Section 1 - General Course Information

Transcription

1 ourse Information Form (IF) The IF provides core information to students, staff teams and others on a particular course of study. Section 1 - General ourse Information ourse Title Qualification Intermediate Qualification(s) Awarding Institution Location of Delivery Mode(s) of Study and Duration ore Teaching Pattern Science BSc (Hons) n/a (ertificate of Higher Education, Diploma of Higher Education as exit awards) University of Bedfordshire AD University ampus Milton Keynes Full-time over 3 years Part-time pathway typically over 6 years core pattern one FHEQ Level 6 Professional, Statutory or Regulatory Body (PSRB) accreditation or endorsement PSRB Renewal Date University of Bedfordshire Employability accreditation Route ode (SITS) Subject ommunity UAS ourse ode Relevant External Benchmarking not applicable not applicable to be confirmed tbc (new course) omputer Science and Information Systems tbc (new course) QAA Subject Benchmark Statement omputing: QAA FHEQ level descriptors: ourse Information Form (IF) - February QAP0021 Page 1 of 12

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3 Section 2 - Published Information Material in this section will be used on the course web site to promote the course to potential students. The text should be written with this potential audience in mind. ourse Structure The Units which make up the course are: Unit ode Level redits Unit Name ore or option [new unit] 4 30 Principles and Practice of core [new unit] 4 30 Fundamentals of omputing and Software core Engineering [new unit] 4 30 Mathematics of core [new unit] 4 30 Science Group Project core [new unit] 5 30 Security and Information Integrity core [new unit] 5 30 Mining and Analysis core [new unit] 5 30 Distributed Management and Semantics core [new unit] 5 30 Science Individual Project core [new unit] 6 30 Engineering and Retrieval core [new unit] 6 30 Presentation and Visualization core [new unit] 6 30 Social Professional Project Management and core Ethics [new unit] 6 30 Science Major Project core Why study this course The course will provide you with academic and technical skills to analyse, interpret and make sense of the huge amount of ubiquitous data created daily. It will enable you to meet the demands of tomorrow s information society. ourse Summary Educational Aims The BSc (Hons) Science course is one of a small number of new courses in the UK that explicitly addresses the challenges coming from organisations using large-scale data, nowadays commonly termed as Big. Large amounts of data are constantly generated world-wide, for instance in the context of social media, digital libraries and escience, multimedia services, internet search engines and business processes. The understanding of this data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. The question of how to handle large amounts of distributed, heterogeneous and linked data is relevant to all companies, from large global players such as Google, Yahoo! or Microsoft to small and medium enterprises as well as for other important applications like digital libraries and digital preservation. The BSc (Hons) Science course seeks to provide technical skills and insight to enable data scientists and data engineers to meet the new challenges that arise in areas such as data management, data infrastructures, data search and mining, data presentation and visualisation as well as data security and privacy. To underpin the importance of the systematic understanding of data not only for omputer Science, the course is designed as an interdisciplinary collaboration between omputer Science, Applied Social Sciences, Psychology and the Business School. The course leads to both a critical understanding of the phenomenon of large-scale data repositories and skills to work in industry and academia in the emerging role of the data scientist. The course covers traditional information systems and data mining applications and their new role in data sciences. It also looks at advanced concepts in data presentation, data engineering and retrieval as well as data security and privacy and will cover theoretical and practical aspects of data analysis. The course is driven by practical projects that provide the opportunity to immediately apply the newly gained knowledge. Your project journey will start in the first year as a group project, continue in the 2nd year as an individual project and will finally feed into your major final year project. The -Hub at the Milton Keynes ampus provides an excellent environment to work directly on large-scale data corpora. The University of Bedfordshire works closely with local and international industry contacts. Our own academic research staff, consisting of experts on Decision Support Systems, Human omputer Interfaces, Security, Information Retrieval, Visualisation and Mining, has the required expertise to provide a course that meets industry ourse Information Form (IF) - February QAP0021 Page 3 of 12

4 as well as academic needs. The strong historic links between the Department of omputer Science and Technology, the Business School and the Faculty of Applied Social Sciences provides a fertile ground for interdisciplinary research and teaching. Drawing from all three of these areas allows the development of a strong and coherent course to handle all aspects of data science. In the more theoretical units (e.g. Distributed Management and Semantics, Engineering and Retrieval) you will gain comprehensive knowledge of main data science concepts and models. Units will be accompanied by practical sessions and seminars to emphasise the possible application of said models. This will not only provide you with an understanding of required techniques, but also enable you to select and employ suitable methods in real contexts. The first year will equip you with required foundations in computing, programming and mathematical analytics and statistics. Gaining an understanding of professional project management and ethics is a further outcome of the first year. In the group project you will get the opportunity to directly apply your knowledge in these subject areas. The group project will also train your collaborative and communication skills. In the second year you will gain specialist knowledge in data mining, security, data management and semantic technologies. While lectures provide you with the underlying concepts, practical sessions will teach you how these methods can be applied. In your individual project you apply your specialist knowledge to solve a real-life problem. In the final year you will commence your major project, which may evolve from your second year individual project. In lectures you will gain further specialist knowledge in data visualisation, data engineering and retrieval, which will enable you to build distributed interactive tools. You will learn to apply this knowledge in practical sessions and by immediate application in your final year project. You will review and present stateof-the-art technology in a seminar, which will enable you to make informed decisions about suitable methods for different kinds of applications. Units at level 4 will provide you with some foundations in computing and mathematics and introduce you to an exciting application area. Units at levels 5 and 6 build upon this foundation to develop your independent study skills for the honours project in your final year. As you assume a greater autonomy and responsibility in your own learning so too will you approach your academic studies and practical work with increasing rigour. Equipped to further develop your interests in academic study or professional training, graduates will have a range of sophisticated skills for data analytics and providing original and convincing solutions to large-scale data science problems. The major project will give you the opportunity to draw from this range of learning experiences with confidence and independence, aided by your supervisor. Entry requirements Standard entry requirements for UK students, students from the European Union and international students. Standard entry requirements for UK students Students from the European Union - International students - In addition at least one grade of at least B in Mathematics or Physics is required (or equivalent qualification for international applicants). PSRB details n/a Graduate Impact Statements The course has been designed to develop graduates who are able to: Exhibit an advanced understanding of methods, concepts and technologies that deal with the analysis, application, interpretation and retrieval of data on a large scale in an enterprise and real-world context. ontribute specialist expertise productively to a multi-specialist development team working on data analytics and problems involving large amounts of data Learn and use new ideas and techniques as they appear within an evolving industry. ourse Information Form (IF) - February QAP0021 Page 4 of 12

5 Higher Education Achievement Report - Additional Information This course benefits from the University s links to the Milton Keynes Hub. The Hub brings together a number of universities, commercial companies and local government to build and operate a data hub to solve the demand problems of cities in terms of critical areas of transport, energy and water. Learning and Teaching The course is delivered by a mixture of lectures, practical sessions and projects. and information are ubiquitous. Even before the course you may have been exposed to various sources of data ranging from social web sites, teaching materials in college and secondary school, statistics or sensitive data hold about you by the Health Service. Our teaching uses this everyday experience as a starting point to embark on systematic analysis and interpretation of this data using the right tools. This is done in a variety of ways at all levels. Most of the teaching is based on a weekly lecture complemented by a practical session that serves to apply and further develop the contents of the lecture within practical exercise. The first year will see more guided activities while the second and third year support you in independent and autonomous study. Several assessments involve group work which will be assessed individually. A key feature of the course is the integrated project that spans across all three years of the course. The first year unit Science Group Project requires you to work in a project team to apply relevant techniques to analyze industry relevant or live data; the second year unit Science Individual Project follows this up by requesting you to contextualize your findings within the application domain. The final year unit Science Major Project then capstones the experience from the previous years: you will work autonomously on a sustained piece of work and you will develop the ability to manage a project from start to finish. Developing your employability Employability is understood widely as encompassing knowledge, skills and a professional attitude which your tutors expect you to display in all your units. All University of Bedfordshire courses aim to help you to be prepared for the world of work. The areers Service is there to support you throughout the three years of your study. Our curriculum gives you skills that are valuable for a career within Science in particular but is also relevant for a much wider range of applications such as information analysis or decision support systems. The final year unit Social Professional Project Management and Ethics in particular requires you to work in a team so as to apply a current project management methodology that embraces all of these knowledge areas in an integrated way while going through the stages of planning, execution and project control; you will work as part of a team, take responsibility and make autonomous decisions that impact on the project team performance. The cross level project that spans from the unit Science Group Project via Science Individual Project to Science Major Project is based on real data sourced from our industry partners, the Milton Keynes Hub or another relevant and recent application domain. Department (s) ourse responsibility: Department of omputer Science and Technology. Development of course: Department of omputer Science and Technology; Department of Psychology Implementation: Other Departments across the University will provide further input to the delivery of the course as part of the cross-level project. Assessment ourse Information Form (IF) - February QAP0021 Page 5 of 12

6 You are assessed in a variety of ways. The majority of units are assessed through coursework, group and individual projects, portfolios, essays, presentations or exams. Presentations are usually given and assessed in the context of a group seminar. You will also produce software artefacts in the area of your specialism. onstant feedback and advice from a supervisory or unit team will be provided to support you in your work. At level 4 you are assessed on your understanding of the fundamental concepts of Science and its application. You are required to comprehend the basic range of intellectual concepts which form the foundations of the subject and application area, and will be assessed on your ability to articulate such concepts in a coherent manner, in a variety of written assessments/written briefs. For example, you will learn about psychology and how psychological data needs to analysed and interpreted. At level 5 you are assessed on your ability to apply the basic concepts of the disciplines introduced in level 4 to existing controversies and issues on which there is already a body of research and critical opinion. You also should be able to demonstrate the inter-relationships between critical theory and practice. For example, you might be asked to discuss how Mining techniques can be applied to provide new insights to Business or Psychology related problems. At level 6 you will be required to demonstrate independent thinking and initiative. This may be in the form of analysing and criticising current approaches and theory in the fields of data presentation and retrieval. In all cases, you will be expected to show an awareness of the major theories and practices of the discipline. You will progress from well-defined briefs to more open-ended and challenging assessments, which culminate in your major project the honours project where you will be given freedom to choose your area of work. After Graduation The critical, theoretical, analytical and practical skills of this degree will prepare you for a range of careers. The most common destination will be in industries dealing with large amounts of data, for instance as data and knowledge engineer or data analyst. Examples are globally operating enterprises where data is dispersed and heterogeneous as well as SMEs that need to organise their internal data and documentation to conduct their business. You may as well work for companies that provide solutions for large-scale data problems, for instance in enterprise search, healthcare or content management. Examples of such companies from a more omputer Science perspective can be found at conferences like Enterprise Search Europe ( but also global players such as Google, Yahoo!, Microsoft and LinkedIn will be interested in successful data science candidates. The theoretical foundations taught in the course will enable you to continue your studies and register on taught or research based Masters courses in omputer Science, Business or Psychology and Sociology. Students can also continue onto PhDs by research which can lead to a career in higher education. Student Support during the course At institutional level, the university has in place a range of easily accessible support structures for new and existing students. The Student Information Desk (SiD, offers confidential advice on all aspects of academic study. It provides information about other areas of university-wide student support such as extenuating circumstances, housing, health, counselling, study support, special needs and disability advice, and careers service. The Personal Academic Development (PAD) provides workshops and one to one support for academic skills. The university chaplaincy runs regular meetings, social events and trips. The Student Union provides additional support and activities. ourse specific support is also in place. First year students receive a comprehensive induction in the week prior to the commencement of the academic year. In addition to this, course co-ordinators will meet with their student groups to explain the course structure and other issues relating to the student experience. These introductions will give you outlines of your course and units, a description of the ways you will be encouraged to develop your knowledge and skills, and signpost resources and materials to assist the process of your learning and success. An important part of this induction is the training to use BREO (Bedfordshire Resources for Education Online). BREO is your personalized virtual learning environment that contains lecture notes, links for online assignment submissions, staff contact details, links to central student services and much more. We expect that you use BREO regularly, and that you use your university ourse Information Form (IF) - February QAP0021 Page 6 of 12

7 where we send you updates about all aspects of your course which need your attention. All students will be allocated a personal tutor when they join the course. This academic will be responsible of monitoring your academic progress throughout your first year and beyond, and will help you with any academic or personal issues that might come up. The personal tutor is your consistent point of contact for support and guidance, but will on occasion refer you to other university staff for specific issues. Further support is provided by lecturers who have office hours and by the course administration team. Students may be required, at the discretion of the course coordinator, to undergo diagnostic testing for academic English language abilities, and may further be required, at the course coordinator s discretion, to participate in academic English support workshops or classes laid on by the University. Our PAL (Peer Assisted Learning) scheme will provide additional support to new students from students at levels 5 and 6. Students with disabilities This course makes intensive use of computing equipment (desktop or laptop computers) and so if you have difficulty accessing these you should discuss this with the Disability Advice Team in conjunction with the course team at the outset to ensure that appropriate support is in place. The University of Bedfordshire is committed to ensuring that curricula across all courses are inclusive to all students. The Disability Advice Team which is associated with the Student Information Desk is available to discuss any issues students may have and can provide services such as dedicated accessibility software, sign language interpreters, note takers, dyslexia screening/tuition and support with mobility on campus. They offer confidential advice and information about academic and personal issues, adjustments in examinations, applying for the Disabled Students Allowances (DSA) and buying suitable equipment. The Disability Advice Team communicates regularly with unit and course co-ordinators to ensure the needs of students are covered. All students concerned that their studies may be affected by disability are encouraged to contact either their Portfolio leader, ourse co-ordinator or Personal Tutor for advice at whatever point in their course the need to do so becomes apparent. ourse Information Form (IF) - February QAP0021 Page 7 of 12

8 Assessment Map Unit ode Mathemati cs of Principles and Practice of Fundament als of omputing and Software Engineerin g Science Group Project Security and Information Integrity Mining and Analysis Distributed Managemen t and Semantics Science Individual Project Engineerin g and Retrieval Presentatio n and Visualisatio n /O WePor Ex-B W- S t Ex- PT W- RW I & I I Weeks WePor t Gr / WePor t W- S W- RW WePor t Gr & Prob I Ex Ex-B Ex ourse Information Form (IF) - February QAP0021 Page 8 of 12

9 Social Profession al Project Manageme nt and Ethics Science Major Project I PJ- Proj / Viva WePor t ourse Information Form (IF) - February QAP0021 Page 9 of 12

10 Section 3 - Academic Information This section will be used as part of the approval and review process and peer academics are the target audience. ourse Learning Outcomes LO1: Demonstrate a thorough understanding of the relevant areas of data science such as: data storage and retrieval, data presentation, data security, data mining and data management; as well as the societal context in which data is used. LO2: ritically apply and reflect upon data analysis and modelling, visualisation and other essential concepts along with the fundamental principles of data retrieval in the context of industry relevant case studies, showing judgement in using the right analysis and visualisation tools and techniques. LO3: Professionally conduct a major project, using problem-solving and evaluation skills relevant to Science that addresses all aspects of a software development cycle including design, implementation and documentation in a coherent and consistent way. LO4: Demonstrate transferable skills and an ability to work under guidance and as a team member. LO5: Identify how the methods, tools and techniques of Science are applied within a professional, legal and ethical framework and develop an understanding of the need of continuing professional development. LO6: ritically discuss societal applications of Science. ourse-specific regulations There are no course-specific regulations Teaching, Learning and Assessment There is a cross-level project that serves to deliver an integrated project experience; this is organized as a series of three units (group project in year 1; individual project in year 2; major project in year 3). These units have special arrangements in place for students with advanced entry or if a continuation of the project from one year to the next is not feasible or desirable (for instance, the industry partner drops out; the problem addressed turns out not to be substantive enough for an honours project or studies have been interrupted in extenuating circumstances leaving a gap in the studies that cannot be bridged). Assessments within the course have been designed to allow students to develop independent learning skills and to take responsibility for what they are undertaking. The following units are examples where the assessment tasks will focus on allowing students to both enhance their knowledge and practical (hands-on) skills as well as being able to contextualize their knowledge using a number of scenarios: Within the unit Engineering and Retrieval students are required to create a distributed Webbased data service that addresses a real-world problem. It should also cover the whole data life cycle. As part of the unit Presentation and Visualisation students are required to first design a real life visualisation and presentation platform and then proceed to develop these tools using the most appropriate techniques. Assessment 2 of the unit Mining and Analysis requires the application of data mining methods to real large-scale data where students will run experiments on the data and evaluate the performance. The use of e-portfolios (a convenient way for the student to assemble heterogeneous material such as project documents, case studies, diaries entries and raw as well as processed data into one place and submit as an assignment) is used in a number of units of the course. This way the marking team can take up a holistic view on the student s journey through the assignment task. Similarly oral assessments are used in the majority of units which allows a direct student-staff interaction as part of the assessment process. This addresses not only subject knowledge but also the student s ability to articulate this knowledge and its application in a coherent way. Nevertheless four of the units feature an end-of-year exam (one unit in the first and third years and ourse Information Form (IF2013-4) Page 10 of 12

11 two units in the second year). These exams test the students ability to respond to problem in a tightly time-constraint setting utilising the knowledge they have acquired throughout the unit. In summary, the assessment methods deployed in this course embrace a number of different approaches ranging from oral to written and time-constraint tasks. Additional Academic Information Peer-assisted learning (PAL) Peer-assisted learning is provided within the first year unit Fundamentals of omputing and Software Engineering. It will be aligned with the PAL arrangements already used for the other undergraduate courses within omputer Science and Technology. Initial Assessment Fundamentals of omputing and Software Engineering Improving students learning Several units allow students to use work and feedback from the first assessment to perform best in the second. All units benefit from weekly practical sessions or supervisor meetings that provide a constant learnerteacher interaction process which also serves to reflect on learning styles. The Science Major Project in the final year features an interim report as Assessment 1 which is formative in nature and provides an opportunity of structured feedback on the approach taken by the students for their honours project. Academic Integrity Academic practice is taught in the three project units ( Science Group Project in year 1, Science Individual Project in Year 2 and the honours project unit in year 3) that constitute the integrated cross-level project experience. While most of the interaction there is one-to-one between student and supervisor there will be some dedicated lectures to the class on key issues such as referencing or utilizing library resources. HEAR implementation in progress Internationalisation Teaching and learning of the courses align with the University s policies of inclusion and internationalisation. Much of the content of project management is internationalised through the use of a number of internationally recognised project management techniques. Similarly, most if not all of the omputing materials are non-country specific, so skills taught to the students here are international by their very nature. Sustainability in progress. ourse Information Form (IF2013-4) Page 11 of 12

12 Section 4 - Administrative Information This section will be used as part of the approval and review process and peer academics are the target audience. Faculty reative Technologies and Science Portfolio Department/School/Division ourse oordinator Undergraduate omputer Science and Technology omputing and Information Systems Ingo Frommholz Version Number Approved by (cf Quality Handbook ch.2) Date of approval (dd/mm/yyyy) Implementation start-date of this version (plus any identified end-date) University Panel Tbc September 2014 for AY 14/15 Form completed by: Name: Marc onrad and Ingo Frommholz Date: June 2014 Authorisation on behalf of the Faculty Teaching Quality and Standards ommittee (FTQS) hair: Date:... ourse Updates Date (dd/mm/yyyy) Nature of Update FTQS Minute Ref: ourse Information Form (IF2013-4) Page 12 of 12