Dynamic visualizations can strengthen chemistry instruction by illustrating atomic level phenomena. Visualizations can help students add ideas about unseen phenomena involving atomic particles. They allow students to interact with phenomena that cannot be investigated in hands-on laboratories. Connecting dynamic, atomic representations with associated observable phenomena and symbolic representations has the potential to increase the coherence and comprehensiveness of student understanding.

Consistent with the knowledge integration framework, students enter chemistry courses with multiple non-normative ideas about chemical reactions. Following the knowledge integration framework, an inquiry project entitled Hydrogen Fuel Cell Cars engaged students in making predictions, exploring new ideas, distinguishing among ideas, and reflecting while connecting atomic interactions to everyday issues such as cars and fuel. To add normative ideas, a dynamic visualization that shows bond breaking and formation during hydrogen combustion was embedded in the unit. Using an iterative design process, a series of studies compared four approaches to distinguishing ideas: unguided exploration of the visualization, generating drawings of the sequence of events in the visualization, critiquing sequences of drawings attributed to a peer, and selecting among alternatives sequences. Progress was assessed using assessments that required students to articulate coherent accounts of chemical reactions.

The dissertation describes the design and development of the instruction, reports on a series of comparison studies conducted in typical middle schools that compare student performance in each of the four conditions: exploration, drawing, critique, and selection. The results reveal that visualizations can be deceptively clear so students may ignore important details when exploring a visualization. When learners generate, select, or critique drawings of atomic interactions, they recognize gaps in their knowledge, develop criteria for distinguishing among ideas, and increase in ability to select normative ideas. The dissertation demonstrates the importance of encouraging students to distinguish ideas when learning with visualizations. It suggests design principles for creating instructions featuring visualizations that can succeed in typical classrooms.

Students studying complex science topics can benefit from receiving immediate, personalized guidance. Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student written work, this dissertation compares forms of automated guidance designed to motivate productive revision and help students improve their science understanding. Online environments can support science learning by providing timely, personalized guidance to students, but challenges for effective implementation still exist. Specifically, (a) students often believe online guidance is generic rather than personalized for them; and (b) students do not always engage effortfully with online guidance and improve their written responses. This dissertation includes a series of three studies that address these challenges. A computerized learning environment is used to explore useful and motivating forms of automated guidance for middle school students learning challenging science topics such as thermodynamics.

Informed by the knowledge integration framework and established ideas about student motivation, these research studies examine effective designs for automated guidance. Study 1 demonstrates that automated knowledge integration guidance provided by a computer can promote integrated understanding of science as effectively as expert teacher guidance. In addition, students who began to distinguish scientific ideas after receiving guidance in the embedded assessment, as evidenced by adding either non-normative or normative ideas to their response, made greater gains over the course of the unit than those who did not add any new ideas in response to guidance. However, in this study some students discounted automated computer guidance, assuming it was generic rather than personalized. In Study 2, transparent guidance clarified to students how the computer generated personalized guidance based on their response. Results showed that transparent personalized guidance had a greater impact than standard adaptive guidance on student revisions, suggesting that student beliefs about how guidance is designed influences their performance. Transparent guidance was particularly effective for students who started with a low initial score. This finding resonates with the idea that students who felt they were struggling may have particularly benefited from the reassurance that automated guidance was provided at a level they were expected to be able to achieve. Study 3 compares two specific guidance strategies: revisiting evidence or planning writing changes, prior to revision. Analysis of student actions after receiving guidance demonstrated that students in the revisiting evidence condition were more likely to revisit prior evidence, and students in the planning writing condition were more likely to make significant writing revisions. Both revisiting and planning guidance resulted in significant improvement in student knowledge integration, although neither guidance strategy showed a significant advantage over the other. In addition, we found that the form of guidance interacted with school, suggesting that teacher practices could reinforce a specific guidance strategy.

This sequence of studies shows that the design of online guidance is important in encouraging students to revisit dynamic models and make effortful revisions to their work. Carefully designed automated guidance can augment the effectiveness of teachers by motivating students to better use computer learning environments and make effortful revisions that ultimately improve science learning. The results also raise important questions about when to encourage revisiting, how to design instruction that best fits with individual classroom strategies, and how to instill a lifelong practice of engaging in iterative refinement of scientific explanations.

This dissertation incorporates three studies that examine how the design of inquiry based science instruction, dynamic visualizations, and guidance for experimentation contribute to physics students` understanding of science. I designed a week-long, technology-enhanced inquiry module on car collisions that logs students` interactions with a visualization. Students studied the module and responded to pretests, posttests, and embedded prompts that assessed students` understanding of motion graphs and collisions. In Study 1, students (N=148) made large, significant overall pretest to posttest gains. Regression models showed that the propensity for students to conduct controlled trials was the strongest predictor of learning when controlling for prior knowledge and other experimentation measures. Successful learners employed a goal-directed experimentation approach that connected their experimentation strategy to content knowledge. Study 2 investigated the effect of limiting students` experimentation on their planning, strategies, and learning outcomes. Students (N=58) made large, significant overall pretest to posttest gains. Students constrained to twelve trials isolated variables in their experiments better than the unconstrained students. However, the constrained students significantly underperformed the unconstrained students on the module assessments, indicating that isolating variables during experimentation did not lead to improved learning outcomes. In Study 3, students (N=166) were assigned to conditions that prompted them either to isolate or compare variables. Both groups made moderate, significant pretest to posttest gains. Students in the compare treatment used more diverse experimentation strategies than students in the isolate treatment. Compare students made nuanced interpretations of collision events based on threshold values. Case studies illustrate how comparing rather than isolating variables helped students use wide-ranging strategies to reach complex insights. The findings illustrate how students can benefit from experimentation strategies that do not isolate variables. Spontaneous exploration can help students test new questions that arise from unexpected results, informing the design of controlled tests that better reveal subtle characteristics of the variables. Guidance that encourages students to compare rather than isolate variables may have important benefits, such as prompting students to search for distinctions among the variables. The findings have important implications for the design of inquiry-based science instruction.

Dynamic visualizations of scientific phenomena have the potential to transform how students learn and understand science. Dynamic visualizations enable interaction and experimentation with unobservable atomic-level phenomena. A series of studies clarify the conditions under which embedding dynamic visualizations in technology-enhanced inquiry instruction can help students develop robust and durable chemistry knowledge. Using the knowledge integration perspective, I designed Chemical Reactions, a technology-enhanced curriculum unit, with a partnership of teachers, educational researchers, and chemists. This unit guides students in an exploration of how energy and chemical reactions relate to climate change. It uses powerful dynamic visualizations to connect atomic level interactions to the accumulation of greenhouse gases. The series of studies were conducted in typical classrooms in eleven high schools across the country. This dissertation describes four studies that contribute to understanding of how visualizations can be used to transform chemistry learning. The efficacy study investigated the impact of the Chemical Reactions unit compared to traditional instruction using pre-, post- and delayed posttest assessments. The self-monitoring study used self-ratings in combination with embedded assessments to explore how explanation prompts help students learn from dynamic visualizations. The self-regulation study used log files of students' interactions with the learning environment to investigate how external feedback and explanation prompts influence students' exploration of dynamic visualizations. The explanation study compared specific and general explanation prompts to explore the processes by which explanations benefit learning with dynamic visualizations.

These studies delineate the conditions under which dynamic visualizations embedded in inquiry instruction can enhance student outcomes. The studies reveal that visualizations can be deceptively clear, deterring learners from exploring details. Asking students to generate explanations helps them realize what they don't understand and can spur students to revisit visualizations to remedy gaps in their knowledge. The studies demonstrate that science instruction focused on complex topics can succeed by combining visualizations with generative activities to encourage knowledge integration. Students are more successful at monitoring their progress and remedying gaps in knowledge when required to distinguish among alternative explanations. The results inform the design of technology-enhanced science instruction for typical classrooms.

Many students leave school with a fragmented understanding of biology that does not allow them to connect their ideas to their everyday lives (Wandersee, 1989; Mintzes, Wandersee, & Novak, 1998; Mintzes, Wandersee, & Novak, 2000a). Understanding evolution ideas is seen as central to building an integrated knowledge of biology (Blackwell, Powell, & Dukes, 2003; Thagard & Findlay, 2010). However, the theory of evolution has been found difficult to understand as it incorporates a wide range of ideas from different areas (Bahar et al., 1999; Tsui & Treagust, 2003) and multiple interacting levels (Wilensky & Resnick, 1999; Duncan & Reiser, 2007; Hmelo-Silver et al., 2007). Research suggests that learners can hold a rich repertoire of co-existing alternative ideas of evolution (for example, Bishop & Anderson, 1990; Demastes, Good, & Peebles, 1996; Evans, 2008), especially of human evolution (for example, Nelson, 1986; Sinatra et al., 2003; Poling & Evans, 2004). Evolution ideas are difficult to understand because they often contradict existing alternative ideas (Mayr, 1982; Wolpert, 1994; Evans, 2008). Research suggests that understanding human evolution is a key to evolution education (for example, Blackwell et al., 2003; Besterman & Baggott la Velle, 2007).

This dissertation research investigates how different concept mapping forms embedded in a collaborative technology-enhanced learning environment can support students' integration of evolution ideas using case studies of human evolution. Knowledge Integration (KI) (Linn et al., 2000; Linn et al., 2004) is used as the operational framework to explore concept maps as knowledge integration tools to elicit, add, critically distinguish, group, connect, and sort out alternative evolution ideas. Concept maps are a form of node-link diagram for organizing and representing connections between ideas as a semantic network (Novak & Gowin, 1984). This dissertation research describes the iterative development of a novel biology-specific form of concept map, called Knowledge Integration Map (KIM), which aims to help learners connect ideas across levels (for example, genotype and phenotype levels) towards an integrated understanding of evolution.

Using a design-based research approach (Brown, 1992; Cobb et al., 2003), three iterative studies were implemented in ethically and economically diverse public high schools classrooms using the web-based inquiry science environment (WISE) (Linn et al., 2003; Linn et al., 2004).

Study 1 investigates concept maps as generative assessment tools. Study 1A compares the concept map generation and critique process of biology novices and experts. Findings suggest that concept maps are sensitive to different levels of knowledge integration but require scaffolding and revision. Study 1B investigates the implementation of concept maps as summative assessment tools in a WISE evolution module. Results indicate that concept maps can reveal connections between students' alternative ideas of evolution.

Study 2 introduces KIMs as embedded collaborative learning tools. After generating KIMs, student dyads revise KIMs through two different critique activities (comparison against an expert or peer generated KIM). Findings indicate that different critique activities can promote the use of different criteria for critique. Results suggest that the combination of generating and critiquing KIMs can support integrating evolution ideas but can be time-consuming.

As time in biology classrooms is limited, study 3 distinguishes the learning effects from either generating or critiquing KIMs as more time efficient embedded learning tools. Findings suggest that critiquing KIMs can be more time efficient than generating KIMs. Using KIMs that include common alternative ideas for critique activities can create genuine opportunities for students to critically reflect on new and existing ideas. Critiquing KIMs can encourage knowledge integration by fostering self-monitoring of students' learning progress, identifying knowledge gaps, and distinguishing alternative evolution ideas.

This dissertation research demonstrates that science instruction of complex topics, such as human evolution, can succeed through a combination of scaffolded inquiry activities using dynamic visualizations, explanation activities, and collaborative KIM activities. This research contributes to educational research and practice by describing ways to make KIMs effective and time efficient learning tools for evolution education. Supporting students' building of a more coherent understanding of core ideas of biology can foster their life-long interest and learning of science.

Over the last decade, the demands on secondary science teachers have shifted to encompass a new range of objectives. Science teachers need support in their efforts to be responsive as they navigate shifting demands in the teaching profession: new state standards, an ever-diversifying student body, and a drive to integrate social justice into science learning. In the US, for example, the K-12 population has immensely diversified, necessitating curriculum adaptations to support the diverse lived experiences and range of prior knowledge represented in their classrooms. Moreover, new curriculum standards such as the Next Generation Science Standards in the US, have required teachers to adapt curriculum materials to meet new performance expectations. Further, technology has become ubiquitous in classrooms, requiring teachers to learn how to meaningfully integrate new tools into their practice. My dissertation project explores how to support teachers as they navigate these emerging trends within the context of a Research Practice Partnership devoted to promoting coherent science learning in technology-enhanced learning environments.

The studies presented in this dissertation are guided by the overarching research questions: How can we leverage technology to support teachers in their efforts to be more responsive to the needs and ideas of their students? Taken together, the three studies presented in this dissertation shed light on teachers’ trajectories for customizing curriculum to be more responsive, their trajectories for teaching science for social justice, and their trajectories for leveraging technology as a support for their teaching practice.

Specifically, the first study leverages the Knowledge Integration Framework to design and study a professional development workshop to empower teachers to customize their curriculum to better support their students develop understanding of NGSS performance expectations. The workshop activities and supporting technologies foreground pedagogy and emphasize using student work as evidence to inform customization decisions. The second study applies the professional development model from the first study to support teachers to customize the curriculum to feature social justice issues. The study follows the development and implementation of the units with three teachers across two school years. The third study focuses on the design and implementation of automatic scoring models that increase teachers’ access to the social justice and science ideas students use to explain the focal phenomena in the units designed in the second study. Across the studies, the findings have implications for expanding our understanding of Knowledge Integration pedagogy by integrating social justice principles and for the design of technologies that support teachers in principled customization.