Assignment title:

Research Portfolio

Group or individual:

Individual

Module title:

Advanced Research Topics in Computer Science

Module code:

7COM1084

Module leader:

Catherine Menon

Moderators initials:

VS

Submission deadline:

16-12-22

Target date for return of marked assignment:

20-01-23

You are expected to spend about

130

hours to complete this assignment to a satisfactory standard.

This assignment is worth

50%

of the overall assessment for this module.

Notes for students

Forundergraduate modules:

• a score of 40% or above represents a pass performance at honours level.
• late submission of any item of coursework for each day or part thereof (or for hard copy submission only, working day or part thereof) for up to five days after the published deadline, coursework relating to modules at Levels 0, 4, 5, 6 submitted late (including deferred coursework, but with the exception of referred coursework), will have the numeric grade reduced by 10 grade points until or unless the numeric grade reaches or is 40. Where the numeric grade awarded for the assessment is less than 40, no lateness penalty will be applied.

Forpostgraduate modules:

• a score of 50% or above represents a pass mark.
• late submission of any item of coursework for each day or part thereof (or for hard copy submission only, working day or part thereof) for up to five days after the published deadline, coursework relating to modules at Level 7 submitted late (including deferred coursework, but with the exception of referred coursework), will have the numeric grade reduced by 10 grade points until or unless the numeric grade reaches or is 50. Where the numeric grade awarded for the assessment is less than 50, no lateness penalty will be applied.

• Late submission of referred coursework will automatically be awarded a grade of zero (0).
• Coursework (including deferred coursework) submitted later than five days (five working days in the case of hard copy submission) after the published deadline will be awarded a grade of zero (0).
• Regulations governing assessment offences including Plagiarism and Collusion are available from

https://www.herts.ac.uk/about-us/governance/university-policies-and-regulations-uprs/uprs (refer to UPR AS14)

Guidance on avoiding plagiarism can be found here:

https://herts.instructure.com/courses/61421/pages/referencing-avoiding-plagiarism?module_item_id=779436

Modules may have several components of assessment and may require a pass in all elements. For further details, please consult the relevant Module Handbook (available on Studynet/Canvas, under Module Information) or ask the Module Leader.

This Assignment assesses the following module Learning Outcomes (from Definitive Module Document):

Knowledge and understanding:

LO1 Have a conceptual understanding of how established techniques of research are used to create and extend existing knowledge in computer science.

LO2 Be able to identify a research problem from synthesizing problem definitions from relevant literature.

LO3 Demonstrate originality in proposing alternative solutions within a chosen area.

Skills and attributes

LO4 Critically evaluate research literature and identify research problems to solve

LO5 Demonstrate ability to propose alternative approaches for future work in a chosen area.

LO6 Communicate research knowledge effectively in scholarly manner.

Aim: To provide exposure to research areas in Computer Science drawn from the Departments research profile in order to provide preparatory ground for students to pursue a deeper investigation of a research topic as part of their Masters project.

Assignment Brief:

In order to conduct independent research in computer science you must fully understand the research area you have chosen. You must have a good grasp of the current open questions in this area, as well as any common techniques used to solve problems.

In this assignment you must provide an extended analysis of the 7COM1084 Research Specialism paper corresponding to your degree award specialism (AI / Networking / Cyber Security / Software Engineering / Data Science).Students without a degree specialism may choose any one of these specialisms, provided it is not the same as the specialism you chose for A1.

You must discuss the research question presented within your chosen 7COM1084 Research Specialism paper, propose some research approaches to investigate this question and identify further work you might undertake which builds on this. You must also explore your personal strengths in this area.

Submission Requirements:

You are required to submit a Word document containing your report via Studynet. Your report must not exceed 2800 words (+ / - 10%).

You must include a title page showing the module code, your name student number, MSc route and the words Portfolio Coursework,

Please note that you are encouraged to use Turnitin as part of your personal development.

Marks awarded for:

Please see the detailed marking scheme below.

Type of Feedback to be given for this assignment:

Feedback will be in the form of a score and tutor comments on your work.

Feedback will be made available via Studynet and email.

Criteria

Fail / No merit

0-19

Clear Fail

20 - 39

Marginal Fail

40-49

Good / Pass

50-59

Very good

60-69

Excellent

70-79

Outstanding

80-100

Content

Report is factually incorrect in several major aspects and contains significant spelling / grammar and structural errors. References are wholly irrelevant, and inadequate to demonstrate a grasp of the material. Technical terms lacking, or frequently used incorrectly. Research skills demonstrate a clear lack of originality in approach to identifying and resolving an open problem. No appropriate techniques to use within the problem domain are described. Discussion of personal investment is absent, or no attempt to perform critical analysis of self and own behaviour.

Report has significant factual errors, in addition to containing spelling / grammar and structural errors. References are sometimes relevant, and inadequate to demonstrate a grasp of the material. Technical terms lacking, or frequently used incorrectly. Research skills do not demonstrate originality in approach to identifying and resolving an open problem. Most techniques described are inadequate to use within the problem domain, failing to demonstrate a grasp of overall expectations in : identifying specific, measurable, attainable, realistic, timely, important and meaningful research solutions. Discussion of personal investment is inadequate for purpose, with little or no attempt to perform critical analysis of self and own behaviour.

Report lacks some clarity and has significant grammar, spelling and structure errors. References are relevant, but inadequate to demonstrate a grasp of the material. Technical terms lacking, or sometimes used incorrectly. Research skills do not demonstrate adequate originality in approach to identifying and resolving an open problem. General use of inadequate techniques

to the problem domain, failing to meet overall expectations in : identifying specific, measurable, attainable, realistic, timely, important and meaningful research solutions. Discussion of personal investment is inadequate for purpose, with insufficient critical analysis of self and own behaviour.

Adequate clarity of writing, with several spelling / grammar errors and one or more structural errors. Adequate referencing, but does not go beyond the material presented in lecture slides. Use of technical terms is sometimes misleading, and research skills demonstrate adequate originality in approach to identifying and resolving an open problem. Adequate use of appropriate techniques

to the problem domain, meeting expectations in : identifying specific, measurable, attainable, realistic, timely, important and meaningful research solutions. Adequate discussion of personal investment, with room for improvement in critical analysis of self and own behavior.

Well-written with potentially several minor spelling / grammar or structural errors. Ideas presented with clarity. Good referencing, but some mistakes present either in references or use of technical terms. Research skills sometimes demonstrate originality and / or creativity in approach to identifying and resolving an open problem, as well as an adequate grasp of the application of any such solution to this. General use of appropriate techniques

to the problem domain, sometimes exceeding expectations in: identifying specific, measurable, attainable, realistic, timely, important and meaningful research solutions. Good discussion of personal investment, demonstrating adequate critical analysis of self and own behavior.

Fluently written with very few errors. Very minor grammar/spelling or structural errors. Ideas presented with excellent clarity.

Excellent referencing in text and generally minimal mistakes in use of technical terms. Research skills demonstrate originality and / or creativity in approach to identifying and resolving an open problem, as well as an excellent grasp of the application of any such solution to this. Excellent use of appropriate techniques

to the problem domain, frequently exceeding expectations in terms of identifying specific, measurable, attainable, realistic, timely, important and meaningful research solutions. Excellent discussion of personal investment, demonstrating critical analysis of self and own behavior and recognition of skills and strengths in conducting research.

Outstanding presentation and clarity. No

significant grammatical / spelling or structural errors. Ideas presented with exceptional clarity. Outstanding standard and breadth of referencing in text and few, if any, mistakes in use of technical terms. Research skills frequently demonstrate originality and creativity in approach to identifying and resolving an open problem, as well as an outstanding grasp of the application of any such solution to this.

Outstanding use of appropriate techniques

to the problem domain, consistently exceeding expectations identifying specific, measurable, attainable, realistic, timely, important and meaningful research solutions. Outstanding discussion of personal investment, demonstrating outstanding critical analysis of self and own behavior and recognition of the role of emotions, skills and strengths in conducting research.