Unit of Competency Mapping – Information for Teachers/Assessors – Information for Learners

MSS025003A Mapping and Delivery Guide
Report environmental data

Version 1.0
Issue Date: April 2024


Qualification -
Unit of Competency MSS025003A - Report environmental data
Description This unit of competency covers the ability to perform scientific calculations, process and interrogate environmental data sets, analyse trends and uncertainty in data, and report results within the required timeframe. The unit requires personnel to solve problems where alternatives are not obvious and where investigations and trials may be required and the implications of various solutions considered.
Employability Skills Not applicable.
Learning Outcomes and Application This unit of competency is applicable to environmental technicians working in all industry sectors.
Duration and Setting X weeks, nominally xx hours, delivered in a classroom/online/blended learning setting.
Prerequisites/co-requisites MSS024004A Process and present environmental data
Competency Field
Development and validation strategy and guide for assessors and learners Student Learning Resources Handouts
Activities 		Slides
PPT 		Assessment 1 Assessment 2 Assessment 3 Assessment 4
Elements of Competency Performance Criteria              
Element: Perform scientific calculations
  • Ensure raw data are consistent with expectations and reasonable ranges
  • Calculate scientific quantities involving algebraic, power, exponential and/or logarithmic functions
  • Ensure calculated quantities are consistent with estimations
  • Present results using the appropriate units, uncertainties and number of significant figures
       
Element: Determine variation and/or uncertainty in data distributions
  • Organise raw data into appropriate frequency distributions
  • Calculate means, medians, modes, ranges and standard deviations for ungrouped and grouped data
  • Interpret frequency distributions to determine the characteristics of the sample or population
  • Calculate standard deviations and confidence limits for means and replicates
  • Estimate the sampling error and/or uncertainty in data using statistical analysis
  • Determine data acceptability using statistical tests and enterprise procedures
       
Element: Interpret data and related statistics
  • Recognise significant trends in data
  • Use standard statistical methods to test for an association or correlation between variables
  • Use standard statistical methods to test hypotheses involving the same variable between samples, samples with more than one variable and for paired samples
  • Verify data interpretation with supervisor, as necessary
       
Element: Check for aberrant data sets
  • Identify data that cannot be reconciled with sample, data set and/or documentation, monitoring procedures and/or expected outcomes
  • Determine appropriate actions in consultation with supervisor, as necessary
       
Element: Report data and analysis
  • Use charts, tables and graphs to present summarised data and analysis results in the required format
  • Verify that entry of data and results are correct
  • Clearly identify summary information and any significant trends and/or problems with data
  • Prepare reports in a format and style consistent with their intended use and enterprise guidelines
  • Communicate results within the specified time and in accordance with enterprise confidentiality and security guidelines.
       


Evidence Required

List the assessment methods to be used and the context and resources required for assessment. Copy and paste the relevant sections from the evidence guide below and then re-write these in plain English.

Overview of assessment

Competency must be demonstrated in the ability to perform consistently at the required standard.

Critical aspects for assessment and evidence required to demonstrate competency in this unit

Assessors must be satisfied that the candidate can competently and consistently apply the skills covered in this unit of competency in new and different situations and contexts. Critical aspects of assessment and evidence include:

storing, retrieving and manipulating environmental data in accordance with enterprise procedures and traceability requirements

calculating scientific quantities relevant to the work and presenting accurate results in the required format

choosing appropriate graphical/statistical methods to analyse given data sets

preparing frequency distributions for given data, and calculating and interpreting measures of central tendency and dispersion

analysing data to determine relationships between variables and samples

maintaining the security and confidentiality of data in accordance with workplace and regulatory requirements

reporting results in the required formats and expected timeframe.

Context of and specific resources for assessment

This unit of competency is to be assessed in the workplace or a simulated workplace environment.

Assessment should emphasise a workplace context and procedures found in the candidate’s workplace.

This unit of competency may be assessed with:

MSL924002A Use laboratory application software

environmental monitoring units, such as the MSS024000A and MSS025000A series units of competency.

The competencies covered by this unit would be demonstrated by an individual working alone or as part of a team.

Resources may include:

data sets and records

computer and relevant software or enterprise information system

relevant workplace procedures.

Method of assessment

The following assessment methods are suggested:

review of data worksheets, calculations, computer files (such as spreadsheets and databases), statistical analysis, graphs and/or tables prepared by the candidate

questions to assess understanding of relevant data handling procedures, graphical/statistical methods, trends in data and sources of uncertainty

review of reports prepared by the candidate

feedback from supervisors and peers regarding the candidate’s ability to analyse and report data in accordance with enterprise procedures.

In all cases, practical assessment should be supported by questions to assess underpinning knowledge and those aspects of competency which are difficult to assess directly.

Where applicable, reasonable adjustment must be made to work environments and training situations to accommodate ethnicity, age, gender, demographics and disability.

The language, literacy and numeracy demands of assessment should not be greater than those required to undertake the unit of competency in a work-like environment.

Guidance information for assessment

Submission Requirements

List each assessment task's title, type (eg project, observation/demonstration, essay, assignment, checklist) and due date here

Assessment task 1: [title]      Due date:

(add new lines for each of the assessment tasks)

Assessment Tasks

Copy and paste from the following data to produce each assessment task. Write these in plain English and spell out how, when and where the task is to be carried out, under what conditions, and what resources are needed. Include guidelines about how well the candidate has to perform a task for it to be judged satisfactory.

Required skills

Required skills include:

interpreting data handling procedures, guidelines and manuals

performing laboratory computations

calculating scientific quantities

performing basic statistical analysis

performing graphical analysis

reporting results in the required formats and expected timeframe

storing, retrieving and manipulating data following document traceability procedures

maintaining the security and confidentiality of data in accordance with workplace and regulatory requirements

seeking advice when issues/problems are beyond scope of competence/responsibility

Required knowledge

Required knowledge includes:

role of statistics in the interpretation/analysis of environmental data

relevant terminology, such as variables, dispersion, central tendency, normal distribution, confidence level and replication, inference, causation, association, correlation and hypothesis

characteristics of a valid measurement and valid sample

sources and estimates of uncertainty in measurements

calculations involving evaluation of formulae containing algebraic, power, exponential and/or logarithmic functions, measures of central tendency, sum of squares, variance and standard deviation

preparation and interpretation on linear and non-linear graphs, and frequency distribution plots

determination of regression line equations and correlation coefficients

statistical analysis and significance tests, such as t-test, analysis of variance (ANOVA), chi squared test and data acceptability tests, such as Q, T and Youden

procedures for data traceability

procedures for verifying data and rectifying mistakes

procedures for maintaining and filing records, and maintaining security of data

Codes of practice

Where reference is made to industry codes of practice, and/or Australian/international standards, it is expected the latest version will be used

Standards, codes, procedures and/or enterprise requirements

Standards, codes, procedures and/or enterprise requirements may include:

Australian and international standards, such as:

AS/NZS ISO 14000 Set:2005 Environmental management standards set

AS ISO 1000:1998 The international system of units (SI) and its application

Eurachem/CITAC Guide CG4 Quantifying uncertainty in analytical measurement

ISO 5725 Accuracy (trueness and precision) of measurement methods and results

ISO/IEC Guide 98-3:2008 Uncertainty of measurement - Part 3 Guide to the expression of uncertainty in measurement (GUM)

national measurement regulations and guidelines

National Association of Testing Authorities (NATA) technical notes

material safety data sheets (MSDS)

equipment manuals and warranty, supplier catalogues and handbooks

sampling and test procedures and standard operating procedures

enterprise quality manual

validation of the equipment and associated software, where applicable

validation of spreadsheets developed in-house for assay and process calculations

Data records

Data records may include:

worksheets

spreadsheets or databases linked to information management systems

the results of tests, measurements, analyses and surveys

Laboratory computations

Laboratory computations may include:

algebraic, logarithmic, exponential and power functions

calculations involving fractions, decimals, ratios, proportions and percentages

evaluation of formulae containing powers, exponents and logarithms functions

use of scientific notation, correct units and correct number of significant figures

calculation of uncertainties

preparation and interpretation of linear, semi-log and log-log graphs

calculation and interpretation of statistical quantities, such as mean, median, mode, range, variance and standard deviation

determination of regression line equations and correlation coefficients

Calculations of scientific quantities

Calculations of scientific quantities may include:

percentage and absolute uncertainties in measurements and test results

density and salinity

noise (dB and dBA)

dose (mg), dilution(1:10), concentration (molarity, g/mL, mg/L, ppm and ppb)

pH, [H+], [OH-], buffer calculations, Ka, pKa, Kb, pKb and Kw

solubility constants Ks and pKs

radioactive half life, dose, activity and exposure

optical properties, such as absorbance, transmittance, path length, extinction coefficient, concentration (Beers law) and detection limits

electrical properties, such as conductivity and resistivity

Graphical analysis

Graphical analysis may include:

determination of linear, logarithmic, exponential and power relationships

regression lines and interpretation of correlation coefficients

preparing frequency distributions for given data

calculating and interpreting measures of central tendency and dispersion

Calculations

Calculations may be performed:

with or without a calculator

with computer software, such as:

spreadsheets

databases

statistical packages

Statistical analysis

Statistical analysis may include the use of:

histograms, frequency plots, stem and leaf plots, box plots and scatter plots

probability and normal probability plots

regression methods for calibration, linearity checks and comparing analytical methods

Pearson’s product moment correlation coefficient

chi squared tests

ANOVA

data acceptability tests, such as Q, t and Youden

Records

Records may include information associated with:

purchase of equipment and materials

service records

safety procedures

history of calibration and test results

management of data sets

Occupational health and safety (OHS) and environmental management requirements

OHS and environmental management requirements:

all operations must comply with enterprise OHS and environmental management requirements, which may be imposed through state/territory or federal legislation - these requirements must not be compromised at any time

all operations assume the potentially hazardous nature of samples and require standard precautions to be applied

where relevant, users should access and apply current industry understanding of infection control issued by the National Health and Medical Research Council (NHMRC) and State and Territory Departments of Health

Copy and paste from the following performance criteria to create an observation checklist for each task. When you have finished writing your assessment tool every one of these must have been addressed, preferably several times in a variety of contexts. To ensure this occurs download the assessment matrix for the unit; enter each assessment task as a column header and place check marks against each performance criteria that task addresses.

Observation Checklist

Tasks to be observed according to workplace/college/TAFE policy and procedures, relevant legislation and Codes of Practice Yes No Comments/feedback
Ensure raw data are consistent with expectations and reasonable ranges 
Calculate scientific quantities involving algebraic, power, exponential and/or logarithmic functions 
Ensure calculated quantities are consistent with estimations 
Present results using the appropriate units, uncertainties and number of significant figures 
Organise raw data into appropriate frequency distributions 
Calculate means, medians, modes, ranges and standard deviations for ungrouped and grouped data 
Interpret frequency distributions to determine the characteristics of the sample or population 
Calculate standard deviations and confidence limits for means and replicates 
Estimate the sampling error and/or uncertainty in data using statistical analysis 
Determine data acceptability using statistical tests and enterprise procedures 
Recognise significant trends in data 
Use standard statistical methods to test for an association or correlation between variables 
Use standard statistical methods to test hypotheses involving the same variable between samples, samples with more than one variable and for paired samples 
Verify data interpretation with supervisor, as necessary 
Identify data that cannot be reconciled with sample, data set and/or documentation, monitoring procedures and/or expected outcomes 
Determine appropriate actions in consultation with supervisor, as necessary 
Use charts, tables and graphs to present summarised data and analysis results in the required format 
Verify that entry of data and results are correct 
Clearly identify summary information and any significant trends and/or problems with data 
Prepare reports in a format and style consistent with their intended use and enterprise guidelines 
Communicate results within the specified time and in accordance with enterprise confidentiality and security guidelines. 

Forms

Assessment Cover Sheet

MSS025003A - Report environmental data
Assessment task 1: [title]

Student name:

Student ID:

I declare that the assessment tasks submitted for this unit are my own work.

Student signature:

Result: Competent Not yet competent

Feedback to student

 

 

 

 

 

 

 

 

Assessor name:

Signature:

Date:

Assessment Record Sheet

MSS025003A - Report environmental data

Student name:

Student ID:

Assessment task 1: [title] Result: Competent Not yet competent

(add lines for each task)

Feedback to student:

 

 

 

 

 

 

 

 

Overall assessment result: Competent Not yet competent

Assessor name:

Signature:

Date:

Student signature:

Date: