Understand the information processing model of memory from sensory input to long-term storage. Practical teaching strategies based on Atkinson-Shiffrin, Baddeley and levels of processing theory.
Information Processing Theory, a cognitive framework developed by American psychologists cambridge. org/core/journals/philosophy-of-science/article/abs/mechanisms-in-cognitive-psychology-what-are-the-operations/82EB1DF1D753BBE6EC7A602929134156">George A. Miller and Richard Shiffrin in the 1960s, explains how the human mind processes, stores, and retrieves information.
What does the research say? Hattie (2009) found that elaboration strategies, a core information processing technique, produce an effect size of 0.75 on student achievement. Dunlosky et al. (2013) ranked practice testing and distributed practice as the two most effective learning strategies from the information processing framework. The EEF rates metacognitive strategies, which draw directly on information processing models, at +7 months additional progress.
This theory suggests that our cognitive abilities are based on the interaction of sensory memory, short-term memory, and long-term memory (Stout & Klett, 2020). These components work together to help us encode, store, and retrieve information efficiently.
George Miller, one of the key figures in this theory, introduced the idea of , which asserts that our of information simultaneously. This concept has significantly influenced our understanding of human memory and has contributed to the development of more advanced models of information processing.
The utilises a processing approach, which emphasises examining the mental processes involved in learning, such as attention, perception, and memory. This approach allows researchers and educators to better understand the complex mechanisms underlying human learning and develop more .
By focusing on mental processes, the Information Processing Theory has greatly contributed to our knowledge of information processing and working memory, including the organisation, storage, and retrieval of information, as well as understanding phenomena like memory interference (Marks et al., 2021). As a result, this theory is widely used in educational settings to understand a nd enhance human learning.
It provides educators with valuable insights into the , allowing them to tailor instruction to meet the needs of diverse learners and promote better learning outcomes (Sudarma et al., 2022).
The three stages of information processing are sensory memory, short-term memory, and long-term memory. Sensory memory briefly holds and filters external stimuli, short-term memory temporarily stores and manipulates information, and long-term memory permanently stores information for later retrieval. These stages work together sequentially to help us encode, process, and retrieve information effectively.
According to the Information Processing Theory, identify three primary stages of information processing, each playing a crucial role in the overall cognitive process:
The processing models within the Information Processing Theory suggest that these memory stages are distinct and sequential, with each stage playing a specific role in the . As we move from sensory memory to STM and finally to LTM, our cognitive system filters, enabling us to learn, remember, and retrieve knowledge effectively.
Understanding these memory stages and their functions provides valuable insights for educators, helping them design instructional strategies that cater to the cognitive processes involved in learning, and ultimately.
Attention acts as a filter that determines which information moves from sensory memory to short-term memory for further processing. Perception interprets and organises sensory information, giving it meaning based on prior knowledge and experiences. Together, attention and perception control what information gets processed and how it is understood by the learner.
Attention is a critical aspect of information processing, as it allows us to selectively focus on specific stimuli while ignoring irrelevant information. There are several types of attention, including selective attention, alternate attention, and sustained attention. Each type plays a role in the efficient processing of information, catering to different cognitive tasks and situations.
Attention span, or the period of time during which an individual can maintain focus, also impacts cognitive performance, particularly in childhood when cognitive processing and long-term memory formation are developing (Aesaert et al., 2014).
Aspects of attention, such as maintaining focus and shifting between tasks, are essential for effective information processing. These attentional processes work in tandem with perception, the process of organising and interpreting sensory information.
Perception allows us to make sense of the world around us, enabling the encoding of information into our memory systems, including semantic memory, which stores general knowledge and concepts.
Both attention and perception are essential for effective cognitive processing, as they help filter and make sense of the massive amount of information our brains encounter daily. By understanding the roles of attention and perception in learning, educators can devise strategies that improve students' cognitive performance, catering to their unique attentional capacities and perceptual abilities (Wahyuni & Bhattacharya, 2021).
This understanding can help improve teaching methods and support the development of long-term memory and overall cognitive processing in learners.
Cognitive LoadTheory explains that learners have limited working memory capacity that can be overwhelmed by too much information at once. It divides cognitive load into three types: intrinsic (task complexity), extraneous (poor instruction design), and germane (learning processes). Teachers can improve learning by reducing extraneous load through clear instructions and breaking complex tasks into smaller chunks (Wang, 2021).
Cognitive Load Theory, developed by John Sweller, is an extension of Information Processing Theory that focuses on the limitations of working memory capacity, specifically in the short-term memory storage.
The theory suggests that our cognitive systems can become overwhelmed when faced with too much information or complex tasks, leading to cognitive overload and reduced learning outcomes (Chans & Castro, 2021). This can directly impact memory performance, particularly in terms of memory span and the formation of strong memory connections.
To avoid cognitive overload, Cognitive Load Theory advocates for instructional design that balances complexity and considers the learners' prior knowledge. This can be achieved by breaking down complex tasks into smaller steps, using efficient strategies like schemas, and employing techniques such as dual coding to enhance the learning process.
By doing so, educators can help students develop effective memory strategies that improve their ability to retain and recall information (Liliyanti et al., 2024).
Implementing these techniques in the classroom not only supports the optimal use of short-term memory storage but also encourages the formation of strong memory connections that promote long-term retention.
By understanding and applying the principles of Cognitive Load Theory, teachers can create learning environmentsthat cater to the natural limitations of human memory capacity, ultimately enhancing memory performance and facilitating the acquisition of new knowledge and skills (Altınay et al., 2024).
Effective strategies include chunking information into smaller units, using visual aids and graphic organisers, and providing regular practise with spaced repetition. Teachers can also use mnemonics, create meaningful connections to prior knowledge, and encourage active processing through discussion and reflection. These techniques help students encode information more effectively and transfer it to long-term memory.
Teachers can implement various strategies to enhance information processing in their students:
By incorporating these strategies into their teaching, educators can support and improve their students' information processing abilities.
Positive emotions and high motivation enhance attention and engagement, making it easier for students to process and retain information. Negative emotions like anxiety can impair working memory and reduce processing efficiency. Teachers can support information processing by creating a positive learning environment and connecting content to students' interests and goals.
Motivation and emotion play crucial roles in the information processing and learning process, influencing not only memory performance but also executive functions and critical thinking skills. When students are motivated, they are more likely to engage in learning activities, expend effort, and persist in the face of challenges.
Positive emotions can enhance learning by increasing attention, facilitating semantic encoding, and promoting a positive learning environment that supports brain maturation and long-term memory formation.
Conversely, negative emotions can hinder learning by reducing attention, impairing memory retrieval, and creating a negative learning environment. These influences on processing can significantly impact students' ability to develop and utilise critical thinking skills, as well as their overall cognitive performance.
Teachers should be aware of the emotional states of their students and strive to create a positive, supportive atmosphere that creates motivation and engagement. By doing so, educators can promote the development of executive functions, encourage critical thinking, and facilitate the efficient encoding and retrieval of information.
This, in turn, will contribute to improved memory performance and support the formation of long-term memories, ultimately enhancing students' overall learning experience and cognitive development.
Information Processing Theory helps students understand how their ownminds work, enabling them to monitor and control their learning processes. By teaching students about memory stages and processing limitations, educators can help them develop strategies like self-testing and planning. This awareness allows students to become more independent learners who can regulate their own information processing.
Metacognition, or the ability to think about one's own thinking, is a crucial aspect of effective in formation processing. Developing metacognitive skills allows students to monitor their learning, evaluate their progress, and make adjustments to their strategies as needed.
Information Processing Theory provides a framework for understanding how metacognition interacts with cognitive processes like attention, memory, and problem-solving.
Teachers can promote the development of metacognitive skills by:
By encouraging metacognitive skills, teachers can help students become more independent and effective learners.
Information Processing Theory provides insights into why some students may struggle with specific learning tasks, such as processing speed or working memory limitations. Teachers can use this knowledge to provide appropriate accommodations like extra processing time, visual supports, or breaking tasks into smaller steps. Understanding individual processing differences helps create more inclusive learning environments that support all learners.
Information Processing Theory (IPT) has profound implications for teaching and learning in Special Educational Needs and Disabilities (SEND) environments. By understanding how information is encoded, stored, and retrieved, educators can tailor strategies to meet the unique needs of students. Here are nine ways IPT can be applied in SEND settings:
1. Utilising Phonological Loop for Language Development:
Implementing auditory exercises that focus on sound and language patterns can enhance the phonological loop, aiding students with language-related disabilities.
Source: Phonological Loop and Language Development.
2. Enhancing Visuospatial Sketchpad through Visual Aids:
Using visual aids and spatial exercises can strengthen the visuospatial sketchpad, supporting students with visual-spatial learning difficulties.
3. Building Long-term Memory through Repetition and Association:
Repeated exposure and associating new information with personal experiences can facilitate the transfer of knowledge to long-term memory, aiding students with memory retention challenges.
4. Focusing on Short-term Memory Strategies:
Implementing techniques that enhance short-term memory, such as chunking, can support students who struggle with retaining information over brief periods of time.
5. Incorporating Procedural Memory in Skill Development:
Utilising procedural memory techniques can help students with motor skill difficulties, such as dyspraxia, through repetitive practise and gradual skill-building.
6. Tailoring Instruction to Middle Childhood Cognitive Development:
Recognising the representational abilities and cognitive development in middle childhood can guide the design of age-appropriate learning materials.
7. Addressing Ineffective Processes through Individualized Strategies:
Identifying and addressing individual ineffective memory processes can lead to personalised interventions, enhancing overall student achievement.
8. Applying Shiffrin Model for Multi-sensory Learning:
Integrating the Shiffrin Model's principles can create a multi-sensory learning environment, accommodating various learning styles and needs.
9. Emphasising Acoustic Encoding in Reading Instruction:
Focusing on acoustic encoding can support students with dyslexia, enhancing their reading and comprehension skills.
Source: Acoustic Encoding and Dyslexia.
In a primary school setting, a teacher might use visual aids to enhance the visuospatial sketchpad for students struggling with spatial awareness, while also incorporating auditory exercises to support phonological loop development.
Dr. Alan Baddeley, a prominent figure in memory research, stated, "Understanding the intricacies of memory can lead to more effective educational strategies, especially in specialised learning environments."
Approximately 15% of students with SEND have specific difficulties related to memory processes, making the application of IPT crucial in these settings.
By integrating the principles of IPT, educators in SEND environments can create targeted and effective learning experiences, addressing the diverse needs and challenges faced by students.
Effective instructional design based on this theory includes presenting information in small chunks, providing clear organisation and structure, and building in regular review opportunities. Teachers should minimise cognitive overload by removing unnecessary information and using multimedia principles that combine visual and verbal information effectively. Lessons should also include opportunities for practise and feedback to strengthen memory consolidation.
When designing instruction, teachers can apply principles from Information Processing Theory to create learning experiences that align with how the human brain processes information. Some strategies for applying information processing principles to instructional design include:
By incorporating these principles into their instructional design, teachers can create learning environments that support and enhance their students' cognitive processes.
This approach enables students to effectively process and store new information, ultimately leading to improved educational results and a deeper understanding of the material.
Educational technologies can support information processing by providing interactive experiences, immediate feedback, and personalised pacing that matches individual processing speeds. Digital toolscan present information through multiple channels, use adaptive algorithms to adjust difficulty levels, and provide spaced practise opportunities. Technology also enables data tracking to help teachers identify and address processing difficulties in real-time.
Educational technologies can support and enhance the application of Information Processing Theory in the classroom. Online learning platforms, for example, can be designed to provide structured, organised content that aligns with the stages of information processing, considering the level of processing required for different types of information.
Additionally, adaptive learning technologies can personalise instruction based on individual students' cognitive abilities, adolescent brain development, and prior knowledge, reducing cognitive load and promoting efficient information processing at the individual level.
Other technologies, such as interactive whiteboards and multimedia presentations, can engage students' attention and facilitate the encoding of information by providing rich, dynamic learning experiences. These tools can aid in the temporary storage of information in short-term memory and help learners transition knowledge to long-term storage, such as declarative memory.
Automatic processing can be enhanced through the use of educational technologies, allowing students to develop executive function skills and improve their overall human thinking capabilities. When used thoughtfully and intentionally, educational technologies can be powerful tools for supporting students' information processing and overall learning success.
The key principles include understanding that learning occurs through three memory stages, recognising that working memory has limited capacity, and knowing that attention and perception filter what gets processed. Teachers should chunk information, reduce cognitive load, and use strategies that help transfer information to long-term memory. Regular practise and meaningful connections enhance retention and retrieval of learned material.
Information Processing Theory is a valuable framework for understanding how the human brain processes, stores, and retrieves information.
By applying principles from this theory to instructional design and incorporating metacognitive strategies, teachers can create learning experiences that support students' cognitive development and promote academic success.
Additionally, educational technologies can be used to enhance the application of Information Processing Theory in the classroom, further supporting students' learning and growth.
Information Processing Theory rests on several fundamental assumptions that shape how we understand student learning. At its core, the theory assumes that the human mind functions like a computer, systematically processing information through distinct stages. This computational metaphor helps teachers understand why students sometimes struggle with complex tasks or forget recently taught material.
The first key assumption is that learning is an active process where students transform information rather than passively receive it. When Year 7 students learn about photosynthesis, for instance, they don't simply memorise facts; they actively connect new concepts to their existing knowledge about plants and sunlight. This transformation occurs through encoding, where students convert sensory input into meaningful mental representations.
Another crucial principle is that our cognitive system has limited capacity, particularly in working memory. This limitation explains why students often feel overwhelmed when presented with too much information at once. A practical strategy is to break down complex procedures, such as solving quadratic equations, into smaller steps. Teaching each step separately before combining them helps prevent cognitive overload and supports better retention.
The theory also assumes that processing speed and efficiency improve with practise and age. Younger pupils in Key Stage 1 process information more slowly than their Key Stage 3 counterparts, requiring teachers to adjust their pacing accordingly. Additionally, the theory emphasises that prior knowledge significantly influences how new information is processed and stored. Students with strong foundational knowledge in a subject area can process related new information more efficiently, which is why spiral curricula that revisit and build upon previous learning prove so effective in practise.
Information Processing Theory draws heavily on the computer metaphor to explain how the human mind works. Just as computers receive input, process data, and produce output, our brains take in sensory information, manipulate it through various cognitive processes, and generate responses. This comparison helps teachers understand how students learn and why certain teaching methods prove more effective than others.
The analogy breaks down into three key components. Input represents the information students receive through their senses during lessons, whether through listening to explanations, viewing visual aids, or engaging in hands-on activities. Processing occurs when students actively work with this information, organising and connecting it to existing knowledge. Output manifests as students demonstrate their understanding through answers, written work, or practical applications.
Understanding this model transforms classroom practise. For instance, when teaching long division, rather than presenting the entire algorithm at once, break it into smaller steps. Present one step (input), allow practise time (processing), then check understanding (output) before moving forwards. This mirrors how a computer processes code line by line rather than attempting to execute an entire programme simultaneously.
Similarly, when introducing new vocabulary in a Year 3 science lesson about plants, present three to four terms at a time. Have students create visual definitions (processing), then use the words in sentences (output). This systematic approach prevents the cognitive system from becoming overwhelmed, much like avoiding a computer crash by not running too many programmes at once.
The computer-mind analogy also explains why repetition and review matter. Just as files need proper organisation and regular access to remain retrievable, students need multiple encounters with information to transfer it effectively from working memory to long-term storage.
Information Processing Theory emerged during the 1950s and 1960s as psychologists began comparing the human mind to the newly developed digital computers of that era. This revolutionary comparison transformed how educators understood learning and memory, moving away from behaviourist approaches that focused solely on observable actions.
The theory's foundations were laid by cognitive psychologists including George A. Miller, whose groundbreaking 1956 paper "The Magical Number Seven, Plus or Minus Two" demonstrated the limits of short-term memory. Richard Atkinson and Richard Shiffrin further developed these ideas in 1968, creating the multi-store model that teachers still use today to understand how pupils process classroom information.
This shift from behaviourism to cognitive psychology coincided with the rise of computer science, leading researchers to view the brain as an information processor that receives input, transforms it, stores it, and produces output. Alan Newell and Herbert Simon's work on problem-solving in the 1970s extended this framework, showing how humans use step-by-step procedures, much like computer algorithms, to tackle complex tasks.
For classroom teachers, understanding this historical context helps explain why certain teaching methods work. When you break down complex topics into smaller chunks (following Miller's principle), you're applying decades of cognitive research. Similarly, when you use visual aids alongside verbal explanations, you're building on Allan Paivio's dual coding theory from 1971, which showed how combining visual and verbal information enhances memo ry.
The theory continues to evolve, with modern neuroscience confirming many of its predictions whilst adding new insights about working memory, attention, and cognitive load that directly inform teaching practise today.
Information Processing Theory emerged during the 1950s and 1960s, marking a revolutionary shift in how psychologists understood human learning and cognition. The theory developed as a direct response to behaviourism, which had dominated psychological thinking but failed to explain the complex mental processes occurring between stimulus and response.
The advent of computer technology proved instrumental in shaping this theory. Psychologists like George Miller, Richard Atkinson, and Richard Shiffrin drew parallels between human cognition and computer operations, proposing that the mind processes information through distinct stages, much like a computer processes data. Miller's groundbreaking 1956 paper, "The Magical Number Seven, Plus or Minus Two," established fundamental limits to human information processing capacity.
During the 1960s, Atkinson and Shiffrin refined these ideas into their influential multi-store model, which described how information flows from sensory registers through short-term memory to long-term storage. This model provided teachers with a scientific framework for understanding why repetition and rehearsal strategies work in the classroom. For instance, when teaching times tables, teachers now understood why presenting information in small chunks (respecting Miller's seven-item limit) and using repetitive practise helped transfer knowledge to long-term memory.
The theory continued evolving through the 1970s and 1980s, incorporating insights from neuroscience and artificial intelligence. Researchers like Alan Baddeley expanded the model to include working memory, explaining how students actively manipulate information whilst learning. This development helped teachers understand why students struggle when asked to perform multiple cognitive tasks simultaneously, such as copying from the board whilst listening to explanations. Today, these historical insights inform evidence-based teaching strategies, from chunking content into manageable segments to implementing regular retrieval practise sessions.
Information Processing Theory draws its foundational framework from comparing the human mind to a computer system. This analogy, whilst simplified, provides teachers with a practical model for understanding how students receive, process, store, and retrieve information in the classroom.
Just as computers have input devices (keyboard, mouse), processing units (CPU), and storage systems (hard drive, RAM), the human mind operates through similar components. Sensory organs act as input devices, collecting information from the environment. The brain processes this data through working memory, much like a computer's RAM handles active tasks. Finally, long-term memory serves as our internal hard drive, storing information for future retrieval.
This comparison helps teachers identify potential learning bottlenecks. For instance, when a student struggles to follow multi-step instructions, it often indicates working memory overload, similar to a computer freezing when running too many programmes simultaneously. Teachers can address this by breaking complex tasks into smaller segments, allowing the brain's "processor" to handle information more efficiently.
In practise, teachers can apply this understanding by structuring lessons like well-designed software programmes. Start with clear "input" through focused presentations, process information through guided practise activities, and ensure proper "storage" through review and consolidation exercises. For example, when teaching fraction multiplication, present one step at a time, practise each component separately, then combine them once students demonstrate mastery of individual processes.
The analogy also highlights regular "system maintenance." Just as computers need updates and decluttering, students benefit from review sessions and organised note-taking systems that help maintain efficient information retrieval pathways.
Information Processing Theory rests on several fundamental assumptions that shape how we understand student learning and memory. These assumptions provide teachers with a framework for designing lessons that align with how the brain naturally processes information.
The first key assumption is that learning occurs through a series of sequential stages. Information moves systematically from sensory input through short-term memory and finally into long-term storage. This linear progression means teachers should structure lessons to guide students through each stage deliberately. For instance, when teaching new vocabulary, present words visually and aurally (sensory input), practise them through repetition (short-term memory), and then connect them to existing knowledge through meaningful activities (long-term storage).
Secondly, the theory assumes that humans have limited processing capacity. Unlike computers, our brains can only handle a finite amount of information at once. This limitation directly impacts classroom practise; presenting too much content simultaneously will overwhelm students' cognitive systems. Break complex topics into smaller chunks, such as teaching photosynthesis in three separate lessons focusing on light reactions, dark reactions, and overall energy flow, rather than attempting to cover everything in one session.
The third assumption centres on active processing. Students aren't passive recipients of information but active participants who must engage with content to learn effectively. This challenges the traditional lecture format and supports interactive teaching methods. Use think-pair-share activities where students process information individually, discuss with a partner, and then share with the class, ensuring multiple opportunities for active engagement.
Finally, the theory assumes that prior knowledge significantly influences new learning. Students interpret new information through the lens of what they already know. Begin lessons by activating prior knowledge through quick review activities or concept mapping exercises that help students connect new material to existing mental frameworks.
Information Processing Theory draws heavily on the computer-mind analogy, viewing the human brain as a sophisticated information processor similar to a computer. Just as computers receive input, process data, and produce output, our minds take in sensory information, manipulate it through various cognitive processes, and generate responses or store it for later use.
This analogy helps teachers understand how students learn by breaking down complex cognitive processes into manageable components. The brain's "hardware" represents our physical neural structures, whilst the "software" comprises our learned knowledge, skills, and strategies. Like a computer's central processing unit, our working memory has limited capacity and speed, which directly impacts how much information students can handle at once.
In the classroom, this understanding translates into practical teaching strategies. For instance, when introducing new mathematical concepts, present information in small, sequential steps rather than overwhelming students with entire procedures at once. This mirrors how computers process code line by line. Similarly, use visual organisers and flowcharts to help students see the "programming logic" of their thinking, making abstract processes more concrete.
Teachers can also apply this analogy to improve revision techniques. Just as computers require regular updates and maintenance, students need repeated exposure and practise to strengthen neural pathways. Create opportunities for "system updates" through spaced repetition and varied practise activities.
When students struggle with retrieval, think of it as a filing system error; the information exists but needs better organisation or stronger retrieval cues. By understanding the computer-mind parallel, teachers can diagnose learning difficulties more effectively and design instruction that aligns with how the brain naturally processes information.
Information Processing Theory is a cognitive framework that explains how the human mind processes, stores, and retrieves information through three memory stages: sensory, short-term, and long-term memory. It provides educators with valuable insights into how students learn, allowing them to tailor instruction to meet diverse learners' needs and promote better learning gains.
Miller's Magic Number 7 indicates that students can only process approximately 7 items simultaneously in their short-term memory. Teachers can apply this by breaking down complex information into smaller chunks of no more than 7 elements and organising lessons to present information in manageable segments to prevent cognitive overload.
Teachers can facilitate memory transfer by ensuring information in short-term memory is meaningful and connected to students' prior knowledge, as this promotes encoding into long-term memory. They should also provide opportunities for rehearsal, practise, and repetition within the 20-30 second window of short-term memory duration to strengthen memory connections.
Attention acts as a filter determining which information moves from sensory memory to short-term memory for processing, making it crucial for effective learning. Teachers can improve attention by designing focused, engaging lessons that minimise distractions and help students selectively focus on relevant information whilst filtering out irrelevant stimuli.
Cognitive overload occurs when working memory becomes overwhelmed with too much information, leading to reduced student achievement and poor memory performance. Teachers can prevent this by breaking complex tasks into smaller steps, using clear instructions to reduce extraneous cognitive load, and ensuring lesson complexity matches students' prior knowledge levels.
The three types are intrinsic load (task complexity), extraneous load (poor instructional design), and germane load (learning processes). Teachers can improve learning by managing intrinsic load through appropriate task difficulty, minimising extraneous load with clear instructions and organised materials, and supporting germane load by helping students build meaningful connections and schemas.
Teachers can apply chunking by presenting vocabulary in groups of 5-7 words rather than long lists, use visual and verbal information together (dual coding), and provide regular breaks to prevent sensory memory overload. They can also use schema-building activities to help students connect new information to existing long-term memory knowledge, making encoding more effective.
These peer-reviewed studies provide the evidence base for the strategies discussed above.
The Application of Information Processing Theory to Design Digital Content in Learning Message Design Course View study ↗
Sudarma et al. (2022)
This study developed digital learning content based on information processing theory for university courses. Teachers can apply these principles to design more effective digital materials that align with how students naturally process information, improving comprehension and retention in technology-enhanced learning environments.
The intersection of career and mental health from the lens of Cognitive Information Processing Theory View study ↗
Marks et al. (2021)
This research examines how career counselling intersects with mental health support using cognitive information processing theory. Teachers and counsellors can use these insights to better understand how anxiety and depression affect students' decision-making processes and provide more targeted support.
The Application of Information Processing Theory in Higher Education View study ↗
Wang (2021)
This study applied information processing theory to design learning activities for 153 university students. Teachers can use IPT principles to structure lessons that match students' cognitive processing capabilities, creating more effective learning sequences that enhance understanding and memory retention.
Higher education students' experiences and opinion about distance learning during the Covid‐19 pandemic View study ↗
79 citations
Stevanović et al. (2021)
This research explored students' experiences with distance learning during COVID-19, examining how remote education affected engagement and learning quality. Teachers can apply these findings to improve online teaching strategies and better understand student needs in digital learning environments.
Development of Newsletter Media in Thematic Learning for Elementary School Students View study ↗
64 citations
Liliyanti et al. (2024)
This study developed newsletter media for thematic learning in primary schools to address limited engaging learning materials. Teachers can use similar media approaches to create attractive, themed educational content that captures students' attention and supports integrated curriculum delivery.
Information Processing Theory, a cognitive framework developed by American psychologists cambridge. org/core/journals/philosophy-of-science/article/abs/mechanisms-in-cognitive-psychology-what-are-the-operations/82EB1DF1D753BBE6EC7A602929134156">George A. Miller and Richard Shiffrin in the 1960s, explains how the human mind processes, stores, and retrieves information.
What does the research say? Hattie (2009) found that elaboration strategies, a core information processing technique, produce an effect size of 0.75 on student achievement. Dunlosky et al. (2013) ranked practice testing and distributed practice as the two most effective learning strategies from the information processing framework. The EEF rates metacognitive strategies, which draw directly on information processing models, at +7 months additional progress.
This theory suggests that our cognitive abilities are based on the interaction of sensory memory, short-term memory, and long-term memory (Stout & Klett, 2020). These components work together to help us encode, store, and retrieve information efficiently.
George Miller, one of the key figures in this theory, introduced the idea of , which asserts that our of information simultaneously. This concept has significantly influenced our understanding of human memory and has contributed to the development of more advanced models of information processing.
The utilises a processing approach, which emphasises examining the mental processes involved in learning, such as attention, perception, and memory. This approach allows researchers and educators to better understand the complex mechanisms underlying human learning and develop more .
By focusing on mental processes, the Information Processing Theory has greatly contributed to our knowledge of information processing and working memory, including the organisation, storage, and retrieval of information, as well as understanding phenomena like memory interference (Marks et al., 2021). As a result, this theory is widely used in educational settings to understand a nd enhance human learning.
It provides educators with valuable insights into the , allowing them to tailor instruction to meet the needs of diverse learners and promote better learning outcomes (Sudarma et al., 2022).
The three stages of information processing are sensory memory, short-term memory, and long-term memory. Sensory memory briefly holds and filters external stimuli, short-term memory temporarily stores and manipulates information, and long-term memory permanently stores information for later retrieval. These stages work together sequentially to help us encode, process, and retrieve information effectively.
According to the Information Processing Theory, identify three primary stages of information processing, each playing a crucial role in the overall cognitive process:
The processing models within the Information Processing Theory suggest that these memory stages are distinct and sequential, with each stage playing a specific role in the . As we move from sensory memory to STM and finally to LTM, our cognitive system filters, enabling us to learn, remember, and retrieve knowledge effectively.
Understanding these memory stages and their functions provides valuable insights for educators, helping them design instructional strategies that cater to the cognitive processes involved in learning, and ultimately.
Attention acts as a filter that determines which information moves from sensory memory to short-term memory for further processing. Perception interprets and organises sensory information, giving it meaning based on prior knowledge and experiences. Together, attention and perception control what information gets processed and how it is understood by the learner.
Attention is a critical aspect of information processing, as it allows us to selectively focus on specific stimuli while ignoring irrelevant information. There are several types of attention, including selective attention, alternate attention, and sustained attention. Each type plays a role in the efficient processing of information, catering to different cognitive tasks and situations.
Attention span, or the period of time during which an individual can maintain focus, also impacts cognitive performance, particularly in childhood when cognitive processing and long-term memory formation are developing (Aesaert et al., 2014).
Aspects of attention, such as maintaining focus and shifting between tasks, are essential for effective information processing. These attentional processes work in tandem with perception, the process of organising and interpreting sensory information.
Perception allows us to make sense of the world around us, enabling the encoding of information into our memory systems, including semantic memory, which stores general knowledge and concepts.
Both attention and perception are essential for effective cognitive processing, as they help filter and make sense of the massive amount of information our brains encounter daily. By understanding the roles of attention and perception in learning, educators can devise strategies that improve students' cognitive performance, catering to their unique attentional capacities and perceptual abilities (Wahyuni & Bhattacharya, 2021).
This understanding can help improve teaching methods and support the development of long-term memory and overall cognitive processing in learners.
Cognitive LoadTheory explains that learners have limited working memory capacity that can be overwhelmed by too much information at once. It divides cognitive load into three types: intrinsic (task complexity), extraneous (poor instruction design), and germane (learning processes). Teachers can improve learning by reducing extraneous load through clear instructions and breaking complex tasks into smaller chunks (Wang, 2021).
Cognitive Load Theory, developed by John Sweller, is an extension of Information Processing Theory that focuses on the limitations of working memory capacity, specifically in the short-term memory storage.
The theory suggests that our cognitive systems can become overwhelmed when faced with too much information or complex tasks, leading to cognitive overload and reduced learning outcomes (Chans & Castro, 2021). This can directly impact memory performance, particularly in terms of memory span and the formation of strong memory connections.
To avoid cognitive overload, Cognitive Load Theory advocates for instructional design that balances complexity and considers the learners' prior knowledge. This can be achieved by breaking down complex tasks into smaller steps, using efficient strategies like schemas, and employing techniques such as dual coding to enhance the learning process.
By doing so, educators can help students develop effective memory strategies that improve their ability to retain and recall information (Liliyanti et al., 2024).
Implementing these techniques in the classroom not only supports the optimal use of short-term memory storage but also encourages the formation of strong memory connections that promote long-term retention.
By understanding and applying the principles of Cognitive Load Theory, teachers can create learning environmentsthat cater to the natural limitations of human memory capacity, ultimately enhancing memory performance and facilitating the acquisition of new knowledge and skills (Altınay et al., 2024).
Effective strategies include chunking information into smaller units, using visual aids and graphic organisers, and providing regular practise with spaced repetition. Teachers can also use mnemonics, create meaningful connections to prior knowledge, and encourage active processing through discussion and reflection. These techniques help students encode information more effectively and transfer it to long-term memory.
Teachers can implement various strategies to enhance information processing in their students:
By incorporating these strategies into their teaching, educators can support and improve their students' information processing abilities.
Positive emotions and high motivation enhance attention and engagement, making it easier for students to process and retain information. Negative emotions like anxiety can impair working memory and reduce processing efficiency. Teachers can support information processing by creating a positive learning environment and connecting content to students' interests and goals.
Motivation and emotion play crucial roles in the information processing and learning process, influencing not only memory performance but also executive functions and critical thinking skills. When students are motivated, they are more likely to engage in learning activities, expend effort, and persist in the face of challenges.
Positive emotions can enhance learning by increasing attention, facilitating semantic encoding, and promoting a positive learning environment that supports brain maturation and long-term memory formation.
Conversely, negative emotions can hinder learning by reducing attention, impairing memory retrieval, and creating a negative learning environment. These influences on processing can significantly impact students' ability to develop and utilise critical thinking skills, as well as their overall cognitive performance.
Teachers should be aware of the emotional states of their students and strive to create a positive, supportive atmosphere that creates motivation and engagement. By doing so, educators can promote the development of executive functions, encourage critical thinking, and facilitate the efficient encoding and retrieval of information.
This, in turn, will contribute to improved memory performance and support the formation of long-term memories, ultimately enhancing students' overall learning experience and cognitive development.
Information Processing Theory helps students understand how their ownminds work, enabling them to monitor and control their learning processes. By teaching students about memory stages and processing limitations, educators can help them develop strategies like self-testing and planning. This awareness allows students to become more independent learners who can regulate their own information processing.
Metacognition, or the ability to think about one's own thinking, is a crucial aspect of effective in formation processing. Developing metacognitive skills allows students to monitor their learning, evaluate their progress, and make adjustments to their strategies as needed.
Information Processing Theory provides a framework for understanding how metacognition interacts with cognitive processes like attention, memory, and problem-solving.
Teachers can promote the development of metacognitive skills by:
By encouraging metacognitive skills, teachers can help students become more independent and effective learners.
Information Processing Theory provides insights into why some students may struggle with specific learning tasks, such as processing speed or working memory limitations. Teachers can use this knowledge to provide appropriate accommodations like extra processing time, visual supports, or breaking tasks into smaller steps. Understanding individual processing differences helps create more inclusive learning environments that support all learners.
Information Processing Theory (IPT) has profound implications for teaching and learning in Special Educational Needs and Disabilities (SEND) environments. By understanding how information is encoded, stored, and retrieved, educators can tailor strategies to meet the unique needs of students. Here are nine ways IPT can be applied in SEND settings:
1. Utilising Phonological Loop for Language Development:
Implementing auditory exercises that focus on sound and language patterns can enhance the phonological loop, aiding students with language-related disabilities.
Source: Phonological Loop and Language Development.
2. Enhancing Visuospatial Sketchpad through Visual Aids:
Using visual aids and spatial exercises can strengthen the visuospatial sketchpad, supporting students with visual-spatial learning difficulties.
3. Building Long-term Memory through Repetition and Association:
Repeated exposure and associating new information with personal experiences can facilitate the transfer of knowledge to long-term memory, aiding students with memory retention challenges.
4. Focusing on Short-term Memory Strategies:
Implementing techniques that enhance short-term memory, such as chunking, can support students who struggle with retaining information over brief periods of time.
5. Incorporating Procedural Memory in Skill Development:
Utilising procedural memory techniques can help students with motor skill difficulties, such as dyspraxia, through repetitive practise and gradual skill-building.
6. Tailoring Instruction to Middle Childhood Cognitive Development:
Recognising the representational abilities and cognitive development in middle childhood can guide the design of age-appropriate learning materials.
7. Addressing Ineffective Processes through Individualized Strategies:
Identifying and addressing individual ineffective memory processes can lead to personalised interventions, enhancing overall student achievement.
8. Applying Shiffrin Model for Multi-sensory Learning:
Integrating the Shiffrin Model's principles can create a multi-sensory learning environment, accommodating various learning styles and needs.
9. Emphasising Acoustic Encoding in Reading Instruction:
Focusing on acoustic encoding can support students with dyslexia, enhancing their reading and comprehension skills.
Source: Acoustic Encoding and Dyslexia.
In a primary school setting, a teacher might use visual aids to enhance the visuospatial sketchpad for students struggling with spatial awareness, while also incorporating auditory exercises to support phonological loop development.
Dr. Alan Baddeley, a prominent figure in memory research, stated, "Understanding the intricacies of memory can lead to more effective educational strategies, especially in specialised learning environments."
Approximately 15% of students with SEND have specific difficulties related to memory processes, making the application of IPT crucial in these settings.
By integrating the principles of IPT, educators in SEND environments can create targeted and effective learning experiences, addressing the diverse needs and challenges faced by students.
Effective instructional design based on this theory includes presenting information in small chunks, providing clear organisation and structure, and building in regular review opportunities. Teachers should minimise cognitive overload by removing unnecessary information and using multimedia principles that combine visual and verbal information effectively. Lessons should also include opportunities for practise and feedback to strengthen memory consolidation.
When designing instruction, teachers can apply principles from Information Processing Theory to create learning experiences that align with how the human brain processes information. Some strategies for applying information processing principles to instructional design include:
By incorporating these principles into their instructional design, teachers can create learning environments that support and enhance their students' cognitive processes.
This approach enables students to effectively process and store new information, ultimately leading to improved educational results and a deeper understanding of the material.
Educational technologies can support information processing by providing interactive experiences, immediate feedback, and personalised pacing that matches individual processing speeds. Digital toolscan present information through multiple channels, use adaptive algorithms to adjust difficulty levels, and provide spaced practise opportunities. Technology also enables data tracking to help teachers identify and address processing difficulties in real-time.
Educational technologies can support and enhance the application of Information Processing Theory in the classroom. Online learning platforms, for example, can be designed to provide structured, organised content that aligns with the stages of information processing, considering the level of processing required for different types of information.
Additionally, adaptive learning technologies can personalise instruction based on individual students' cognitive abilities, adolescent brain development, and prior knowledge, reducing cognitive load and promoting efficient information processing at the individual level.
Other technologies, such as interactive whiteboards and multimedia presentations, can engage students' attention and facilitate the encoding of information by providing rich, dynamic learning experiences. These tools can aid in the temporary storage of information in short-term memory and help learners transition knowledge to long-term storage, such as declarative memory.
Automatic processing can be enhanced through the use of educational technologies, allowing students to develop executive function skills and improve their overall human thinking capabilities. When used thoughtfully and intentionally, educational technologies can be powerful tools for supporting students' information processing and overall learning success.
The key principles include understanding that learning occurs through three memory stages, recognising that working memory has limited capacity, and knowing that attention and perception filter what gets processed. Teachers should chunk information, reduce cognitive load, and use strategies that help transfer information to long-term memory. Regular practise and meaningful connections enhance retention and retrieval of learned material.
Information Processing Theory is a valuable framework for understanding how the human brain processes, stores, and retrieves information.
By applying principles from this theory to instructional design and incorporating metacognitive strategies, teachers can create learning experiences that support students' cognitive development and promote academic success.
Additionally, educational technologies can be used to enhance the application of Information Processing Theory in the classroom, further supporting students' learning and growth.
Information Processing Theory rests on several fundamental assumptions that shape how we understand student learning. At its core, the theory assumes that the human mind functions like a computer, systematically processing information through distinct stages. This computational metaphor helps teachers understand why students sometimes struggle with complex tasks or forget recently taught material.
The first key assumption is that learning is an active process where students transform information rather than passively receive it. When Year 7 students learn about photosynthesis, for instance, they don't simply memorise facts; they actively connect new concepts to their existing knowledge about plants and sunlight. This transformation occurs through encoding, where students convert sensory input into meaningful mental representations.
Another crucial principle is that our cognitive system has limited capacity, particularly in working memory. This limitation explains why students often feel overwhelmed when presented with too much information at once. A practical strategy is to break down complex procedures, such as solving quadratic equations, into smaller steps. Teaching each step separately before combining them helps prevent cognitive overload and supports better retention.
The theory also assumes that processing speed and efficiency improve with practise and age. Younger pupils in Key Stage 1 process information more slowly than their Key Stage 3 counterparts, requiring teachers to adjust their pacing accordingly. Additionally, the theory emphasises that prior knowledge significantly influences how new information is processed and stored. Students with strong foundational knowledge in a subject area can process related new information more efficiently, which is why spiral curricula that revisit and build upon previous learning prove so effective in practise.
Information Processing Theory draws heavily on the computer metaphor to explain how the human mind works. Just as computers receive input, process data, and produce output, our brains take in sensory information, manipulate it through various cognitive processes, and generate responses. This comparison helps teachers understand how students learn and why certain teaching methods prove more effective than others.
The analogy breaks down into three key components. Input represents the information students receive through their senses during lessons, whether through listening to explanations, viewing visual aids, or engaging in hands-on activities. Processing occurs when students actively work with this information, organising and connecting it to existing knowledge. Output manifests as students demonstrate their understanding through answers, written work, or practical applications.
Understanding this model transforms classroom practise. For instance, when teaching long division, rather than presenting the entire algorithm at once, break it into smaller steps. Present one step (input), allow practise time (processing), then check understanding (output) before moving forwards. This mirrors how a computer processes code line by line rather than attempting to execute an entire programme simultaneously.
Similarly, when introducing new vocabulary in a Year 3 science lesson about plants, present three to four terms at a time. Have students create visual definitions (processing), then use the words in sentences (output). This systematic approach prevents the cognitive system from becoming overwhelmed, much like avoiding a computer crash by not running too many programmes at once.
The computer-mind analogy also explains why repetition and review matter. Just as files need proper organisation and regular access to remain retrievable, students need multiple encounters with information to transfer it effectively from working memory to long-term storage.
Information Processing Theory emerged during the 1950s and 1960s as psychologists began comparing the human mind to the newly developed digital computers of that era. This revolutionary comparison transformed how educators understood learning and memory, moving away from behaviourist approaches that focused solely on observable actions.
The theory's foundations were laid by cognitive psychologists including George A. Miller, whose groundbreaking 1956 paper "The Magical Number Seven, Plus or Minus Two" demonstrated the limits of short-term memory. Richard Atkinson and Richard Shiffrin further developed these ideas in 1968, creating the multi-store model that teachers still use today to understand how pupils process classroom information.
This shift from behaviourism to cognitive psychology coincided with the rise of computer science, leading researchers to view the brain as an information processor that receives input, transforms it, stores it, and produces output. Alan Newell and Herbert Simon's work on problem-solving in the 1970s extended this framework, showing how humans use step-by-step procedures, much like computer algorithms, to tackle complex tasks.
For classroom teachers, understanding this historical context helps explain why certain teaching methods work. When you break down complex topics into smaller chunks (following Miller's principle), you're applying decades of cognitive research. Similarly, when you use visual aids alongside verbal explanations, you're building on Allan Paivio's dual coding theory from 1971, which showed how combining visual and verbal information enhances memo ry.
The theory continues to evolve, with modern neuroscience confirming many of its predictions whilst adding new insights about working memory, attention, and cognitive load that directly inform teaching practise today.
Information Processing Theory emerged during the 1950s and 1960s, marking a revolutionary shift in how psychologists understood human learning and cognition. The theory developed as a direct response to behaviourism, which had dominated psychological thinking but failed to explain the complex mental processes occurring between stimulus and response.
The advent of computer technology proved instrumental in shaping this theory. Psychologists like George Miller, Richard Atkinson, and Richard Shiffrin drew parallels between human cognition and computer operations, proposing that the mind processes information through distinct stages, much like a computer processes data. Miller's groundbreaking 1956 paper, "The Magical Number Seven, Plus or Minus Two," established fundamental limits to human information processing capacity.
During the 1960s, Atkinson and Shiffrin refined these ideas into their influential multi-store model, which described how information flows from sensory registers through short-term memory to long-term storage. This model provided teachers with a scientific framework for understanding why repetition and rehearsal strategies work in the classroom. For instance, when teaching times tables, teachers now understood why presenting information in small chunks (respecting Miller's seven-item limit) and using repetitive practise helped transfer knowledge to long-term memory.
The theory continued evolving through the 1970s and 1980s, incorporating insights from neuroscience and artificial intelligence. Researchers like Alan Baddeley expanded the model to include working memory, explaining how students actively manipulate information whilst learning. This development helped teachers understand why students struggle when asked to perform multiple cognitive tasks simultaneously, such as copying from the board whilst listening to explanations. Today, these historical insights inform evidence-based teaching strategies, from chunking content into manageable segments to implementing regular retrieval practise sessions.
Information Processing Theory draws its foundational framework from comparing the human mind to a computer system. This analogy, whilst simplified, provides teachers with a practical model for understanding how students receive, process, store, and retrieve information in the classroom.
Just as computers have input devices (keyboard, mouse), processing units (CPU), and storage systems (hard drive, RAM), the human mind operates through similar components. Sensory organs act as input devices, collecting information from the environment. The brain processes this data through working memory, much like a computer's RAM handles active tasks. Finally, long-term memory serves as our internal hard drive, storing information for future retrieval.
This comparison helps teachers identify potential learning bottlenecks. For instance, when a student struggles to follow multi-step instructions, it often indicates working memory overload, similar to a computer freezing when running too many programmes simultaneously. Teachers can address this by breaking complex tasks into smaller segments, allowing the brain's "processor" to handle information more efficiently.
In practise, teachers can apply this understanding by structuring lessons like well-designed software programmes. Start with clear "input" through focused presentations, process information through guided practise activities, and ensure proper "storage" through review and consolidation exercises. For example, when teaching fraction multiplication, present one step at a time, practise each component separately, then combine them once students demonstrate mastery of individual processes.
The analogy also highlights regular "system maintenance." Just as computers need updates and decluttering, students benefit from review sessions and organised note-taking systems that help maintain efficient information retrieval pathways.
Information Processing Theory rests on several fundamental assumptions that shape how we understand student learning and memory. These assumptions provide teachers with a framework for designing lessons that align with how the brain naturally processes information.
The first key assumption is that learning occurs through a series of sequential stages. Information moves systematically from sensory input through short-term memory and finally into long-term storage. This linear progression means teachers should structure lessons to guide students through each stage deliberately. For instance, when teaching new vocabulary, present words visually and aurally (sensory input), practise them through repetition (short-term memory), and then connect them to existing knowledge through meaningful activities (long-term storage).
Secondly, the theory assumes that humans have limited processing capacity. Unlike computers, our brains can only handle a finite amount of information at once. This limitation directly impacts classroom practise; presenting too much content simultaneously will overwhelm students' cognitive systems. Break complex topics into smaller chunks, such as teaching photosynthesis in three separate lessons focusing on light reactions, dark reactions, and overall energy flow, rather than attempting to cover everything in one session.
The third assumption centres on active processing. Students aren't passive recipients of information but active participants who must engage with content to learn effectively. This challenges the traditional lecture format and supports interactive teaching methods. Use think-pair-share activities where students process information individually, discuss with a partner, and then share with the class, ensuring multiple opportunities for active engagement.
Finally, the theory assumes that prior knowledge significantly influences new learning. Students interpret new information through the lens of what they already know. Begin lessons by activating prior knowledge through quick review activities or concept mapping exercises that help students connect new material to existing mental frameworks.
Information Processing Theory draws heavily on the computer-mind analogy, viewing the human brain as a sophisticated information processor similar to a computer. Just as computers receive input, process data, and produce output, our minds take in sensory information, manipulate it through various cognitive processes, and generate responses or store it for later use.
This analogy helps teachers understand how students learn by breaking down complex cognitive processes into manageable components. The brain's "hardware" represents our physical neural structures, whilst the "software" comprises our learned knowledge, skills, and strategies. Like a computer's central processing unit, our working memory has limited capacity and speed, which directly impacts how much information students can handle at once.
In the classroom, this understanding translates into practical teaching strategies. For instance, when introducing new mathematical concepts, present information in small, sequential steps rather than overwhelming students with entire procedures at once. This mirrors how computers process code line by line. Similarly, use visual organisers and flowcharts to help students see the "programming logic" of their thinking, making abstract processes more concrete.
Teachers can also apply this analogy to improve revision techniques. Just as computers require regular updates and maintenance, students need repeated exposure and practise to strengthen neural pathways. Create opportunities for "system updates" through spaced repetition and varied practise activities.
When students struggle with retrieval, think of it as a filing system error; the information exists but needs better organisation or stronger retrieval cues. By understanding the computer-mind parallel, teachers can diagnose learning difficulties more effectively and design instruction that aligns with how the brain naturally processes information.
Information Processing Theory is a cognitive framework that explains how the human mind processes, stores, and retrieves information through three memory stages: sensory, short-term, and long-term memory. It provides educators with valuable insights into how students learn, allowing them to tailor instruction to meet diverse learners' needs and promote better learning gains.
Miller's Magic Number 7 indicates that students can only process approximately 7 items simultaneously in their short-term memory. Teachers can apply this by breaking down complex information into smaller chunks of no more than 7 elements and organising lessons to present information in manageable segments to prevent cognitive overload.
Teachers can facilitate memory transfer by ensuring information in short-term memory is meaningful and connected to students' prior knowledge, as this promotes encoding into long-term memory. They should also provide opportunities for rehearsal, practise, and repetition within the 20-30 second window of short-term memory duration to strengthen memory connections.
Attention acts as a filter determining which information moves from sensory memory to short-term memory for processing, making it crucial for effective learning. Teachers can improve attention by designing focused, engaging lessons that minimise distractions and help students selectively focus on relevant information whilst filtering out irrelevant stimuli.
Cognitive overload occurs when working memory becomes overwhelmed with too much information, leading to reduced student achievement and poor memory performance. Teachers can prevent this by breaking complex tasks into smaller steps, using clear instructions to reduce extraneous cognitive load, and ensuring lesson complexity matches students' prior knowledge levels.
The three types are intrinsic load (task complexity), extraneous load (poor instructional design), and germane load (learning processes). Teachers can improve learning by managing intrinsic load through appropriate task difficulty, minimising extraneous load with clear instructions and organised materials, and supporting germane load by helping students build meaningful connections and schemas.
Teachers can apply chunking by presenting vocabulary in groups of 5-7 words rather than long lists, use visual and verbal information together (dual coding), and provide regular breaks to prevent sensory memory overload. They can also use schema-building activities to help students connect new information to existing long-term memory knowledge, making encoding more effective.
These peer-reviewed studies provide the evidence base for the strategies discussed above.
The Application of Information Processing Theory to Design Digital Content in Learning Message Design Course View study ↗
Sudarma et al. (2022)
This study developed digital learning content based on information processing theory for university courses. Teachers can apply these principles to design more effective digital materials that align with how students naturally process information, improving comprehension and retention in technology-enhanced learning environments.
The intersection of career and mental health from the lens of Cognitive Information Processing Theory View study ↗
Marks et al. (2021)
This research examines how career counselling intersects with mental health support using cognitive information processing theory. Teachers and counsellors can use these insights to better understand how anxiety and depression affect students' decision-making processes and provide more targeted support.
The Application of Information Processing Theory in Higher Education View study ↗
Wang (2021)
This study applied information processing theory to design learning activities for 153 university students. Teachers can use IPT principles to structure lessons that match students' cognitive processing capabilities, creating more effective learning sequences that enhance understanding and memory retention.
Higher education students' experiences and opinion about distance learning during the Covid‐19 pandemic View study ↗
79 citations
Stevanović et al. (2021)
This research explored students' experiences with distance learning during COVID-19, examining how remote education affected engagement and learning quality. Teachers can apply these findings to improve online teaching strategies and better understand student needs in digital learning environments.
Development of Newsletter Media in Thematic Learning for Elementary School Students View study ↗
64 citations
Liliyanti et al. (2024)
This study developed newsletter media for thematic learning in primary schools to address limited engaging learning materials. Teachers can use similar media approaches to create attractive, themed educational content that captures students' attention and supports integrated curriculum delivery.
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