Thursday, October 10, 2019

Inquiry learning Essay

Introduction Discovery learning or Inquiry Learning has a long history in education and has regained popularity over the last decade as a result of changes in the field of education that put more emphasis on the role of the learner in the learning process. Zachos, Hick, Doane, and Sargent define discovery learning as â€Å"the self-attained grasp of a phenomenon through building and testing concepts as a result of inquiry of the phenomenon. † The definition emphasizes that it is the learner who builds concepts, that the concepts need to be tested, and that building and testing of concepts are part of the inquiry of the phenomenon. Computer simulations have rich potential to provide learners with opportunities to build and test concepts, and learning with these computer simulations is also referred to as simulation-based discovery learning (Lester, Vicari, & Paraguacu, 2004). Students engaged in discussions – raising questions, resting ideas, challenging each other’s assertions – is at the heart of inquiry learning. Such discussions enable students to go beyond hands-on activities to interpret and reflect on their experiences and develop new ways of thinking. Reflecting their understanding of inquiry learning, the originators of network science aimed to have students in distant classrooms use the network to discuss science with one another like collaborating scientists (Feldman, 2000). Literature Review The main goal of discovery learning activity is to obtain and/or construct knowledge about a domain by performing experiments and inferring rules and properties of the domain from the results of those experiments. Research on discovery learning has shown that learners can experience a range of problems that can prevent successful learning. Discovery learning requires learners to act in the same manner as scientist when discovering the properties and relations of the domain that is simulated, using processes that are very similar to the processes of scientific discovery. Learners need to generate hypotheses, design experiments, predict their outcome, interpret data and reconsider hypotheses in order to construct knowledge about the domain. With each of these learning processes, problems can arise. Learners can fail to state testable hypotheses, design uninformative experiments or interpret experimental results badly (Gauthier, Frasson, & VanLehn, 2000). In order to make discovery learning successful, learners can be supported from within the learning environment. The learning environment can contain cognitive tools that can be directed at the support of one or more learning processes. Cognitive tools can offer support to the learner in several ways of support, creating a learning dialogue between the learning environment and the learner and at establishing the conditions under which profitable learning processes takes place. Cognitive tools play a role in supporting and provoking these learning processes (Gauthier et al. , 2000; McTighe & Wiggins, 2005). Like in discovery learning, the idea of simulation-based discovery learning is that the learner actively engages in a process. In an unguided simulation-based discovery environment learners have to set their own learning goals. At the same time they have to find and apply the methods that help to achieve these goals, which is not always easy. Two main goals can be associated with simulation-based discovery learning; development of knowledge about the domain of discovery, and development of skills that facilitate development of knowledge about the domain (Lester, Vicari, & Paraguacu, 2004). Those who read Guthrie, Cornford, Allen, and Bluck, among others, will find there what we might call the â€Å"traditional view. † According to this view, the paradox is a dilemma about one’s epistemic resources at the outset of inquiry and the role those resources play at the inquiry’s conclusion. The alternatives that the dilemma proposes are beginning with 1) total, explicit knowledge or 2) absolute ignorance. The doctrine of recollection provides the solution with its proposal that all inquiry begins with something intermediate between 1) and 2): latent, unconscious, or implicit knowledge. When these commentators speak of â€Å"total knowledge,† they seem to have in mind â€Å"self-consciously clear† or â€Å"conscious† knowledge (Anton & Preus, 1989). There are three points to be borne in mind in any discussion on learning by discovery. First, what is involved primarily is the learning of facts, concepts and principles rather than skills, techniques or sensitivities; and the subjects most relevant to discovery learning are mathematics, science and environmental studies. Second, it is usually associated with the traditional classroom, and third learning by discovery does not just happen; it comes about as a result of a particular teaching method or strategy. Numerous strategies can be distinguished in this connection; perhaps the most common one to be found is that of guided discovery (Manion, Morrison, & Cohen, 2004). Discovery or Inquiry must ultimately in the history of the race precede instruction; for if it’s this teacher who teaches from someone else who learned it from another teacher that cannot go back indefinitely. Somewhere in the knowledge that we pass on in the process of teaching, someone must have discovered it for himself. so we see, first of all, that learning by discovery is primary (Loucks-Horsley & Olson, 2000). Learning by instruction is secondary. And if this is so then we also see that teachers are, in an absolute sense, dispensable. For nothings which can be learned by instruction with teachers is impossible to learn without teachers. I don’t mean teachers aren’t useful; they are. For most of us would not be able to learn without the help of teachers or learn as rapidly or learn as easily the things we have to come to know in the course of our lifetime. But I do not mean that teachers are only helps. And this understanding of the teacher as an aid, as something which helps in the process of learning, is the deepest insight into the nature of teaching in relation to learning (Adler, 2000). Learning by instruction, learning with the help of teachers is no less active than learning by discovery or inquiry. Perhaps it would be better then, instead of saying learning by instruction and learning by discovery, to call them both learning by discovery; learning with a teacher as â€Å"aided discovery† and learning without a teacher, as â€Å"unaided discovery (Adler, 2000). Analysis Many network science projects have not lived up to their potential to involve students in productive inquiry. Firstly, the network science model of curriculum typically constraints classrooms by imposing rigid schedules for data submission and exchanges. The low level of completion for many network science projects – which, was less than 50% of classes in one project submitting data – may reflect teacher’s inability to fit the real lives of their classrooms, punctuated by school events and holidays and snowstorms, into the schedule demands of many network science projects (Feldman, 2000). Aiming to coordinate work among classes, many network science projects are constrained by centralized schedules. To refocus science learning on inquiry, teachers and students need flexible schedules to allow questions to be pursued in greater depth. Without such flexibility, the potential of the curriculum to support student inquiry is greatly diminished (Feldman, 2000). Secondly, network science encourages the use of scientific and social problems to spark learning, focusing on the importance of investigating questions for which the answer is not known. However, this emphasis on questions for which the answer is not known and the questions are of genuine interest to scientists excludes the possibility of students investigating concepts that may be well known to scientist but no longer of interest to them. Because such concepts are still unknown to students and potentially of great interest, they offer a scientific excursion through which students can reliably have successful and powerful learning experiences. For example, students might investigate phenomena as simple as why some objects float – a topic that is unlikely to be of any interest to scientists (Feldman, 2000). Inquiry learning, under appropriate conditions, is highly desirable; an elaborate pattern of ideas must be built up in a child’s head and only the child can built it; it is the teacher’s job to help the child to build up this elaborate structure of interrelated ideas, and to help the child correct the structure of interrelated ideas, and to help the child correct the structure whenever it is found to be in error (Solomon, 1988). By means of discovery learning we may reasonably expect children to learn something new; and to do so through some initiative of their own. Moreover, a teacher supports a child’s self-chosen activity with questions, commentary and suggestions (Manion et al. , 2004). Conclusion In this paper, we presented a view on combining collaborative learning and the discovery learning. The aim was to show how we can benefit from theoretical knowledge on discovery learning to enhance the added value that collaboration can have and, vice versa, how collaboration in itself can serve as support for the processes of discovery that learners can engage in. Mutual gain can be created from combining collaborative and discovery learning by increasing the mutual awareness in tools supporting either type of learning. Adding knowledge about discovery to collaborative tools can enhance collaborative tools to adapt themselves or give feedback on their contents. On the other hand, collaborative processes take the role of cognitive tools for discovery learning in making learning processes explicit. Of course the examples given in the paper are only a small part of what become possible combining two powerful paradigms of learning (Gauthier et al., 2000). In the latter part of the paper we show how a theory of discovery learning can help to design architecture for communicative support for discovery learning. A central place is taken by a common frame of reference that supports the communication between the different components in the architecture (Gauthier et al. , 2000). References: Adler, M. J. (2000). How to Think About the Great Ideas: From the Great Books of Western Civilization. Chicago and La Salle: Open Court Publishing. Anton, J. P. , & Preus, A. (1989). Essays in Ancient Greek Philosophy: Plato. New York: SUNY Press. Feldman, A. (2000). Network Science, a Decade Later: The Internet and Classroom Learning. Mahwah, New Jersey: Lawrence Erlbaum Associates. Gauthier, G. , Frasson, C. , & VanLehn, K. (2000). Intelligent Tutoring Systems. Germany: Springer. Lester, J. C. , Vicari, R. M. , & Paraguacu, F. (2004). Intelligent Tutoring Systems. Berlin Heidelberg, NY: Springer. Loucks-Horsley, S. , & Olson, S. (2000). Inquiry and the National Science Education Standards: A Guide for Teaching and Learning. Washington DC: National Academies Press. Manion, L. , Morrison, K. R. B. , & Cohen, L. (2004). A Guide to Teaching Practice. London and New York: RoutledgeFalmer. McTighe, J. , & Wiggins, G. P. (2005). Understanding by Design. Virginia USA: Association for Supervision and Curriculum Development. Solomon, C. (1988). Computer Environments for Children: A Reflection on Theories of Learning and Education. Cambridge, Massachusetts; London, England: MIT Press.

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