Student and teacher regulation of learning in technology-enhanced science instruction

This study investigates student and teacher regulation of learning during a 7-day technology-enhanced inquiry unit on the topic of global warming, and changes in students’ strategies for learning science after interacting with the curriculum. Results reveal that students engage in some productive learning strategies promoted in the design of the project, such as learning with visualizations and collaborating with others. Students reported the visualizations to be the most helpful to their learning. The teacher provided the most guidance to students in the form of high-level questions that prompted students to make connections and to monitor their comprehension during days when the students interacted with the visualizations. After completion of the project, students reported engaging in more active and productive strategies for learning and monitoring their understanding of new science material. Implications and plans for further research are discussed. Inquiry-based science learning and teaching can be enhanced by the use of technology in the classroom (Bransford, Brown, & Cocking, 1999; Linn, Davis, & Bell, 2004). However, integration of inquiry-based science curricula and technology integration can be difficult for teachers and students. Given the more studentdirected versus teacher-delivered aspects of both inquiry and technology-enhanced learning, learners must be skilled at regulating their own learning and teachers must be prepared to manage a variety of learners who are progressing at different rates. Many students lack the self-regulated learning strategies needed to be successful in these types of learning activities (Azevedo, Cromley, Winters, Moos, & Greene, 2005; Quintana, Zhang, Krajcik, 2005; White & Frederikson, 2005). Specifically, students need to know what to learn, how to learn it, how to monitor their understanding of the topic, how to monitor the effectiveness of their learning strategies, and how to revise their strategy use and understanding of the topic if needed (Azevedo et. al, 2005; Jonassen & Reeves, 1996). Azevedo and colleagues have found specific aspects of self-regulated learning to be associated with increased understanding of complex science topics in hypermedia learning environments (Azevedo et. al, 2005, Green & Azevedo, 2007) and developmental differences of self-regulated learning strategy use. Younger students were much less likely to use effective self-regulated learning strategies than high school and college students. This suggests that younger students need more guidance when learning complex science concepts with technologyenhanced curricula. Guidance for students in technology-enhanced inquiry learning environments often comes from the teacher or from various types of cognitive tools and scaffolds built into the technology. This scaffolding has potential to increase students’ understanding by making aspects of metacogniton more explicit, (Lajoie, 1993; Quintana, Zhang, Krajcik, 2005; White & Frederikson, 2005) prompting reflection, (Davis, 2003) and making students’ thinking visible (Linn, Clark, & Slotta, 2001). Quintana and colleagues (2004) offer suggestions in their scaffolding design framework for ways to support students’ sense making, process management, and articulation and reflection in technology-enhanced learning environments in science. Linn and Eylon (2006) discuss patterns of instructional design and how these patterns influence the process of students’ knowledge integration, which involves students monitoring their ideas to determine how new ideas relate to previous ideas. Adaptive scaffolding from human tutors, peers, and teachers can also support students’ metacognitive monitoring and understanding during technology-enhanced learning situations (Chi, Siler, & Jeong, 2004). This research demonstrates the importance of metacogniton and self-regulated learning in students’ ability to be successful in technology-enhanced inquiry curricula. In this study we investigate students preferences for learning new science material both before and after their interaction with technology enhanced inquiry curriculum. We also examine student and teacher regulation of learning during a 7-day technology-enhanced inquiry unit on the topic of global warming. The teacher involved in the study is participating in a 5-year NSF grant funded professional development project, MODELS (Mentored and Online Development of Educational Leaders for Science). The program is designed to enable schools to implement technology-enhanced inquiry instruction by supporting teachers as they plan, implement, and reflect on their experiences using the technology in the classroom. The teacher has participated in the project for 3 years and has attended a summer professional development workshop each year focused on teaching and assessment strategies to help students learn with the technology-enhanced curricular projects. The purpose of this study is to answer the following questions: (1) What self-regulated learning processes do students engage in during the technology-enhanced inquiry curricular project? (2) How does the teacher use questioning strategies to regulate and scaffold students’ learning? and (3) How do students’ preferences for learning science material change after interacting with the curriculum? This study serves as a first step to investigate how students learn with technology-enhanced curricula and how teachers scaffold student learning, which will inform the design of technology-enhanced inquiry learning environments, professional development, and instructional strategies for teachers to better support student learning within these environments. Methods Participants Participants were 141 mixed-ability sixth grade science students from an ethnically and economically diverse school in the San Francisco Bay Area. All students were enrolled in a science class taught by the same teacher. The teacher has 33 years teaching experience. He has taught science for 20 of the 33 years, and has been using WISE curricular projects for 3 years. Learning Environment Students completed a computer-based unit on the topic of the Greenhouse Effect and global warming using the Web-based Inquiry Science Environment (WISE; http//wise.berkeley.edu). Students conduct experiments with a greenhouse effect visualization by manipulating levels of solar energy, atmospheric carbon dioxide, Albedo, sunlight, and cloud cover. Following their investigations, students draw conclusions about the role of the different factors involved in the greenhouse effect (Varma, 2006). The project engages students in various collaborative activities, such as designing solutions to problems, investigating hypotheses, and critiquing scientific claims. Procedure Participants individually completed pre and post-tests measuring their preferences for learning new science content, comprehension monitoring strategies, and content knowledge of the greenhouse effect. Students spent 7 days working in pairs through the Global Warming Project during their science class time. After completion of the project, students completed a questionnaire about their learning behaviors when working with the WISE project. Data Sources Pre/Post Tests The pre/post tests consisted of 6 likert-scale items about students’ preferences for learning new science material. Students were given the prompt, “When learning new science material I prefer to ...” and then circled either always, sometimes, or never for six common strategies for learning science (e.g., be told what is correct by the teacher, do experiments and try to figure things out, discuss material with classmates). Additionally students responded to two items, one multiple choice and the other free response, about their strategies for monitoring their understanding of new science material. Students also answered 4 free response questions about the greenhouse effect and global warming. Classroom observations A University researcher observed both teachers and students during 4 of the 7 days of the project for approximately 1.5 classes each day. Observations of the teacher’s actions were recorded on an observation form containing specific categories: general interactions, working with visualizations, and small group interactions. Additionally, all questions the teacher asked to either the entire class or to groups of students were recorded. Learning Strategies Questionnaire The questionnaire consisted of 11 likert-scale items about students’ self-regulated learning behaviors when working through the WISE Global Warming project. Students were given the prompt, “When working on the Global Warming project, I ...” and then asked to circle either a lot, some, a little, or none for 11 common strategies when learning with WISE projects (e.g., went back to previous steps in the project to help me understand something better, checked to make sure that I truly understood the material presented in the project, discussed ideas and questions with my partner while I was working) Students also responded to three free response items asking them to explain the strategies they used for monitoring their understanding, how the models/visualizations helped them learn, and what helped them learn the most about global warming. Results Student learning strategies during inquiry unit Students responded how frequently (none, a little, some, a lot) they engaged in 11 strategies when learning with the Global Warming Project. Items were coded: none = 1, a little = 2, some = 3, and a lot = 4. Frequencies of each response and averages were calculated for each of the 11 strategies. Students reported using the models and visualizations most often when working through the Global Warming project, followed by thinking about the learning goals of the project and discussing ideas with their partners. Students reported revising their work, asking the teacher for help, and using Amanda (online hint tool) least frequently. The project was designed to enable students to manipulate a complex visualization to facilitate their learning and to allow students to work together, so it is encouraging that students reported engaging in these strategies frequently when learning about global warming. However, it is unfortunate that students did not take advantage of some of the scaffolds provided within the program more frequently, such as the online discussion tool and hint tool, or use the opportunity to revise their work within the program more often. See Table 1. Table 1: Student learning strategies in the Global Warming Project Response Percentage (n) Strategies None A little Some A lot n Mean Used the visualizations 2.36% (3) 4.72% (6) 25.98% (33) 66.93% (85) 127 3.57 Thought about learning goals 2.31% (3) 5.38% (7) 37.69% (49) 54.62% (71) 130 3.45 Discussed ideas and questions with partner 1.59% (2) 10.32% (13) 35.71% (45) 52.38% (66) 126 3.39 Went back to previous steps to understand something better 1.54% (2) 16.92% (22) 37.69% (49) 43.85% (57) 130 3.24 Thought about prior knowledge 3.08% (4) 18.46% (24) 43.85% (57) 34.62% (45) 130 3.10 Checked understanding 3.10% (4) 25.58% (33) 33.33% (43) 37.98% (49) 129 3.06 Read online discussion posts 6.30% (8) 22.05% (28) 33.86% (43) 37.80% (48) 127 3.03 Posted to online discussion 8.73% (11) 26.98% (34) 38.10% (48) 26.19% (33) 126 2.82 Revised work after learning something new 9.52% (12) 29.37% (37) 43.65% (55) 17.46% (22) 126 2.69 Asked teacher for help 7.14% (9) 38.10% (48) 38.89% (49) 15.87% (20) 126 2.63 Used Amanda (hint tool) when extra help was needed 33.07% (42) 36.22% (46) 24.41% (31) 6.30% (8) 127 2.04 Students responses to the open-ended question, “What helped you learn the most about global warming?” are consistent with the results of the previous questions regarding the learning strategies students reported engaging in. Responses were coded into categories. Categories were not mutually exclusive because some students listed more than one thing that was helpful to their learning. The visualizations were overwhelmingly the most reported response, at 67%. The teacher, hint tool, and the online discussions were mentioned least frequently. See Table 2. Table 2. Students’ responses to what was most helpful in their learning. Reported to facilitate student learning % of student responses Visualizations 67% Explanation and note steps 7% Reading/studying 6% Partner 5% All of it 5% Teacher 2% Online discussion 1% Amanda (online hint tool) 1% Students were then asked to elaborate on how the visualizations helped them to learn about global warming. Student responses were coded into categories. The categories were not mutually exclusive because some students listed more than one way the visualizations helped them to learn. The most frequently stated response was that the visualizations showed scientific processes or effects of various variables (e.g. carbon dioxide, albedo, cloud cover) on global warming. This was followed by a more general answer; 20% of students stated that the visualizations made it easier to “see” or “visualize” or that it was easier to look at the visualization than to read the information. See Table 3. Table 3. Students’ responses to how the visualizations helped their learning. Ways visualizations facilitated student learning % of student responses Showed processes/effects of variables 30% Helped to visualize/easier than readying 20% Showed an example 11% Allowed for experimentation to determine effects 10% Helped to understand the problem and answer the questions 10% It didn’t help 2% Allowed to see or do things you can not in real world 2% Results of a paired t-test revealed significant learning gains in students’ knowledge of the greenhouse effect and global warming (t (125) = -11.04, p<.001). Mean composite scores on the content items increased from 4.71 on the pre-test to 7.14 on the post-test. There was no correlation between students’ reported use of self-regulated learning strategies when working through the project and learning outcomes. Teacher questioning strategies During 4 days of classroom observations, a total of 67 questions that the teacher asked to students were recorded; 58% were directed to the entire class and 42% were asked to pairs of students working together through the project. Questions were coded in two ways, level of knowledge integration the question promoted and purpose of the question. The Knowledge Integration (KI) Framework views learning as building important bridges among pre-existing ideas as well as making links between existing ideas and new ideas (Linn & Hsi, 2000). We used this framework to code questions into low, medium, or high level questions, based on the type of knowledge integration it promoted. Of the 67 questions, 42% were low-level questions, 34% were mediumlevel questions, and 24% were high-level questions. See Table 4. Table 4. Teacher questions to support students’ knowledge integration. Level of KI Questions support students to: Examples Percentage Low Define a term or element of the model What is IR? What is a greenhouse made of? 42% Medium Make one connection Why is a greenhouse made of glass? What happens when IR hits the atmosphere? 34% High Reflect and make many connections What is the role of albedo in the greenhouse effect? Why are we worried about global warming? 24% When questions were broken down by day, more questions were asked on days 4 and 5 than days 2 and 7, and the majority of the questions asked on days 4 and 5 were medium to high-level questions. During these days the students were primarily interacting with the visualizations, manipulating variables to determine their effects on global temperature. See Figure 1.