(MSc) Master of Science
Cognitive Neuroscience
Withdrawn
University of Essex
University of Essex
Psychology
Colchester Campus
Masters
Full-time
None
MSC C85012
10/05/2023
Details
Professional accreditation
None
Admission criteria
A 2.1 degree in Psychology, Cognitive Science or a related subject .
If you hold a degree in Psychology it would be preferable, though not essential, if this was British Psychological Society accredited.
IELTS (International English Language Testing System) code
IELTS 7.0 overall with a minimum component score of 5.5
If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.
Additional Notes
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
Course qualifiers
A course qualifier is a bracketed addition to your course title to denote a specialisation or pathway that you have achieved via the completion of specific modules during your course. The
specific module requirements for each qualifier title are noted below. Eligibility for any selected qualifier will be determined by the department and confirmed by the final year Board of
Examiners. If the required modules are not successfully completed, your course title will remain as described above without any bracketed addition. Selection of a course qualifier is
optional and student can register preferences or opt-out via Online Module Enrolment (eNROL).
None
Rules of assessment
Rules of assessment are the rules, principles and frameworks which the University uses to calculate your course progression and final results.
Additional notes
None
External examiners
External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment.
External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course.
They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards.
External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.
Programme aims
1. To provide an advanced education in core subjects of cognitive neuroscience
2. To provide an advanced knowledge of cognitive neuroscience research techniques and instrumentation, and appropriate statistical methodology.
3. To provide a suitable foundation for graduates wishing to proceed to a programme of further postgraduate study
4. To provide training in transferable skills necessary to meet the current requirements of graduate employers.
5. To provide knowledge and skills (critical evaluation and argument, quantitative empirical methods, effective communication) that will prepare students for academic careers as well as a wide range of alternative careers, and will be widely sought by employers.
Learning outcomes and learning, teaching and assessment methods
On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:
A: Knowledge and understanding
A1: Graduates will demonstrate an advanced knowledge and understanding of statistics appropriate for cognitive neuroscience
A2: Graduates will demonstrate an advanced knowledge and understanding of psychological theory within the core domains of cognitive neuroscience
A3: Graduates will demonstrate an advanced knowledge and understanding of functional localisation within the brain and the neural structures supporting cognitive capacity
A4: Graduates will demonstrate an advanced knowledge and understanding of research methods, instrumentation and experimental design appropriate for cognitive neuroscience
A5: Graduates will demonstrate an advanced knowledge and understanding of specialist knowledge, principles and techniques in a substantive area of cognitive neuroscience and cognitive neuropsychology in which the student has chosen to develop special expertise.
A6: Acquire advanced knowledge and understanding of fundamental theoretical issues in the natural, social and cognitive sciences, and the philosophy of mind
Learning methods
Learning methods The scheme has been designed to incorporate a range of core and specialist topics within Cognitive Neuroscience.
Understanding of the core topics is provided by modules in core areas within Cognitive Neuroscience and supplemented by a range of options in Cognitive Neuropsychology and related topics.
Deeper understanding of specialist topics is provided primarily by completing an independent research project under supervision (A4).
While lectures are the principal method of delivery for the concepts and principles outlined in A1-A3, A5 and A6 the department encourages learning through the integration of other teaching activities, including tutorials or discussion groups (A1-A3), laboratory research classes (A1, A3, A4), project research and supervision (A4), and directed reading (A1-A4).
Assessment methods
A2, A5, A6 are assessed by 2000-word coursework essays.
A1, A3, A4, are assessed by practical exercises, by statistical examination and the 10,000-word dissertation.
A1, A3 and A4 are also assessed through the dissertation.
B: Intellectual and cognitive skills
B1: Graduates will show evidence of enhanced ability to evaluate the theoretical issues and experimental techniques of cognitive neuroscience
B2: Graduates will show evidence of enhanced ability to employ evidence-based reasoning to develop coherent research plans and hypotheses
B3: Assemble and integrate evidence from a variety of sources, especially primary sources.
B4: Graduates will show evidence of enhanced ability to analyse and interpret quantitative information in graphs, figures, tables, and determine what the appropriate statistical tests would be
Learning methods
Learning methods The basis for intellectual skills is provided in lectures and laboratory classes.
B1 is developed in both lecture-based and laboratory-based courses.
B2 Is taught and developed by the research project completed under individual supervision.
B3 is developed through lectures, guided reading and tutor led discussion groups.
B4 is a key element of statistics and methods courses, and of the supervised research project
Assessment methods
Evaluation and integration skills are assessed through coursework essays (B1, B3).
Statistical knowledge and quantitative skills are assessed by practical exercises and an unseen examination (B4).
All intellectual and cognitive skills are assessed by the dissertation (B2).
C: Practical skills
C1: Graduates will be able to deploy research skills, including use of scientific databases, referencing packages, and modelling packages
C2: Graduates will be able to deploy writing skills, including use of academic conventions for publication
C3: Graduates will be able to effectively test research hypotheses using appropriate statistical techniques.
C4: Present quantitative data in tabular and graphical form.
C5: Graduates will be able to use a range of psychological tools related to cognitive neuropsychology, such as specialist software, laboratory equipment and psychological assessment tests.
Learning methods
Lectures, seminars, practical classes and computer workshops are used to teach research and writing skills (C1-C2).
C3 is developed through class exercises using a range of statistical software and during the supervision of the research project.
C4 and C5 are acquired in laboratory-based project work and the research project.
Assessment methods
Research and writing skills and use of psychological tools are assessed through the coursework essays and practical exercises, and the dissertation (C2, C3, C5).
Statistical skills are assessed by a 2-hr statistical examination, the practical exercises, and the dissertation (C3 - C5).
Data collection skills are assessed by the dissertation.
D: Key skills
D1: A graduate will show evidence of enhanced ability to communicate ideas effectively.
Communicate information, arguments and ideas cogently and effectively in a range of different contexts using a range of different aids or resources
D2: A graduate will show enhanced ability to be computer literate.
(i) Use appropriate IT facilities to prepare and present laboratory reports & essays.
(ii) Use statistical software to analyse quantitative data.
D3: A graduate will show evidence of enhanced ability to handle data and be numerate.
i) Analyse and present numerical data.
ii) Use statistical techniques in the process of experimental analysis and design
D4: A graduate will show enhanced ability to problem solve and reason scientifically
D5: A graduate will show evidence of the ability to work with others in a research context
D6: (i) Produce work that is properly presented against strict deadlines.
(ii) Reflect on their own performance and make constructive use of feedback.
(iii) Work independently, and plan work effectively
Learning methods
Students are introduced to appropriate statistical software from the first term, and thereafter the further development of key skills forms an integral part of their learning activity.
In particular, D1(i) is developed in laboratory classes, tutorials, and the supervised research project.
D2 (i) and D2 (ii) are developed through the use of an extensive computer laboratory with access to the internet.
These key skills are taught in laboratory courses and statistics courses throughout the year.
D3 (i) and D3 (ii) are developed primarily in laboratory courses and in the supervised research project.
D4 is developed in practical exercises and laboratory classes.
D5 is addressed through the development of ideas and methods along side the supervisor in the research project.
D6 (i) and D6 (ii) is emphasised throughout the programme and is developed by means of rigid deadlines, feedback on assignments, and discussions with class tutors.
Assessment methods
D1 (i) is directly assessed throughout the course.
All coursework must be word-processed, and laboratory-classes require statistics that are performed with dedicated computer software packages, such that students must demonstrate basic competence in computer literacy (D2 (i)).
Students are also assessed on their ability to use a dedicated statistical package (D2 (ii)).
Statistical analyses are assessed in coursework and end of year examinations, such that students must demonstrate advanced competence in numeracy (D3).
Problem solving is assessed in all courses in the programme (D4) in terms of the ability to generate cogent arguments and answers to novel questions in course-work essays.
The ability to generate convincing hypotheses, to work with other, and to develop an appropriate experimental design to answer a question is mostly assessed in the research dissertation (D3, D4, D5).
Improvement of students' own learning and performance is assessed by awarding marks in coursework and examinations for evidence of additional reading (D6 (ii)) and by imposing strict deadlines for coursework assignments (D6 (i).