ࡱ>  -bjbjjj 7e1ge1g$,& & 8T<l3X:6LLLs%% %_3a3a3a3a3a3a3$868b3%Q%"s%%%3LL3')')')%8LL_3')%_3')')r2T2L- !&2K33032P9'P92P92T%%')%%%%%33(^%%%3%%%%P9%%%%%%%%%& X ~:  1Programme TitleQuantitative Social Science2Programme CodeSMIU1013JACS CodeL9904Level of StudyUndergraduate5aFinal QualificationBSc5bQAA FHEQ Level66aIntermediate Qualification(s)None6bQAA FHEQ LevelNone7Teaching Institution (if not «Ӱҵ)Not applicable8FacultySocial Science9DepartmentThe «Ӱҵ Methods Institute10Other Departments involved in teaching the programmeTown and Regional Planning, Landscape Architecture, Politics, Sociological Studies, Law, Management11Mode(s) of AttendanceFull-time12Duration of the Programme3 years for regular degree; There may also be options for study overseas or for employment experience.13Accrediting Professional or Statutory BodyNot applicable14Date of production/revisionJuly 202015. Background to the programme and subject area In the UK, there is a shortage of social science graduates with quantitative skills, yet an increasing number of employers demand related skills; such as the ability to evaluate evidence and analyse large datasets. The Nuffield Foundation, in collaboration with the ESRC and HEFCE, have funded 15 national centres to address this problem and «Ӱҵ has one of them. This degree is part of that initiative. The degree will be one of a number of interdisciplinary degrees located within the «Ӱҵ Methods Institute.16. Programme aims To develop undergraduate social science students skills in quantitative data analysis; To provide a strong grounding in substantive social science knowledge, reflecting the subject areas of the participating departments; To give students strong practical experience in the use of quantitative analytical techniques to address substantive social science problems. To give students practical experience of survey design and implementation.17. Programme learning outcomes Knowledge and understanding:K1Familiarity with intellectual debates in contemporary social science;K2Strong knowledge of quantitative data analysis methods in social science;K3The capacity to conduct independent quantitative research in social science;K4The ability to design and conduct a social survey. Skills and other attributes:S1Strong skills in the quantitative analysis of social science data;S2Clear oral and written communication skills;S3A strong capacity for logical thought and analysis.18. Teaching, learning and assessment Development of the learning outcomes is promoted through the following teaching and learning methods: K1: Lectures will provide grounding in the core material, while seminars will allow students to debate and hone their understanding. In addition, students will be expected to read widely around their subjects. K2: Lectures in quantitative methods will provide the core background; practical classes and assignments will provide hands-on experience of data analysis and of the interpretation of results; field assignments will give students practical experience of collecting data to answer substantive social science problems. K3: Throughout the degree, students will conduct small research projects and assignments which will require them to put their data analysis skills into practice. The compulsory third year dissertation project will require students to design, implement and report on a major piece of original quantitative social science research on a subject of their own choosing. K4: At all stages of the degree, students will take part in the design and implementation of an annual State of «Ӱҵ questionnaire survey. Opportunities to demonstrate achievement of the learning outcomes are provided through the following assessment methods: S1: Quantitative methods modules will be assessed through exams and practical assignments. In addition, the research project modules at levels 1 and 2, and the research dissertation module at level 3 will require students to implement the quantitative skills they have developed in pursuit of substantive research questions. S2: Written communication skills will be assessed through essays, projects, and the dissertation. Oral communication skills will be assessed via participation in an annual undergraduate conference (one module each year will be devoted to this). S3: This will be assessed via exams, projects, and the dissertation.19. Reference points The learning outcomes have been developed to reflect the following points of reference: Substantive subject understanding as outlined in the subject benchmarks for the participating departments. Core competencies in social science quantitative methods, as outlined in the Nuffield/ESRC/HEFCE Q-Step initiative.20. Programme structure and regulations Students on the degree share methodology and research project modules at all levels. Substantive social science modules are delivered through three different routes, emphasising different areas of social science: (i) the Geography, Urban Studies and Landscape route; (ii) the Politics, Sociology and Criminology route; and (iii) the Management route. Students will choose which route through the degree they intend to follow before the commencement of level 1 of the course, though there will be scope to move from one route to another during the first three weeks of semester 1 level 1. Once embarked on a route through the degree, however, students will normally be unable to switch to another route when progressing from one route to another. At level 1, all students take: 60 credits of core Quantitative Methods modules, including modules on survey design; data visualisation; data analysis; a research project; and a student conference; Level 1 students on the Geography, Urban Studies and Landscape route and the Politics, Sociology and Criminology route also take: 40 credits of substantive social science modules, chosen from level 1 modules offered by the relevant participating departments; 20 credits of unrestricted choice. Level 1 students on the Management route also take: 50 credits of substantive social science modules, chosen from level 1 modules offered by the relevant participating department; 10 credits of unrestricted choice At level 2, all students take: 40 credits of core Quantitative Methods modules, including: multivariate analysis; research design; a research project; and a student conference; 60 credits of substantive social science modules, chosen from level 2 modules offered by the seven participating departments; 20 credits of unrestricted choice. At level 3, all students take: 80 credits of core modules: a 40-credit research dissertation in quantitative social science; and a 20-credit student conference module; 40 credits of substantive social science modules, chosen from level 3 modules offered by the seven participating departments; 20 credits of unrestricted choice.Detailed information about the structure of programmes, regulations concerning assessment and progression and descriptions of individual modules are published in the University Calendar available on-line at  HYPERLINK "http://www.sheffield.ac.uk/calendar/regs" http://www.sheffield.ac.uk/calendar/regs.21. Student development over the course of study Over the course, students will develop their understanding of substantive social science issues through the study of appropriate modules at levels 1, 2 and 3. Throughout, students will strengthen their communication and presentation skills not only via written projects and assignments, but through participation in the annual student conference in which students enrolled on the programme will showcase their own research work (based on assigned projects at levels 1 and 2, and on the research project at level 3). Core to the intention of the degree is also the development of students capacities to understand and conduct quantitative social science research: At level 1, the emphasis is on data collection, data visualisation, and a firm grounding in basic descriptive statistics, statistical inference, and bivariate analytical methods; At level 2, the focus is on multivariate statistical analysis and training to design and conduct independent quantitative social science research (in preparation for the level 3 dissertation); At level 3, the focus shifts to the implementation of the research methodologies developed at levels 1 and 2, through the medium of the independent research project in quantitative social science.22. Criteria for admission to the programme Detailed information regarding admission to programmes is available from the Universitys On-Line Prospectus at  HYPERLINK "http://www.shef.ac.uk/courses/" \h http://www.shef.ac.uk/courses/. A-levels: ABB International Baccalaureate: 34 BTEC: DDM Cambridge Pre-U: D3 M2 M2 Scottish Highers: AAABB Welsh Baccalaureate + 2 A levels: B + AB Advanced Diploma: Minimum of grade A + A level grade B (Hair and Beauty Studies, Sport and Leisure, Hospitality, Travel and Tourism not accepted).23. Additional information This specification represents a concise statement about the main features of the programme and should be considered alongside other sources of information provided by the teaching department(s) and the University. In addition to programme specific information, further information about studying at «Ӱҵ can be accessed via our Student Services web site at  HYPERLINK "http://www.shef.ac.uk/ssid" \h http://www.shef.ac.uk/ssid.     smiu101 ver21-22 PAGE1 Programme Specification A statement of the knowledge, understanding and skills that underpin a taught programme of study leading to an award from «Ӱҵ 12345CDHIKLMNOXY]^_`aop}~ʿʿʿʿʿʿʿʿʿʿʿʿʿh".B*phh".5B*phhB*phhUh{Lh2&B*phh{LhUB*phh{Lh2&5B*phhUCJaJjh{LUmHnHu#jh{Lh{L5UmHnHu;27(($$d%d&d'd(dIfNOPQRgd".$a$235DLe---7(($$d%d&d'd(dIfNOPQRgd".kdhS$$IfHF'@0`'    44 Hapyt{LLMOY^e---7(($$d%d&d'd(dIfNOPQRgd".kd T$$IfHF'@0`'    44 Hapyt{L^_ap~e---7(($$d%d&d'd(dIfNOPQRgd".kdT$$IfHF'@0`'    44 Hapyt{L~e---7(($$d%d&d'd(dIfNOPQRgd".kdU$$IfHF'@0`'    44 Hapyt{Le---7(($$d%d&d'd(dIfNOPQRgd".kdHV$$IfHF'@0`'    44 Hapyt{Le---7(($$d%d&d'd(dIfNOPQRgd".kdW$$IfHF'@0`'    44 Hapyt{Le---7(($$d%d&d'd(dIfNOPQRgd".kdW$$IfHF'@0`'    44 Hapyt{L    ' ( ) * + 2 3 A B C D E O P o p q s t    & ' + - 0 1 2 4 5 N O R      hFB*phh".5B*phh{Lh2&B*phh".h2&B*\phhUh".B*phh{LhUB*phh{Lh2&5B*phE ( e---7(($$d%d&d'd(dIfNOPQRgd".kdpX$$IfHF'@0`'    44 Hapyt{L( ) + 3 B e---7(($$d%d&d'd(dIfNOPQRgd".kd(Y$$IfHF'@0`'    44 Hapyt{LB C E P p e---7(($$d%d&d'd(dIfNOPQRgd".kdY$$IfHF'@0`'    44 Hapyt{Lp q t e---7(($$d%d&d'd(dIfNOPQRgd".kdZ$$IfHF'@0`'    44 Hapyt{L   ' 1 e---7(($$d%d&d'd(dIfNOPQRgd".kdP[$$IfHF'@0`'    44 Hapyt{L1 2 5 O e---7(($$d%d&d'd(dIfNOPQRgd".kd\$$IfHF'@0`'    44 Hapyt{L e---7(($$d%d&d'd(dIfNOPQRgd".kd\$$IfHF'@0`'    44 Hapyt{L   e---7(($$d%d&d'd(dIfNOPQRgd".kdx]$$IfHF'@0`'    44 Hapyt{L  P e(=$ @ xx$d%d&d'd(dNOPQRgd".kd0^$$IfHF'@0`'    44 Hapyt{L O P X Y Z l m JK$%&EFbcdfgKLMOPcҼݯݯݯݯҧݟݯݯh".5B*phhUB*phh".B*phh{Lh2&5B*phh".hUB*phh{LhUB*phh{Lh2&B*phhUh{Lh2&B*ph#>>hU5B*phh2&5B*ph:P Y Z m I=$ @ xx$d%d&d'd(dNOPQRgd".jkd^$$IfH'`'0`'44 Hap yt{Lxx$1$Ifgd".m K%{C & FVxx$$d%d&d'd(dIfNOPQR^`Vgd".A & FVx$$d%d&d'd(dIfNOPQR^`Vgd".%&FcX 7PP$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd".jkdo_$$IfH'`'0`'44 Hap yt{Lcdg7(<$$d%d&d'd(dIfNOPQRgd".Ekd_$$IfH'`'`'44 Hap yt".ii7(<$$d%d&d'd(dIfNOPQRgd".]kdY`$$IfH0'@ %`'44 Hapyt".Lii7(<$$d%d&d'd(dIfNOPQRgd".]kd`$$IfH0'@ %`'44 Hapyt".LMPii7(<$$d%d&d'd(dIfNOPQRgd".]kdMa$$IfH0'@ %`'44 Hapyt".m57PP$$d%d&d'd(dIfNOPQRgd".4$d%d&d'd(dNOPQR^`]kda$$IfH0'@ %`'44 Hapyt".7(($$d%d&d'd(dIfNOPQRgd".EkdAb$$IfH'`'`'44 Hap yt".ii7(($$d%d&d'd(dIfNOPQRgd".]kdb$$IfH0'@ %`'44 Hapyt".QRSxyZ[ghTU345\]GHfg  23h".hUB*phh".hU5B*phh2&5B*phh{Lh2&5B*phhUh{LhUB*phh{Lh2&B*phGRii7(($$d%d&d'd(dIfNOPQRgd".]kd#c$$IfH0'@ %`'44 Hapyt".RSyd...5x$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd".]kdc$$IfH0'@ %`'44 Hapyt".[$lkdd$$IfH'`'0`'44 Hap yt{L7xx$$d%d&d'd(dIfNOPQRgd".5x$$d%d&d'd(dIfNOPQRgd".h7xx$$d%d&d'd(dIfNOPQRgd".5x$$d%d&d'd(dIfNOPQRgd".UU5x$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd".lkdd$$IfH'`'0`'44 Hap yt{LU45!jkd%e$$IfH'`'0`'44 Hap yt{L; & Fxx$$d%d&d'd(dIfNOPQRgd".9 & Fx$$d%d&d'd(dIfNOPQRgd".5]Hg Q; & Fxx$$d%d&d'd(dIfNOPQRgd".5x$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd". 3g ( 8![!ZZ5x$$d%d&d'd(dIfNOPQRgd".9 & Fx$$d%d&d'd(dIfNOPQRgd".5$$d%d&d'd(dIfNOPQRgd". 3fg  ' ( !7!8!Z![!y!z!{!""""""""#t#u#############$$ $%& & &&&'S'T'ȾȨ֞hU5B*phh".5B*phh2&5B*phh2&h".0J!h{Lh".>*B*phh".>*B*phjh".>*B*UphhUh2&h".hUB*phh{LhUB*phh{Lh2&B*ph6[!z!"""U; & Fxx$$d%d&d'd(dIfNOPQRgd".9 & Fx$$d%d&d'd(dIfNOPQRgd".5x$$d%d&d'd(dIfNOPQRgd".""#]7xx$$d%d&d'd(dIfNOPQRgd".jkde$$IfH'`'0`'44 Hap yt{L## $ &X"5x$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd".jkd7f$$IfH'`'0`'44 Hap yt{L &&T'((U; & Fxx$$d%d&d'd(dIfNOPQRgd".9 & Fx$$d%d&d'd(dIfNOPQRgd".5x$$d%d&d'd(dIfNOPQRgd".T'(((((()))w)x)))))))))))*****3*4*\*]****+ + +,,,,,,,,,,,,,,,,,,,,,,,ڠhkfjhkfUh{Lh2&>*B*ph!jh{Lh2&>*B*UphhU5B*phh2&5B*phhUh".hUB*phh{LhUB*phh{Lh2&B*ph;(())X"5x$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd".jkdf$$IfH'`'0`'44 Hap yt{L)))**4*]**[5$$d%d&d'd(dIfNOPQRgd".7xx$$d%d&d'd(dIfNOPQRgd".5x$$d%d&d'd(dIfNOPQRgd".** +,X 7xx$$d%d&d'd(dIfNOPQRgd".=$ @ xx$d%d&d'd(dNOPQRgd".jkd]g$$IfH'`'0`'44 Hap yt{L,,,,,,,,,,,caaaaaaaa/$d%d&d'd(dNOPQRgd".lkdg$$IfH'`'0`'44 Hap yt{L ,,,,,,,,,,,,,,,,,,-------------̿󘌌||h2&5B*CJphhUh2&5B*CJphhkfhFB*mHnHphujh{LB*Uphh2&B*phjh2&B*Uphh".hUB*CJaJphh".B*CJaJphh;B*CJaJphh2&hUB*ph,,,,,,--^S $<<:Da$4$ 9r $d%d&d'd(dNOPQRa$4 9r $d%d&d'd(dNOPQRgd".4$ 9r $d%d&d'd(dNOPQRa$-------/$d%d&d'd(dNOPQRgd".:D<<:D $<<:Da$gd".50P. 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