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CMT206 Human Centric Computing

Creation date：2024-05-02 11:25:27

Belonging category：计算机computer science

Tag CMT206

Human Centric Computing

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CMT206

Human Centric Computing
Assessment Number: 1
This assignment is worth 100% (Q1: 33%, Q2: 33%, Q3:34%) of the total marks available for
this module. If coursework is submitted late (and where there are no extenuating
circumstances):

1 If the assessment is submitted no later than 24 hours after the deadline,
the mark for the assessment will be capped at the minimum pass mark;
2 If the assessment is submitted more than 24 hours after the deadline, a
mark of 0 will be given for the assessment.

Your submission must include the official Coursework Submission Cover sheet, which can be
found here:

Submission Instructions

Description Type Name
Cover sheet Compulsory One PDF (.pdf) file per assignment Q1_[student number].pdf
Q2_[student number].pdf
Q3_[student number].pdf
Q1 Compulsory One PDF (.pdf) file (Part 1)
+
Spreadsheet for Q1(Part 2)
Q1_[student number].pdf
Q1_[student number]_HE.xlsx
Q2 Compulsory One PDF (.pdf) file Q2_[student number].pdf
Q3 Compulsory One PDF (.pdf) file Q3_[student number].pdf

Any deviation from the submission instructions above (including the number and types of
files submitted) will result in a mark of zero for the assessment or question part.
Staff reserve the right to invite students to a meeting to discuss coursework submissions.

Q1

Virtual meeting applications (such as Zoom, Teams, Webex, Blackboard collaborate, etc.)
have become essential working and social communication tools. There are many
applications on the market, and all compete for users.
In this assignment you will consider the design of one of these tools and write a heuristic
evaluation report on the usability of its interface.
Q1. Part 1: User and Task Analysis (10 marks out of 20)
a. Choose one example of these applications. You can choose to consider a web
interface for the application or a mobile version of it.
Identify and describe One primary Persona for your application. Include all
components of the persona description, as discussed in the lectures.

Note: Applications can serve a wide variety of users and as such, may have multiple
primary personas. The persona you choose will guide your consideration for the
subsequent steps in this exercise. ((3 marks out of 10))

b. Identify and describe one primary and one secondary tasks/use cases in the system
(primary tasks are important and frequently used functions by your primary persona,
secondary tasks are desirable but are of less importance to your primary persona
than primary ones). For every use case, provide a brief (text) description and the
outline of the steps in its basic flow scenario and Two of its alternative flow
scenarios. ( (3 marks out of 10))

Note: Tasks such as Register/Login are not primary use cases. These are
supplementary functions to allow a user to access the primary function of the
system.

c. Produce Two State Transition Networks (STNs) to describe the interaction flow in
your use case scenarios (for the basic and alternative flows in each use case).
Use an abstract depiction of the screens with no detail on design elements of the
interface. Your STNs need only depict states and user actions between states in the
use case scenarios. ((4 marks out of 10))

Note: Generally speaking, an interface state changes when an event occurs. For
example, an entry of text in a text field, a click of a button, etc. Your STNs need to
depict all possible states of interaction in the use case scenarios.

Q1. Part 2: Heuristic Evaluation (10 marks out of 20)
For every use case, do a heuristic evaluation of the individual states of the interface,
identifying all usability issues.
Report on the usability issues in an objective manner and present the issues in a
systematic and standard format using the templates (Excel spreadsheet) provided and
discussed in the lectures. Your report should include,
a. the usability problems you identified with some justification of the severity score
assigned to the problems and your suggestions for addressing the issues you
identified in subsequent revisions of the interface, (5 marks out of 10)
b. the good design features that should be maintained in any subsequent revision of
the application. (5 marks out of 10)

Learning Outcomes Assessed
1. Understand the complex nature of users and apply heuristics to create and evaluate
inclusive and multimodal user experiences.
2. Evaluate competing proposals for interface design and implementation.
3. Apply human centric design methodologies in the context of current and emerging
interaction technologies such as virtual and augmented reality.
Criteria for assessment

Credit will be awarded against the following criteria.

Case category

Tag cloud

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LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 FINC5090 MATH1052 SciComp Elec4622 FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 MAT 237 BISM2201 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SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum

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