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The call for the implementation of integrated science, technology, engineering, and mathematics (iSTEM) teaching has been on the rise. This teaching approach helps students to develop innovative skills and meet twenty-first century challenges. However, teachers need to possess positive attitudes toward iSTEM teaching to implement it. Therefore, studying factors that influence these attitudes is important. So far, investigated factors have focused on teachers' personal and professional experiences. Predisposing and enabling factors related to iSTEM teaching are yet to be investigated. One putative construct that includes predisposing and enabling factors is adaptive expertise (AE) which allows professionals to highly perform in new tasks. Here, we argue that AE in science teaching is linked to teachers' iSTEM attitudes through its three dimensions: perceived relevance (PR), self-efficacy (SE), and anxiety (Anx). We utilized a cross-sectional survey method to verify the proposed relationship on fourth year preservice primary science teachers (n = 91). They completed two online surveys measuring AE in science teaching and iSTEM attitudes, respectively. Results from multivariate regression modeling indicate a significant positive effect of AE in science teaching was found significantly positive on all three dimensions of iSTEM attitudes. These findings draw teacher educators' attention to the importance of developing adaptive expertise while preparing iSTEM teaching advocates.

We investigate students' eye movements when they solve sequential and simultaneous synthesis physics problems. In sequential synthesis problems, multiple events occur chronologically, whereas in simultaneous synthesis problems, multiple events take place concurrently. We captured students' eye fixations on each problem diagram and recorded their verbal descriptions of problem-solving approaches. Results indicate that for sequential synthesis tasks, students fixated heavily and frequently on regions of a diagram where information is unknown or on empty space related to future events. Further, most students could invoke all relevant principles and intermediate variables to solve the sequential problems. However, for simultaneous synthesis tasks, students prioritised aspects of the diagram where information is given in the problem statement. Moreover, they mostly invoked only one fundamental principle to solve the problems by either using the values given in the statement or identifying one relevant intermediate variable. These findings may be explained by the differences in the spatiotemporal occurrence of the multiple events in the two types of synthesis problem. The chronological events in sequential synthesis tasks seem to support students' sensemaking, but the concurrent events of simultaneous synthesis tasks do not.

Information and communication technology (ICT) is key to educational development. This study explores the mechanism influencing the use of ICT on students' science literacy. We utilized two-level hierarchical linear models and structural equation models to analyze data collected from the 2015 Program for International Student Assessment (PISA) in China. Results indicate that student-level and school-level ICT factors, in particular ICT interest, autonomy in using ICT, and ICT availability at school positively impact the development of students' science literacy. Further, we found some notable interactions between school-level factors and student-level ICT variables. Moreover, there are structural relationships among ICT availability, ICT emotional perception, ICT learning usage behaviors, science self-efficacy, and science literacy. We also found that teacher-delivered science instruction has a negative moderating effect on ICT learning usage and science self-efficacy. These findings have important implications of how to integrate ICT in future science teaching practices.

This study examines students' visual behaviors when they tackle two types of synthesis problems, sequential and simultaneous problems. Sequential synthesis tasks can be solved by applying pertinent concepts consecutively, whereas simultaneous synthesis tasks require concurrent application of multiple concepts. Twenty-two students from an introductory calculus-based physics course participated in the study. We used an eye-tracker to record the students' eye movements when they silently reflected on how to solve the problems and subsequently when they talked aloud their problem-solving strategies. We found that the students made more gaze transitions between text and diagram for the simultaneous problems than for the sequential ones. However, they spent more time looking at the diagram and making within-diagram eye transitions in the sequential tasks than in the simultaneous tasks. Further, most students invoked two concepts to solve the sequential tasks but only one for the simultaneous tasks. These findings indicate that the students made less effort to link text and diagram in solving sequential problems but frequently attempted to integrate information within each diagram. The pattern for the simultaneous problems appeared to be reversed. Our results suggest that different types of synthesis (i.e., sequential and simultaneous) may differentially influence the ways students handle tasks. As suggested by the eye-tracker data and confirmed by the participants' verbal explanations, students tend to divide the situation in sequential problems into subtasks but treat simultaneous problems as a single-step task.

We examine students' mathematical performance on quantitative "synthesis problems" with varying mathematical complexity. Synthesis problems are tasks comprising multiple concepts typically taught in different chapters. Mathematical performance refers to the formulation, combination, and simplification of equations. Generally speaking, formulation and combination of equations require conceptual reasoning; simplification of equations requires manipulation of equations as computational tools. Mathematical complexity is operationally defined by the number and the type of equations to be manipulated concurrently due to the number of unknowns in each equation. We use two types of synthesis problems, namely, sequential and simultaneous tasks. Sequential synthesis tasks require a chronological application of pertinent concepts, and simultaneous synthesis tasks require a concurrent application of the pertinent concepts. A total of 179 physics major students from a second year mechanics course participated in the study. Data were collected from written tasks and individual interviews. Results show that mathematical complexity negatively influences the students' mathematical performance on both types of synthesis problems. However, for the sequential synthesis tasks, it interferes only with the students' simplification of equations. For the simultaneous synthesis tasks, mathematical complexity additionally impedes the students' formulation and combination of equations. Several reasons may explain this difference, including the students' different approaches to the two types of synthesis problems, cognitive load, and the variation of mathematical complexity within each synthesis type.

The ability to solve physics problems that require multiple concepts from across the physics curriculum--"synthesis" problems--is often a goal of physics instruction. Three experiments were designed to evaluate the effectiveness of two instructional methods employing worked examples on student performance with synthesis problems; these instructional techniques, analogical comparison and self-explanation, have previously been studied primarily in the context of single-concept problems. Across three experiments with students from introductory calculus-based physics courses, both self-explanation and certain kinds of analogical comparison of worked examples significantly improved student performance on a target synthesis problem, with distinct improvements in recognition of the relevant concepts. More specifically, analogical comparison significantly improved student performance when the comparisons were invoked between worked synthesis examples. In contrast, similar comparisons between corresponding pairs of worked single-concept examples did not significantly improve performance. On a more complicated synthesis problem, self-explanation was significantly more effective than analogical comparison, potentially due to differences in how successfully students encoded the full structure of the worked examples. Finally, we find that the two techniques can be combined for additional benefit, with the trade-off of slightly more time on task.

Scientific reasoning is crucial to any scientific discipline. One sub-skill particularly relevant to the scientific enterprise is theory evidence coordination. This study, underpinned by Kuhn's framework for scientific reasoning, investigates how university students coordinate their self-generated theory and evidence in a physics topic (energy) and in non-content specific (non-physics-based) situations. Twenty-seven students completed five written reasoning tasks, three of which deal with energy concepts (physics-based) and two tasks concern with non-physics-based situations. The analysis focused on: (a) the completeness and correctness of the theory; (b) the source of the evidence; (c) theory evidence coordination or non-coordination; and (d) if coordination occurs, whether the evidence supports or refutes the theory, and the quality of students' explanations. The outcomes revealed that the students tended to coordinate theory and evidence for non-physics tasks as opposed to physics problems. When theory evidence coordination occurred, regardless of the type of scenarios, the evidence primarily supported the theory in the form of a poor explanation. The importance of content knowledge for scientific reasoning is discussed. The implications for applying scientific reasoning as an assessment tool in science are also highlighted.

In this paper, we report on a project concerned with the role of cognition during problem solving. We specifically explore the categories of mental representations that students work with during problem solving of different representational task formats. The sample, consisting of 19 engineering students taking a calculus-based physics course, attempted tasks from the topics of kinematics and work. Profiles were designed to capture the overall actions and reasoning of individual students across the various tasks. Two main profiles emerged from each topic under consideration. They were related to the Johnson-Laird cognitive framework to infer about the kinds of mental constructs. The results indicate that, for both topics, students work primarily at the level of propositional mental representation. When handling the kinematics tasks, a few students construct mental images and none of them can be categorized as using a mental model. In contrast, in the context of work, none of the participants generated a mental image while a minority of the sample was classified as using a mental model. Moreover, a comparison across the two topics indicates the predominance of propositional mental representation. (Contains 28 figures and 1 table.)

Previous studies have reported that students employed different problem solving approaches when presented with the same task structured with different representations. In this study, we explored and compared students' strategies as they attempted tasks from two topical areas, kinematics and work. Our participants were 19 engineering students taking a calculus-based physics course. The tasks were presented in linguistic, graphical, and symbolic forms and requested either a qualitative solution or a value. The analysis was both qualitative and quantitative in nature focusing principally on the characteristics of the strategies employed as well as the underlying reasoning for their applications. A comparison was also made for the same student's approach with the same kind of representation across the two topics. Additionally, the participants' overall strategies across the different tasks, in each topic, were considered. On the whole, we found that the students prefer manipulating equations irrespective of the representational format of the task. They rarely recognized the applicability of a "qualitative" approach to solve the problem although they were aware of the concepts involved. Even when the students included visual representations in their solutions, they seldom used these representations in conjunction with the mathematical part of the problem. Additionally, the students were not consistent in their approach for interpreting and solving problems with the same kind of representation across the two topical areas. The representational format, level of prior knowledge, and familiarity with a topic appeared to influence their strategies, their written responses, and their ability to recognize qualitative ways to attempt a problem. The nature of the solution does not seem to impact the strategies employed to handle the problem. (Contains 13 figures and 12 tables.)

The present study explores the relationship between students' views of the nature of science (NOS) and their views of the nature of scientific measurement. A questionnaire with two-tier diagnostic multiple-choice items on both the NOS and measurement was administered to 179 first-year physics students with diverse school experiences. Students' views on the NOS were classified into four NOS "profiles", and views on measurement were classified according to either the point or set paradigms. The findings show that students with a NOS profile dominated by a belief that the laws of nature are to be discovered by scientists are more likely to have a view of the nature of scientific measurement characterised by a belief in "true" values. On the other hand, students who believe that scientific theories are inventions of scientists, constructed from observations that are then validated through further experimentation, are more likely to have a view of the nature of scientific measurement that is underpinned by the uncertain nature of scientific evidence. The implications for teaching scientific measurement at tertiary level are discussed. (Contains 1 figure and 5 tables.)

The views on various aspects of the nature of science (NOS) of 179 novice undergraduate physics students were investigated using six open-ended, written probes. These views were consolidated within compact NOS "profiles", which were designed based on the students' responses to the probes. These profiles may be understood as sets of key descriptors, which represented the variation in the views of individual students in a succinct way. The views of 86% of the sample were found to be represented by four profiles, each containing five descriptors. The consequences for the teaching and learning of tertiary science, and advantages for linking NOS views to other research observables were explored. (Contains 1 figure and 8 tables.)

The article discusses the view of freshman physics students on the nature of science. The authors investigated the views on various aspects of the nature of science through the use of open-ended written probes. The vast majority of views among nearly 200 novice undergraduate physics students were found to be represented by four stock profiles that contained five key descriptors. These descriptors represented the variation in the views of individual students. Consequences for the teaching and learning of tertiary science are examined.