An effort to train the biological computation skill and teach animal phenetic taxonomy to pre-service biology teacher

Abstract

Abstract Computational biology skills for studying phenetic taxonomy is inseparable from learning outcomes of Animal Systematics Course. Pre-service biology teachers are expected to have computational biology skills, which can support further study in bioinformatics. This study was aimed to train computational biology skills and evaluate learning outcomes of phenetic taxonomy material. Phenetic taxonomy practicum was held online and assignments were given as mini-projects. Indicators of biological computation skills were evaluated using ntsys 2.2 software and analysis of resulting dendograms based on synapomorphy, automorphy, and apomorphy. Respondents consisted of three classes contained 84 students who programmed Animal Systematics Course. Computational biology skills were quantified based on self-assessment questionnaire while learning outcomes were evaluated based on mini-project assessment. Data were analyzed using descriptive quantitative method. Results indicated that mastery of computational biology for phenetic taxonomy was very good, as supported by students’ ability to use Ntsys software of 86.04%, dendogram analysis of 83.33% or categorized as good. In addition, learning outcomes of phenetic taxonomy were classified as good with average score of 77.7 ± 4.17. Evaluation of qualitative assessment data showed that computational biology skills supports the development of higher-order thinking skills (data synthesis, analysis, and evaluation) of pre-service biology teachers.