PHY1030 | 2023 | University of Exeter

MODULE TITLE	Practical Physics and IT Skills	CREDIT VALUE	15
MODULE CODE	PHY1030	MODULE CONVENER	Prof Volodymyr Kruglyak (Coordinator), Dr Jennifer Hatchell (Coordinator)

DURATION: TERM	1	2	3
DURATION: WEEKS	11	5	1

Number of Students Taking Module (anticipated)	14

DESCRIPTION - summary of the module content

The practical laboratory work section of this module provides a broad foundation in experimental physics, upon which experimental work in Stage 2 and project work in Stage 3 builds. It starts with a short series of lectures, supplemented with a problems set, on error analysis and graph plotting. Laboratory work is normally undertaken in pairs, with support from demonstrators. Experiments are recorded in lab-books and presented as formal reports. The last of the experiments is done as a larger group and involves joint work on a poster, presented in a conference-like environment, and a formal report.

In the IT Skills section of this module students learn to use Python for scientific applications. Python is an interpreted, high-level, general-purpose programming language that can be used for a range of academic and research-based activities including high level mathematics and data processing work. Python is widely used in commercial and research environments.

The PHY0000 Communication and Key Skills course constitutes the third section of this module.

AIMS - intentions of the module

Experimentation is one of the central activities of a scientist. Experimental observations form the bases for new hypotheses and test scientific theories. In this module, you will learn to understand and to apply the experimental method, develop your ability to make reliable measurements and to report them in an effective and ethical manner, and write clearly structured and documented programs in Python.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

Intended Learning Outcomes (ILOs)

A student who has passed this module should be able to:

Module Specific Skills and Knowledge:

1. use a computer language (i.e. Python) to manipulate data and solve equations using numerical methods;

2. plan and execute experimental investigations;

3. apply and describe a variety of experimental techniques;

4. identify, estimate, combine and quote experimental errors and uncertainties;

Discipline Specific Skills and Knowledge:

5. keep accurate and thorough records;

6. discuss and analyse critically results of investigations;

7. minimize experimental errors and uncertainties;

8. demonstrate awareness of the importance of safety within the laboratory context and of the relevant legislation and regulations;

9. identify the hazards associated with specific experimental apparatus, and comply with the safety precautions required;

10. deliver written reports and poster presentations;

11. work in a team (working in pairs on standard experiments and in groups of four or more for extended experiments and poster presentations);

12. manage time (meeting deadlines for assignments);

13. use computers for data analysis and collection;

14. collect, analyse and report data and conclusions in an ethical manner;

Personal and Key Transferable / Employment Skills and Knowledge:

15. use a computer to solve problems;

16. solve problems logically;

17. interact with demonstrators in a laboratory environment;

18. as specified in PHY0000 Communication and Key Skills component.

SYLLABUS PLAN - summary of the structure and academic content of the module

Part A: Practical Laboratory

General guidance on the module, experiments, data analysis and result reporting is provided in the Laboratory Manual. Each experiment is described in a laboratory script.

General supervision and assistance are available from the demonstrators during the timetabled practical sessions. Each demonstrator conducts the initial discussion and monitors the progress of the assigned students, taking a pastoral role and reporting any problems to the module leader. Feedback is given during an assessment and feedback discussion with a demonstrator. Poster presentations in the Student Conference are assessed by demonstrators.

Note: The Communication and Key Skills content and activities are described in the PHY0000 component description.

Part B: IT Skills

Introduction to Python
1. Running interactive Python; loading modules and packages; using Python as a graphical calculator; simple calculations, maths, simple functions and plotting.
2. Using Jupyter notebooks with Numpy and Matplotlib.
Core Python programming
1. Objects, variables and assignments. Dynamic 'Duck' typing. Numerical datatypes.
2. More datatypes: strings, lists, tuples, and dictionaries.
3. Control flow I: Conditionals, comparisons and Boolean logic.
4. Control flow II: Loops.
5. Functions: keyword and positional arguments, default arguments, *args and **kwargs, docstrings, variable scope.
6. Program structure and documentation, error handling, testing and debugging.
Python for labs
1. Numpy arrays and datatypes.
2. Using Numpy for reading and writing data; simple statistics; plotting data with error bars.
3. Fitting a straight line with a least-squares fit.
4. Nonlinear least-squares fitting with Scipy.
5. Publication-quality plots with Matplotlib: multiple axes, control of plot elements.

LEARNING AND TEACHING

LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)

Scheduled Learning & Teaching Activities	89	Guided Independent Study	61	Placement / Study Abroad

DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS

Category	Hours of study time	Description
Scheduled learning & teaching activities	3 hours	3x1 hour data analysis lecture
Scheduled learning & teaching activities	10 hours	10×1-hour computing lectures
Guided independent study	6 hours	3×2-hour self-study packages (problem sets)
Scheduled learning & teaching activities	22 hours	11×2-hour practical laboratory sessions
Scheduled learning & teaching activities	20 hours	5×4-hour computing homework
Scheduled learning & teaching activities	30 hours	10×3-hour practical laboratory sessions
Scheduled learning & teaching activities	3 hours	1×3-hour peer-assessment workshop
Scheduled learning & teaching activities	3 hours	3-hour student conference
Guided independent study	21 hours	Communication and Key Skills component (PHY0000)
Guided independent study	32 hours	Reading and private study

ASSESSMENT

FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade

Form of Assessment	Size of Assessment (e.g. duration/length)	ILOs Assessed	Feedback Method
10×Python classwork assignments	4 hours	1, 13, 15-17	Written and verbal

SUMMATIVE ASSESSMENT (% of credit)

Coursework	40	Written Exams	0	Practical Exams	60

DETAILS OF SUMMATIVE ASSESSMENT

Weight	Form	Size	When	ILOS assessed	Feedback
50%	5 x computing homework assignments	4 hours per assignment	Deadline Monday week T1:03,05,08,10,12	1, 13, 15-17	Written and verbal
40%	A data analysis problem set, experiments written up as formal experiment reports and presented as a conference poster; the median mark is awarded	One 6-hour self-study package including a problem set, two 1250-word individual reports, one 1500-word group report, and one group poster presentation	Weeks T1:03 (problem sets), T2:03 (standard report), T2:06 (standard report), T2:09 (group poster), T2:11 (group report)	2-14, 16, 17	Written and verbal
10%	Communications and key skills component PHY0000	as specified in PHY0000	as specified in PHY0000	18	Written and verbal

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)

Original form of assessment

Form of re-assessment

ILOs re-assessed

Time scale for re-assessment

5×computing homework assignments

Computing Data analysis exercise

1, 13, 15-17

Summer period

Experiments written up as formal experiment reports and presented as a conference poster;

Extended experiment, presented as a formal report (1250 words)

2-14, 16, 17

Summer Period

Communications and key skills component PHY0000

Recorded video/presentation explaining the process followed to perform the experiment.

15

Summer Period

RE-ASSESSMENT NOTES

RESOURCES

INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

ELE:

http://newton.ex.ac.uk/redirects/ELE/phy1030

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE	15	ECTS VALUE	7.5

PRE-REQUISITE MODULES	None
CO-REQUISITE MODULES	None

NQF LEVEL (FHEQ)	4	AVAILABLE AS DISTANCE LEARNING	No
ORIGIN DATE	Thursday 15th December 2011	LAST REVISION DATE	Tuesday 10th October 2023

KEY WORDS SEARCH	Physics; Data; File; Experience; Function; Laboratory; Stage; Errors; Methods; Python; Analysis.

Practical Physics and IT Skills - 2023 entry