Res Sci Educ (2008) 38:127–147 DOI 10.1007/s11165-007-9041-1
Fostering High School Students’ Conceptual Understandings About Seasons: The Design of a Technology-enhanced Learning Environment Ying-Shao Hsu & Hsin-Kai Wu & Fu-Kwun Hwang
Published online: 6 May 2007 # Springer Science + Business Media B.V. 2007
Abstract The purpose of this study is to understand in what ways a technology-enhanced learning (TEL) environment supports learning about the causes of the seasons. The environment was designed to engage students in five cognitive phases: Contextualisation, Sense making, Exploration, Modeling, and Application. Seventy-five high school students participated in this study and multiple sources of data were collected to investigate students’ conceptual understandings and the interactions between the design of the environment and students’ alternative conceptions. The findings show that the number of alternative conceptions held by students were reduced except for the incorrect concepts of “the length of sunshine” and “the distance between the sun and the earth.” The percentage of partial explanations held by students was also reduced from 60.5 to 55.3% and the percentage of students holding complete scientific explanations after using Lesson Seasons rose from 2.6 to 15.8%. While some students succeeded in modeling their science concepts closely to the expert’s concepts, some failed to do so after the invention. The unsuccessful students could not remediate their alternative conceptions without explicit guidance and scaffolding. Future research can then be focused on understanding how to provide proper scaffoldings for removing some alternative concepts which are highly resistant to change. Keywords Technology-enhanced learning . Alternative conception . Conceptual change . Instructional model . Science learning
Y.-S. Hsu (*) Department of Earth Sciences & Science Education Center, National Taiwan Normal University, 88 Sec. 4 Ting-Chou Road, Taipei 116, Taiwan e-mail:
[email protected] H.-K. Wu Taiwan, Graduate Institute of Science Education, National Taiwan Normal University, Taipei, Taiwan e-mail:
[email protected] F.-K. Hwang Department of Physics, National Taiwan Normal University, Taipei, Taiwan e-mail:
[email protected]
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Introduction There has been a substantial amount of research on students’ conceptual understanding and conceptual change in science education. Previous studies noted that students’ preconceptions are often irremediable through traditional expository forms of instruction (Brumby 1984; Kang et al. 2004; Windschitl and Andre 1998). To foster conceptual change, several learning models (e.g., conceptual change model, generative learning model, etc.) and instructional approaches were proposed (Hashweh 1986). Among these methods, using computer simulations and animations seems promising (Hameed et al. 1993; Windschitl and Andre 1998). Because technology has potential to support science learning, it has been identified as an important component of current science education reform (Ministry of Education in Taiwan 1999). Computer-based simulations, animations and modeling tools have been used to promote conceptual change (Barnea and Dori 1999; Dori and Barak 2001; Monaghan and Clement 1999; Tao and Gunstone 1999; Whitelock et al. 1991; Windschitl and Andre 1998). For example, Windschitl and Andre (1998) argued that “the issues of dissatisfaction with a current conception, and the intelligibility, plausibility, and fruitfulness of the scientific conception can all be addressed in a learning environment supported by the constructivist use of simulations” (p. 148). A learning environment that combined technology with a constructivist instructional approach could activate students’ prior knowledge, offer a possibility of cognitive conflict for dissatisfaction, and capitalise on contextually bound knowledge for intelligibility. Their research showed that the constructivist approach resulted in significantly greater conceptual change than the traditional approach. Instructional methods play an important role in science learning with technology. Both technology and instructional approaches should be part of the instructional design. Therefore, effective use of technology in classrooms requires well-designed computer applications as well as a change in instructional approaches (Dwyer et al. 1991; Wallace 2002; Windschitl and Sahl 2002). As more and more multimedia tools are developed and released by research institutions and publishing companies, teachers will need pedagogical support in order to create an effective technology-enhanced learning environment. In response to the teachers’ needs, we developed a theory-based instructional model that takes a situational cognitive approach, integrates the use of multimedia tools into instruction, and supports the development of students’ conceptual understanding. Using the model, we designed an instructional unit that integrated videos, animations, and simulations, and emphasise causes of the four seasons and related concepts (Lessons Seasons). The purpose of this study is to understand in what ways the technology-enhanced learning (TEL) environment supports conceptual change. The following questions guide this study: (1) (2)
What conceptions about the seasons do student have before and after learning with the Lessons Seasons? How does the design of the environment interact with students’ cognitive process (i.e., contextualisation, sense-making, exploration, modeling, and application)?
Alternative Conceptions About the Seasons Learners’ explanations, when they are alternative to scientific conceptions, usually come from their prior experiences and seem to legitimate these experiences (Gilbert and Swift 1985; Windschitl and Andre 1998). Most alternative conceptions are poorly articulated and
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internally inconsistent; in some cases, they are highly resistant to change (Windschitl and Andre 1998). Students’ alternative conceptions about seasons have been assessed by interviews or openend tests. For instance, Baxter (1989), Sharp (1996), Jiang (1993), and Chiu and Wong (1995) conducted interviews to examine students’ alternative conceptions; and Chen (2000) used open-end questions to survey 156 students in grade 6. Summarising the key findings of these past studies, we classify students’ alternative conceptions about seasons into five types: (1) (2)
(3)
(4)
(5)
Phenomenon or experiences: the sun covered by clouds (Baxter 1989; Sharp 1996; Jiang 1993) or the planetary wind systems (Jiang 1993; Chen 2000) cause seasons. Facing toward or away from the sun: the revolution of the sun around the earth (Baxter 1989; Chen 2000; Chiu and Wong 1995) or the rotation of the earth (Chen 2000; Chiu and Wong 1995; Sharp 1996) makes the sun sometimes face toward the earth (summer) and sometimes face away from the earth (winter). The duration of sun’s irradiation of the earth: changing the speed of the earth’s revolution around the sun causes the seasons (the speed is slow in summer which makes the sun’s radiation higher and contrariwise in winter) (Chen 2000; Sharp 1996). The tilt of the earth’s axis causing the change in distance or sunshine area: the sunshine area in the northern hemisphere is bigger (summer) than that in the southern hemisphere (winter) because of the earth’s tilt (Chen 2000). The distance between the sun and the earth: The aphelion of the earth’s revolution is winter and the perihelion is summer (Baxter 1989; Jiang 1993; Philips 1991; Sharp 1996).
Among the five types of alternative conceptions, young students tend to explain the seasons based on their life experiences such as cloud, wind, and legend, whereas older students intend to use celestial bodies and their relative positions to reason the season formation, such as the distance change between Earth and Sun, and facing toward or away from the sun. Most students have alternative conceptions related to seasons because they learn them from life experiences or books with incomplete explanations (Baxter 1989). In Taiwan, the topic of seasons is typically covered in fifth, sixth, tenth and eleventh grade textbooks. Before formal schooling, students’ explanations about seasons are poorly articulated and internally inconsistent. Developing scientific understandings about seasons is difficult for several reasons. First, students’ spatial abilities affect their learning about seasons because the explanatory model of season formation involves the perception of axis tilt and relative positions between the Earth and Sun (Chiu and Wong 1995). Second, some students’ alternative conceptions about seasons fit into their life experiences; for instance, it is hot close to a heat source so the aphelion of the earth’s revolution is winter and the perihelion is summer (Baxter 1989; Jiang 1993; Philips 1991; Sharp 1996). Finally, the scientific explanation for seasons is difficult for students to understand because it surpasses our observation on the earth. Students cannot visualise how the axis tilt of the Earth and the orbit of the earth’s revolution around the sun affects the seasons. To promote students’ conceptual understanding about seasons, we designed a technology-enhanced learning environment that integrated multimedia tools into students’ learning process.
Design of a Technology-enhanced Learning Model Drawing from the work of Karplus and Thier (1967) on the Learning Cycle and of White and Frederiksen (1998) on the Inquiry Cycle, we developed a Technology-Enhanced
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Learning (TEL) model for designing learning activities that support students’ acquisition and integration of scientific knowledge. The TEL model includes five cognitive phases, with a description of the mode of technology-implementation corresponding to each phase (see Fig. 1). The five phases are: Contextualisation, Sense making, Exploration, Modeling, and Application. In this first phase, science instruction is contextualised in a situation that is relevant to students’ personal experiences. Contextualisation can support the development of conceptual understanding by activating students’ prior knowledge and experiences, which now are used in the learning situation, and thus by engaging students with meaningful problems (Cognition and Technology Group at Vanderbilt 1997). In this phase, students are encouraged to describe their observations about the phenomenon, gain an intuitive comprehension of it, and connect it to their personal experiences. To focus students’ attention on the scientific content embedded in a given phenomenon, the second phase of the model supports students’ ability to make sense of their observations and intuitive comprehension, and to use various representations to guide the direction of their thinking (Bell 1997; Quintana et al. 2002). In this phase, students are encouraged to manipulate and link multiple representations and generate simple rules or hypotheses to explain what they have observed. In the Exploration phase, students have more opportunities to form and test their hypotheses, through which they may develop a deeper understanding of scientific concepts. Technological features that allow students to manipulate the quantities of variables and observe changes (de Jong and van Joolingen 1998), link conceptual information (e.g., equations) to representations (e.g., graphs) (Kozma et al. 1996), and provide situations in which students can test their ideas could encourage students to explore concepts.
Cognitive Process
Technology Use
Contextualisation
Situation Provider
Sense-Making
Exploration
Animation Display
Simulation Exploration
Modeling
Application
Construction Pad
Assessment Administration
Fig. 1 The framework of the Technology-enhanced Learning Model
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In the modeling phase, students are encouraged to synthesise the context or network of the phenomenon’s interrelationships and its possible explanations, and so develop a coherent understanding of the phenomenon they are investigating. Technological tools used in this phase should provide students with a working space in which to develop, modify and connect ideas, reflect on their modeling process, and evaluate the accuracy of their model (Gobert and Buckley 2000; Ingham and Gilbert 1991). In the final phase, students verify the accuracy of their model by applying it to different situations. In doing so, students could realise the errors and limitations of their model, transfer ideas from one setting to another, reinforce their ideas, and thus gain a new understanding of the phenomenon and relevant concepts. This application phase could also help students to overcome the “inert knowledge” problem by fostering the conceptual understanding that will come when the situation is relevant to what they have learned (Krajcik et al. 1999).
Descriptions of the Lesson Seasons Lesson Seasons is a TEL environment designed to promote high school students’ understandings about the reason(s) for the four seasons. Students may transform their intuitions and experiences into scientific understanding when cognitively engaging in the activities provided by the Lesson Seasons. Following the major phases of the TEL model, five technological tools are used in the environment: Situation Provider, Animation Display, Simulation Exploration, Construction Pad, and Assessment Administration (Fig. 1). In the Situation Provider, videos and animations of scenes around the world during different seasons are presented to help students make connections between the topic of the Lesson and their own life experiences. A guiding question of “why the Earth has seasons” is then provided to focus students’ attentions on the changes of the seasons. Animation Display includes a series of animations to help students visualize the scientific concepts embedded in the phenomenon. Simulation Exploration involves a computer simulation called SeasonSim that allows students to explore related concepts about the seasons through manipulating variables that influence the seasons, such as latitude, longitude, the tilted angle of the earth’s axis and eccentricity (see Fig. 2). Students can change these variables to see how solar radiation changes the Earth’s surface temperature. They can also test their hypotheses and reconstruct or build a model to explain why the Earth undergoes seasonal change. After using the Simulation Exploration, in the Construction Pad students draw concept maps to represent their ideas about the reasons of the seasons. The Construction Pad allows students to connect their ideas, develop causal relationships, and reflect on their modeling process. Finally, the Assessment Administrator helps students apply their new concepts. Students are provided with a new situation that requires them to explain, for instance, how the seasons on Mars change and what the major factors cause seasons on Mars. This learning task helps students use their model in a new situation, verify the accuracy of their model, and discover its possible limitations.
Methodology The participants of this study included 76 grade 11 senior high school students at a public senior high school located in the north of Taiwan. These students, typical eleventh grade
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Fig. 2 Screen shot of simulation: SeasonSim
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students, had a mean age of 17. They were from three earth science classes and were taught by the same teacher. This study used a pre-test/post-test (concept mapping) design associated with semi-structured interviews to explore how a TEL environment promotes students’ conceptual understanding about reasons for the seasons. Procedures Students attended a training lesson in concept mapping skills and the acquaintance of computer interfaces in the online lesson. Then students were required to complete preconcept maps, which were used to determine their patterns of alternative conceptions. After students finished their pre-concept maps, they interacted with the TEL environment: Lesson Seasons. Finally, they were asked to draw post-concept maps after completing the TEL activities. Totally, the pre-, post-concept mapping and engagement of the TEL environment took 8 h of class time. Semi-structured interviews were conducted immediately after the selected students made their post-concept maps. Data Collection Students’ conceptions about the seasons were assessed by the pre- and post-concept mapping (see Appendix for examples). Their perceptions about the TEL environment were evaluated through a feedback questionnaire. The questionnaire employed a Likert scale from 1 (strongly disagree) to 5 (strongly agree), and included four subscales: contextualisation (three items), sense-making (three items), exploration (two items), and modeling (two items). The items of the questionnaire are shown in Table 3. All students completed the preand post-concept mapping and answered the feedback questionnaire. Several steps were taken to select interviewed students. Students were first categorised into three groups based on their mean scores on the feedback questionnaire: high (H: upper 27%), middle (M: 46%) and low (L: lower 27%). Students within each group were then classified according to the type of conceptual change presented by their pre- and postconcept maps. We identified seven types of conceptual change: Type 1, maintaining the same alternative conceptions; Type 2, changing from an alternative conception to other alternative conceptions (Appendix-A); Type 3, changing from partial scientific explanation to alternative conceptions (Appendix-B); Type 4, changing from alternative conceptions to partial scientific explanations (Appendix-C); Type 5, changing from alternative conceptions to scientific explanations (Appendix-D); Type 6, changing from partial scientific explanations to scientific explanations (Appendix-E); Type 7, maintaining partial or complete scientific explanations. Three types of conceptual change occurred in the highscore group and we randomly selected two interviewees from Type 4 and Type 7 and an interviewee from Type 6. Five types (Types 1 to 5) were shown in the middle-score group and one interviewee was randomly selected from each type. Four types were shown in the low-score group and we randomly selected two interviewees from Type 7 and one interviewee from Type 2, Type 3, and Type 6. A total of 15 students were selected for 12– 15 min follow-up interviews. During interviews, students were asked why students’ concepts had changed and what their opinions were about the TEL environment. For example, interviewees were provided with models of the earth and sun, and asked to use models to explain what causes the seasons.
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Data Analysis Students’ concept maps were scored by comparing them with an expert’s concept map (see Fig. 3), following the rules suggested by Novak and Gowin (1984) on propositions, hierarchy, cross links and examples. If students’ concept maps appeared the same propositions including concepts and a linkage as the expert’s, we scored one point for each correct proposition and 0.5 point for an unclear proposition using indefinite linkages or vague concepts. According to the expert’s concept map, we identified six hierarchies in the branch of major factors and six hierarchies in the branch of minor factors. Each correct hierarchy scored five points. If a hierarchy included a correct node, a student would earn one point but lose an extra two points for each wrong node. Each meaningful cross link scored 10 points and each correct example scored one point. The inter-person reliability of the concept map scoring was .84. It is noted that the concept maps were scored using double-blind procedures. The identity of the student was not known, and it was not known whether the concept map being scored was a pre-map or a post-map. The level of students’ explanations was also coded. Complete explanations of the seasons should include the tilt of the earth’s axis, the earth’s revolution, the angle of the suns’ rays as they shine on the earth, and the interrelations of all these factors. Only such explanations may approximate the expert’s concept map (Fig. 2). If students mentioned some of these explanations, free of the confusion of alternative conceptions, we classified them in the group of those who could give partial scientific explanations. Statistical analyses were conducted using SPSS (Statistical Package for Social Science, version 12.0). The frequency analyses of students’ alternative conceptions as shown in their pre- and post-concept maps were used to understand how students developed their conceptual understanding in the TEL environment. In order to examine whether there was a statistically significant difference between the level of understanding before and after students engaged in the learning activities, a paired t-test was used to compare the scores of
Fig. 3 An expert’s concept map about the reasons for the seasons
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the pre- and post-concept maps. The assumption of normal distribution of dependent variables for the t-test was tested before applying statistical methods. Additionally, a descriptive analysis of the feedback questionnaire was used to understand students’ perceptions about Lesson Seasons. Interview data were coded and summarised to assess students’ understandings of their own learning processes and their perceptions about the “Lesson Seasons.”
Results This section follows the research questions and presents students’ conceptual understandings before and after learning with the Lessons Seasons, the interactions between the design of the TEL environment and students’ alternative conceptions, and their perceptions about the environment. Conceptual Understanding A paired t-test was conducted to compare students’ conceptual understanding before and after the intervention. The paired t-test results and the related descriptive statistics are summarised in Table 1. There were statistically significant differences in mean scores between students’ pre- and post- concept mapping (t (75)=8.0, p
