This paper explores the theoretical foundations of “constructivism” and “socio-constructivism” which underlie the conception of inquiry-based science teaching. The proposed synthesis aims at disentangling the multiple sources of influence of this approach in science education, which come from the field of psychology of cognitive development, on the one side, and from that of epistemology, on the other. The goal of this paper is also to make explicit what is assumed to be “constructed” by the students during such a teaching, according to the authors under study.

Key words: cognitive psychology, constructivism, epistemology, socio-constructivism

This paper aims at shedding light on what students can “construct” when they learn science and how this construction process may be supported. Constructivism is a pluralist theory of science education. As a consequence, I support, there are several points of view concerning this construction process. Firstly, I stress that constructivism is rooted in two fields, psychology of cognitive development and epistemology, which leads to two ways of describing the construction process: either as a process of enrichment and/or reorganization of the cognitive structures at the mental level, or as a process of building or development of models or theories at the symbolic level. Secondly, I argue that the usual distinction between “personal constructivism” (PC) and “social constructivism” (SC) originates in a difference of model of reference: the one of PC is Piaget’s description of “spontaneous” concepts, assumed to be constructed by students on their own when interacting with their material environment, the one of SC is Vygotsky’s description of scientific concepts, assumed to be introduced by the teacher by means of verbal communication. Thirdly, I support the idea that, within SC, there are in fact two trends: one, in line with Piaget’s work, demonstrates how cooperation among students affects the development of each individual’s cognitive structures; the other, in line with Vygotsky’s work, claims that students can understand and master new models only if they are introduced to the scientific culture by their teacher. Fourthly, I draw attention to the process of “problem construction” identified by some French authors. Finally, I advocate for an integrated approach in science education, taking into account all the facets of science learning and teaching mentioned above and emphasizing their differences as well as their interrelations. Some suggestions intended to improve the efficiency of science teaching are made.

Key words: science learning science teaching, personal constructivism, social constructivism, cooperation, enculturation, problem construction.

Radical constructivism grows out of the belief that knowledge is constructed and legitimated by individuals as they make sense of their experiences in particular contexts and drawing on their own histories. Extending this understanding of learning and ways of knowing to girls as they work in the terrain of science, we argue that honoring student experience as the starting place for science instruction fundamentally alters the nature of science, the purpose of teaching and learning science, and the focus of relationships in science class. The implications for this position are extensive: they suggest that the dynamic relationships between language and cultural background of students and teachers alter the ways in which science education historically has enacted discipline, curriculum and pedagogy. We argue that this is particularly important to understand, for science and science education have historically operated within the masculine domain and working with girls in science in ways that respect their (gendered and cultural) construction of knowledge and their experiences, fundamentally alters the enterprise of science – an idea contradictory to most visions of the purposes of education and current reform efforts in science education, even the most liberal.

Constructivism is an important theory of learning that is used to guide the development of new teaching methods, particularly in science education. However, because it is a theory of learning and not of teaching, constructivism is often either misused or misunderstood. Here we describe the four essential features of constructivism: eliciting prior knowledge, creating cognitive dissonance, application of new knowledge with feedback, and reflection on learning. We then use the criteria we developed to evaluate five representative published articles that claim to describe and test constructivist teaching methods. Of these five articles, we demonstrate that three do not adhere to the constructivist criteria, whereas two provide strong examples of how constructivism can be employed as a teaching method. We suggest that application of the four essential criteria will be a useful tool for all professional educators who plan to implement or evaluate constructivist teaching methods.

Discusses the research findings of two Learning in Science Projects (LISP) and their influence on the new science syllabus. Considers the extent to which syllabus is based on a constructivist view of learning and refers to the aims of science education.

Constructivism is a theory of learning, which claims that students construct knowledge rather than merely receive and store knowledge transmitted by the teacher. Constructivism has been extremely influential in science and mathematics education, but much less so in computer science education (CSE). This paper surveys constructivism in the context of CSE, and shows how the theory can supply a theoretical basis for debating issues and evaluating proposals. An analysis of constructivism in computer science education leads to two claims: (a) students do not have an effective model of a computer, and (b) computers form an accessible ontological reality. The conclusions from these claims are that: (a) models must be explicitly taught, (b) models must be taught before abstractions, and (c) the seductive reality of the computer must not be allowed to supplant construction of models.

Key words: computer science education, dominant theory, idiosyncratic version, accessible ontological reality, ective model, theoretical basis, seductive reality, store knowledge, mathematics education

Excerpt: Since World War II, mathematics and science education have been high on the educational reform agenda in many countries, including the United States. […] In this chapter, I wish to suggest some ways to reframe this conception of reform in science education. These ways are at one time theoretical and empirical – that is, rooted in the constructivist perspective and in The Professional Practice Community (PPC), a grassroots model for collaboration that may be a constructivist medium to foster educational reform even in the present era of national standards. This model may offer effective structures not only for “valuing questions and ideas” in relation to the usual beliefs on cognition, learning, and teaching, but also for providing a network to support risk taking and change. But before that, some comments on the current U. S. reform project.

Expressions like “constructivism,” “construction of knowledge,” “learners construct meaning,” and similar ones are starting to become part of the language of science education. We are liable to hear them in professional meetings or inservice workshops and to read them in articles in the professional journals. As the term constructivism becomes more widespread, different people tend to use it with slightly different meanings, and some use it in a loose way to designate a complex of different pedagogical, psychological, or philosophical tendencies. (The ideas about constructivism explained in this chapter are in no way to be taken as an attempt to define the “orthodoxy” of constructivism. Consistent with a constructivist view, they are simply a model of what it means to know. The claim of this model is to be a viable view of knowledge. This chapter aims at presenting the model and exploring from there some relations with teaching and learning of science.) These tendencies seem to have in common the central assumption that all we come to know is our own construction.

The merits of Empirical Modelling (EM) principles and tools as a constructivist approach to computer science education are illustrated with reference to ways in which they have been used in teaching topics related to the standard computer science curriculum. The products of EM are interactive models – construals – that serve a sense-making role. Model-building proceeds in an incremental fashion through the construction of networks of definitions that reflect the observables, dependencies and agents associated with a current situation. The three principal case studies discussed (teaching bubblesort, solving Sudoku puzzles, and recognising groups from their abstract multiplication tables) highlight respects in which EM accounts for aspects of computing that cannot be effectively addressed by thinking primarily in terms of abstractions, procedures and mechanisms. The discussion of EM as a constructivist approach to computer science education is set in the context of an analysis of constructivism in computer science published by Ben-Ari in 2001. Reconciling EM’s constructivist epistemology with this analysis involves recognising its pretensions to a broader view of computer science.

This work discusses the affordances of the textbook in current classroom scenarios, and identifies the need to design learning media that support dynamism and enaction, specifically in science education. We illustrate this by a learning tool we’ve developed – Vector canvas, an AR based application linked with the textbook and the curricula. This is a work in progress attempting to observe and articulate changes in learning practice brought by introducing mixed media.

Key words: ar, mixed media, dynamic systems, enaction, science education