Course Identification

Throughout the 20th century, several revolutions took place in the way of the scientific perception of the learning process. The course will follow the development of the various learning theories, emphasizing their application in science and mathematics educational research and teaching practice.

These theories can be grouped under three main theoretical approaches to cognition, learning and instruction in mathematics and science. These include: Behaviorism, cognitive and socio-cultural approaches.

Within the Behaviorist approach we discuss Skinner's stimulus- response theory, and Gange's perspective on the pre-conditions needed for learning .

Within the Cognitive approach we discuss Piaget's theory of intellectual development and principles of cognitive structure organization - the basis of constructivism, and Karplu's ideas on how to apply Piaget's theory in instructional design; Bruner's theory about the three ways student represent learning tasks and his  ideas on how to design an environment that supports learning.  Ausubel's theory of meaningful verbal learning and its application within knowledge integration instructional design framework; Driver's theory on children's alternative frameworks in science and Posner's ideas on how to design instruction based on this perspective. Some examples from mathematics and science education research  demonstrating children's alternative framework will be demonstrated. Finally, diSessa's theory of  knowledge in transition will be presented .

Within the Socio-Cultural approach we include Vygotsky's theory of learning, the neo-vygotskian addenda, the cognitive apprenticeship model and references to situated learning. Within this approach differences between novices and experts in mathematical problem solving and complex systems understanding and their implications to teaching and learning will be discussed. 

As a routine, in parallel to the lectures students will read original articles written by the theory developers and and will work with a peer to design a lesson plan or a learning activity in line with the a learning theory. The student will choose 3 theories out of those learned in the course. 

In the final assignment each student will choose a key concept / skill from science or mathematics curriculum and design three lessons plans for teaching it  in class, based on principles of a theory from each one of the approaches learned in the course. The students will also analyze the three lesson designs with regard to their possibilities and limits in teaching this key  concept / skill.

Upon successful completion of the course- students should be able to:

1. Describe the main theoretical approaches to cognition, learning and instruction in mathematics and science and how they are related to their practice.
2. Describe the instructional design principles suggested by educational researchers to apply Skinner's, Piaget's, and Vygotsky's theories in the classroom.
3. Design instructional activities based on these principles.
4. Analyze possibilities and limits of each approach in teaching a certain concept / skill.

1. Burrhus F. Skinner (1968). The Technology of Teaching, chapter 2.
2. Benjamin S. Bloom (1956). Taxonomy of Educational Objectives , Handbook I: Cognitive Domain, chapter 1.
3. Robert M. Gagne (1970). “Some New Views of Learning and Instruction”. Phi Delta Kappa, 51, 468-472.
4.  H. Ginsburg & S. Opper (1969). Piaget’s Theory of Intellectual Development – An Introduction, 13-25.
5. Robert Karplus (1977). “Science Teaching and the Development of Reasoning”. J. Res. Sci. Teaching, 14, 169-175.
6. Jerome S. Bruner (1974). Toward a Theory of Instruction, 54-72.
7. David P. Ausubel (1967). Learning Theory and Classroom Practice, 17-27.
8. Novak, J. D. (2010). Ausubel's assimilation learning theory, Learning, Creating, and Using Knowledge: Concept Maps as Facilitative Tools in Schools and Corporations (2nd ed., pp. 56-89). New York: Routledge.
9. Linn, M. C., & Eylon, B. S. (2006). Science education: Integrating views of learning and instruction. In P. A. Alexander & P. H.Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 511–544). Mahwah, NJ: Lawrence Erlbaum Associates.
10. Rosalind Driver (1981). “Pupils’ Alternative Frameworks in Science”, Eur. J. Sci. Educ., 3, 93-101
11. Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: toward a theory of conceptual change. Science Education, 66(2), 211-227.
12. Clement, J. (1982). Algebra word problem solutions: Thought processes underlying a common misconception. Journal for Research in Mathematics Education, 13(1), 16-30.
13. McCloskey, M. (1983). Naive theories of motion. In A. L. Stevens (Ed.), Mental Models (pp. 299-324). Hillsdale, NJ: Lawrence Erlbaum Associates.
14. Ben-Zvi, R., Eylon, B., & Silberstein, J. (1986). Is an atom of copper malleable? Journal of Chemical Education, 63(1), 64-66.
15. Smith, J. P. I., diSessa, A. A., & Roschelle, J. (1993). Misconceptions reconcieved: A constructivist analysis of knowledge in transition. The Journal of the Learning of Sciences, 3(2), 115-163.
16. Lev S. Vygotsky (1980). Mind in Society, chapters 4 & 6.
17. Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, Learning, and Instruction: Essays in Honor of Robert Glaser (pp. 453-493). Hillsdale, NJ: L.E.A.
18. Moschkovich, J. N. (2004). Appropriating mathematical practices: A case study of learning to use and explore functions through interaction with a tutor. Educational Studies in Mathematics, 55, 49-80.
19. Schoenfeld, A. H. (1985). A framework for the analysis of mathematical behaviour, Mathematical Problem Solving (pp. 11-45). Orlando, FL: Academic Press, Inc. Harcourt Brace Jovanovich, Pub.
20. Hmelo?Silver, C. E., & Pfeffer, M. G. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive science, 28(1), 127-138.‏
21. Greeno, J. G., Collins, A. M., & Resnick, L. B. (1996). Cognition and learning. In D. C. Berliner & R.