The following information was from the following website:
http://www.uottawa.ca/academic/cut/options/Nov_98/TeachingStrategies_en.htmNovember 1998
Teaching Strategies to Foster "Deep" Versus "Surface LearningElizabeth Campbell, Centre for University Teaching
In the spring of this year, the Centre for University Teaching organized a workshop led by Dr. Christopher Knapper, Professor of Psychology and Director of the Instructional Development Centre at Queen’s University in Kingston, Ontario. During this two hour interactive session, Dr. Knapper initially explained what was meant by "deep" and "surface" learning so that workshop participants could then determine what their perceived approaches to teaching were.
When considered in terms of Bloom’s Taxonomy of Educational Objectives (1956), "deep" learning requires higher order cognitive thinking skills such as analysis (i.e. compare, contrast) and synthesis (students are required to integrate components into a new whole, e.g. What is the relationship...). "Surface" learning, on the other hand, consists mainly of comprehension and reproducing knowledge (rote learning) which is often forgotten by students shortly after the course has ended. "Deep" learners are intrinsically motivated and incorporate new ideas they are learning with existing knowledge and personal experience, while "surface" learners are extrinsically motivated — those students typically motivated by grades wanting only to know what to study for the next test.
Workshop participants were provided with a questionnaire together with a scoring key designed to probe students about how they approach learning in order to determine if they are deep or surface learners. In addition, Dr. Knapper supplied a questionnaire to help professors define their views on teaching and learning. This included statements such as:
A good teacher guides students in the process of learning so that they have an understanding of how to approach the subject and actually learn [a "deep" learning approach] instead of just memorising ["surface" learning].
A final questionnaire was distributed enabling professors to elicit feedback from their students regarding the learning climate in the department as a whole. Studies done at several universities world-wide using a similar approach produced some surprising results. Researchers actually found that students became stronger surface learners over the course of their undergraduate program and not deep learners as one might have expected.
Given these results, approaches that facilitate deep learning in the classroom were then examined in detail. Research indicates that the following list of six factors specifically promote deep learning:
Good teaching - Faculty are well prepared, confident
Openness to student - Faculty are friendly, flexible, helpful
Freedom in learning - Students have choice in what they study
Clear goals and standards - Assessment standards, expectations are clearly defined
Vocational relevance - Courses seen as relevant to future careers
Social climate - Good relations between students (social, academic)
Factors that detract from deep learning are heavy workloads and the exclusive use of formal teaching methods such as lecturing. The key is to ensure a reasonable workload for students even if it means sacrificing content "coverage". Deep learning can also be achieved by cutting down on lecture time and extending individual study time and time designated for projects.
Research also indicates the following instructional methods help promote deep learning:
Encouraging faculty/student interaction (e.g. meet groups to plan projects, "personalize" teaching)
Encouraging student/student interaction (e.g. group projects, peer tutoring)
Using active and interactive teaching methods (e.g. case studies, buzz groups)
Making links with what students already know to encourage sense of structure
Allowing students input into course goals and methods, being receptive and flexible
Discussing/teaching learning skills explicitly
Trying to link course topics to students’ lives and career aspirations
Since testing can sometimes run counter to this kind of learning, the following suggestions enable professors to select appropriate assessment methods when teaching for deep learning:
Define assessment goals and tasks clearly, and ensure they are congruent
Allow choice of assessment tasks
Stress tasks that allow time for information gathering, depth, and reflection (e.g. projects vs. exams)
Encourage collaborative projects
Choose tasks that require integration of information from a range of sources
Give full and proactive feedback on labs, assignments, and tests
If you currently implement even one of these instructional methods, then you are already well on your way to making the shift toward deep learning in the classroom. If you are interested in learning more about this topic or would like to view the video of Dr. Knapper’s workshop, please contact the Centre for University Teaching at (613) 564-2350, by fax (613) 564-6356, or by e-mail
centre@uottawa.ca.
Bloom, Benjamin S. (Ed). (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals. Handbook I. Cognitive Domain (pp. 201-207). New York: McKay.
Kember, David. (1997). A reconceptualisation of the research into university academics’ conceptions of teaching. Learning and Instruction, 7, 255-275.
Gow, L., & Kember, D. (1993). Conceptions of teaching and their relationship to student learning. British Journal Of Educational Psychology, 63, 20-33.
Ramsden, P. (1983). The Lancaster Approaches to Studying and Course Perceptions Questionnaire: Lecturers’ Handbook. Oxford, England: Oxford Polytechnic, Educational Methods Unit.
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