eLearning Tools for

PLAR

Uri ShafrirOntario Institute for Studies in Education

University of Toronto

Masha EtkindRyerson University

• Demonstration of prior learning through portfolios and challenge exams

• Recognition of prior learning accepted by academic institutions and employers

PLAR: Goals

• Encourage learners to demonstrate prior learning by focusing on meaning

• Create an authentic record of direct interaction with conceptual content

eLearning Tools: Goals

1 Interactive Concept Discovery Learning

2 Meaning Equivalence

Reusable Learning Objects (MERLO)

eLearning Toolsfor

PLAR

Interactive Concept Discovery Learning

Explore alternative representations

of important concepts

through semantic searches of

digital text-bases (e.g., digital libraries;

company archives; World Wide Web)

Novel semantic search technology enable demonstration of prior learning by:

1. Showing different representations of important concepts within particular contexts

2. Mapping their building blocks

3. Mapping their lateral and hierarchical links to other concepts

Process/Outcomes

Process

By recursively accessing different sources of

information on a particular concept, learners

demonstrate familiarity with:

• Alternative representations of the concept that share equivalence of meaning

• Building blocks of the concept: consistently

co-occurring subordinate concepts

Process/Outcomes

Outcomes

Interactive Concept Discovery Learning

creates an authentic record of:

• Concept mapping that reveals lateral and hierarchical links between concepts and their building blocks

• Learning at the conceptual level

1 Interactive Concept Discovery Learning

2 Meaning Equivalence

Reusable Learning Objects (MERLO)

eLearning Tools: Pragmatics

Meaning Equivalence Reusable Learning Object

MERLO are knowledge databases that encode conceptual content, in any discipline, in multiple representations that include text; mathematical equations; images; etc.

MERLO encode conceptual content in nodes of item families that include multiple representations of:

• Target statements that focus on particular features of a concept

• Additional statements, sorted by

i surface similarity to the target

ii meaning equivalence with the target

TARGET STATEMENT

Surface similarity [SS]

Yes No

Meaning equivalence [M

E]

Yes

No

SS Yes

ME Yes

SS No

ME Yes

SS Yes

ME No

SS No

ME No

Process/Outcomes

Process

• MERLO-based challenge exams provide

learners with opportunities to

produce and evaluate

multiple representations of concepts

• Clear conceptual framework that encourage learners to focus on meaning

Process/Outcomes

Outcomes• Scoring algorithms accurately map

‘soft conceptual spots’ and partial knowledge

• Frequent and accurate feedback encourage detailed analysis of concepts and their building blocks

• Enhanced learning outcomes

eLearning Tools:Evaluative Implementations

K-12: High school of Russian Academy of Sciences, St. Petersburg

Post-secondary: University of Toronto; Ryerson University; George Brown College

Workplace/adult: Material and Manufacturing Ontario Center of Excellence

eLearning Tools :Evaluative Implementations

Mathematics Architecture

Physics ESL

Biology Business

Teacher Education

eLearning Tools for

PLAR• Create authentic record of mastery of

knowledge

• Can be used in ePortfolios and in challenge exams

• Identical to eLearning tools being used in colleges, universities, and workplace learning

eLearning tools are part of Canada Knowledge Network

(now under construction)

Contact: ushafrir@oise.utoronto.ca