11:15 1
Task Details: This will be an online quiz based on multiple choice questions which the students will attempt during their tutorial session on campus only. Mobile phones, tablets, books, paper or any other writing material is not permitted. Students must use laptops provided by KOI and not open any tabs in browser apart from Moodie.
Submission requirements details: Quiz will be completed on Moodie and automatically graded. Assessment 3 Assessment type: MCQ Quiz. Individual
Purpose: Assessments will test the student’s understanding of concepts learnt in lecture, will be based on topics learnt in weeks 1 to 8. This assessment contributes to learning outcomes a, b.
Value: 10% Due Date: Week 7
Assessment topic: Based on weekly learning in lecture week 1 to 6
ICT 370 DATA ANALYTIC 1320 19/10/2020 16 08 ‘AUSTRALIAN INSTITUTE OF BUSINESS AND MANAGEMENT Pre LTD C ABN 72 132 629 979 Approved by KOI Academic Board for T3 2020
PAGE 9 OF IS CRICOS 03171A
ICT370 K > KO 1
Task Details: This will be an online quiz based on multiple choice questions which the students will attempt during their tutorial session on campus only. Mobile phones, tablets, books, paper or any other writing material Is not permitted. Students must use laptops provided by KOI and not open any tabs in browser apart from Moodie. Submission requirements details: Quiz will be completed on Moodie and automatically graded. Assessment 4 Assessment type: Group project – Presentation and Report (2,000 words) Purpose: The purpose of this assessment is that students will learn different Analytics techniques by searching for data sets and then analyzing these data sets using different tools and also by listening to presentations made by their peers. This assessment contributes to learning outcomes a, b, d.
Value: Total 25% (Presentation 10%, Report 15%) Due Date: Weeks 10-11 Assessment topic: Students to select a data source and suggest a topic of analysis for that data source. Tutors to approve the topic before students proceed further. Submission requirements details: The presentation to be conducted by group and also uploaded on Moodie in week 10. Report will have to be uploaded via Turnitin on Moodie in Week 11.
Task details: Students will work in groups (minimum 3 and maximum 4 students In each group) on data set identified by them and approved by their tutor. They will apply analytical methods to select a data set and summarize some of target models In Descriptive and Predictive Analytic layers to get it approved for their project. They will then use any analytical tools (e.g. Excel, Tableau, Rapid Miner) to extract their findings and draw insights from this data set.
The outcomes need to presented using Visualization models and also explained in a detailed report as explained below.
Students will present their findings as a group during tutorial sessions in week 10 for a duration of 10-15 mins per group. Tutors will provide feedback on their findings and students will then need to update their findings to reflect this feedback in their group report. Submission of group report will be due in Week 11. This will be 2,000 words report excluding references and executive summary. It should consist of the following structure: • Title Page (Student’s name and ID, Tutors name) • Executive Summary • Table of contents • Introduction (usually includes below section to explain the Data Set and its background): o Brief background information o Purpose o Scope o Definition of terms
Data Analysis Findings (could consist of): o Review of literature related to similar data sets o Summary of Groups Findings o Discussion about findings including any models and Visualizations to support the findings
Conclusion/recommendations (Response to Feedback and also any other suggestions to provide improvements in data set or findings)
ICT 370 DATA ANALYTIC T320 19/10/2020 1608
PAGE 10 OF 15
‘AUSTRALIAN INSTITUTE OF BUSINESS AND MANAGEMENT Pr! LTD C ABN: 72 132 629 979 CRICOS 03171A Approved by KOI Academic Board for T3 2020
ICT370
Marking Rubrics Assessment 4: Presentation (10%)
K >K0 I
Criteria Fall (0 – 49%) Pass (SO – 64%) Credit (BS – 74%) Distinction (75 – 84%) High Distinction (BS – 100%) sual appeal (group) There are m are no errors in No errors, engaging