1. Enable students to analyse and interpret scientific data and communicate results; 2. Enhance the employability prospects of students and career awareness.
A Find information through literature searches and use IT or artificial intelligences effectively to analyse and report findings B Summarise and interpret advanced data using graphs and tables C Interpret and evaluate quantitative terms and approaches used in the scientific literature within a range of pharmaceutical science fields D Competently utilise a range of skills to design scientific projects in order to address real pharmaceutical questions E Manage time, balance urgency and priority of workloads F Structure and communicate professional projects effectively, either orally or in writing
The module will be delivered through standard lectures, which will be accompanied by relevant lecture handouts. Students will also be guided to sections of specific textbooks, and if reading of specific reviews or literature sources is required, then copies of these will be made available in the library for use by the students. At intervals during the module, tutorials will be held for the students to deeply understand the principle of this module. Animations and/or videos will be shown for some of the topics. Review sessions will be arranged towards end of the semester and the students will have opportunities to self-assess their understanding of the course. Students will attend a 2-hour lecture and 1-hour tutorial for 7 weeks. Students will also be given guidance and opportunities to practice the various skills mentioned in the specifications. Self-study activities will be extensions or consolidations of work carried out in the lecture and tutorial. Assessment components of this module will include: 1) questions or tests in lectures or tutorials; 2) course work consisting of tasks to review the topics; 3) group discussion or report that summarises the lab practicals; and 4) presentation of a critique of the teaching topics. Timely, relevant and specific, constructive and actionable feedback will be provided to students in class, on paper, via artificial intelligences and/or in person for each assignment. The feedback will help improve the teaching quality and ensure the quality of summative assessment.