Module title: Scientific Communication - Dissertation and Statistics

SCQF level: 09:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: MIC09101
Module leader: David Smith
School School of Applied Sciences
Subject area group: Microbiology & Drug Discovery


2018/9, Trimester 1, Face-to-Face, Edinburgh Napier University
Occurrence: 001
Primary mode of delivery: Face-to-Face
Location of delivery: SIGHTHILL
Partner: Edinburgh Napier University
Member of staff responsible for delivering module: David Smith
Module Organiser:

Learning, Teaching and Assessment (LTA) Approach:
For the dissertation (word limit 3000) the student will be expected to choose a topic under guidance from staff (LO1) and search for, compare and evaluate primary scientific literature (LO2). Lectures will be given to explain the nature of a dissertation, and to explain its structure and presentation. Practical classes will be provided to give guidance on bibliographic database and other electronic searching. The first two Tutorials will be provided on a one-to-one basis to support the processes of choice of topic (LO1), information gathering (LO2), critical review (LO4), structuring of the dissertation (LO3) and presentation in a logical and scientific style (LO5). The third tutorial will present the students with examples of good and bad practice in writing, presentation and citation (LO4 and LO5) and they will mark these according to the module Marking Criteria.
Statistics will be taught by a mixture of lectures and practical classes. In lectures the theory of the various statistical tests will be explained, and when particular tests should be used will be discussed (LO6). Students will have the opportunity to practise the various tests in the computer laboratories, and their abilities will be tested in through the series of lab assessments and test.
Questioning is encouraged during face-to-face teaching in lectures, practicals, tutorials and on-line using Moodle discussion forums. Personalised feedback is given during Tutorials 1 and 2 and on the final submitted dissertation. Feedback on lab assessments will be given through WebCT. Students will be given specific guidance on the use of Turnitin® for self-evaluation of the originality of their work, in addition to its use for electronic submission on Moodle for assessment of coursework.

Formative Assessment:
For the Dissertation component, Formative assessment occurs during Tutorial 1 when students are given feedback on choice of topic, in Tutorial 2 when students present an outline and list of references and in Tutorial 3 when students will assess examples of good and bad practice using the module marking criteria.

For the Statistics component, formative assessment takes the form of digital exams from which feedback is available; this also provides summative assessment (20%) as does the final digital exam (30%).

Summative Assessment:
Summative assessment takes the form a potential 5 marks for submission of a properly formatted list of appropriate references at Tutorial 2.
For the Statistics component, formative assessment takes the form of digital exams from which feedback is available; this also provides summative assessment (20%) as does the final digital exam (30%).

Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Lecture 15
Face To Face Practical classes and workshops 25
Independent Learning Guided independent study 160
Total Study Hours200
Expected Total Study Hours for Module200

Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Report 5.00 1,3 7 HOURS= 0.10, WORDS= 0
Dissertation 45.00 2,4,5 12 HOURS= 0, WORDS= 3000
Digital Examination (not Centrally Timetabled) 20.00 6 6 HOURS= 1, WORDS= 0
Digital Examination (not Centrally Timetabled) 30.00 6 12 HOURS= 1, WORDS= 0
Component 1 subtotal: 50
Component 2 subtotal: 50
Module subtotal: 100

Description of module content:

Use of online electronic databases. Identification of primary sources of literature. Abstraction of information. Interpretation of data. Writing in a scientific style. Presentation of conflicting arguments. Selection and use of citations. Presentation of refences in Harvard format. Consideration of how to design experiments Analysis of data using appropriate statistical methods.

Learning Outcomes for module:

LO1: Choose a topic relevant and appropriate to your subject area
LO2: Search for, compare and evaluate primary literature on the topic.
LO3: Construct an outline of the review and a preliminary list of sources.
LO4: Examine scientific argument and present a balanced and critical review.
LO5: Present information in a logical and scientific style.
LO6: Determine appropriate statistical methods to analyse data from experiments.

Indicative References and Reading List - URL:

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