Mental Models and Network Pedagogy Philip Barker ENABLE99 Presentation Espoo, Finland 2nd June, 1999 Human-Computer Interaction Laboratory University of Teesside Cleveland, UK
Overview • Introduction • What are Mental Models? • Why are they Important? • How are the Studied? • Network Pedagogy • Concluding Remarks
1. Introduction knowledge and skills innate limitations augmented performance performance support skilled behaviour
Knowledge Skills The Importance of Knowledge and Skills Task Domain Goal fulfilment via Task Execution
Knowledge Defined • a representation of previous experience of a domain • reflects ‘what we know’ about a topic • usually developed through observation, exploration, experiment and inference • collectively referred to as ‘learning processes’
Skills Defined • skills are affective processes that we use in order to solve problems and achieve goals • they may be ‘innate’ or ‘acquired’ • usually improve with practice • there is a limit to improvement
Performance N Innate Limitations We are all subject to the limitations of our natural abilities. Many skills are subject to the Power Law of Practice How can we improve performance beyond our natural abilities?
Human Task Human Human Task Human Augmented Performance We must consider tools and techniques (called performance aids) that will enable us to augment our own individual abilities. Group
Technology Task Human Technology Task Group Using Technological Support
Performance Support • EPSS • DPSS • MPSS
Performance Support • EPSS • DPSS • MPSS Further details: http://www-scm.tees.ac.uk/users/philip.barker/edmedia99 presentation.ppt and paper.htm
Skilled Behaviour • Can we build learning systems that will enable users to develop ‘skilled behaviour’ in a minimal time span at minimal cost? • We need to study the relationship between knowledge and expert/skilled behaviour. • An important steping stone in achieving this is an understanding of mental models.
2. What are Mental Models? What is Knowledge? How do we Know Things? The Role of Memory Types of Knowledge Cognitive Structures Mental Models Defined
What is Knowledge? put stimuli Memory fetch behaviour Knowledge is what we have ‘in our heads’ and which controls higher order behaviour.
Knowing Things • Verbatim Knowledge • poem • song • speech • multiplication tables • Procedures • generic (eg long multiplication) • specific (eg key recognition - largest off small ring) • Mental Images • house • car • person • Mental Models • rich structures based on a variety of representational techniques
The Role of Memory Stimuli Transient Memory Stimuli Working Memory (Short Term Memory Long Term Memory
Types of Knowledge • tacit and explicit • private and public • local and global • declarative and procedural
Some Definitions Declarative Knowledge - facts and figures - relationships Procedural Knowledge - how to do things NB The ‘recall’ versus the ‘rule’ debate (eg multiplication)
Cognitive Structures • simple associations • lists • plans • schemata • scripts • simple models • complex models
Mental Models Defined According to Rogers et al: mental models are representations ‘in the head’ of experiences gained through the process of living
Models and Model Building rules properties Generic Class Associated Object referent e.g. Jim MENTAL MODELS Associated Object Generic Class referent e.g. house Generic Class specific properties specific rules
3. Why are they Important? general points dialogue and knowledge transfer human-computer interaction teaching and learning the mental model hypothesis
General Points • reduce memory overheads • reduce complexity • allow derivation of information • support cognitive processing • dynamic character
Mental Models Mental Models Dialogue and Knowledge Transfer experiments experiments knowledge transfer books books dialogue environments and experiences environments and experiences Computer Mediation dialogue dialogue
Mental Models SYSTEM USER Interface Mental Models in HCI
The Role of Interfaces communicate system image to user teach user about system help user to develop skills help user to achieve goals map ‘intent’ onto ‘results’ enable tasks to be performed provide ‘handles’ onto system functionality
text icons drawings widgets images SYSTEM video sound Interface tactile sensations Interface Agents
Environments generate produce Stimuli Experiences initiate Learning Activities activate generate involve Cognitive Structures control Mental BEHAVIOUR Models Designing Learning Environments
A Research Problem Task Domain Skilled Behaviour Performance Knowledge Skills
Mental Model Hypothesis The quality of a person’s mental models determines the quality of task performance in a given problem domain.
4. How are they Studied? Representational Spaces Basic Techniques Experimental Design Case Study Findings
Basic Techniques • diagramming • concept maps • hierarchy diagrams • rating • sorting • laddering • teach-back • think aloud • acton sequences
Applicability of Methods Different techniques can capture: (a) different aspects of mental models, and (b) the same aspects in different ways
Experimental Design • identify domain to be studied (eg Web browsing) • select participants (eg 1st Year Students) • identify measurement techniques to be used (eg concept mapping, laddering, teachback) • design scenario involving these techniques • rate solutions against an expert’s answer • additionally, rate task performance (using metrics such as time on task, error counts, quality of solution. and so on)
Case Study - Word for Windows • applied these techniques to measuring mental models students had of Word for Windows • Experiment 1 (richness of mental models) (1) concept elicitation (2) sorting (3) laddering (4) teachback • Experiment 2 (performance on task) (1) Task using Word (Prepare an Invoice) (2) Solution’s compared with an Expert’s • Statistical Analysis
Findings • strong correlations found between those who performed well in Experiment 1 and the quality of solution observed in Experiment 2 • results confirm mental model hypothesis • two basic types of model (1) generic - applicable across all systems (2) specific - relevant to a particular system • represented as hierarchical tree structures • object hierarchies • command hierarchies • states of system • transitions and transformations between states
4. Network Pedagogy definition principle techniques examples results mental models
Definition Network pedagogy refers to the use of computer network systems for the support of and/or delivery of teaching and learning
Definition Network pedagogy refers to the use of computer network systems for the support of and/or delivery of teaching and learning What are the implications of this for the development of mental models?
Mental Models E1 E2 E4 E3 E5 Principle Time Network interactions provide a powerful mechanism for stimulating the growth and adaptation of mental models.
Techniques • delivery • browsing • monitoring • email • chat • conferencing
Examples • using networks to provide access to teaching material • development of new teaching strategies • using networks to support self-study • lifelong learning applications
Expected Language Spelling Maths Reading Results Gain http://www.nn.com/results.htm
Implications for Studying Mental Models • results suggest richer mental models are being performed • however, this needs to be confirmed • how can mental models in network environments be studied? • appropriate techniques need to be developed
5. Concluding Remarks Our Own Position on Mental Models van Merriënboer’s view (1997) Seel’s opinion (1995) Final Questions
Our Own View Research into the development of mental models is a fundamental requirement if we are to gain a complete understanding of teaching and learning activities
van Merriënboer’s view ‘from an instructional point of view, it may be worthwhile to think in terms of mental models because they provide a higher level of reasoning about the knowledge underlying skilled performance’
Seel suggests that ‘learning a complex cognitive skill can be regarded as the development of increasingly complex mental models that describe both the procedural and the declarative knowledge that is required for effectively solving problems at each stage of acquiring the skill’
Final Questions • For any given skill, what mental models are needed? • How do we design learning experiences to facilitate the development of these models? • How do we create effective learning environments to generate the necessary learning experiences?