completely specify the enacted object of learning or the students' courses of action in the labs. ... MBL at university level introductory courses in mechanics.
Paper to be presented at ESERA2003, August 19 – 23, 2003, Noordwijkerhout, The Netherlands.
Approaching Discovery Learning Jonte Bernhard ITN, Campus Norrköping, Linköping University, S-601 74 Norrköping, Sweden Oskar Lindwall Dep. of Communication, Linköping University, S-581 83 Linköping, Sweden ABSTRACT In previous studies, we have showed that the teacher’s formulation of tasks in Microcomputer-based laboratories (MBL) is decisive for the students’ understanding. However, it is never possible to completely specify the enacted object of learning or the students’ courses of action in the labs. In this study, we have used videotaped material to investigate how students orient to, interpret, and participate in MBL. Although all students used the same technology and participated in the same tasks, they solved these tasks in quite different ways. The courses of action, taken by the students, could broadly be divided in three categories: (a) Sometimes the relation between different phenomena and their representations were the centre of attention. (b) At other times, most of the students’ attention were directed towards the production of good lab reports; (c) At still other times, the students tried to solve the tasks with the least effort possible, using strategies disconnected from both the representations and the phenomena. Although students’ different orientations were creating differences between groups, they were not stable over time. Certain encounters with the instructions, the technology, the teacher, and other peers, made an orientation towards understanding phenomena and representations prominent most of the times.
INTRODUCTION In science education, reformed curricula and teaching methods often involves the implementation of some kind of “discovery learning”. Other terms to label and characterise such approaches include “interactive engagement” (Hake 1997) and “guided discovery” (Novak 1979). One popular way of implementing discovery learning approaches is to use Microcomputer-Based Labs (MBL). The MBL technology is based on a sensor (measuring force, motion, temperature, light, sound, EKG etc.) attached to a computer that visualises the collected data. In earlier studies we have investigated students’ learning results after participating in MBL at university level introductory courses in mechanics. In accordance with other studies (For example Tinker 1996, Thornton 1997 and Hake 1997), we have showed that the students’ results increased dramatically after participation in these labs (Bernhard 2000, 2001 and 2003). Furthermore, we have showed that it is important to frame the lab in terms of discovery learning. In a previous study (Bernhard 2003), the way teachers approached the learning environment and curricula are discussed. It is showed that the perceptions and judgments of teachers sometimes transformed these labs into traditional “formula-verification” or “cookbook” labs. When such an approach was taken, the students did not perform as well on conceptual tests. Thus, If the teacher create instructions apply teaching strategies in line with “guided discovery” approach the students will get better results than if the teacher takes a “cookbook approach”. However, it is never possible for the teacher to completely specify the enacted object of learning or the students’ courses of action in the labs. This has raised an interest for the four interrelated questions presented below. •
In which different ways do the students approach the learning environment?
• • •
How do the different approaches influence the students enacted learning objects? Which aspects of the learning environment turn the students toward the intended object of learning? How can we further develop these aspects?
METHODS In two different introductory mechanics courses (one for teacher students and one for engineering students), the interaction of 16 lab-groups was recorded using digital camcorders. The data, resulting in 260 hours of videotaped interaction, were used to detect typical interactional patterns and find evidence of, or to reject hypotheses on, the generality of these patterns (Jordan and Henderson 1995). Initially, very preliminary hypotheses guided the search for regularities in the participants’ interaction. After repeated viewings, some of the sessions were found to contain more interesting and comparable sections. Particularly interesting parts of these sessions were transcribed to allow for detailed examination of interactional patterns. RESULTS The approaches – constituted by different lines of actions, differences in what was made central, differences in which resources that were used, and differences in what counted as completing the lab – could broadly be divided in three categories: • • •
Conceptual orientation. The relation between different phenomena and their representations were the centre of attention, creating an activity in line with the intention of the teacher. Cook-book orientation. The attention was directed towards the production of “good” (nice looking) lab reports and finding the “right” answer. Reproducing orientation. The students tried to solve the tasks with the least effort possible, using strategies disconnected from both the representations and the phenomena.
The differences could be seen in several parts of the students problem-solving activity. For example, the groups differed in what was regarded as a nice looking graph. For some groups, a nice looking graph was a graph with no conceptual errors. For these students it was not that important that the graph exactly resembled the predefined one as long as they could make a qualitative interpretation of the graph. Other groups were more pre-occupied with making graphs that quantitatively resembled the pre-defined one. These groups might choose to hand in a graph to the teacher, which had some conceptual errors but which looked more like the predefined one. Still other groups, were not interested in producing nice looking graphs at all, but rather to find a way of finishing the assignments in the shortest time possible. However, after a few assignments, most of the students took a conceptual approach toward the activity. We observed that certain encounters with instructions, technology, teacher, other peers, made an orientation toward meaning prominent. It is not possibly to describe all these encounters in full detail in this synopsis but some aspects of these are described below: The instructions framed the activity through open-ended questions but specified the process (predict – observe – explain) in such a way that students have to deal with certain concepts in certain ways. The technology gave immediate feedback and students could literary see when they make mistakes. It also made use of multiple representations and resources and
highlighted critical conceptual distinctions. The teacher framed the activity through “scaffolding” and elicited student knowledge and helped students to shift focus to central aspects of the activity. Finally in peer discussions the students upheld a common orientation toward the graph and different interpretations were negotiated by the students making argumentation important in the process of solving the task. Thus, the students’ different orientations, although creating differences between groups, were not stable over time. CONCLUSIONS AND IMPLICATIONS As pointed out above our curricula frames the tasks in such a way that a conceptual approach is almost a requirement for solving the tasks successfully. The documented success of certain curricula using MBL, may be understood from this design. Our material also shows the importance of the teacher in this technology rich learning environment. The teachers acts in two different ways: Indirectly by the formulation of tasks in the lab instructions and the choice and appropriate use of technology and by facilitating peer interaction but also directly by appropriate interventions. Finally our material shows, in contrast to what others have proposed, that these “orientations” are not an inherent “property” of different students, but something they display at a certain time under certain circumstances and thus are possible to affect with proper interventions. BIBLIOGRAPHY Bernhard J, 2000, Teaching engineering mechanics courses using active engagement methods, In Pacher P and Pipek J (eds) Proceedings of PTEE2000, Budapest 13 - 17 June, 2000. Bernhard J, 2001, Does active engagement curricula give long-lived conceptual understanding? In Pinto R and Surinach S (eds) Physics Teacher Education Beyond 2000, p 749 – 752, Paris: Elsevier. Bernhard J, 2003, Physics learning and microcomputer based laboratory (MBL): learning effects of using MBL as a technological and as a cognitive tool. In Psillos D et al (eds) Science Education Research in the Knowledge Based Society, p 313 – 321, Dordrecht: Kluwer Academic Publishers. Hake R, 1997, Interactive-engagement vs traditional methods: A six-thousandstudent survey of mechanics test data for introductory physics courses. Am J Physics, 66, 64–74. Hammer D, 1997, Discovery learning and discovery teaching, Cognition and Instruction, 15, 485-529. Jordan B, and Henderson A, 1995, Interaction analysis: foundations and practice. The Journal of the Learning Sciences, 4, 39-103. Laws P, 1997, Workshop Physics Activity Guide, New York: Wiley. Sokoloff D, Thornton R, and Laws P, 1998, RealTime Physics, active learning laboratories, New York: Wiley. Novak J, 1979, The reception learning paradigm, J Res Sci Teach, 16, 481-88. Thornton R, 1997, Learning Physics Concepts in the Introductory Course: Microcomputer-based Labs and Interactive Lecture Demonstrations, in Wilson J (ed.) Proc Conf on Intro Physics Course, p 69–86, New York: Wiley. Tinker R F (ed.), 1996, Microcomputer-Based Labs: Educational Research and Standards. NATO ASI Series F vol 156, Berlin: Springer.
