Pedagogic strategy

Jump to navigation Jump to search


Pedagogic Strategies can be defined at 3 levels:

  1. General instructional designs
  2. Designs applied to a teaching/learning unit (e.g. a lesson or a course module)
  3. Pedagogic methods that are part of a wider design (e.g. of a pedagogic strategy as defined here) and that we discuss elsewhere.

Effective course designs (or teachers) may make use of different teaching strategies or methods.

According to Dick et al. (2001:184) “instructional strategy is used generally to cover the various aspects of sequencing and organizing the content, specifying learning activities, and deciding how to deliver the content and activities.”

Important notice: DSchneider doesn't feel very sure how to distinguish pedagogic strategies from what he calls instructional design models. Here is a provisional distinction:

  • Pedagogic strategies refer to a general abstract teaching method. They can influence instructional design models.
  • Instructional design models refer to more precise instructional designs (based on some more explicit teaching and learning goals). A model can (but must not) implement several kinds of pedagogic strategies and methods.

Alternative entry points:

  • Instructional design models (It might be good idea to merge at some point these articles, but then it's sometimes a good idea to look at a similar problem with different instrumentation ...)
  • Teaching style (models that focus on the classroom teacher)

Types of pedagogic strategies

Definitions of pedagogic strategies draw often from several fields.

Firstly pedagogic strategies (at least the ones discussed in instructional design) are based on general learning theoretical concepts, e.g. Behaviorism, Cognitivism, Constructionism, Constructivism, Socio-constructivism, Situated learning, etc. Learning theorists often also address pedagogical issues . There is an overlap between theories that explain how people learn and how one could bring people to learn. This is particularly true regarding larger families of thought like constructivism.

Second, design of strategies draws a lot from general pedagogical theory, but also from specialized research (displinary didactics, school vs. vocational training etc.).

Third, educational technology has been a driving force to develop new strategies, with the basic assumption that educational technologies can facilitate pedagogical scenarios.

Ruth Clark four instructional architectures

According to Merril (2002), Ruth Clark (1998) suggests four different instructional architectures (receptive, directive, guided discovery, and exploratory) that he calls instructional style.

In the context of educational technology:

  • Receptive instruction is characterized by a lecture or an Internet site where the student is merely provided with information.
  • Directive instruction is characterized by a computer-based tutorial where information is presented, the student responds, feedback is provided and this tutorial learning cycle is repeated.
  • Guided Discovery is characterized by a computer simulation that allows the student to manipulate some device or environment.
  • Exploratory instruction is characterized by an open learning environment in which the student is provided a rich, networked database of information, examples, demonstrations, and exercises from which the student can select whatever is appropriate to their current needs and mental models.

Weston & Cranton

Cynthia Weston and P. A. Cranton (1986:278) defined a still popular taxonomy that relates instructional strategies to different types of learning contents, i.e. domain content levels. Different strategies are viewed as useful for different types of contents and learning outcomes.

Matching Domain and Level of Learning to Appropriate Methods
Domain & Level Method
Cognitive Domain
Knowledge Lecture, programmed instruction, drill and practice
Comprehension Lecture, modularized instruction, programmed instruction
Application Discussion, simulations and games, CAI, modularized instruction, field experience, laboratory
Analysis Discussion, independent/group projects, simulations, field experience, role-playing, laboratory
Synthesis Independent/group projects, field experience, role-playing, laboratory
Evaluation Independent/group projects, field experience, laboratory
Affective Domain
Receiving Lecture, discussion, modularized instruction, field experience
Responding Discussion, simulations, modularized instruction, role-playing, field experience
Valuing Discussion, independent/group projects, simulations, role-playing, field experience
Organization Discussion, independent/group projects, field experience
Characterization by a Value Independent projects, field experience
Psychomotor Domain
Perception Demonstration (lecture), drill and practice
Set Demonstration (lecture), drill and practice
Guided Response Peer teaching, games, role-playing, field experience, drill and practice
Mechanism Games, role-playing, field experience, drill and practice
Complex Overt Response Games, field experience
Adaptation Independent projects, games, field experience
Origination Independent projects, games, field experience

Baumgartner - Learning I-II-III

We expand Baumgartner's (2004) learning I-II-III typology with associated pedagogical strategies and instructional design models. The following table is based on Baumgartner et al. (2004) picture (up to row 6) and to which we made additions.

Dominant Strategy Transfer (teaching I) Tutoring (teaching II) Coaching (teaching III)
Knowledge type Factual knowledge, "know-that" Procedural knowledge, "know-how", problem solving, concepts Social practice, "knowing in action"
Aims of Teaching Transfer of propositional knowledge Presentation of predetermined problems Action in (complex and social) situations
Learning goal to know, to remember to do, to practice, to argue to cope, to master
Assessment Production of correct answers Selection of correct methods and its use Realization of adequate action strategies
Learning content type Verbal knowledge, Memorization Skill, Ability Social Responsibility
Teaching and learning strategies and activities to teach, to explain to observe, to help, to demonstrate to cooperate, to support
Learning theory Behaviorism Cognitivism
Socio-constructivism, Situated learning
Examples of instructional design models programmed instruction,
(simple mastery learning,
problem-based learning,

case-based learning,
Discovery learning with simulations, microworlds,

inquiry-based learning, project-based learning
Situated discovery learning and exploratory learning,
learning level Stimulus-response
Bloom's level 1
chaining, association, discrimination, concept

learning, problem solving

(Blooms levels 1-6)
situated problem solving

Schneider's modified Learning I-I-III

  • See the learning type article. The idea is to expand these learning types a bit in order to take into account levels of complexity and also have a slot for orthogonal designs (e.g. that deal with motivation).
DSchneider is not yet very sure of this ...

Learning categories - suitable for instructional design planning

Learning I-II-III Revised version Example designs

I: know that

I-a Facts : recall, description, identification, etc.

direct instruction, programmed instruction, mastery learning, e-instruction

I-b Concepts: discrimination, categorization, discussion, etc.

discovery learning, exploratory learning

II: know how

II-a Reasoning and procedures: inferences, deductions, etc. + procedure application

drill programs, simulation, virtual laboratory

II-b Problem solving and production strategies: identification of subgoals + application of heuristics/methods

case-based learning, inquiry-based learning, problem-based learning

III: knowing in action

III Situated action: action strategies in complex and authentic situations

project-based learning

IV: Other

IV Other: e.g. motivation, emotion, reflection, i.e. elements that could intervene in all the other categories

FEASP, learning e-portfolio

Greeno, Collins and Resnick

Greeno, Collins and Resnick (1996), based on learning psychological reflection, distinguish between behaviorist, cognitive and situative approaches and formulate first principles as defined by Brown and Campione (1994). Johri and Olds (2011), in a article on bridging learning sciences and engineering education, created the following table summarizing the headings of the Greeno et al. article and that we reproduce in turn with slight modifications. Numbers of design principles are taken from the original Greeno et al. article.

Behaviorist Cognitive Situative
Nature of knowing as having associations as concepts and cognitive abilities as distributed in the world
Nature of learning and transfer acquiring and applying associations acquiring and using conceptual and cognitive structures becoming attuned to constraints and affordances through participation
Nature of motivation and engagement extrinisic motivation intrinsic motivation engaged participation
Design guidelines for learning environments (b1) Routines of activity for effective transmission of knowledge.

(b2) Clear goals, feedback, and reinforcement.

(b3) Individualization with technologies.

(c1) Interactive environments for construction of understanding (s1) Environments of participation in social practices of inquiry and learning.

(s2) Support for development of positive epistemic identities.

Curricula design guidelines (b4) Sequences of component-to-composite skills. (c2) Sequences of conceptual development.

(c3) Explicit attention to generality.

(s3) Development of disciplinary practices of discourse and representation.

(s4) Practices of formulating and solving realistic problems

Assessment design guidelines (b5) Assessment of knowledge components. c4) Assessments of extended performance.

(c5) Crediting varieties of excellence.

(s5) Assessing participation in inquiry and social practices of learning.

(s6) Student participation in assessment.

(s7) Design of assessment systems.


Joyce, Weil and Calhoun (2000) defined 4 major families of models for teaching, i.e. strategies that are used in schooling.

  1. Behavioral systems family of models
  2. Information-processing family of models
  3. Personal family of models
  4. Social family of models
Familiy of models Description (see Allen) Examples of Models
Behavioral systems To change the behavior of the learner / transmit the culture by teaching skills and knowledge. E.g. the learner is considered to be a system that can be influenced by feedback.
Information-processing To improve logical thinking processes. This includes search for information, concept learning, hypothis formulation and testing, creative thinking.
  • Inductive thinking: find and organize information leading to concept formation) (H. Taba)
  • Concept attainment: teaching concepts and helping to students to develop concepts, (J. Bruner)
  • Memorization: strategies for memorizing and assimilatating information
  • Advance Organizers: provide learners with the cognitive structure to understand complex materials (Ausubel).
  • Scientific Inquiry: teach how to collect and analyze data, and test hypothesis and theories. (e.g. inquiry-based learning
  • Inquiry training: Engage students in causal reasoning, i.e. ask questions, build concepts and hypothesis and test them.
  • Synectics: creative thought, i.e. help students to "break set" in problem-solving and writing activities
Personal/Individual family To take into account particular traits of individuals and to analyse them. This includes meta-cognitive activities to develop internal resources to see things in new/different ways.
  • Nondirective (facilitative) teaching (Rodgers)
  • Enchancing self-esteem, development of self concepts
Social family

Build learning communities that profit from interactions between learnings.
At the strategic level: to teach learning by apprenticeship, social skills and communication.

Update (2015): This book is now in it's 9th edition and includes additions. Joyce, B., Weil, M., Calhoun, E. (2014). Models of Teaching (9th Edition) Hardcover, 9th edition, Pearson, ISBN 0133749304 .

Reeves' pedagogical dimensions of computer-based education

Reeves (and Reeves) proposed several variants of a multi-dimensional model that allows categorization of various computer-based pedagogical designs. Identified pedagogical dimensions can be used to compare one form of Computer-based-education (CBE) with another or to compare different implementations of the same form of CBE. Reeves' motivation was the claim that “Systematic evaluation of computer-based education (CBE) in all its various forms (including integrated learning systems, interactive multimedia, interactive learning environments, and microworlds) often lags behind development efforts (Flagg, 1990).” (Reeves, 1997). The authors identifies frour reasons: (1) Technological innovations advertized as beeing effective are taken to be effective. This is reinforced by industry spending more money on marketing than on evaluation. (2) Decision makers are more interested in numbers dealing with technology investements, spread and quantitative use of CBE in the school system. (3) Evaluation formats are indadequate, e.g. “evaluation reports are usually presented in the format of social science research reports, a format that "is almost useless for most clients and audiences" (Scriven, 1993, p. 77)” (Reeves, 1997). (4) Evaluators often compare the incomparable. “A major weakness in traditional empirical approaches to evaluation is that the treatments being compared (e.g., interactive multimedia versus classroom instruction) are often assumed to be cohesive, holistic entities with meaningful differences.”(Reeves, 1997).

“Berman and McLaughlin (1978) and other implementation researchers (Cooley and Lohnes, 1976) have illustrated the fallacy of assuming that meaningful differences exist between two programs just because they have different names. It is imperative to open up the "black boxes" of instructional alternatives and reveal the relevant pedagogical dimensions they express if evaluations are to be meaningful and have utility. Pedagogical dimensions are the keys to unlocking the black boxes of various forms of CBE.” (Reeves, 1997).

DimensionsScales (2 ends)
Pedagogical epistemology objectivism - constructivism
Pedagogical philosophy (Epistempology) instructivism - constructivism
Underlying psychology (Learning theory) behavioriral - cognitive
Goal orientation (learning objectives) sharply focused (precise) - unfocused (general)
Experiental validity (orientation of the activity) abstract (academic) - concrete (applied). On an other scale: reproduce, classify, explain, apply, invent, solve a problem.
Teacher role didactic - facilitative
Flexibility teacher-proof - easily modifiable
Value of errors errorless learning - learning from experience
Origin of motivation extrinsic - intrinsic
Accommodation of Individual Differences non-existant - multi-faceted
Learner control non-existant - unrestricted
User activity mathemagenic - generative
Cooperative learning unsupported - integral
Cultural sensitivity non-existent - integral

While these dimensions rather represent a framework for comparative analysis, this table also can be use to think about the design of a pedagogical scenario.

Bates choosing

Tony Bates his free online book on Teaching in a Digital Age: Guidelines for Designing Teaching and Learning presented a short table that is based on five criteria: Epistemological basis, industrial vs. digital skills (20st vs. 21st century ones), academic quality, and flexibility.

Bates (2015) Choosing design models (CC BY NC SA license)

According to learning style

The idea is that different pedagogies are better adapted to individuals preferences for given learning styles.

See the learning style article.

Major families according to learning theoretical considerations


This needs to be completed, my plan is make short summaries for each and then point to instructional design models (as shown with a few examples below) - DSchneider 19:32, 22 May 2006 (MEST)

Behaviorist strategies

Cognitivist strategies

Cognitivist/Constructivist strategies

Constructivist/Situated strategies


  • Allen (1996), Instructional Models Key, HTML.
  • Conaway, J. (1997) Educational technologies effect on models of instruction. University of Delaware. HTML, retrieved 15:45, 11 August 2007 (MEST). A good and short overview of instructional models.
  • Huitt, W. (2003). Classroom instruction. Educational Psychology Interactive. Valdosta, GA: Valdosta State University. Retrieved 19:24, 22 May 2006 (MEST), from (This is an excellent resource for classroom instruction / direct instruction).
  • Models of Teaching, College of Education and Human Development, UTSA. (Good resources for educators who are interested in approaches to and models of teaching)


  • Baumgartner, P., I. Bergner und L. Pullich (2004). Weblogs in Education - A Means for Organisational Change. In: Multimedia Applications in Education Conference (MApEC) Proceedings 2004. L. Zimmermann. Graz: 155-166. PDF
  • Baumgartner, P. (2004). The Zen Art of Teaching - Communication and Interactions in eEducation. Proceedings of the International Workshop ICL2004, Villach / Austria 29 September-1 October 2004, Villach, Kassel University Press. CD-ROM, ISBN: 3-89958-089-3. PDF
  • Berman, P., and McLaughlin, M. (1978). Federal programs supporting education change. A model of education change, Vol. VIII: Implementing and sustaining innovations. Santa Monica, CA: Rand.
  • Cooley, W. W., and Lohnes, P. R. (1976). Evaluation research in education. New York: Irvington.
  • Chamberland, G., L. Lavoie et D. Marquis (1995). 20 formules pédagogiques, Sainte-Foy: Presses universitaires du Québec.
  • Clark, Ruth (1998). Building Expertise: Cognitive Methods for Training and Performance Improvement. Washington D.C.: International Society for Performance Improvement.
  • Derry, S. J., & Steinkuehler, C. A. (2003). Cognitive and situative theories of learning and instruction. In L. Nadel (Ed.), Encyclopedia of cognitive science (pp. 800–805). London, UK: Nature Publishing Group.
  • Dillon, J.T. Using diverse styles of teaching, HTML (retrieved 19:24, 22 May 2006 (MEST))
  • Flagg, B. N. (1990). Formative evaluation for educational technologies. Hillsdale, NJ: Lawrence Erlbaum.
  • Greeno, J., Collins, A., & Resnick, L. (1996). Cognition and learning. In R. Calfee & D. Berliner (Eds.), Handbook of educational psychology (pp. 15–46). New York, NY: MacMillan.
  • Kahn, Badrul H. A Framework for Web-Based Learning, in Khan, B.H. (ed) Web-Based Training ISBN 0-87778-303-9
  • Mafune, Patricia, Teaching and Learning Models HTML (retrieved 19:24, 22 May 2006 (MEST) ).
  • Hassard, Jack, 2004, The Art of Teaching Science, Oxford Univesity Press.
  • Hassard, Jack, 2005, The Art of Teaching Science, Syllabus Helpers and Agenda Strategies to support the "Art of Teaching Science" book. HTML
  • Hassard, Jack, 2000, Minds ON Science Online, A Web Course on Teaching Science, Georgia State, [1] (this is a very nice on-line open access book on learning theory and models of science teaching).
  • Hassard, Jack, Using the Internet As An Effective Science Teaching Tool, HTML
  • Merrill, M. D. (2002). Instructional strategies and learning styles: which takes precedence? In R. A. Reiser & J. V. Dempsey (Eds.), Trends and Issues in Instructional Technology. (pp. 99-106). Columbus, OH: Prentice Hall. PDF Preprint
  • Séminaire sur les méthodes d'enseignement (1999) La didactique internationale en management public [2]
  • Joyce, B., Weil, M., Calhoun, E. : (2000). Models of teaching, 6th edition, Allyn & Bacon, 2000. ISBN 0205389279
  • Joyce, B., & Weil, M., & Calhoun, E. (2003). Models of teaching (7th ed.). Englewood Cliffs, NJ: Prentice-Hall.
  • Philips, Rob (1998). Models of learning appropriate to educational applications of information technology, eaching and Learning Forum, held at the University of Western Australia. HTML
  • Reeves, Tom, C. (1997). Evaluating What Really Matters in Computer-Based Education HTML, HTML - HTML copy
  • Reeves, T. C. (1993). Pseudoscience in computer-based instruction: The case of learner control research. Journal of Computer-Based Instruction, 20(2), 39-46.
  • Reeves, T. C. (1992a). Evaluating schools infused with technology. Education and Urban Society Journal, 24(4), 519-534.
  • Reeves, T. C. (1992b, September). Effective dimensions of interactive learning systems. Invited keynote paper presented at the Information Technology for Training and Education (ITTE `92) Conference, Queensland, Australia.
  • Reeves, T.C., Reeves, P.M., (1997b) Effective Dimensions of Interactive Learning on the World Wide Web, in B Khan (Ed.), Web-Based Instruction, Englewood Cliffs N.J. : Educational Technology Publications, 59-66).
  • Scriven, M. (1993). Hard-won lessons in program evaluation. San Francisco, CA: Jossey-Bass.
  • Van Wart, Montgomery, N. Joseph Cayer, et Steeve Cook; Handbook of Training and Developement for the Public Sector; San Francisco, CA; Jossey-Bass; 1993
  • Weston, C., & Cranton, P. A.. (1986). Selecting Instructional Strategies. The Journal of Higher Education, 57(3), 259–288.

(need some more)--------


Content of this article has been taken from EduTechWiki (en) or EduTechWiki (fr) at the date indicated in the history. DKS was the main founder and main contributor of EduTechWiki. If you cite this page you also must cite and credit EduTechWiki, according to the CC BY-NC-SA license. View the pageinfo-toolboxlink for this article.