Modules

Core Module Information
Module title: Scientific Enquiry
SCQF level: 07:
SCQF credit value: 20.00
ECTS credit value: 10
Module code: ENV07101
Module leader: Kasia Siemienowicz
School School of Applied Sciences
Subject area group: Life Sciences
Prerequisites

There are no pre-requisites for this module to be added
Description of module content:

In this module you will learn how to understand, collect, and analyse research data. You will explore aspects of study design in the context of a variety of research questions which require both field and laboratory approaches to test relevant hypotheses. You will use relevant techniques to collect data and subsequently present, describe and interpret these in relation to the original research question and hypothesis. The skills developed are basic to science and cut across subject disciplines. They include the development of a clear research question or hypothesis, principles of study design, the choice of appropriate descriptive statistics, graphical representation, and inferential statistical tests.
Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Present and summarise data using appropriate graphs and descriptive statistics

LO2: Select the most appropriate statistical test and interpret the data

LO3: Develop basic R software skills.

LO4: Develop basic field and laboratory techniques through practical laboratory experience.
Full Details of Teaching and Assessment
2025/6, Trimester 2, Blended,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: Blended
Location of delivery: SIGHTHILL
Partner:
Member of staff responsible for delivering module: Kasia Siemienowicz
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Online Guided independent study 141 Throughout the trimester, you are expected to structure in time to reflect upon the learning you have undertaken in your scheduled sessions and to complete your essential tasks and reading. You are encouraged to engage in Moodle activities and resources. You will need to ensure that you have sufficient time to prepare and plan for your assessment tasks.
Face To Face Lecture 8 There will be in-person lectures on the scientific method, data handling and principles of statistical analysis. These lectures will be recorded and uploaded to the module Moodle site.
Face To Face Practical classes and workshops 51 During workshops you will learn how to present, summarise, and analyse data using R, and how to choose the most appropriate presentation and data analysis techniques. In practical classes you will develop field and laboratory techniques through practical laboratory experience. You will also learn how to write a lab report.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Discussion/Participation 10 3 Week 9 HOURS= task completion R workshop participation and workshop task completion. To get a full 10 marks, you need to participate in more than 70% of on-campus R workshops and complete the tasks assigned. No marks will be awarded if participation is less than 70% and if tasks are not completed during the on-campus R workshops.
Practical Skills Assessment 10 4 Week 12 HOURS= 10 minutes For students undertaking biomedical laboratory route this assessment will evaluate pipetting skills and for students on environmental laboratory route it will evaluate freshwater invertebrate sampling skills.
Report 40 1~2~3 Week 13 , WORDS= 1500 words This assessment will involve producing a laboratory report based on data collected during your practical classes. You will demonstrate essential skills of data analysis, presentation and interpretation, literature searching, referencing, and structuring a report.
Class Test 40 1~2~3 Week 9 HOURS= 2 hours For this assessment, you will need to use R software to analyse the characteristics of the data, derive summary statistics for all or part of the dataset, assess the distribution of the data, perform suitable analysis, and report on the results. Additionally, you will have to demonstrate an understanding of basic statistical concepts, which were covered during the lectures and R workshops.
Component 1 subtotal: 50
Component 2 subtotal: 50
Module subtotal: 100

Indicative References and Reading List - URL:
ENV07101- Scientific Enquiry
 

Related information