Course Title: Collect and manage data
Part B: Course Detail
Teaching Period: Term2 2020
Course Code: MATH7077C
Course Title: Collect and manage data
School: 174T School of VE Engineering, Health & Science
Campus: City Campus
Program: C5367 - Diploma of Conservation and Land Management
Course Contact: Namrita Kaul
Course Contact Phone: +61 3 9925 4837
Course Contact Email: namrita.kaul@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Gay De Lisle
gay.de.lisle@rmit.edu.au
Nominal Hours: 120
Regardless of the mode of delivery, represent a guide to the relative teaching time and student effort required to successfully achieve a particular competency/module. This may include not only scheduled classes or workplace visits but also the amount of effort required to undertake, evaluate and complete all assessment requirements, including any non-classroom activities.
Pre-requisites and Co-requisites
None
Course Description
This unit of competency describes the skills and knowledge required to collect, analyse and manage data.
National Codes, Titles, Elements and Performance Criteria
National Element Code & Title: |
AHCWRK502 Collect and manage data |
Element: |
1. Determine the type and extent of data to be collected |
Performance Criteria: |
1.1 Define data requirements and communicate to all staff involved in data collection |
Element: |
2. Access and collate data |
Performance Criteria: |
2.1 Format data collection sheets to assist collection |
Element: |
3. Evaluate data |
Performance Criteria: |
3.1 Collect data that is relevant, valid and sufficient |
Element: |
4. Manage and retrieve data |
Performance Criteria: |
4.1 Store data by appropriate electronic means 4.2 Present data using appropriate graphical aids and techniques |
Element: |
5. Analyse and interpret data |
Performance Criteria: |
5.1 Analyse data using appropriate statistical and analytical techniques |
Learning Outcomes
Details of Learning Activities
Learning activities include online classes using Collaborate Ultra in Canvas, field trips, online research and group discussions.
Within this course students will receive training in how data is collected, recorded, managed and reported. It includes different methodologies of collection and evaluation, including two key examples of data collection.
All learning activities will provide opportunities for students to learn accepted procedures for collecting and managing data and to evaluate the effectiveness of those procedures.
Teaching Schedule
Teaching Schedule 2020
Week No |
Week Starting |
Teaching schedule |
1 |
6 July |
Intro Intro to Assessment Task 1 |
2 |
13 July |
Create a map Create a data sheet |
3 |
20 July |
Types of Data Data Collection Methods |
4 |
27 July |
Field Work Carlton Gardens |
5 |
3 Aug |
Preparation for Assessment Task 1 Field Work Thursday Aug 6 - Royal Park |
10 Aug |
Collate Tree Data Using Excell for graphs |
|
7 |
17 Aug |
Statistical Terminology |
8 |
24 Aug |
EVC's |
|
31 Aug |
Semester Break |
9 |
7 Sep |
No Class Monday Field Work Thursday September 10 - Dandenongs |
10 |
14 Sep |
Issues of Data Collection |
11 |
21 Sep |
No Class |
12 |
28 Sep |
No Class |
13 |
5 Oct |
Community Data Collection Macroinvertebrate Sampling Discussion of Assessment Task 3 |
14 |
12 Oct |
No class Monday Thursday Field Trip Darebin Parklands Collect Data for Assessment Task 3 |
15 |
19 Oct |
Collate Data for Assessment Task 3 Discuss Assessment Task 3 |
16 |
26 Oct |
No Class |
Learning Resources
Prescribed Texts
References
Other Resources
Overview of Assessment
Assessment for this competency may include collection, analysis, evaluation and interpretation of data following field trips, written reports and group work
Assessment Tasks
Sun, 23 Aug 2020 |
|
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Sun, 6 Sep 2020 |
|
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Sun, 25 Oct 2020 |
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Assessment Matrix
Other Information
Assessment information
This course is graded in accordance with competency-based assessment
CA Competency Achieved
NYC Not Yet Competent
DNS Did Not Submit for assessment
To pass this course you need to achieve a satisfactory result for all assessments. Students may be given additional opportunities to demonstrate competence.
Late work that is submitted without an application for an extension (see below) will not be corrected.
- APPLICATION FOR EXTENSION OF TIME FOR SUBMISSION OF ASSESSABLE WORK - A student may apply for an extension of up to 7 days from the original due date. They must lodge the application form (available online http://www1.rmit.edu.au/students/assessment/extension) at least 24 hours before the due date. The application should be emailed to the program Coordinator (namrita.kaul@rmit.edu.au) Students requiring longer extensions must apply for SPECIAL CONSIDERATION.
- For missed assessments such as tests and field trips- you (& your doctor if you are sick) must fill out a special consideration form. This form must be lodged online with supporting evidence prior to, or within, 5 days of the scheduled time of the assessment http://www1.rmit.edu.au/students/specialconsideration
Plagiarism is the presentation of the work, idea or creation of another person as though it is your own. It is a form of cheating and is a very serious academic offence that may lead to expulsion from the University. Plagiarised material can be drawn from, and presented in, written, graphic and visual form, including electronic data and oral presentation. Plagiarism occurs when the origin of the material used is not appropriately cited. It also occurs through enabling plagiarism, which is the act of assisting or allowing another person to plagiarise or to copy your own work. Please make sure you consider this carefully in completing all your work and assessments in this course and if you are unsure about whether you might have plagiarised, seek help from your teacher.
Course guides for Semester 2, 2020 were finalised and published before the semester started with all the teaching, learning and assessment information current at that time. Please note that some course guides may have small differences between Part A and Part B because of necessary changes (related to COVID-19) made to Part B during the semester.
Course Overview: Access Course Overview