Dataset Information

Does Concrete Content Help People to Reason Scientifically?: Adaptation of Scientific Reasoning Scale.

ABSTRACT: In this paper, we explored the scientific literacy of a general sample of the Slovak adult population and examined factors that might help or inhibit scientific reasoning, namely the content of the problems. In doing so, we also verified the assumption that when faced with real-life scientific problems, people do not necessarily apply decontextualized knowledge of methodological principles, but reason from the bottom up, i.e. by predominantly relying on heuristics based on what they already know or believe about the topic. One thousand and twelve adults completed three measures of scientific literacy (science knowledge, scientific reasoning, attitudes to science) and several other related constructs (numeracy, need for cognition, PISA tasks). In general, Slovak participants' performance on scientific reasoning tasks was fairly low and dependent on the context in which the problems were presented-there was a 63% success rate for a version with concrete problems and a 56% success rate for the decontextualized version. The main contribution of this study is a modification and validation of the scientific reasoning scale using a large sample size, which allows for more thorough testing of all components of scientific literacy.

Supplementary information

The online version contains supplementary material available at 10.1007/s11191-021-00207-0.

SUBMITTER: Basnakova J

PROVIDER: S-EPMC8035062 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Does Concrete Content Help People to Reason Scientifically?: Adaptation of Scientific Reasoning Scale.

Bašnáková Jana J Čavojová Vladimíra V Šrol Jakub J

Science & education 20210410 4

In this paper, we explored the scientific literacy of a general sample of the Slovak adult population and examined factors that might help or inhibit scientific reasoning, namely the content of the problems. In doing so, we also verified the assumption that when faced with real-life scientific problems, people do not necessarily apply decontextualized knowledge of methodological principles, but reason from the bottom up, i.e. by predominantly relying on heuristics based on what they already know ...[more]

PMID: 33867682

Similar Datasets

Project description:Science historians have recognized the importance of heuristic reasoning strategies for constructing theories, but their extent and degree of organization are still poorly understood. This paper first consolidates a set of important heuristic strategies for constructing scientific models from three books, including studies in the history of genetics and electromagnetism, and an expert think-aloud study in the field of mechanics. The books focus on qualitative reasoning strategies (processes) involved in creative model construction, scientific breakthroughs, and conceptual change. Twenty four processes are examined, most of which are field-general, but all are heuristic in not being guaranteed to work. An organizing framework is then proposed as a four-level hierarchy of nested reasoning processes and subprocesses at different size and time scales, including: Level (L4) Several longer-time-scale Major Modeling Modes, such as Model Evolution and Model Competition; the former mode utilizes: (L3) Modeling Cycle Phases of Model Generation, Evaluation, and Modification under Constraints; which can utilize: (L2) Thirteen Tactical Heuristic Processes, e.g., Analogy, Infer new model feature (e.g., by running the model), etc.; many of which selectively utilize: (L1) Grounded Imagistic Processes, namely Mental Simulations and Structural Transformations. Incomplete serial ordering in the framework gives it an intermediate degree of organization that is neither anarchistic nor fully algorithmic. Its organizational structure is hypothesized to promote a difficult balance between divergent and convergent processes as it alternates between them in modeling cycles with increasingly constrained modifications. Videotaped think-aloud protocols that include depictive gestures and other imagery indicators indicate that the processes in L1 above can be imagistic. From neurological evidence that imagery uses many of the same brain regions as actual perception and action, it is argued that these expert reasoning processes are grounded in the sense of utilizing the perceptual and motor systems, and interconnections to and possible benefits for reasoning processes at higher levels are examined. The discussion examines whether this grounding and the various forms of organization in the framework may begin to explain how processes that are only sometimes useful and not guaranteed to work can combine successfully to achieve innovative scientific model construction.

Project description:Besides teachers' professional knowledge, their self-efficacy is a crucial aspect in promoting students' scientific reasoning (SR). However, because no measurement instrument has yet been published that specifically refers to self-efficacy beliefs regarding the task of teaching SR, we adapted the Science Teaching Efficacy Belief Instrument (STEBI) accordingly, resulting in the Teaching Scientific Reasoning Efficacy Beliefs Instrument (TSR-EBI). While the conceptual framework of the TSR-EBI is comparable to that of the STEBI in general terms, it goes beyond it in terms of specificity, acknowledging the fact that teaching SR requires very specific knowledge and skills that are not necessarily needed to the same extent for promoting other competencies in science education. To evaluate the TSR-EBI's psychometric quality, we conducted two rounds of validation. Both samples (N1 = 114; N2 = 74) consisted of pre-service teachers enrolled in university master's programs in Germany. The collected data were analyzed by applying Rasch analysis and known-group comparisons. In the course of an analysis of the TSR-EBI's internal structure, we found a 3-category scale to be superior to a 5-category structure. The person and item reliability of the scale proved to be satisfactory. Furthermore, during the second round of validation, it became clear that the results previously found for the 3-category scale were generally replicable across a new (but comparable) sample, which clearly supports the TSR-EBI's psychometric quality. Moreover, in terms of test-criterion relationships, the scale was also able to discriminate between groups that are assumed to have different levels of self-efficacy regarding teaching SR. Nonetheless, some findings also suggest that the scale might benefit from having the selection of individual items reconsidered (despite acceptable item fit statistics). On balance, however, we believe that the TSR-EBI has the potential to provide valuable insights in future studies regarding factors that influence teachers' self-efficacy, such as their professional experiences, prior training, or perceived barriers to effective teaching.

Dataset Information

Does Concrete Content Help People to Reason Scientifically?: Adaptation of Scientific Reasoning Scale.

Supplementary information

Publications

Does Concrete Content Help People to Reason Scientifically?: Adaptation of Scientific Reasoning Scale.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets