Aims and Fit of Module
The aim of the module is to help students develop skills that should allow students to thrive during the UG studies, and as well later during their professional career. Students will be introduced to general transferable skills, general scientific skills and pharmaceutical sciences-related skills.
Learning outcomes
A Use a range of mathematical and numerical tools and artificial intelligences to address pharmaceutical sciences-related problems
B Understand the basic concepts of pharmaceutical sciences
C Retrieve, understand and manage web-based and artificial intelligence-derived knowledge and information related to pharmacy
D Manage time, balance urgency and priority of workloads
E Use appropriate software for macromolecular visualization
F Structure and communicate professional projects effectively, either orally or in writing
Method of teaching and learning
The theoretical aspects of this module will be delivered through lectures that will be supported with course work consisting of tasks. The coursework will be summative assessments that could include problem solving exercises, presentation and quizzes that students will need to complete at home, or in class.
Students will attend a 2-hour lecture per week and 2-hour lab practicals for 4 weeks. Students will also be given guidance and opportunities to practice the various skills mentioned in the specifications. The module will also be delivered through computer practicals to allow students to gain hands-on experience and practice with specific bioinformatics tools, software and artificial intelligences. The learning outcomes associated to these practicals will be assessed with summative assessment tasks.
Self-study activities will be extensions or consolidations of work carried out in the lecture and lab practical. Assessment components of this module will include: 1) questions or tests in lectures or tutorials; 2) coursework to review the topics; 3) group discussion or report that summarizes the lab practicals; and 4) presentation of a critique of the teaching topics. The feedback will help improve the teaching quality and ensure the quality of summative assessment. Timely, relevant and specific, constructive and actionable feedback will be provided to students in-class, on-paper, via artificial intelligences and/or in-person on for each assignment.