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The study employed epistemic network analysis (ENA) to investigate students' conceptions of science learning with technology. One-hundred and eleven tenth-grade students were asked to express via drawings their conceptions of experienced and ideal learning of science with technology. Their drawings were coded into 20 elements in seven categories. ENA was then employed to generate and compare network models that show structures of the students' conceptions. The results suggest that the students' conceptions are diverse and connected. It was found that (1) the students' conceptions of experienced and ideal learning of science with technology were significantly different, (2) the students who emphasized understanding as the main goal of science learning were better able to envision ideal learning of science with technology in light of how innovative technology can be used to enhance learning experiences, (3) the students who emphasized testing showed conceptions of science learning with technology limited to inside classrooms, and (4) the students who emphasized both understanding and testing demonstrated a pragmatic view of science learning and paid more attention to the affordances and effects of technology. Implications include that the potential of technology has yet to be fully taken advantage of to support science learning and that specific learning experiences may be tailored for students to address or broaden their conceptions of learning. The study may contribute to research by introducing new analysis methods of combining ENA with drawings and to theory and practice by revisiting theoretical frameworks of learning environments based on understanding of students' conceptions.

Promoting understanding of the epistemologies of science has long been the primary objective in science education, and can be viewed as a form of science learning outcome. Many studies have attempted to understand learners' conceptions of epistemology in science from various perspectives and methods; however, no recent reviews have focused on the measurement of various constructs and variables of epistemologies of science. The main purpose of this review study is to understand how these epistemologies in science teaching and learning were measured, and to provide an overview of recent developments with respect to the measurement issue in the epistemology of science. We searched for articles that were published between 2010 and 2019 and retained 225 eligible studies passing all review criteria for inclusion in this review. Major constructs of epistemologies of science emerging from the studies include epistemic beliefs and views, nature of science, epistemic emotions, epistemic metacognition, epistemic practices, and epistemic resources. These constructs were further categorized into personal, productive, and practical epistemologies. Among these studies, most of the quantitative studies used questionnaires for measuring personal epistemologies, while only a few utilized close-ended items. The majority of the studies adopting qualitative methods investigated personal epistemologies as well. Nevertheless, among studies of practical epistemologies, more studies adopted qualitative methods than quantitative methods. We summarize the characteristics and psychometric properties of the most frequently used quantitative research instruments. Examples of qualitative data collection and data analyses are provided. Relationships between epistemologies and science learning outcomes are discussed, and suggestions are made for future directions.

We engaged 47 eighth-grade students in a newly developed learning environment that integrates mobile augmented reality (AR) technology to support students' learning of nuclear energy use and radiation pollution, a topic related to a socioscientific issue (SSI) that involves complex reasoning considering scientific evidence and multiple perspectives. We employ the partial least squares structural equation modeling to investigate how the students' context-specific epistemic justification and prior knowledge contributed to their engagement in the learning environment and socioscientific reasoning (SSR) performance after the learning. Data collected include students' responses to the knowledge pretest that assessed students' prior knowledge related to the SSI, the pretest survey that measured students' context-specific epistemic justifications, the Cognitive and Emotional Engagement Survey (CEES) right after the end of the AR activities that measured students' self-reported cognitive and emotional engagement, and the posttest that measured students' socioscientific reasoning performance. The results indicate that students' context-specific epistemic justifications can predict their engagement in the environment, and that prior knowledge and belief in justification by authority can predict students' SSR performance, but in different directions. The results provide insights into how to support students with different personal characteristics to learn with AR technology about SSI, and contribute to a model of personal epistemology within the environment of integrating AR technology for the learning of SSI.

In this study, we reviewed 76 journal articles on employing drawing assessment as a research tool in science education. Findings from the systematic review suggest four justifications for using drawing as a type of research tool, including assessment via drawing as (a) an alternative method considering young participants' verbal or writing abilities, and affective or economic reasons, (b) a unique method that can reveal aspects not easily measured by other methods, (c) a major method that reflects characteristics of science subjects, and (d) a formative assessment to diagnose students' ideas to benefit their learning. Furthermore, five research trends of studies using drawing as assessment tools are identified, including: (a) students' conceptions of scientists from the Draw-a-Scientist-Test (DAST) and evolving studies, (b) students' understanding or mental models of science concepts, (c) participants' conceptions of science learning or teaching, (d) students' inquiry abilities and modelling skills via drawing, and (e) technology to support drawing. For each trend, we synthesised and commented on the current findings. A framework conceptualising phases and issues when designing research and instruments employing drawing assessments is proposed. The review provides insights into the design and future direction of research employing drawing assessments in science education.

This study investigated high school students' conceptions of technology-assisted science learning via drawing analysis, and explored how students with different degrees of computer experience and science learning self-efficacy may show different conceptions via their drawings. The participants included 335 senior high school students in Taiwan (179 male and 156 female). All of them were asked by guiding questions to make two drawings to represent their conceptions of technology-assisted science learning in actual and ideal contexts, respectively. Their background information including computer experience and science learning self-efficacy were obtained using self-reported questionnaires. Through drawing analysis, seven categories of conceptions of technology-assisted science learning were identified, including types of technology, location of learning, types of learning activities, content of learning, participants of learning activities, affordance of learning technology, and effects of learning technology. The results further revealed that the students' conceptions of actual and ideal technology-assisted science learning significantly differed in some sub-categories of all categories except the category of participants of learning activities. Moreover, students' computer experience and science learning self-efficacy may link to different conceptions of technology-assisted science learning. Future research and directions are also discussed.

In this study, we have synthesized the research on visualization and representation to propose a model consisting of 4 major components of visualization competence in learning science: constructing, interpreting, transforming, and critiquing visualizations. We have developed and validated an assessment that measures students' visualization competence of matter (VCM). We administered the VCM assessment to 762 7th to 12th grade students at 2 public high schools in Taiwan. The students had started to learn concepts of matter at the particulate level in the 7th grade. However, traditional assessments rarely measure students' visualization competence in science. It was therefore unclear how well the students performed on visualization of matter across grade levels. Overall, the results indicated that the students' visualization competence of matter improved as they advanced to higher grades. A significant factor accounting for the development of their visualization competence of matter is their course experience, not their age or gender. We also found that content knowledge plays only a conditional role in students developing visualization competence of that content. Implications and future studies are discussed.

Research has indicated the importance of representational competence for learning science. Issues related to the nature of students' representational competence, such as how they demonstrate representational competence across different domains of science, require investigation. In the present study, four aspects of representational competence across two domains of science were investigated: use of dynamic representations, use of multiple representations, use of adequate science concepts, and use of visualization strategies. Two instruments, the representational competence of states of matter and the representational competence of carbon cycling assessments were delivered via a computer-based drawing tool and were used to measure 40 senior high school students' representational competence for the topic of states of matter and carbon cycling. The results indicated that the representational competence demonstrated in one topic was not significantly correlated to that demonstrated in the other. The results of path analyses using multiple regressions indicated a trend that the extent to which multiple representations were employed was significantly and closely related to the extent to which appropriate science concepts were applied to make the drawings. Implications of the findings are discussed.

Two investigations were conducted in this study. In the first experiment, the effects of two types of interactivity with a computer simulation were compared: experimentation versus observation interactivity. Experimentation interactivity allows students to use simulations to conduct virtual experiments, whereas observation interactivity allows students to observe segmented video clips of the simulation at their own pace and sequence. In the second experiment, the effects of two types of scaffolding for experimentation interactivity were compared: the driving question versus structured prompt scaffolding. A total of 128 eighth-grade students were involved. The learning outcomes examined include the students' understanding of the concepts in the simulation, their learning time, total numbers of virtual experiments conducted or observed, and learning efficiency. All four designs resulted in comparable learning gains for the students. The driving question scaffolding resulted in better learning efficiency, whereas the structured prompt scaffolding supported students in conducting more virtual experiments.

The issues of metacognitive scaffolding in science education (MSiSE) have become increasingly popular and important. Differing from previous content reviews, this study proposes a series of quantitative computer-based analyses by integrating document co-citation analysis, social network analysis, and exploratory factor analysis to explore the intellectual structure of the MSiSE literature (i.e. the relationships within and between subfields of MSiSE). Co-citation refers to any two articles that are jointly referenced in other articles. After the computation of co-citation analysis, 27 articles that have been co-cited at least once by follow-up studies as references were identified as the final set of core articles. The whole co-citation profile of 27 cores with the 434 links was then visualized in a network through social network analysis, representing an overview for the intellectual structure of core MSiSE studies. The most cross-referenced underpinnings in the network focused on adaptive scaffolding for self-regulated learning to enhance students' conceptual understanding and on younger students' metacognition in online science inquiry learning environments. Furthermore, two emerging topics in the network were identified through an exploratory factor analysis as "non-technological metacognitive scaffolding media," and "behavior patterns & task analysis in technology-infused environments." Overall, the study provides an innovative review method of scholarly communication in the MSiSE literature.

In order to promote scientific inquiry in secondary schooling in Taiwan, the study developed a computer-based inquiry curriculum (including structured and guided inquiry units) and investigated how the curriculum influenced students' science learning. The curriculum was implemented in 5 junior secondary schools in the context of a weeklong summer science course with 117 students. We first used a multi-level assessment approach to evaluate the students' learning outcomes with the curriculum. Then, a path analysis approach was adopted for investigating at different assessment levels how the curriculum as a whole and how different types of inquiry units affected the students' development of conceptual understandings and inquiry abilities. The results showed that the curriculum was effective in enhancing the students' conceptual knowledge and inquiry abilities in the contexts of the six scientific topics. After the curriculum, they were able to construct interconnected scientific knowledge. The path diagrams suggested that, due to different instructional designs, the structured and guided inquiry units appeared to support the students' learning of the topics in different ways. More importantly, they demonstrated graphically how the learning of content knowledge and inquiry ability mutually influenced one another and were reciprocally developed in a computer-based inquiry learning environment.

Powerful online visualizations can make unobservable scientific phenomena visible and improve student understanding. Instead, they often confuse or mislead students. To clarify the impact of molecular visualizations for middle school students we explored three design variations implemented in a Web-based Inquiry Science Environment (WISE) unit on thermodynamics: Observation, Research Guidance, or Critique. We tested these variations in an inquiry unit designed following the knowledge integration framework to promote coherent understanding. Seven middle school classes (205 students) and their two teachers participated in the study. Students studying each version of the unit made significant gains on knowledge integration items designed to measure coherent understanding of thermodynamics. Compared to Research Guidance, the Critique condition was more successful, especially in helping students conduct consequential experiments. Embedded assessments revealed that students who critiqued a confounded experiment were more successful in conducting valid experiments than students who did not critique. In addition, the combination of critique and virtual experimentation increased student ability to connect molecular and observable phenomena. These results suggest design guidelines to help future designers. Specifically, preceding experimentation with critique activities helps students distinguish among existing and new ideas.

One issue facing teachers who implement model-based instruction within the school system is the tight curricular schedule. The 'lesson objective tension' calls for investigations to address instructional issues such as how to organise modelling-based instruction at the curriculum level which is across multiple units. We investigated the effect of the cyclic curricular design spacing out three modelling-based instruction units with virtual labs over three semesters, each involving 73, 181, and 150 junior high school students, respectively. Results indicate that, overall, the approach of modelling with virtual labs better promoted students' scientific literacy than the traditional instruction did. Specifically, students with low and moderate school science achievements benefitted more as shown in their scientific literacy scores than did the high achievement students. Furthermore, this study found that receiving one unit of modelling-based instruction may not be sufficient to promote students' scientific literacy, whereas the cyclic approach that suggests students receive two or more units of modelling-based instruction with virtual labs spaced over consecutive semesters had significant effects on promoting students' scientific literacy. The results provide insights into when and how modelling-based learning with virtual labs can promote scientific literacy at a curricular level. [ABSTRACT FROM AUTHOR]

Dynamic visualisations capture aspects of scientific phenomena that are difficult to communicate in static materials and benefit from well-designed scaffolds to succeed in classrooms. We review research to clarify the impacts of dynamic visualisations and to identify instructional scaffolds that mediate their success. We use meta-analysis to synthesise 47 independent comparisons between dynamic and static materials and 76 comparisons that test the effect of specific instructional scaffolds. These studies show that dynamic visualisations are better than static visuals at promoting conceptual inferences about science, consistent with the success of inquiry instruction in science. To realise this potential of dynamic visualisations, instruction needs to help students use the dynamic visualisation to make sense of their own ideas. Scaffolds that are most successful include prompts for reflection, prompts to distinguish among parts of the visualisation, visual cues that identify salient features, multiple visualisations presented sequentially, and interactive features that govern the pacing of activities. We extract guidelines from this research to help researchers plan future studies of visualisations, designers create and refine instructional materials using visualisations, and practitioners customise instruction that features visualisations. [ABSTRACT FROM PUBLISHER]