Learning & Teaching with Technology

Claire O’Malley

School of Psychology

Outline

• Why use IT?

• A brief history of IT and learning

• Some approaches to learning

• Implications for teaching

• Applications to learning technologies

Why use IT?• Elaborates other teaching material

– e.g., lectures; practicals

• Students can learn at their own pace• Computers can take care of the routine stuff while

students focus on the more important stuff• Can provide learning experiences not possible

with other means• Others….?

Paradigms in Educational Computing

‘60s – Computer Assisted Learning (CAL)

‘70s – Intelligent Tutoring Systems (ITS)

‘80s – Interactive Learning Environments (ILEs)

‘90s – Computer Supported Collaborative Learning (CSCL)

Computer Assisted Learning

CAL Computer Assisted Learning

CAI Computer Assisted Instruction

CBT Computer Based Training

CBL Computer Based Learning

(Etc.)

Computer Assisted Learning• “Programmed learning”• Learning theory

– Behaviourism & reinforcement

– Associationism

• Learning activities– Drill-and-practice

– Present-test-feedback

• Instructional theory– Transmission model of instruction

Computer Assisted Learning

• Advantages– Instruction adapted to individual needs

• Issues– How to give the right feedback at the right time– How to diagnose ‘errors’

• The ‘credit assignment’ problem

– No theory of the learner’s knowledge

Intelligent Tutoring Systems

ITS Intelligent Tutoring Systems

ICAI Intelligent Computer Assisted Instruction

AI Ed Artificial Intelligence in Education

(Etc.)

Intelligent Tutoring Systems

Domain representation(what to teach)

Student model(what the student knows)

Teaching strategy(how to teach)

Intelligent Tutoring Systems

• Adaptive control of teaching• Learning theory

– Representational change

• Learning activities– Goal directed problem solving– Skill acquisition (drill-and-practice)

• Instructional theory– Transmission model (but adaptive!)

Intelligent Tutoring Systems

• Advantages– Explicit theory of learner’s knowledge

• Issues– Requires very detailed models of domain &

learner– The credit assignment problem remains...

Integrated Learning Systems (ILS)

• Originally developed in USA (Patrick Suppes, Stanford, 1970s)

• Modern version– E.g., RM’s SuccessMaker– a system that includes extensive courseware

plus management software usually running on a networked system

Essential elements

• ILS– Curriculum content

– Record system

– Management system

• ITS– Domain representation

– Student model

– Teaching strategy

FunctionalityUpdate student recordsInterpret learner’s responsesProvide performance feedback to learner and teacher

Interactive Learning Environments

• Simulations, microworlds, spreadsheets, etc.

• Learning theory– Learning is best achieved when learners

actively construct their own knowledge

• Learning activities– Discovery learning, experiential learning, etc.– Instructional theory

• Learner-as-tutor

Interactive Learning Environments

• Example– Papert’s LOGO system (1980)

REPEAT 4[FORWARD 90

RIGHT 90]

Papert’s ‘Powerful Ideas’• Making thinking explicit

• Making reasoning and its consequences ‘visible’

• Fostering effective problem solving & planning skills

• Learning to learn from errors – ‘debugging’ skills

• Developing reflective metacognitive skills

Interactive Learning Environments

• Advantages– Tools to think with rather than information

transmission

• Issues– Instructional transfer– ‘LOGO-as-Latin’

Computer Based Representations• Routine computations can be off-loaded • Can focus learners’ attention on the essentials of the

domain• Computer based notational systems may capture

procedures or abstract structure in perceptually concrete ways

• Representations can be placed under active control • Interactive manipulation may help learners construct their

own understanding of a domain• Screen based representation can be more easily shared

Multiple representations

Multiple representations

Benefits of Graphical Representations

• Reducing effort needed for search and recognition • Transformation of the problem space • Can support powerful perceptual inferences • Often have emergent features that make implicit

information explicit• Experts have more highly structured and principled

representations than novices

Multiple Representations

• Support different ideas/processes• Can promote deeper understanding

– Common invariants allow learners to construct abstractions

– Representations at different levels of abstraction• But learners need support in mappings

Computer Supported Collaborative Learning• Groupwork, peer tutoring, computer-

mediated communication• Learning theory

– Socio-cultural context of learning

• Learning activities– Knowledge building communities

• Instructional theory– Apprenticeship; ‘legitimate peripheral

participation’

Implications for LearningImplications for Learning• Learning occurs most effectively in

situations resembling those of eventual practice

• Learning should involve "legitimate peripheral participation" in communities of practice (Lave & Wenger, 1991)

• Learning occurs when the learner is confronted with a "problematic" situation

References

• Ainsworth, S.E., (1999) A functional taxonomy of multiple representations. Computers and Education, 33(2/3), 131-152.

• Koschmann, T. (1996) CSCL: Theory and Practice of a New Paradigm. Erlbaum. (Chapter1)

• Papert, S. (1980) Mindstorms: Children, Computers and Powerful Ideas. Basic Books.

• Wood, D. & Underwood, J. (1999) Integrated learning systems in the classroom. Computers & Education, 33 (2/3), 91-108.