ACARA Digital Technologies Years 7–8 — Acquiring and Storing Data
Collecting data and keeping it clean.
Modules (73)
1
Data and information
2
Primary and secondary data sources
3
Quantitative data
4
Qualitative data
5
Data requirements for a research question
6
Judging whether collected data is essential
7
Collecting data with a survey
8
Writing unbiased survey questions
9
Closed and open survey questions
10
Choosing who to survey: sample and sample size
11
Data quality: bias
12
Linking an online form to a spreadsheet
13
Entering survey responses consistently
14
What a sensor is
15
Temperature sensor
16
Moisture sensor
17
Light sensor
18
Accelerometer sensor
19
Matching sensors to the data they capture
20
Data collected over a period of time
21
Reading the micro:bit temperature with input.temperature()
22
Recording readings with datalogger.log()
23
Copying a micro:bit data log into a spreadsheet
24
Faulty sensor readings and outliers
25
Open data portals and data licences
26
Authentic data in large repositories
27
Searching and filtering a data repository
28
Dataset file formats: CSV, XLSX, JSON and XML
29
Importing data from a CSV file
30
Generating sample test data
31
Spreadsheet rows, columns and cells
32
Cell references like A1
33
Entering data into cells
34
Header labels for rows and columns
35
Organising data in a table with headings
36
Naming worksheets consistently
37
Text data: character and string
38
Numeric data: integer
39
Numeric data: floating point
40
Date/time data
41
Choosing a data type for a value
42
Formatting numbers and cells
43
Formulas start with =
44
Copying a formula down a column
45
Absolute cell references with $
46
The MIN and MAX functions
47
The COUNT function
48
The AVERAGE function
49
Sorting data
50
Filtering data
51
The IF function in a spreadsheet
52
COUNTIF and SUMIF
53
Data quality: accuracy
54
Cleaning data
55
Keeping an untouched copy of the raw data
56
Existence checking in a spreadsheet
57
Handling missing values
58
Flagging duplicates with a COUNTIF formula
59
Removing duplicate rows
60
Range checking in a spreadsheet
61
Flagging out-of-range values with IF and OR
62
Type checking in a spreadsheet
63
Converting text to numbers and fixing date formats
64
Conditional formatting
65
Cleaning text with TRIM, UPPER and PROPER
66
Fixing spelling variations with Find and Replace
67
Validation: why data is checked on entry
68
Types of validation check
69
Number range validation in a spreadsheet
70
Drop-down list validation in a spreadsheet
71
Validation messages and error alerts
72
Counting data problems with a quality summary
73
Keeping a cleaning log
Smaller journeys, one per content description
The same modules, split up so a class can take just the content description it's working on.
13
ACARA 7-8 Digital Technologies: Understanding data and collecting it with surveys — AC9TDI8P01, AC9TDI8P14
Students learn the kinds and sources of data, decide what data is essential, and collect and record survey data fairly.
17
ACARA 7-8 Digital Technologies: Acquiring data from sensors and online repositories — AC9TDI8P01
Students learn how sensors, the micro:bit data logger and online data repositories supply data, and how to bring that data into a spreadsheet.
12
ACARA 7-8 Digital Technologies: Storing data in a spreadsheet — AC9TDI8P01
Students learn how to lay out data in cells, headings and tables and choose the right data type for each value.
10
ACARA 7-8 Digital Technologies: Spreadsheet formulas and tools for data — AC9TDI8P01
Students learn to use formulas, functions, sorting and filtering to summarise and examine stored data.
14
ACARA 7-8 Digital Technologies: Cleaning data — AC9TDI8P01
Students learn to keep a raw copy and then find and fix missing, duplicate, out-of-range and badly formatted values using spreadsheet formulas and techniques.
7
ACARA 7-8 Digital Technologies: Validating data and checking quality — AC9TDI8P01
Students learn to block bad data with validation rules when it is entered, then count remaining problems and record the cleaning they did.
Printables for this journey
Every module above has its own free printable worksheet with an answer key. These crosswords and word searches cover the same terms:
✎
Years 5–6 Data & Information Crossword: Data, information and binary representation (Modules 1–10)
10 clues · Data and information, Types of data: numbers and text, Types of data: images, sound and video, Same data, different representations and more
✎
Years 5–6 Data & Information Crossword: Data, information and binary representation and Acquiring and manipulating data (Modules 11–20)
10 clues · Representing images with pixels, Primary and secondary data sources, Collecting data with a survey, Spreadsheet rows, columns and cells and more
✎
Years 5–6 Data & Information Crossword: Acquiring and manipulating data and Analysing and visualising data (Modules 21–30)
10 clues · Cleaning data, Formulas start with =, Arithmetic operators + - * /, The SUM function and more
🔎
Years 5–6 Data & Information Word Search: Data, information and binary representation and Acquiring and manipulating data (Modules 1–20)
20 words to find · Data and information, Types of data: numbers and text, Types of data: images, sound and video, Same data, different representations and more
🔎
Years 5–6 Data & Information Word Search: Acquiring and manipulating data to Digital footprint and privacy (Modules 21–56)
20 words to find · Cleaning data, Formulas start with =, Arithmetic operators + - * /, The SUM function and more
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VCE Data Analysis Crossword: Types and purposes of data (Modules 3–14)
10 clues · Quantitative data, Qualitative data, Purposes of qualitative and quantitative data, Interviews to gather perspectives on a topical issue and more
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VCE Data Analysis Crossword: Types and purposes of data and Data types and data characteristics (Modules 15–24)
10 clues · Open data portals and data licences, Text data: character and string, Numeric data: integer, Numeric data: floating point and more
✎
VCE Data Analysis Crossword: Data types and data characteristics to Privacy and the Australian Privacy Principles (Modules 25–37)
10 clues · Characteristic of data: accessibility, Characteristic of information: clarity, Characteristic of information: context, Data quality: accuracy and more
🔎
VCE Data Analysis Word Search: Types and purposes of data and Data types and data characteristics (Modules 3–24)
20 words to find · Quantitative data, Qualitative data, Purposes of qualitative and quantitative data, Interviews to gather perspectives on a topical issue and more
🔎
VCE Data Analysis Word Search: Data types and data characteristics to Ethics and APA referencing (Modules 25–54)
20 words to find · Characteristic of data: accessibility, Characteristic of information: clarity, Characteristic of information: context, Data quality: accuracy and more
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VCE Spreadsheets, SQL & Visualisation Crossword: Spreadsheet structure, formulas and functions and Descriptive statistics (Modules 4–20)
10 clues · Naming worksheets consistently, Header labels for rows and columns, Relative and absolute cell references, The COUNTIF function and more
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VCE Spreadsheets, SQL & Visualisation Crossword: Descriptive statistics and Manipulating, validating and testing spreadsheet data (Modules 21–34)
10 clues · Grouping numbers into bins with COUNTIFS, The STDEV.S function, Interpreting standard deviation, Cleaning text with TRIM, UPPER and PROPER and more
🔎
VCE Spreadsheets, SQL & Visualisation Word Search: Spreadsheet structure, formulas and functions to Manipulating, validating and testing spreadsheet data (Modules 4–34)
20 words to find · Naming worksheets consistently, Header labels for rows and columns, Relative and absolute cell references, The COUNTIF function and more
✎
VCE Software Development U3O1 Crossword: Data sources and files to Graphical user interfaces (Modules 114–124)
10 clues · Reading an XML file with ElementTree, Validation: why data is checked on entry, Types of validation check, Existence checking in code and more
🔎
VCE Software Development U3O1 Word Search: Data sources and files to Object-oriented programming (Modules 114–141)
20 words to find · Reading an XML file with ElementTree, Validation: why data is checked on entry, Types of validation check, Existence checking in code and more
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VCE Data Analytics U3O1 Crossword: Data types and relational databases to Sourcing, validating and referencing data (Modules 17–49)
10 clues · Field sizes, SQL column data types and sizes, One-to-many relationships between tables, Boolean operators AND, OR and NOT in a WHERE clause and more
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VCE Data Analytics U3O1 Crossword: Sourcing, validating and referencing data to Statistical analysis of data (Modules 50–91)
10 clues · Setting spreadsheet data validation rules, Removing duplicate rows, Handling missing values, Converting text to numbers and fixing date formats and more
🔎
VCE Data Analytics U3O1 Word Search: Data types and relational databases to Statistical analysis of data (Modules 17–91)
20 words to find · Field sizes, SQL column data types and sizes, One-to-many relationships between tables, Boolean operators AND, OR and NOT in a WHERE clause and more
✎
VCE Data Analytics U3O2 Crossword: Research questions and project planning to Collecting primary and secondary data (Modules 3–31)
10 clues · What a research question is, Research question feature: clarity, Research question feature: measurability of data requirements, Research question feature: feasibility and more
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VCE Data Analytics U3O2 Crossword: Collecting primary and secondary data to Data integrity (Modules 32–75)
10 clues · Searching with keywords and search operators, Searching and filtering a data repository, One-dimensional arrays, Records: grouping fields of different data types and more
🔎
VCE Data Analytics U3O2 Word Search: Research questions and project planning to Evaluating designs and design tools (Modules 3–146)
21 words to find · What a research question is, Research question feature: clarity, Research question feature: measurability of data requirements, Research question feature: feasibility and more
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Years 7–8 Data & Information Crossword: Representing data with binary and Acquiring, storing and validating data (Modules 9–45)
10 clues · 8-bit binary numbers and the range 0 to 255, Converting a larger decimal number to binary, How many values n bits can store, Looking up characters in the ASCII table and more
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Years 7–8 Data & Information Crossword: Sharing online and managing projects and Digital footprint and privacy (Modules 100–124)
10 clues · Tracking task progress, Roles and responsibilities in a team project, The iterative cycle: create, test, improve, Cookies and trackers and more
🔎
Years 7–8 Data & Information Word Search: Representing data with binary to Using digital tools and conventions (Modules 9–80)
22 words to find · 8-bit binary numbers and the range 0 to 255, Converting a larger decimal number to binary, How many values n bits can store, Looking up characters in the ASCII table and more
🔎
Years 7–8 Data & Information Word Search: Using digital tools and conventions to Digital footprint and privacy (Modules 87–124)
20 words to find · Applying heading and style conventions in a document, Adding alt text to images, Choosing a file format for sharing content, Sharing a file online with permissions and more
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Years 9–10 Data & Information Crossword: Data compression to Acquiring, storing and validating data (Modules 17–51)
10 clues · Choosing a compression format for a task, Content, structure and presentation of a document, Restyling one document with a different stylesheet, Why separating content, structure and presentation matters and more
🔎
Years 9–10 Data & Information Word Search: Data compression to Data privacy and the Australian Privacy Principles (Modules 6–132)
21 words to find · Redundancy: repeated data that can be shortened, Lossless compression, Lossy compression, Run-length encoding: encoding text and more
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IGCSE Computer Science Paper 1 Crossword: 3.2 Input and Output Devices (Modules 273–282)
10 clues · 3D printer, Speaker, Actuator, Choosing a suitable output device for a context and more
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IGCSE Computer Science Paper 1 Crossword: 3.2 Input and Output Devices (Modules 283–292)
10 clues · Humidity sensor, Infra-red sensor, Level sensor, Light sensor and more
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IGCSE Computer Science Paper 1 Crossword: 3.2 Input and Output Devices and 3.3 Data Storage (Modules 293–303)
10 clues · Sensors, microprocessor and actuator in a control system, Matching sensors to the data they capture, Choosing the most suitable sensor for a given context, Choosing input devices, output devices and sensors together for a system and more
🔎
IGCSE Computer Science Paper 1 Word Search: 3.2 Input and Output Devices (Modules 262–282)
22 words to find · Choosing a suitable input device for a context, LCD screen, LED screen, Comparing LCD and LED screens and more
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IGCSE Computer Science Paper 1 Word Search: 3.2 Input and Output Devices and 3.3 Data Storage (Modules 283–303)
22 words to find · Humidity sensor, Infra-red sensor, Level sensor, Light sensor and more
✎
Crossword: Binary Number Representation and Acquiring and Storing Data (Modules 204–236)
10 clues · How storage keeps bits, Explaining why digital technology uses binary, Closed and open survey questions, Choosing who to survey: sample and sample size and more
✎
Crossword: Acquiring and Storing Data and Analysing and Visualising Data (Modules 261–300)
10 clues · Keeping an untouched copy of the raw data, Flagging duplicates with a COUNTIF formula, Flagging out-of-range values with IF and OR, Fixing spelling variations with Find and Replace and more
🔎
Word Search: Binary Number Representation and Acquiring and Storing Data (Modules 189–236)
21 words to find · Most and least significant bit, Reading 101 in binary: digits, not a hundred and one, Converting numbers 0 to 31 with five bits, Leading zeros and fixed-width binary and more
🔎
Word Search: Acquiring and Storing Data and Analysing and Visualising Data (Modules 261–324)
20 words to find · Keeping an untouched copy of the raw data, Flagging duplicates with a COUNTIF formula, Flagging out-of-range values with IF and OR, Fixing spelling variations with Find and Replace and more
Frequently Asked Questions
Are these worksheets free?
Yes — every worksheet and its answer key is free to view, download, and print, with no account required to access any individual module.
Do I need an account?
No account is needed to view or print a worksheet. A free teacher account adds extras like assigning modules to a class and tracking progress automatically — it takes under three minutes to set up and doesn't need a credit card.
What year level is this for?
This curriculum is aligned to the Australian Curriculum (ACARA) and Victorian Curriculum, spanning roughly Years 3 to 10 — from first sequencing and variables through to object-oriented programming and advanced data structures. Start wherever matches your class's current level; each module builds on the last.
Can I print them?
Yes — every module has a one-click Print Worksheet button that generates a printable page with the practice questions and a full answer key.
Is this aligned to a curriculum?
Yes — the module sequence is mapped to the Australian Curriculum (ACARA) and Victorian Curriculum, and a class's progress is reported back against those curriculum bands (e.g. ACARA Years 5–6 sequencing and iteration, Years 7–8 functions and data structures), not just a generic difficulty scale.
Can students use this without a teacher?
Yes — students can start any module and practice directly, no class or account required. Joining a teacher's class with a class code adds progress tracking, class badges, and live Sprints, but isn't needed to work through the worksheets or modules solo.
Do I need to know ACARA Digital Technologies Years 7–8 myself to teach this?
No — every module comes with a full worked answer key, and Cloodit tracks who's stuck automatically, so you don't need to solve each exercise yourself before assigning it or be able to debug a student's work line by line.
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