Explicit instruction breaks down what students need to learn into smaller learning outcomes and models each step. It allows students to process new information more effectively.

Why explicit instruction works

Understanding the science behind learning and memory can help teachers understand why explicit instruction is so effective. Explicit instruction is a very efficient strategy for helping students learn because it suits how the brain processes, stores, and retrieves information.

Memory types

The human brain can store a large amount of information in long-term memory, which can be thought of as a vast network of interconnected ideas. Effective teaching will successfully establish and build connections to new information in students’ long-term memory. Having more connections to a specific piece of information makes it easier to recall and use.

Another type of memory is working memory, which holds the information being used at any one time. The information held in working memory is not always stored as an individual fact, but rather a ‘chunk’ which can be anything from a single fact to a complex idea. Research has suggested that people can only hold four to seven chunks of information in working memory.

Preventing cognitive overload

Learning can suffer, and it can be harder to move information to long-term memory, if people are presented with more information than working memory can contain. The scientific term for having too much information in working memory is cognitive overload.

Presenting new information in manageable amounts helps students to learn more effectively. When a small amount of information is taught at one time, or when there are ample breaks in learning, students are not cognitively overloaded. They are more likely to be able to move the information from working memory to their long-term memory, where it can be easily used to build on existing long-term memories and retrieved in the future.

Effective across a variety of contexts

Explicit instruction has a strong evidence base that meets our highest standards of evidence. To understand whether explicit instruction is effective across different contexts, AERO conducted a review of more than 328 studies. The review found that explicit instruction is an effective teaching practice across a variety of contexts and for different subgroups of students. Studies conducted across various locations suggest that explicit instruction: 

  • has a positive impact on student achievement in mathematics, reading, spelling, problem solving and science  
  • works for primary and secondary students
  • benefits students with and without additional learning needs. 

Because of this, explicit instruction is likely to work in most contexts.

Using the practice

To be effective, explicit instruction needs to be implemented well. See below for more information on the ‘things to know’ when using the practice.

Planning for explicit instruction

Archer and Hughes (2011) provide a useful planning guide with their 6 teaching functions of explicit instruction. By cycling through this planning process, you can deliberately embed explicit instruction in your lesson processes.

To plan explicit instruction activities and supports as referenced by Archer and Hughes, it may also be helpful to work backwards from where you want your students to be at the end of the learning session to see how you can slowly remove scaffolds and supports to enable student mastery.

Glossary & notes

Long-term memory

Long-term memory is the system that handles persistent memories of experiences and ideas. Long-term memory is a network of overlapping information with many rich connections. There does not seem to be any limit to the amount or complexity of information that can be stored in long-term memory. Forgetting has more to do with accessing memories than having enough space for them.

In the image below, think of the circles as ideas, and the connections in each colour as one of the overlapping memories, made up of several ideas.


A random array of circles interconnected by lines of different colours.


Long-term memories are relatively stable and tend to come out the same way they went in, meaning that it can be difficult to adapt existing information to new situations. With time and repeat use, information in long-term memory can change, becoming generalised or less dependent on a specific context. Information can also be lost over time or changed by interference from other memories (particularly those which overlap).

Memories of experiences, which are heavily tied to a context, are known as episodic memories. Semantic memory, on the other hand, is the store of general or concept knowledge, which is less specifically tied to a single context. Procedural knowledge is another form which memory can take, containing knowledge of how to perform various tasks and skills at conscious and unconscious levels. For example, not all the knowledge required to ride a bike is something that you could easily put into words – some of that information is unconscious or ‘implicit’. 

Working memory

Working memory is a fast and flexible system which we use to represent and manipulate information. Unlike long-term memory, working memory is strictly limited in capacity and is not a persistent store, so information must be moved to long-term memory for lasting storage.

Working memory can be thought of as using 'chunks' of varying amounts to represent information. In general, the more parts and ideas that are involved, the more chunks will be required. For instance, learning about 'mammals' might initially require separate chunks for their features: animals with hair, spines, and that produce milk.

However, previously learned information from long-term memory can be heavily condensed as a single chunk. Once children are familiar with the concept of a 'mammal' it can be represented as a single chunk, using the idea from long-term memory which contains multiple associated facts. There is debate over the number of chunks that working memory can handle, but it can clearly be overloaded and so managing the burden can improve learning.


Three circles in a row, with plus signs in-between. From left to right the circles contain the words 'spine', 'milk' and 'hair'. An arrow points to a fourth circle on the right with the word 'Mammal'


An example of working memory

When you first meet someone, you use working memory to store the new name and face, but because this space is limited, it is hard to learn a lot of new names and faces at once. On the other hand, when you know all the students in your class, their names and faces are already in long-term memory, and you can easily recall all that information.

Types of memory 

The word memory covers two smaller diagrams. The first diagram, on the left, shows a series of circles connected by lines and the text 'Long-term memory'. The diagram on the right shows four circles. An arrow extends from one to a larger circle enlargement with three small connected circles. The text shows in 'Working memory'.

In this diagram each circle is a ‘chunk’ of information. In this example, one ‘chunk’ in the working memory is a complex concept from long-term memory made up of multiple connected pieces of information, and others are new information.

Cognitive overload

Working memory is what we use to learn new ideas and manipulate information. Working memory has limited capacity.

When we are required to manage a lot of new information, we can run out of space in our working memory. The scientific term for this is cognitive overload. If you are cognitively overloaded, learning can suffer, and it can be harder to move information to long-term memory.

Example of preventing cognitive overload

A student might initially need nearly all their working memory (several chunks) to represent the idea of an atom, leaving no further room to learn about related topics like an atom’s structure or properties. However, when the idea of an atom is learned and accessed from long-term memory, that complex idea will only take up one chunk, leaving the rest of working memory free to build on that knowledge.

Preventing cognitive overload diagram

Two rows of four circles, divided by a line 'working memory chunks'. The top line has text on the right that says 'concept of an atom is new'. The first three circles have text - small, nucleus and electrons. The fourth circle has the text 'free memory'. The four circles below the line also have text to the left - concept of an atom is stored in long-term memory. The first circle has the text Atom, with smaller text below - small, nucleus, atoms. The three other circles represent 'working memory'

Presenting new information gradually so students can store and then retrieve information from long-term memory is one of the ways teachers can reduce the burden on working memory and make learning more effective.


References & further reading


Cowan N (2008). ‘What are the differences between long-term, short-term, and working memory?’, Progress in brain research, 169: 323-338.

Nadel L and Moscovitch M (1997). ‘Memory consolidation, retrograde amnesia and the hippocampal complex’, Current opinion in neurobiology, 7(2):217-227.

Squire, L R, Cohen, N J and Nadel L (1984). ‘The medial temporal region and memory consolidation: A new hypothesis’, Memory consolidation: Psychobiology of cognition, 185-210.

Sweller J (2011). ‘Cognitive load theory’, Psychology of learning and motivation, Vol. 55: 37-76.

Further reading

Archer A and Hughes C (2011) ‘Exploring the foundations of explicit instruction’ in Explicit Instruction: Effective and Efficient Teaching, The Guildford Press.  

This is a book chapter that draws on the seminal literature on explicit instruction to explore: 1. elements of explicit instruction; 2. the underlying principles of effective instruction; and 3. the research evidence supporting explicit instruction. It also responds to possible concerns about an explicit approach to teaching. It states that explicit instruction is characterised by a series of supports or scaffolds, whereby students are guided through the learning process until independent mastery has been achieved. Guidance through the learning process requires clear statements about the purpose and rationale for learning the new skill, clear explanations and demonstrations of the instructional target, and supported practice with feedback. 

A sample chapter is available from the author's website.

Ellis E and Worthington L (1994) ‘Research Synthesis on Effective Teaching Principles and the Design of Quality Tools for Educators’, Technical Report No. 5., National Center To Improve the Tools of Educators. 

This monograph presents a synthesis of the literature on empirically supported effective teaching principles, including ‘making instruction explicit’. It finds that the extent to which instruction is made explicit directly impacts both student achievement and independent, self-regulated learning. It finds that: 1. teachers should make explicit to students their goals, objectives, and expectations; 2. teachers should provide lessons that are clear, accurate, and rich in example and demonstration of a particular task; 3. teachers should develop specific instructional routines and make sure the boundaries between the different segments of a lesson are well-defined.  

Hughes CA, Morris JR, Therrien WJ and Benson SK (2017) ‘Explicit Instruction: Historical and Contemporary Contexts’, Learning Disabilities Research & Practice, 32:140-148.   

This paper is a systematic review of 68 papers on explicit instruction published between 2000 and 2016. To be included in the review, each paper had to include a definition of or a list of teaching components describing explicit instruction. The papers could either describe an intervention or focus on explicit instruction as the main topic. The authors analysed these papers to identify the most common components of explicit instruction. This paper identifies five essential components of explicit instruction: 1. segment complex skills; 2. draw student attention to important features of the content through modelling/think-alouds; 3. promote successful engagement by using systematically faded supports/prompts; 4. provide opportunities for students to respond and receive feedback; and 5. create purposeful practice opportunities. 

Kirschner P, Sweller, J and Clark R (2006) ‘Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching’, Educational Psychologist, 41(2):75-86.  

This paper draws on cognitive load theory to explain how and why guided instruction leads to better learning outcomes for students than unguided instruction. It asserts that guided instruction not only produces more immediate recall of facts than unguided approaches, but also longer-term transfer and problem-solving skills. It finds that worked examples and/or process worksheets are two forms of guided instruction that are of particular benefit, especially for novice leaners. 

Martin AJ and Evans P (2018) ‘Load reduction instruction: Exploring a framework that assesses explicit instruction through to independent learning’, Teaching and Teacher Education: An International Journal of Research and Studies, 73(1):203-214.  

This paper is an individual study that explores an instructional model (load reduction instruction) intended to manage the cognitive burden on students as they learn. Load reduction instruction (LRI) aims to manage the cognitive burden on students in the initial stages of learning, and then, as fluency and automaticity develop, students are encouraged to engage in guided independent learning. LRI comprises five factors: 1. difficulty reduction, 2. support and scaffolding, 3. practice, 4. feedback, and 5. guided independence. This study examined an instrument (the Load Reduction Instruction Scale, LRIS) aimed at assessing these five factors. The instrument was tested among sample of Australian high school students from 40 classrooms. The findings supported the validity of the LRIS, the conceptualising underpinning it, and its potential to guide instructional practice. 

Sweller J, van Merrienboer J and Paas F (1998) ‘Cognitive Architecture and Instructional Design’, Educational Psychology Review, 10:251–296.  

This seminal literature review provides an overview of cognitive load theory – what it is, how it relates to the human brain and the implications of cognitive load theory for instructional design. It finds that: 1. human brains can only process a small amount of new information at once; 2. unguided problem-solving places a heavy burden on working memory and inhibits student learning; 3. students do not learn effectively when their attention is directed to unnecessary or redundant information; and 4. fully guided instruction becomes less effective as students become more expert at a particular skill. 

Rosenshine B (1986) ‘Synthesis of research on explicit teaching’, Educational Leadership, 4:60-69. 

This seminal paper explores the existing evidence on explicit teaching. The author states that a decade of experiments undertaken in classrooms with regular teachers teaching regular subject matter has consistently shown that when teachers teach more systematically, student achievement improves. Teaching systematically is defined by the author as a pattern of instruction whereby there is a systematic method for presenting material in small steps, there is pausing to check for student understanding, and where teachers elicit active and successful participation from all students. The paper goes on to elaborate on these practices and highlight 6 ‘teaching functions’ that should be employed in the classroom. 

Sweller J, van Merriënboer J and Paas F (2019) ‘Cognitive Architecture and Instructional Design: 20 Years Later’. Educational Psychology Review, 31:261–292.  

This paper explores cognitive load theory and its relationship with instructional design over the last 20 years. It begins with a short history of cognitive load theory, including the categories of cognitive load and the effects of cognitive load. It then goes on to discuss the major developments in cognitive load theory between 1998 and 2018, including ‘four-component instructional design’ and new methods for measuring the different categories of cognitive load. It concludes by describing five new ‘effects’ that have been identified over the past twenty years and that have direct practical implications for instruction. These new effects are:  1. the self-explanation effect, 2. the imagination effect, 3. the isolated elements effect, 4. the collective working memory effect, and 4. the human movement effect.


Australian Institute for Teaching and School Leadership (AITSL) – Explicit number fluency  

This resource provides examples of ‘chunking and sequencing learning’ and ‘providing practice opportunities’. 

This video is an illustration of practice that shows a teacher in a Victorian primary school implementing a whole-school policy to improve explicit number fluency in his students. The video demonstrates how to develop students’ knowledge of number sequence and skills in counting from any starting point. The teacher sets aside five to ten minutes of time at the beginning of every mathematics lesson for students to practice counting. He then invites individual students to use the interactive whiteboard to set the starter counter from which students will count in unison by ‘twos’. 

Australian Institute for Teaching and School Leadership (AITSL) – Explicit numeracy experiences  

This resource provides examples of ‘breaking down complex skills and knowledge’ and ‘sequencing tasks’. 

This video shows a Victorian teacher in her first year of teaching, designing and implementing explicit learning experiences for her culturally diverse Year 3/4 class. She selects and uses content and resources for her numeracy lessons that are appropriate to the strengths and needs of individual students from diverse backgrounds. In the illustration, she develops teaching activities to assist students to understand the mathematical concepts of whole numbers, fractions and decimals. She uses a literacy approach to support these numeracy activities.  

Australian Institute for Teaching and School Leadership (AITSL) – Explicit instruction  

This resource provides examples of ‘worked examples’ and ‘removing scaffolding’. 

This video is an illustration of practice that shows a teacher demonstrating the 'I do, we do, you do' strategy in a primary school in Torres Strait. The teacher emphasises the importance of providing students with purposeful and understandable feedback to support achievement. He also demonstrates use of an online resource to differentiate teaching to meet individual student strengths and needs. 

Australian Institute for Teaching and School Leadership (AITSL) – Explicit language teaching  

This resource provides examples of ‘chunking and sequencing learning’. 

This video shows a teacher in her second year of teaching, using individual learning plans to cater for students in her Year 1 classroom in a purpose built ‘language development school’ in Western Australia. She uses a lesson on 'What is happening in the story?' to explicitly teach comprehension, chronological understanding, phonological awareness and pragmatics. The teacher uses differentiated teaching and personal feedback to reinforce learning and behaviour to students. 

Keywords: explicit teaching