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ALT-C/eLN Webinar: The Science of Learning Richard Cox School of Informatics University of Sussex 22 nd June 2010.

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Presentation on theme: "ALT-C/eLN Webinar: The Science of Learning Richard Cox School of Informatics University of Sussex 22 nd June 2010."— Presentation transcript:

1 ALT-C/eLN Webinar: The Science of Learning Richard Cox School of Informatics University of Sussex 22 nd June 2010

2 Learning One definition: “Change in behaviour not attributable to maturation…” Human learning (because the science of learning includes much research on learning by non-humans…) Science, scientific method…a ‘way of knowing…’ – LT, e- learning, TEL a real boon to study of learning in educational contexts – e.g. nice methodological innovations such as controlled experiments comparing subtle variations in presentation, type of feedback given to students etc, collect massive amounts of data for educational data mining later…

3 Issues (in 20’ !) Learning what? Learning how? Learning context Learning types Learning to learn Learning and feedback Learning and information modalities

4 Learning what? Declarative information – Knowing that Procedural skills – Knowing how

5 Learning how? Direct instruction – Instructionism – Instructional model/design – Curriculum structure (conceptual pre/co-requisites of a topic in a domain, etc) (Bloom, Ausubel) By exploration – constructionism/constructivism (Piaget, Papert, Bruner) By doing – Teaching in context of problem solving – Maximise receptivity to needed information kind of JIT teaching(Anderson) By observing others (vicarious) – Learned emotional responses (Bandura) – Also cognitive skills (e.g. Cox, Lee, et al.)

6 Learning context Formal settings – Schools – Universities – Workplace training Real-world – Hobbies – Interests – sports

7 Learning types Explicit – Available to articulation e.g. via spoken/written language – Students encouraged to ‘stay explicit’ (e.g. for assessment) – Analytical, rational, rule-based, controlled, cognitively demanding, slow, cultural, formal tuition Implicit – Heuristic, tacit, associative, quick, automatic… – Hallmark of expertise, practiced skill – Intuitive (and not necessarily inaccurate) Aka system 1 and system 2 cognition – (see Stanovich’s “dual-process framework”, 1999)

8 Learning to learn Metacognition E.g. Chi’s ‘self-explanation effect’ Awareness of own learning – Achievements – Styles – Cognitive and emotional states Learning to learn – can be taught? – Study skills courses…

9 Learning and feedback Feedback crucial to (efficient) learning – Marks – Remarks – Knowledge of results – Applies to learning declarative knowledge and procedural skills However, instructionless (& feedbackless) learning does occur too - students have insights of their own

10 Learning modalities Information can be presented to students in two modalities – Graphical Pictures Diagrams, charts, graphs – Linguistic Natural language (spoken, written) Formal languages and notations – Mathematics, logic Two modalities have very different expressive, cognitive and semantic properties Mix and match judiciously (cf Richard Mayer’s CHoMMLng; Cox jnl paper in Lng &Instr. (1999); Stenning’s book ‘Seeing reason’) Students (may) differ individually in their propensities to learn graphically and/or linguistically…

11 Of course these factors interact massively… E.g. Constructivist learning approach X procedural skill X graphical information presentation probably maximises likelihood of implicit learning… Direct instruction X declarative knowledge X natural language modes of information expression probably maximises likelihood of explicit learning…

12 References Bransford, J.D., Brown, A.L., & Cocking, R.R. (Eds), (2000) How people learn: Brain, mind, experience and school. Wa:DC. National Academy Press. Mayer, R.E. (Ed.) (2005) The Cambridge Handbook of Multimedia Learning. Cambridge University Press. Stanovich, K.E. (1999) Who is rational: Studies of individual differences in reasoning. Mahweh:NJ, LEA.


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