Evidence shows that we best learn in context (Bangs 2012:50). Context-rich problems can help students move past rote memorisation of economic vocabulary and concepts (bangs 2012:50). Learning in context is not a new idea (Bangs 2012:50). It relates to the process of apprenticeship where the master (Bangs 2012:50):
- models the process
- coaches the apprentice as he/she starts doing the work
- start with simple parts of the process before moving to more complex parts.
- fades over time to allow the apprentice to work independently.
Brown, Collins and Duguid (1989) labels the process of bringing context into the classroom cognitive apprenticeship. Context-rich problems can serve as a tool during the cognitive apprenticeship process (model, coach, fade) (Bangs 2012:50). In economics, instructors can (Bangs 2012:5):
- model the way economics can be used
- demonstrate their thought processes while solving a complex context-rich problem for the students
- use cooperative learning techniques to help students solve context-rich problems
- begin with simple context-rich problems and move on to more complex problems
- coach students through the process
- fade when students can work independently.
This approach is new in economics, but is used for a number of years in physics education (Bangs 2012:50). The aim is to improve problem-solving skills (Bangs 2012:50).
Context-rich problems are an active learning technique that is designed specifically with the goal to help students to think like economists (Bangs 2012:48). This approach to teaching put students in realistic scenarios so they can practice applying economic concepts (Bangs 2012:48). Bangs (2012:48) provided the following examples to differentiate between traditional and context-rich problems
A discount bond mature in five years. It has a face value of $10 000. If interest rates are 2%, what is the present value of this bond?
The same problem can be reshaped into a context-rich problem:
You and your sister inherited a discount bond. The bond has a face value of $10 000 and matures in five years. You would like to hold onto the bond until maturity, but your sister wants her money now. She offers to sell you her half of the bond, but only if you give her a fair price. What is a fair price to offer her? How can you convince her it is a fair price?
Based on these examples, the following characteristics of context-rich problems can be identified (Bangs 2012:48-49):
- The student is placed in a realistic scenario
- The statement generally start with the word ‘you’
- The student can relate to the problem
- It answers the frequent student question: ‘Why do I need to know this stuff?’
- It uses events happening in real life communities, in small businesses, or decisions that a new emplyee or an intern might be asked to work on
- It lacks an explicit target
- It rarely include directives such as ‘calculate present value’ (Traditional problems often just do that)
- It requires students to think critically like an economist by first identify the relevant concept (present value) in order to be able to solve the problem
- It does not provide complete information or excess information (The students are not told what interest rate should be used to calculate the present value)
- Students have to use knowledge of current interest rates, or expand it if incomplete, to select the appropriate interest rate
If all information was provided, students do not learn how difficult it is to solve real life problems where all of the available information have to be evaluated to determine which information is relevant to the decision (Bangs 2012:49). For more examples, read Bangs 2012:49-50.
How can we use context-rich problems in the classroom?
Students accustomed to traditional plug and chug sort of problems will likely need help getting started (Bangs 2012:51). Heller, Keith and Anderson (1992) suggest the following problem-solving strategy:
- Visualise the problem
- Describe in terms appropriate for the discipline
- Plan a solution
- Execute a plan
- Check and evaluate
Instructors need to include a period of coaching as students work with their own context-rich problems (Bangs 2012:52). Ideas include (Bangs 2012:52):
- What do you need to know to solve the problem?
- Incorporating an explicit target
- Prompts within the problem (Interesting idea for branched MCQ’s).
- Students coaching one another
- Think-pair-share approach (work independently, paired with peers, share ideas, discuss differences, come with a final solution, share with whole class afterwards is also an option)
- Careful consideration of degree of difficulty
The level of difficulty (Bangs 2012:52):
- determined by degree to which some of the characteristics of context-rich problems are included
- increased by leaving out needed information as the omission forces the students to consider where they should go to find the required information
- can be increased when working in pairs
- can be increased when providing more time
- can be increased by providing irrelevant information as it happens in real life and forces the student to evaluate usefulness of each piece of information provided.
- can be increased by requiring more than one key concept to be used to solve the problem
- the lack of an explicit target can increase the level of difficulty: in stead of telling them what they need to do to solve the problem, students are asked what they should do to solve the problem.
Context-rich problems in relation to other active learning techniques
Maier, Bangs, Blunch and Peterson (2010) noted that context-rich problems can be incorporated with other active learning techniques:
- Context-rich problems can serve as basis around which cooperative learning exercises are structured
- Context-rich problems can serve as basis of final evaluation following a cooperative learning round table exercise (see Rhoads 2009)
- Context-rich problems with more than one solution in concert with just-in-time teaching can lead to rich discussions
- Variety of responses gathered prior to class through course management system can spark discussion of the strengths and weaknesses of the responses
Bangs, J. 2012. Teaching with context-rich problems. In: Hoyt, G.M. and McGoldrick, K (ed). International handbook on teaching and learning economics. pp. 48-56. Cheltenham, Glos, UK:Edward Elgar Publishing Limited.
Brown, J.S, Collins, A. and P. Duguid (1989). Situated cognition and the culture of learning, Educational Researcher, 18(1), 32-42,
Maier, Bangs, Blunch and Peterson (2010)
Rhoads 2009Context-rich problems