PN3322 From data to insight in the behavioural and neural sciences

2023 to 2024 Semester 1

Curricular information may be subject to change

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 9

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Enrollment is limited to BSc Neuroscience students

Planned timetable

Lectures: Tue, 1-2pm Tutorials: Wed, 1-2pm, Fri, 1-2pm

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr M F Zwart

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Team Taught

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This module aims to introduce students to an increasingly important aspect of the scientific process in psychology and neuroscience: data analysis and visualisation. Weekly lectures delivered by a different member of staff drawn from various subdisciplines of the biological/behavioural sciences will highlight the variety and complexity of different data types and how insights from these data can be visualised and communicated effectively. Students will self-direct their learning and work to analyse datasets provided by members of staff, and create scientific figures for assessment. Throughout, students will learn to critically evaluate primary research articles. At the end of the module, a one-day conference will be held in which students give oral presentations on new advances in the field.

Relationship to other modules

Pre-requisites

HONOURS ENTRY TO BSC NEUROSCIENCE

Assessment pattern

Coursework = 100%

Re-assessment

Coursework = 100%. Re-assessment applies to failed components only.

Learning and teaching methods and delivery

Weekly contact

Week 1: -1-hour introductory meeting with teaching staff, Weeks 2-11: -6 x 1-hour lectures -6 x 1-hour tutorials -2 hours devoted to critical analysis of primary research -1 full day (5 hours) of oral presentations as part of research festival

Scheduled learning hours

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

To understand the variety and complexity of different data types in the behavioural and neural sciences;
To understand how insights from these data can be visualised and communicated effectively;
To create scientific figures from datasets provided by members of staff;
To critically evaluate primary research literature.