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2019/20 Undergraduate Module Catalogue

BLGY1125 Biology Practicals and Data Analysis

20 creditsClass Size: 200

Module manager: Professor Jurgen Denecke
Email: j.denecke@leeds.ac.uk

Taught: Semester 1 View Timetable

Year running 2019/20

Pre-requisite qualifications

meet entry requirements for BSc

Module replaces

BLGY1116, BLGY1119 and BLGY1270 consolidated into one single first semester module.

This module is not approved as a discovery module

Module summary

This module offers a thorough introduction to laboratory experiments addressing processes at the molecular-, cellular-, whole organism and population level within the broader remit of biology. The selection of practicals should lead to a basic familiarisation with a broad range of standard laboratory practices and the application of molecular studies, as well as methods to study systematics, taxonomy, evolution, physiology, morphology. The course focuses on safe working practices in a laboratory environment, but also teaches how to keep accurate records that can be understood by third parties. Students will acquire an understanding of scientific experimentation, to the extent that they appreciate the value of suitable controls and understand orders of magnitude and appropriate levels of accuracy required, as well as critical thinking and thorough statistical analysis to test reproducibility and significance of observations.

Objectives

The module provides an opportunity to experience routine laboratory techniques and offers a chance to acquire basic experimental routines associated with the study of Biology at all levels, including whole organisms and populations, single cells and tissues, as well as subcellular structures and biochemical processes comprised. Students are to be familiarised with scientific principles such as the difference between experimental science and pure observation, data recording, analysis and presentation as well as the formulation of models and testing a hypothesis. During the practical sessions, there will be opportunities to meet postgraduate researchers and to use their experience to help develop a sense of scale and significance in practical data acquisition. This module will familiarise students with basic equipment and analytical techniques and help them to acquire basic conceptual understanding of scientific practices. This does not only include the use of basic pieces of equipment but includes risk assessments for all activities, adequate recording of experimental setups and obtained research data. Students will be made aware of how to apply and interpret a range of statistical tests to scientific data and be taught how to import data into data-handling programs (i.e. Excel), manipulate and graph them, and perform a number of parametric statistical procedures. On completion of the course students should show an understanding of scientific experimentation, to the extent that they begin to design experiments, appreciate the value of suitable controls and understand appropriate levels of accuracy required.

Learning outcomes
A basic appreciation of good experimental design principles is one of the key outcomes, as well as the definition of a working model and the principle that science cannot absolutely "prove" models, although a single type of experiment can disprove or refute a model, requiring a modification of the working model so that the previous and the new data can be explained. It is important that students understand that models are valuable until they are disproven.
On completion of this module, students should have acquired basic conceptual understanding of laboratory practices for Cell Biology and Biochemistry, as well as whole organism and population studies. They should be able to manage and interpret data (numbers but also images and sounds) and apply statistical tests to address issues of significance and reproducibility. Professional development opportunities include personal time management, good record keeping, common sense and action planning for multi-task procedures, as well as standard presentational skills (spreadsheets, powerpoint presentations and word documents with embedded figures and legends.). This course teaches literacy in statistics and the use of Excel, both of which are skills that are highly sought after by employers.

Skills outcomes
Students will be expected to work following health & safety guidelines for manual handling.


Syllabus

This module is built around practical sessions of 3 hours each on a weekly basis, which cover the full range of scientific skills required in the biological sciences, starting from common laboratory numeracy, a thorough understanding of the terms molarity, molecular weight/mass, percentages, and basic units of volumes and weight, as well as solving simple equations with single unknowns (respecting the units). Practicals move on to explore/develop competence in preparing stock solutions and accurate dilutions, accurate pipetting and using standard laboratory equipment (balances, spectrophotometers/plate readers and microscopes, basic sterile handling techniques) and various forms of data analysis/display methods. The remainder of the laboratory sessions are intended to convey a basic understanding of the diversity of biological life forms, classification systems and the relationship between organisms and their environment. These topics will allow students to understand the complexity of life on earth as it is today, and in the past, as well as the importance of appreciating biodiversity.
A solid appreciation of good experimental design principles remains one of the key outcomes throughout this module and will be taught by theory lectures to cover scientific principles. This is supplemented by a dedicated series of lectures on basic mathematics and in particular aiming for a thorough understanding of the various statistical methods to analyse highly variable biological data in for instance ecological studies. An additional set of dedicated in silico practicals will allow ample opportunity to practice specific IT skills required for statistical analysis.

Teaching methods

Delivery typeNumberLength hoursStudent hours
On-line Learning91.009.00
Computer Class21.002.00
Lecture111.0011.00
Practical113.0033.00
Seminar111.0011.00
Private study hours134.00
Total Contact hours66.00
Total hours (100hr per 10 credits)200.00

Private study

There are no reading lists and private study should be restricted to specific exercises in mathematics and statistics (44 hours), as well as the preparation of practical report for peer review and private exam revision (22 hours), studying the laboratory notes and practical schedules before the practical (22 hours) and after the practical in preparation of the exam (22 hours), supplemented by any curiosity-driven extra reading on the subjects covered in the module (24 hours). Laboratory notes are to be completed during the scheduled time of the practicals, students are strongly discouraged from adopting the bad habit of taking rough notes first during the practical and copying them neatly after the practical, as this is unrealistic in the work place, be it fundamental academic research or in industry/private sector.

Opportunities for Formative Feedback

Practical leaders as well as demonstrators will inspect laboratory books on a weekly basis and provide feedback during the practicals on the adequacy of the notes taken. One formative in-course assessment in week 8 will be held, followed by a specific responsive mode session to discuss class weaknesses and strengths. One assessed computer exercise will help to prepare students for the statistical component of the main unseen exam in January.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
In-course MCQformative assessment0.00
Computer Exercisein-course statistics exam10.00
Total percentage (Assessment Coursework)10.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)3 hr 00 mins90.00
Total percentage (Assessment Exams)90.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 25/04/2019

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