BI2S200 - Skills and Professional Development 2 01 Jul 2022 - 31 Aug 2028 | Version 2
Associated Module Information
| Module Code: | BI2S200 | ||
|---|---|---|---|
| Module Title: | Skills and Professional Development 2 | ||
| Faculty: | Faculty of Computing, Engineering and Science | ||
| Faculty Group: | Applied Sciences | ||
| Faculty Sub Group: | Biological Sciences | ||
| Module Leader: | Niamh Breslin | ||
| Module Team: | Emma Higgins, Anthony Caravaggi, Cerith Jones, Gareth Powell | ||
| First Intended Intake: | SEP 2027 | Final Year of Intake: | 2027 |
| Date Closed: | |||
| Credit Value: | 20 | Credit Level: | 5 |
| Language: | English | ||
| Percentage of Module Taught in Welsh: | 50 | ||
| Equivalent Module: | |||
| HECOS codes: | 100406 - statistics | 100962 - research skills | 101030 - applied statistics |
| HECOS Code Weighting: | 30 | 30 | 40 |
Document Version Information
| Version | 2 |
|---|---|
| Valid From | 01 Jul 2022 |
| Valid To | 31 Aug 2028 |
Module Aims
This module aims to build on the key professional skills introduced in Year 1 and develop more advanced understanding of interacting with scientific literature and data. On successful completion of this module, students will be competent in critically and systematically analysing peer reviewed scientific articles. Competencies in data acquisition, manipulation and science communication using statistical analysis, cartography and spatial analysis, and remote sensing.
By the end of the module students will be able to use relevant data and software to effectively analyse and present solutions to real-world problems. Throughout the module students will be encouraged to work independently, take ownership of their learning and working, and apply their skills to real-world scenarios, providing a solid foundation for developing their final year projects and transferrable skills for future employment.
In engaging with the module appropriately, students will fully achieve level-appropriate Behaviour Domains of the following USW Graduate Attributes:
Communication: Behaviour 1, 2, 3
Project Management: Behaviour 1, 2, 3
Digital Literacy: Behaviour 1, 2, 3
Innovation and Enterprise: Behaviour 1, 2, 3
Leadership: Behaviour 1, 2, 3
Content Summary
Students will learn frameworks for the critical and systematic analysis of scientific literature and data. This module will equip students with the ability to solve real-world problems and answer contemporary questions in biological science fields through the acquisition, manipulation, and presentation of available datasets. Students will develop an understanding of what is meant by ‘big data’ and how to effectively manage large datasets and extract relevant data. Content for this module falls under 3 core disciplines:
Statistical analysis in R: Scientific numeracy and statistics; data entry, storage, analysis, and presentation; theory and application of more complex statistic; and meta-analysis.
Cartography and spatial analysis: Further development of skills in QGIS. Data acquisition and cleaning, and integration of data from various sources. Cartographic design as a form of science communication.
Remote sensing: Introduction to applicable remote sensing products and techniques and the use of ArcGIS Pro to manipulate and visualize earth observation data from a variety of sources.
Students will receive refresher (statistical & spatial)/introductory (remote sensing) lectures and tutorials for each discipline before participating in tutorials and case study-based workshops for each.
The assessment for this module is a student-led project which brings together the three disciplines and demonstrates applied abilities in data acquisition, manipulation and presentation while encouraging student autonomy and ownership in learning and working.
Throughout the module students will be encouraged to engage in self-reflection on their personal skill development.
Learning and Teaching Methods
| Activity Type | Hours |
|---|---|
| Tutorial | 18 |
| Practical classes and workshops | 20 |
| Independent Study | 110 |
| Directed Study | 42 |
| Seminar | 10 |
| Total Hours Selected | 200 |
Learning Outcomes
| # | Learning Outcome |
|---|---|
| LO1 | Perform statistical, spatial and bioinformatic analyses, to exploit value and meaning from scientific datasets. Acquire, manipulate, analyse, interpret and present scientific data clearly. |
| LO2 | Critically and systematically engage with scientific literature. |
Module Requisites
N/A
Assessment Criteria
| Assessment Category | Assessment Type | Description | Duration | Word Count | Weight (%) | Best of? | Pass Mark |
|---|---|---|---|---|---|---|---|
| Portfolio | Portfolio 1 | A data analysis, interpretation, and presentation portfolio with systematic review and critical analysis of scientific literature, self- reflection statement on skills development and lay summary. | 0 | 3500 | 100 | No | 40 |
Assessment Matrix
| Assessment Type | Learning Outcomes | ||
|---|---|---|---|
| LO1 | LO2 | ||
| Portfolio 1 | ✔ | ✔ | |