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Tag: education

  • The Next OzLearn Tweet Chat is on 9/12/14

    Ozlearn tweet chat

    On Tuesday 9th December at 8:00pm AEDST (UTC +11hrs), @OzLearn is having its final monthly twitter chat for 2014. We are very fortunate to have Nigel Payne – @ebase – join us! You can read an introductory post for the chat by clicking here.

    To join the chat, go to Twitter at 8pm on 9/12, search for @OzLearn and join in the conversation (don’t forget to add #ozlearn to your tweets).

    There is also an OzLearn LinkedIn group where you can view the Storify of the chat afterwards.

    Hope you can join us for the chat!

  • Working with Cognitive Load

    When I first started working as an eLearning instructional designer I became interested in the learning process and how people learn. I figured that if I knew more about information processing and learning, I could hopefully design more effective courses and materials. I came across a book called Efficiency in Learning: Evidence-Based Guidelines to Manage Cognitive Load by Ruth Colvin Clark, Frank Nguyen and John Sweller. In this book I discovered – among other things – Cognitive Load Theory (CLT) which is based on studies of human cognitive architecture – how we process and organise information.

    In our brains, we have two types of memory. One is our working memory, which we use to process new information. The capacity of our working memory is quite limited so it can only handle so much before it becomes overloaded. The second is our long-term memory, which is where we store information from our working memory and where we retrieve that information from later. Within our long-term memory, information is organised into schemas, which are organisational frameworks of storage (like filing cabinets). Not exceeding working memory capacity will result in greater transfer of information into long-term memory.

    CLT proposes that there are three types of cognitive load:

    Intrinsic: this is the level of complexity inherent in the material being studied. There isn’t much that we can do about intrinsic cognitive load; some tasks are more complex than others so will have different levels of intrinsic cognitive load.

    Extraneous: this is cognitive load imposed by non-relevant elements that require extra mental processing e.g. decorative pictures, animations etc. that add nothing to the learning experience.

    Germane: these are elements that allow cognitive resources to be put towards learning i.e. assist with information processing.

    The three types of cognitive load are additive so according to the theory, for instruction to be effective:

    Intrinsic load + Extraneous load + Germane load < Working memory capacity

    To assist learners in transferring information from their working memory to their long-term memory, we need to present the information in such a way that it reduces extraneous cognitive load (non-relevant items) and, if possible, increases germane cognitive load (items that assist with information processing). Note: I’ve found that much of the literature tends to focus on reducing extraneous cognitive load.

    Mayer and Moreno (2003) conducted research into ways to reduce cognitive load in multimedia learning. Their research, built on CLT, was based on three assumptions:

    1. Humans possess separate information processing channels for verbal and visual material (Dual Channel).
    2. There is only a limited amount of processing capacity available via the visual (eyes) and verbal (ears) channels (Limited Capacity).
    3. Learning requires substantial cognitive processing via the visual and verbal channels (Active Processing).

    They found that designers should do the following to assist learners in processing information:

    • Present some information via the visual channel and some via the verbal channel.
    • Break content into smaller segments and allow the learner to control the pace.
    • Remove non-essential content – this includes background music and decorative pictures that don’t add value.
    • Words should be placed close as possible to the corresponding graphics.
    • Don’t narrate on-screen text word-for-word.
    • Synchronise visual and verbal content i.e. don’t place them on separate screens.

    As instructional designers, we need to be aware of the cognitive requirements our designs impose and ensure that our learners can meet those requirements. We must also ensure that all aspects of our design focus on adding value to the learning experience.

    References:

    Efficiency in Learning: Evidence-Based Guidelines to Manage Cognitive Load (2006) by Ruth Colvin Clark, Frank Nguyen and John Sweller. Pfeiffer

    Mayer, R. E. & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist. 38, (1), 43-52.

  • Integrating Motivation with Instructional Design

    As an Instructional Designer, motivating learners is an important consideration because in reality learners are not always motivated to learn. They are busy, have other things to do, don’t see the course/session as being important or have had a bad learning experience in the past. I’ve written previously about motivation – Motivation and eLearning – which was about satisfying autonomy, competence and relatedness needs of learners. I’ve come across Dr John Keller’s motivational design model known as ARCS and thought it was worth sharing.

    The ARCS model comprises four major factors that influence the motivation to learn – Attention, Relevance, Confidence and Satisfaction. It’s described as a problem-solving model and helps designers identify and solve specific motivational problems related to the appeal of instruction. The model was developed after a comprehensive review and synthesis of motivation concepts and research studies. It has also been validated in studies across different education levels.

    Dr John Keller

    The four categories of motivation variables consist of sub-categories along with process questions to consider when designing:

    Attention = Capturing the interest of learners, stimulating their curiosity to learn.

    • Perceptual Arousal: What can I do to capture their interest?
    • Inquiry Arousal: How can I stimulate an attitude of inquiry?
    • Variability: How can I maintain their attention?

     

    Relevance = Meeting the personal needs/goals of the learner to affect a positive attitude.

    • Goal Orientation: How can I best meet my learner’s needs? (Do I know their needs?)
    • Motive Matching: How and when can I provide my learners with appropriate choices, responsibilities and influences?
    • Familiarity: How can I tie the instruction to the learners’ experience?

     

    Confidence = Helping the learners believe/feel that they will succeed and control their success.

    • Learning Requirements: How can I assist in building a positive expectation for success?
    • Success Opportunities: How will the learning experience support or enhance the learners’ beliefs in their competence?
    • Personal Control: How will learners clearly know their success is based upon their efforts and abilities?

     

    Satisfaction = Reinforcing accomplishment with rewards (internal and external).

    • Natural Consequences: How can I provide meaningful opportunities for learners to use their newly acquired knowledge/skill?
    • Positive Consequences: What will provide reinforcement to the learners’ successes?
    • Equity: How can I assist the learners in anchoring a positive feeling about their accomplishments?

     

    The following link is to a YouTube video where Dr Keller discusses the ARCS Model, some background in its development and the addition of volition to the model.

    ARCS: A Conversation with John Keller

    Apart from the motivational aspects of the model, what I really like about ARCS is that it puts the learner at the centre of the design process.

    After all, that’s how it should be.

     

    References:

    arcsmodel.com

    Keller, J. M. (1987) Strategies for stimulating the motivation to learn. Performance and Instruction. 26 (8), 1-7.