EFFECTS OF TEACHER INTERVENTION ON LEARNING PROCESSES OF PRIMARY SCHOOL STUDENTS IN PHYSICS

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1 EFFECTS OF TEACHER INTERVENTION ON LEARNING PROCESSES OF PRIMARY SCHOOL STUDENTS IN PHYSICS Andreas Trautmann¹ and Alexander Kauertz¹ ¹ University of Koblenz-Landau, Germany Abstract: In science education a typical learning aim is to solve problems by applying methods of scientific inquiry. Experimental learning environments that follow the idea of self-regulated learning have high potential to reach this aim. We developed an experimental environment for German primary school students (8 to 10 years) which consists of 16 learning tasks on the physical content flying with the aim to initiate a self-regulated scientific problem solving process. From a moderat-constructivistic view the teacher should scaffold students learning in such a learning environment. Therefore the teacher must know how intervention affects a student s learning process. This video-study investigates what kind of teacher intervention helps to establish a reasonable structure in the scientific problem solving process that is necessary for successful learning. Consequently, this study analyzes how the structure of a learning process changes after a teacher intervention. Learning sequences of students and teacher interventions are videotaped and two sets of video-categories and a paper-pencil test are applied. First results of the video-analysis indicate students problems finding explanations for their hypothesis and controlling a variable. Keywords: scientific problem-solving, experimental learning environment, videoanalysis, teacher intervention SUBJECT This study focuses on the effects of teacher intervention on the learning processes of 3 rd and 4 th grade students in an experimental learning environment. An experimental learning environment with 16 experimental tasks on the topic flying was created for students in 3 rd and 4 th grade. This experimental environment is slightly pre-structured and the students work in a scientific problem solving process. Each task defines a research problem adequate for the primary school students and provides some basic information and materials to conduct small and partially hands-on experiments. Consequently, the students need to structure their work whilst doing experimental work and communicating with each other to find an appropriate solution for the problem. The teacher is asked to support students if necessary. In science education a typical learning aim is to solve problems by using methods of scientific inquiry (Klahr, 2000; Lederman et al., 2012). This method of scientific problem-solving contains four aspects: perceiving or clarifying the problem, hypothesizing, planning and conducting a scientific experiment, and using results for testing the hypothesis (c.f Klahr, 2000; Hammann, Phan & Bayrhuber, 2007). Each of these aspects has to occur in a successful process to foster problemsolving abilities (Oser & Baeriswyl, 2001). Each aspect is operationalized by more detailed process elements (see table 1). Depending on their previous knowledge and abilities students are challenged differently by working systematically and strategically on poorly structured tasks (de Jong & van Joolingen, 1998). Possible

2 problems are caused by the need to set aims, plan, monitor, and evaluate, which require meta-cognitive activities (Wirth, Thillmann, Künsting et al., 2008). As a result, elements of scientific problem-solving are lacking if the students fail in applying these meta-cognitive acitivities. Table 1 Aspects and elements of the scientific problem-solving process (c.f. Heine, Trautmann & Kauertz, in print) Scientific aspects Problem perception 1 Perceiving problem Elements of the scientific problem-solving process Search hypothesis space 2 Activating previous knowledge 3 Making explanation based on elements of real context 4 Finding analogies 5 Making explanation based on elements of laboratory context 6 Generating hypothesis Test hypothesis 7 Varying independent variable Evaluate evidence 8 Controlling a variable 9 Collecting Data 10 Analyzing data 11 Concluding in laboratory context 12 Concluding in real context This experimental learning environment allows for many options to start and work on the task. Consequently self-regulation is necessary for effective learning (Weinert, 1982). Therefore, the students have to decide which aspects of the problem solving process they should attempt to apply (or none of them). The sequence of the aspects we call the structure of their learning process with the aim of problem solving. Few similar suggestions for appropriate structures could be found in literature (Oser & Baeriswyl, 2001; Klahr, 2000). Oser and Beariswyl (2001) provide an overview of several studies demonstrating that an appropriate structure is necessary for successful learning processes. Students often have problems in working systematically and strategically on such unstructured tasks (de Jong & van Joolingen, 1998). The problems are caused by the need to set aims, plan, monitor, and evaluate which require metacognitive activities (Wirth, Thillmann, Künsting et al., 2008). Therefore students will benefit from teacher scaffolding in order to apply metacognitive strategies (Simons & Klein, 2006). The specific needs of a student for support depend on his capability and his learning situation (Simons & Klein, 2006). Teacher support can be defined as the interaction between teacher and student aiming to achieve successful learning processes (Seidel, 2011). Teacher intervention includes organizational support, evaluating the students learning progress, providing feedback on students work, and giving hints and explanations (Krammer, Reusser & Pauli,

3 2010). In addition to the availability, the support also must be adapted to the needs of the learner (Littleton & Häkkinen, 1999). As shown above, students could face difficulties applying elements of scientific problem-solving depending on their knowledge and abilities in science during their work on the tasks. Teachers need to address these difficulties in their support. Hence, the research questions are: 1. Which elements of the problem solving process are difficult for students? 2. Which kind of teacher intervention is helpful for students to overcome their difficulties in a scientific problem solving process? DESIGN AND METHODS To measure the variables a test and two sets of video-categories were developed and tested. The main study started in December Test and video-categories are jointly used on a sample of 8 to 10 year old students from 48 courses in primary school to answer the research question. The students work in pairs in the experimental learning environment for six lessons (t = 270 minutes in total). Four pairs of students of each class are videotaped (N videos = 192, N students = 384). Videos of the learning process are taken from two lessons (fourth and fifth lesson in the unit). Instruments Test for students' knowledge and abilities To measure the variables previous knowledge and abilities and growth of knowledge and abilities a paper-pencil-test for students is developed according to similar tests for German schools (Hammann et al., 2007 and Hardy, Kleickmann, Koerber et al., 2010). The test assesses students previous knowledge and abilities about the physical content of the tasks (flying of airplanes, balloons and rockets) and their abilities to identify and name research questions, hypotheses, experiments and conclusions to given descriptions of experimental settings. It is also used to measure the growth of knowledge and abilities after working on the complete unit in the learning environment. The test for students knowledge and abilities (Trautmann & Kauertz, 2013) contains 22 single select items. Data is gathered in a pre-study from N = 210 students from grade three and four (age: 8-10) in primary schools. The data is analyzed by means of the dichotomous Rasch model. All items show a sufficient item fit (.9 < MNSQ < 1.1, T < 2). The reliability is acceptable ( =.78). The mean item difficulty fits the mean of person s parameters. The validity of the test is investigated by using a correlation matrix including a mathematics test (Roick, Gölitz & Hasselhorn, 2004), a literacy test (Küspert & Schneider, 1998) and an additional physics test (Fischer, Möller, Ewerhardy et al., 2009). The partial correlations are shown in table 2.

4 Table 2 Test for knowledge and abilities: correlation matrix (** p <.01) Test for students knowledge and abilities Controlled variables: other physics test mathematics test literacy test.345**.250**.123 mathematics test score; literacy test score other physics test score; literacy test score other physics test score; mathematics test score Video-categories for analyzing the teacher intervention A set of video-categories with three different variables (as shown in figure 1) is developed to measure and to specify interactions of the teacher with the students. In a first step the videos are encoded with variable 1. In a second step only the time frames where the category process or content is assigned are encoded with variable 2 and 3. Figure 1. Video categories "Teacher intervention" Variable 1 consists of three categories. The category Organisation describes interactions of teachers and students only referring on organizational matters for example when a teacher provides the material for an experiment. The category Evaluation describes a teacher s activities to evaluate a student s knowledge or understanding of a task. The category Process or subject matter describes all interactions referring on the problem solving process of students or subject matters. Variable 2 differs between interactions with the focus on student s problem solving process and interactions with the focus on subject matters. Variable 3 differs between cognitive activating interactions where the teacher activates students to think on and transmissive interactions where the teacher directly gives information or instruction to the students. At this time the development and the pilot study of these categories is work in progress.

5 Video-categories for analyzing the completeness of the problem-solving process A set of five video-facets with 24 categories is developed to investigate the structure of the learning process. The main category consists of process elements of the scientific problem solving process based on the structure of the scientific problem solving (Oser & Baeriswyl, 2001; Klahr 2000) (as shown in table 1). In addition to the main facet, the four attendant facets asking for help, organization, off-task and misc are used to incorporate most of students activities. The aim of the video-analysis is to analyze and to rate student learning processes. Therefore videos are analyzed by coding intervals of 5 seconds with the categories showed above. The pilot study showed acceptable intercoder-agreements (.75 к.81) gathering the scientific problem-solving process (Heine et al., in print). For the analysis of the completeness of the learning process this data needs to be edited. For each video it is encoded if a scientific process element is occurring or not. If a process element is occurring anytime in a video it is encoded with 1 and if it isn t occurring it is encoded with 0. The more process elements are occurring in a video the more complete is the problem solving process. Hence, the number of process elements in one video can be used to measure the completeness of a problem solving process. On the other hand this can be used to analyze the difficulty of a process element. If a process element is occurring in almost none of the videos this element seems to be difficult for students. Therefore item difficulty parameters are calculated by using Rasch analysis. ANALYSIS AND FINDINGS First results of the Rasch analysis show an acceptable item fit (.7 < Infit < 1.1) of the process elements except for the process elements perceiving problem and collecting data. Therefore they are excluded from further analyzes. The item parameters give hints for difficulties of students in the problem solving problems (c.f. figure 2): If the item parameter is lower this element seems to be easier for students to apply and if the item parameter is higher it seems to be more difficult. For example, generating a hypothesis is very easy, because most of the students do generate a hypothesis.

6 Figure 2. Item parameters of process elements Item parameter (logit scale) SUMMARY AND OUTLOOK Until now all data is collected. The test for students knowledge and abilities is piloted and analyzed. The video categories for analyzing the teacher intervention need to be evaluated. After that all videos need to be analyzed with these categories. The pilot study for the video-categories for analyzing the completeness of the problem-solving process is done and all the videos are analyzed with these categories. Answering the first research question it seems to be difficult for students to give explanations for the hypothesis and to control a variable. These preliminary findings need to be validated as a next step. With this data correlations between the variables of teacher intervention and the completeness of the problem-solving processes can be calculated to investigate how different kinds of teacher intervention affect problem solving processes. In a second step it is analyzed whether this correlation depends on the previous knowledge of the students. Therefore the sample is divided in a group with higher previous knowledge and a group with lower previous knowledge. The results of those analyses can be used to answer the second research question to show which kind of teacher intervention is helpful for students to overcome their difficulties in a scientific problem solving process. REFERENCES De Jong, T. & van Joolingen, W.R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68, Fischer, H.E., Möller K., Ewerhardy, A., Fricke, K., Kauertz, A., Kleickmann, T., Lange, K. & Ohle, A. (2009). Schülerleistungstest. Internes Papier der

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8 Trautmann, A. & Kauertz, A. (2013). Effekte von Lernbegleitung auf den naturwissenschaftlichen Problemlöseprozess. [Effects of teacher intervention on the scientific problem-solving process] In S. Bernholt (Ed.), Inquiry-based Learning - Forschendes Lernen. Gesellschaft für Didaktik der Chemie und Physik Jahrestagung in Hannover 2012 (pp ). Kiel: Lit. Wirth, J., Thillmann, H., Künsting, J., Fischer, H.E. & Leutner, D. (2008). Das Schülerexperiment im naturwissenschaftlichen Unterricht. [Students experiments in science education.] Zeitschrift für Pädagogik, 54,