Course Title: Collect and manage data
Part B: Course Detail
Teaching Period: Term1 2017
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 4309
Course Contact Email: namrita.kaul@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Dr Anna Moodie
anna.moodie@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 face to face classes, field trips, online research and group discussions.
Within this course students will receive a 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
Week No. |
Date |
Learning activity |
Assessment |
1. |
7/02/17 |
No class
|
|
2. |
14/02/17 |
Class introductions Introduction to Data Collection Why survey? What is a hypothesis? |
|
3. |
21/02/17 |
Types of data What are variables? Preparation for Assessment 1: What techniques are to be used? Data collection sheet |
|
4. |
28/02/17
2/3/17 |
Tuesday: Statistical terms - Simple Data analysis Preparation for Assessment 1 – check of Data collection sheet Use of excel introduction
Thursday: Collecting tree data – practical at Royal Park gardens |
Field trip |
5. |
7/03/17 |
Enter Data - collation of Assessment task 1 Use of excel; graphs in excel |
|
6. |
14/3/17
|
Results for assessment task one Graphs in excel |
|
7. |
21/03/17 |
What is validity? Sufficiency? Reliability? Relevant? |
Assessment task 1 due |
8. |
28/03/17 |
Macroinvertebrates and Waterwatch Planning Data Collection for Macroinvertebrates Data statistics Community Data collection |
|
9. |
4/04/17 |
Tuesday 4th: Field trip preparation
Thursday 6th: Field trip waterwatch to collect data |
Field trip |
10. |
11/04/17 |
Macroinvertebrate data collation
|
|
|
|
Mid Semester Break, no classes Thursday 13th April – Wednesday 19th April |
|
11. |
25/04/17 |
No class – ANZAC Day
|
Assessment task 2 due |
12. |
02/05/17 |
No class – work on assignments (Anna on second year camp) |
|
13. |
9/05/17 |
Data collection problems |
Assessment task 3 due |
14. |
16/05/17 |
Field trip prep
Thursday: field trip to be confirmed |
Field trip |
15. |
23/05/17 |
Interpreting results |
|
16. |
30/06/17 |
Creating maps and graphs |
|
|
|
Mid year break No Classes between 6 June and 2 July |
|
Semester 2 schedule to be advised
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
Assessments demonstrating competence |
Title |
Due Date
|
% Mark |
1 Tree Study |
Tree Study
|
26/03/2017 |
15% |
2 Macroinvertebrate Survey scope |
Define and discuss the Waterwatch project
|
30/04/2017 |
10% |
3 Macroinvertebrate Survey Data Collection |
Collect macroinvertebrate data using Waterwatch technique |
14/05/17 |
15% |
|
Second semester assessments – more information at the start of semester 2 |
|
60% |
Assessment Matrix
Other Information
Assessment information
This course is graded in accordance with competency-based assessment, but which also utilises graded assessment
CHD Competent with High Distinction (80 – 100%)
CDI Competent with Distinction (60 – 79%)
CC Competent with Credit (50 – 59%)
CAG Competency Achieved – Graded (0 – 49%)
NYC Not Yet Competent
DNS Did Not Submit for assessment
To pass the course you need to pass, on average, each type of assessment (reports, assignments etc.)
- 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 is lodged with the School Admin Office on Level 6, Bdg 51. 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, 48 hours 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.
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