Course Title: Collect and manage data

Part B: Course Detail

Teaching Period: Term1 2016

Course Code: MATH7058C

Course Title: Collect and manage data

School: 155T Vocational Health and Sciences

Campus: City Campus

Program: C5305 - 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

Sally Heeps

email: sally.heeps@rmit.edu.au

Please note that Sally is a sessional teacher and is only at RMIT on Tuesdays and Fridays. She may not be able to respond promptly to your emails. 
Please contact Namrita Kaul if the matter is urgent

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 competency standard covers the process of collecting, analysing and managing data.
It requires the ability to determine the type and extent of data to be collected, access and collate data, evaluate data,
manage, analyse and retrieve data. Collecting and managing data requires knowledge of data collection techniques and procedures,
data recording and evaluation techniques, data analysis and data storage and retrieval methods.


National Codes, Titles, Elements and Performance Criteria

National Element Code & Title:

AHCWRK502A Collect and manage data

Element:

1. Determine the type and extent of data to be collected
 

Performance Criteria:

1.1. Data requirements are clearly defined and communicated to all staff involved in data collection.
1.2. Relevant data sources are identified.
1.3. Type and extent of data required is clearly defined.
1.4. Occupational Health and Safety (OHS) hazards associated with data collecting are identified.
1.5. Data collection methods and techniques are clearly defined relative to data requirements.
 

Element:

2. Access and collate data
 

Performance Criteria:

2.1. Data collection sheets are formatted to assist collection.
2.2. Data is researched and/or collected from field sources according to enterprise guidelines and with standard research approaches.
2.3. Data is collated by appropriate electronic means.
2.4. Appropriateness of data is monitored and recorded during collection.
2.5. Information is researched using appropriate methods and technologies.
2.6. Sources of information are regularly reviewed for usefulness, validity, reliability and cost.
2.7. Channels and sources of information are used effectively.
2.8. Opportunities are taken to establish and maintain contacts with those who may provide useful information.
2.9. Appropriate OHS requirements and work practices are followed.

 

Element:

3. Evaluate data
 

Performance Criteria:

3.1. Data collected is relevant, valid and sufficient.
3.2. Where data is unclear or difficult to interpret, clarification and assistance is sought.
3.3. Where data is inadequate, additional data is obtained.
3.4. Information is analysed for its validity and reliability.
 

Element:

4. Manage and retrieve data
 

Performance Criteria:

4.1. Data is stored by appropriate electronic means.
4.2. Data is presented using appropriate graphical aids and techniques.
4.3. Data is assembled and provided to the manager/client as required and in accordance with standard research approaches.
4.4. Data is retrieved as required.
4.5. New methods of recording and storing data are suggested/introduced as needed.
 

Element:

5. Analyse and interpret data
 

Performance Criteria:

5.1. Data is analysed using appropriate statistical and analytical techniques.
5.2. Data is interpreted to determine its significance, validity and reliability.
5.3. Findings based on the analysis and interpretation of the data is reported.
5.4. Data is organised into a suitable report format to aid decision-making.
5.5. Conclusions drawn are based on reasoned argument and appropriate evidence.
 


Learning Outcomes


  • Data is researched using appropriate methods and technologies.
  • Data is collected from scientific sources and in the field.
  • Data collected is analysed for relevance and validity.
  • Data is stored by electronic means.
  • Data is assembled and provided to client as required to industry standard.
  • Data is analysed using appropriate statistical and analytical techniques.
  • Findings based on analysis and interpretation are reported.


Details of Learning Activities

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. These are the collection of macroinvertebrate data and techniques for vegetation surveys.
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.DateLearning ActivityAssessment
1 9/02/16 Introduction to Data Collection and Sampling
Types of data
Why survey? What is a hypothesis?
 
2 16/02/16 Preparation for Assessment 1: What types of data are to be collected?
What techniques are to be used? Data collection sheet
 
 
3 23/02/16 Statistical terms - Simple Data analysis
What are variables?
Preparation for Assessment 1 – check of Data collection sheet
 
 
4 01/03/16 Collecting tree data – practical at Royal Park gardens Field trip - am
5 8/03/16 Enter Data collation of Assessment task 1  
6 15/03/16 Results for assessment task one
Data statistics
What is validity? Sufficiency? Reliability? Relevant?
 
 
7 22/03/16 Data statistics
What is validity? Sufficiency? Reliability? Relevant?
 
Assessment task 1 due
8 5/04/16 Macroinvertebrates and Waterwatch
Planning Data Collection for Macroinvertebrates Data statistics
Community Data collection
 
 
9 12/04/16 Field trip prep  
  14/04/16 Field trip to collect data Field trip – Thursday
10 19/04/16 Data entry
Statistics and survey design
 
 
11 26/04/16 Data collection problems  
12 03/05/16 No class  
13 10/05/16 Results
Statistics
 
 
14 17/05/16 Field trip prep  
  19/05/16 Field trip to collect data Field trip – Thursday
15 24/05/16 Results
Creating maps and graphs
 
 
16 31/05/16 Assessment task 2 and 3 Assessment task 2 and 3 due

Semester Two schedule to follow
 


Learning Resources

Prescribed Texts


References


Other Resources


Overview of Assessment

 

  • Collect data on vertebrate fauna and freshwater macroinvertebrate fauna.
  • Prepare reports for clients (2 assessments).
  • Analyse, evaluate and interpret data following field trips (2 assessments). 


Assessment Tasks

There are seven assessment tasks for this course.  Six formative assessments and one summative assessment as follows:

Formative Task 1 – Tree Study due  22/03/2016 10%


Formative Task 2 – Macroinvertebrate Survey scope due 31/05/2016 10%


Formative Task 3 – Collect macroinvertebrate data using Waterwatch technique, to be carried out in the field  on the 12/04/2016 and 24/05/2016, assessment due 31/05/2016 10%


Formative Task 4 – Define project and Develop techniques for Data Collection of  Vegetation Data due 29/07/2016 10%


Formative Task 5 – Data collection in a Vegetation survey to be carried out in the field on the 2/08/2016 and 20/09/2016, assessment due 27/09/16  15%


Formative Task 6 – Self assessment of data collection techniques due  4/10/2016 15%
 

Summative Task 1 – Major Report - Data analysis and Data Collection Report due 25/10/2016 30%
 


Assessment Matrix

Other Information

Assessment information

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 exams 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
     

Course Overview: Access Course Overview