(BSc) Bachelor of Science
Cognitive Science
Withdrawn
University of Essex
University of Essex
Psychology
Colchester Campus
Honours Degree
Full-time
BSC C831
10/05/2023
Details
Professional accreditation
None
Admission criteria
A-levels: ABB, including Mathematics
Please note we are unable to accept A-level Use of Mathematics in place of A-level Mathematics
BTEC: DDD, only in conjunction with A-level Mathematics.
IB: 32 points or three Higher Level certificates with 655. Either must include Higher Level Mathematics grade 5. We will accept 5 in either Higher Level Mathematics: Analysis and Approaches or Higher Level Mathematics: Applications and Interpretation.
We are also happy to consider a combination of separate IB Diploma Programme Courses (formerly certificates) at both Higher and Standard Level. Exact offer levels will vary depending on the range of subjects being taken at higher and standard level, and the course applied for.
We can also consider combinations with BTECs or other qualifications in the Career-related programme – the acceptability of BTECs and other qualifications depends on the subject studied, advice on acceptability can be provided. Please contact the Undergraduate Admissions Office for more information.
Access to HE Diploma: 15 level 3 credits at Distinction and 30 level 3 credits at Merit, only in conjunction with A-level Mathematics.
T-levels: Distinction, only in conjunction with A-level Mathematics.
What if I don’t achieve the grades I hoped?
If your final grades are not as high as you had hoped, the good news is you may still be able to secure a place with us on a course which includes a foundation year. Visit our undergraduate application information page for more details.
What if I have a non-traditional academic background?
Don’t worry. To gain a deeper knowledge of your course suitability, we will look at your educational and employment history, together with your personal statement and reference.
You may be considered for entry into Year 1 of your chosen course. Alternatively, some UK and EU applicants may be considered for Essex Pathways, an additional year of study (known as a foundation year/year 0) helping students gain the necessary skills and knowledge in order to succeed on their chosen course. You can find a list of Essex Pathways courses and entry requirements here
If you are a mature student, further information is here
IELTS (International English Language Testing System) code
English language requirements for applicants whose first language is not English: IELTS 6.0 overall. Different requirements apply for second year entry, and specified component grades are also required for applicants who require a visa to study in the UK.
Other English language qualifications may be acceptable so please contact us for further details. If we accept the English component of an international qualification then it will be included in the information given about the academic levels listed above. Please note that date restrictions may apply to some English language qualifications
If you are an international student requiring a visa to study in the UK please see our immigration webpages for the latest Home Office guidance on English language qualifications.
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
If you’re an international student, but do not meet the English language or academic requirements for direct admission to this degree, you could prepare and gain entry through a pathway course. Find out more about opportunities available to you at the University of Essex International College here.
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
This interdisciplinary course will combine psychology, mathematics and computer science skills to enable graduates to gain the skills required for careers in the IT industry, data science and data journalism or trades and professions that rely heavily on computing systems, including media, communications, finance, energy and medicine. The course plays to the strength of the psychology department with world-leading academics in cognitive psychology and a number with background training in cognitive science, computer science and mathematics.
Its teaching aims are to enable students to acquire a broad understanding of cognitive science, while also providing opportunities to develop expertise within particular areas of specialisation; to provide students with a foundation for further study, research and professional development; to produce students who are statistically literate, have programming skills and can perform data analysis; to provide teaching which is informed and enhanced by the research activities of the staff.
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: Basic psychological theory, research methods and statistics.
A2: Experience in mathematical computer packages and programming
A3: Statistical theory and experimental design appropriate for cognitive science
A4: Use of probability and statistics for research methods, data analysis, hypothesis testing and statistical modelling
Learning methods
Lectures are the principal method of delivery for the concepts and principles involved in A1-A4.
Students are also directed to reading from textbooks, academic papers and material available online.
Understanding is reinforced by means of classes (A1-A4), laboratories (A2, A3, A4) and assignments (A1-A4).
Assessment methods
Achievement of knowledge outcomes is assessed primarily through unseen closed-book examinations, and also, in some modules, through marked coursework, laboratory reports, statistical assignments, project reports, and oral examinations (A1-A4).
Methods employed to assess knowledge and understanding of statistics include: class presentations, written coursework, project work and class tests.
B: Intellectual and cognitive skills
B1: Critically evaluate the relative strengths of a range of theories and techniques used in cognitive science.
B2: Understand psychological, mathematical and programming problems and select the most appropriate tools for their solution.
B3: Assemble and integrate evidence from a variety of sources, including primary sources.
B4: Analyse and interpret quantitative information and determine whether appropriate statistical tests have been used.
Learning methods
The basis for intellectual skills is provided in lectures and laboratory classes. The skills are developed by means of recommended reading, guided and independent study, assignments and project work.
B1 is developed in both lecture-based and laboratory-based courses.
B2 is developed in most laboratory assignments, and is developed through exercises supported by classes.
B3 is developed through lectures, guided reading and tutor led discussions groups, as well as the final-year research project.
B4 is developed in statistics and laboratory courses, as well as the final-year research project.
Assessment methods
Intellectual and cognitive skills are assessed primarily through unseen closed book examinations, and also through marked laboratory reports, essays, assignments and project work.
Methods employed to assess knowledge and understanding of statistics include: class presentations, written coursework, project work and class tests.
C: Practical skills
C1: Use computational tools and packages.
C2: Organising and presenting data.
C3: Ability to apply relevant practical and laboratory skills.
C4: Plan, undertake and report an empirical project.
Learning methods
Learning methods
Practical skills (C1-C4) are developed particularly in laboratory classes, exercise classes, assignments and project work.
C1 is acquired through the learning of at least one programming language and the use of a number of computer packages.
C2 is taught in laboratory-based project work, exercise classes and further developed in the final year research project.
C3 and C4 are developed and enhanced throughout the course especially in laboratory classes and during the supervision of the final year project.
Assessment methods
Practical Skills C1-C4 are assessed throughout course by means of marked laboratory reports, written coursework, oral presentations, class tests, end-of-year examinations, and the final year empirical project.
D: Key skills
D1: Communicate ideas effectively by producing written reports/essays and using programming skills.
D2: Use appropriate IT facilities to prepare and present laboratory reports and essays and to use statistical software to analyse quantitative data.
D3: Collect, analyse and present numerical data and use statistical techniques correctly.
D4: Problem solve and reason scientifically in cognitive science.
D5: Improve own learning and performance by working autonomously, showing organisation and time management.
Learning methods
Students are introduced to statistical and computing software in their first year, and thereafter the development of key skills forms an integral part of their learning activity.
D1 is developed throughout the course in laboratory classes, lecture-based courses, tutorials and the final year individual project.
D2 is developed through the use of word processing and computer packages in a number of modules.
D3 is developed in laboratory courses, statistics modules and in the final year project.
D4 is developed in lectures, exercises and laboratory classes.
D5 is developed and enhanced throughout the course of the degree by means of rigid deadlines, feedback on assignments and discussions with class tutors.
Assessment methods
Key Skills are assessed throughout the modules comprising the degree by means of examinations and coursework.
D1 is assessed through coursework, oral examination and the final year project.
D2 is assessed primarily through coursework.
D3 is assessed through laboratory reports, statistical exercises and in the final year project.
D4 is assessed throughout the degree and is intrinsic to the assessment in cognitive science.
D5 is assessed mainly through successful submission of coursework including the final year project.