtual simulation tool, students engaged in simulating each stage of the backcross program—from the initial crosses, through five successive generations of backcrossing, to a final generation of self-fertilization—with the purpose of producing genotypes that contained the target alleles while maintaining a maximum genetic similarity to the recurrent parent. Throughout the exercise, students were required to utilize IntGenSim to assess genotypes, calculate phenotypes, and subsequently apply relevant selection criteria to identify and advance the individuals with the best characteristics in each generation. Finally, they should document their procedures and results using IntGenSim outcomes from all steps, accompanied by responses to conceptual questions regarding their decision-making. Our findings indicate that holistically designed virtual simulation environments such as IntGenSim substantially improve students’ comprehension and mastery of complex genetic breeding processes, representing a significant advance over conventional teaching approaches.Keywords:
Virtual Learning Environment (VLE), Simulation Software, Graphical Genotypes, Dynamic phenotype selection, Excel VBA programming.