Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Exploring Adolescents' Critical Reading of Socioscientific Topics Using Multimodal Texts.

ABSTRACT: This qualitative within-individual case design study involved six adolescents (age 10-14 years) engaging in a think-aloud observational protocol to read two texts on climate change from contrasting viewpoints. The participants completed a prior knowledge assessment and survey of technology used to assess potential mediating factors. Survey and observational data are presented as participant profiles. Results illustrated the effect of participants' background knowledge, emotional elicitation of text features, cognitive dissonance argument analysis due to the contrasting multimodal texts, and impact of visual images on participants' comprehension. Our data analyses revealed that there is an interconnected and nuanced relationship amongst many text and individual factors when adolescents engage in critical reading of SSI multimodal texts. This research provides direction for future science education research that support learners in critical reading of complex socioscientific topics as presented in multimodal texts with adolescent learners.

Supplementary information

The online version contains supplementary material available at 10.1007/s10763-022-10280-8.

SUBMITTER: Fazio X

PROVIDER: S-EPMC9052734 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

The Influence of Reading Texts on L2 Reading-to-Write Argumentative Writing.

Project description:Reading-to-write is an essential skill in academic writing, and reading-writing tasks have been widely adopted in standardized English tests. Much more recent literature on integrated reading-writing tasks has focused on writers' use of source texts or the validity of integrated writing assessment, while little is known about whether the nature of the types of reading texts has any bearing on integrated reading-writing tasks. This study examines whether the types of reading texts (i.e., similar views or opposing views on a debatable issue) have any influence on second language (L2) students' argumentative writing in terms of the use of argument elements and its overall quality. Fifty-four Chinese second-year university students majoring in English language teaching were asked to write an argumentative essay after reading texts with either similar views or opposing views. Results show that students reading texts with opposing viewpoints presented more data and higher overall quality of argumentative essays than students reading texts with similar viewpoints, although the latter group presented more counterargument data. Pedagogical implications on teaching argumentative writing are discussed.

| S-EPMC8017206 | biostudies-literature

Reading Fast, Reading Slow: The Effect of Interviewers' Speed in Reading Introductory Texts on Response Behavior.

Project description:Guidelines for interviewers frequently include instructions to read question texts exactly as they are worded. Deviations from these guidelines on standardized interviewing might affect the comparability of survey answers and impair the quality of data. This paper contributes to the literature on interviewer behavior by analyzing how interviewers change their reading behavior during fieldwork and whether this behavioral change influences the response behavior of survey respondents. We use item-level paradata from the Survey of Health, Ageing and Retirement in Europe (SHARE) to measure interviewers' reading times and focus our analyses on introductory questions that do not require an immediate response by the respondent. In contrast to prior research, this focus enables us to disentangle the reading times of interviewers from the response times of respondents. Based on fixed effects regression, our results show systematic changes in interviewers' reading times of introductory items: First, reading times significantly decrease over the survey's field period, even after controlling for relevant respondent characteristics and specific aspects of the interview situation. Second, a cross-national comparison, including fourteen European countries plus Israel, reveals that the decrease is uniform in almost all countries, suggesting its generalizability across different cultural contexts. Third, the decrease in reading times influences response behavior to varying degrees. Response behavior is affected if introductions contain relevant information for understanding or fulfilling the required task and especially if the response refers to within-survey requests. On the basis of these findings, we discuss the possible consequences for questionnaire design, interviewer training, and fieldwork monitoring.

| S-EPMC7147818 | biostudies-literature

Inferring multimodal latent topics from electronic health records.

Project description:Electronic health records (EHR) are rich heterogeneous collections of patient health information, whose broad adoption provides clinicians and researchers unprecedented opportunities for health informatics, disease-risk prediction, actionable clinical recommendations, and precision medicine. However, EHRs present several modeling challenges, including highly sparse data matrices, noisy irregular clinical notes, arbitrary biases in billing code assignment, diagnosis-driven lab tests, and heterogeneous data types. To address these challenges, we present MixEHR, a multi-view Bayesian topic model. We demonstrate MixEHR on MIMIC-III, Mayo Clinic Bipolar Disorder, and Quebec Congenital Heart Disease EHR datasets. Qualitatively, MixEHR disease topics reveal meaningful combinations of clinical features across heterogeneous data types. Quantitatively, we observe superior prediction accuracy of diagnostic codes and lab test imputations compared to the state-of-art methods. We leverage the inferred patient topic mixtures to classify target diseases and predict mortality of patients in critical conditions. In all comparison, MixEHR confers competitive performance and reveals meaningful disease-related topics.

| S-EPMC7242436 | biostudies-literature

Modulation of oculomotor control during reading of mirrored and inverted texts.

Project description:The interplay between cognitive and oculomotor processes during reading can be explored when the spatial layout of text deviates from the typical display. In this study, we investigate various eye-movement measures during reading of text with experimentally manipulated layout (word-wise and letter-wise mirrored-reversed text as well as inverted and scrambled text). While typical findings (e.g., longer mean fixation times, shorter mean saccades lengths) in reading manipulated texts compared to normal texts were reported in earlier work, little is known about changes of oculomotor targeting observed in within-word landing positions under the above text layouts. Here we carry out precise analyses of landing positions and find substantial changes in the so-called launch-site effect in addition to the expected overall slow-down of reading performance. Specifically, during reading of our manipulated text conditions with reversed letter order (against overall reading direction), we find a reduced launch-site effect, while in all other manipulated text conditions, we observe an increased launch-site effect. Our results clearly indicate that the oculomotor system is highly adaptive when confronted with unusual reading conditions.

| S-EPMC7060224 | biostudies-literature

Neurocognitive Signatures of Naturalistic Reading of Scientific Texts: A Fixation-Related fMRI Study.

Project description:How do students gain scientific knowledge while reading expository text? This study examines the underlying neurocognitive basis of textual knowledge structure and individual readers' cognitive differences and reading habits, including the influence of text and reader characteristics, on outcomes of scientific text comprehension. By combining fixation-related fMRI and multiband data acquisition, the study is among the first to consider self-paced naturalistic reading inside the MRI scanner. Our results revealed the underlying neurocognitive patterns associated with information integration of different time scales during text reading, and significant individual differences due to the interaction between text characteristics (e.g., optimality of the textual knowledge structure) and reader characteristics (e.g., electronic device use habits). Individual differences impacted the amount of neural resources deployed for multitasking and information integration for constructing the underlying scientific mental models based on the text being read. Our findings have significant implications for understanding science reading in a population that is increasingly dependent on electronic devices.

| S-EPMC6681173 | biostudies-literature

Differential brain mechanisms during reading human vs. machine translated fiction and news texts.

Project description:Few neuroimaigng studies on reading comprehension have been conducted under natural reading settings. In this study, we showed texts presented in a natural way during functional MRI (fMRI) measurements to reveal brain areas sensitive to reading comprehension. Specifically, this paradigm independently manipulated two holistic features of article style: text genre and translation style, a qualitative index of how typical word choices and arrangements are made in daily use of the language. Specifically, articles from The New York Times (news) and Reader's Digest (fiction) translated from English to Mandarin Chinese either by human experts or machine (Google Translate) were used to investigate the correlation of brain activity across participants during article reading. We found that bi-hemispheric visual cortex, precuneus, and occipito-parietal junction show significantly correlated hemodynamics across participants regardless of translation style and article genre. Compared to machine translation, reading human expert translation elicited more reliable fMRI signals across participants at precuneus, potentially because narrative representations and contents can be coherently presented over tens of seconds. We also found significantly stronger inter-subject correlated fMRI signals at temporal poles and fusiform gyri in fiction reading than in news reading. This may be attributed to more stable empathy processing across participants in fiction reading. The degree of stability of brain responses across subjects at extra-linguistic areas was found correlated with subjective rating on the text fluency. The functional connectivity between these areas was modulated by text genre and translation style. Taken together, our imaging results suggested stable and selective neural substrates associated with comprehending holistic features of written narratives.

| S-EPMC6744568 | biostudies-literature

Exploring climate change on Twitter using seven aspects: Stance, sentiment, aggressiveness, temperature, gender, topics, and disasters.

Project description:How do climate change deniers differ from believers? Is there any correlation between human sentiment and deviations from historic temperature? We answer nine such questions using 13 years of Twitter data and 15 million tweets. Seven aspects are explored, namely, user gender, climate change stance and sentiment, aggressiveness, deviations from historic temperature, topics discussed, and environmental disaster events. We found that: a) climate change deniers use the term global warming much often than believers and use aggressive language, while believers tweet more about taking actions to fight the phenomenon, b) deniers are more present in the American Region, South Africa, Japan, and Eastern China and less present in Europe, India, and Central Africa, c) people connect much more the warm temperatures with man-made climate change than cold temperatures, d) the same regions that had more climate change deniers also tweet with negative sentiment, e) a positive correlation is observed between human sentiment and deviations from historic temperature; when the deviation is between -1.143°C and +2.401°C, people tweet the most positive, f) there exist 90% correlation between sentiment and stance, and -94% correlation between sentiment and aggressiveness, g) no clear patterns are observed to correlate sentiment and stance with disaster events based on total deaths, number of affected, and damage costs, h) topics discussed on Twitter indicate that climate change is a politicized issue and people are expressing their concerns especially when witnessing extreme weather; the global stance could be considered optimistic, as there are many discussions that point out the importance of human intervention to fight climate change and actions are being taken through events to raise the awareness of this phenomenon.

| S-EPMC9491544 | biostudies-literature

Using precise word timing information improves decoding accuracy in a multiband-accelerated multimodal reading experiment.

Project description:The blood-oxygen-level-dependent (BOLD) signal measured in functional magnetic resonance imaging (fMRI) experiments is generally regarded as sluggish and poorly suited for probing neural function at the rapid timescales involved in sentence comprehension. However, recent studies have shown the value of acquiring data with very short repetition times (TRs), not merely in terms of improvements in contrast to noise ratio (CNR) through averaging, but also in terms of additional fine-grained temporal information. Using multiband-accelerated fMRI, we achieved whole-brain scans at 3-mm resolution with a TR of just 500 ms at both 3T and 7T field strengths. By taking advantage of word timing information, we found that word decoding accuracy across two separate sets of scan sessions improved significantly, with better overall performance at 7T than at 3T. The effect of TR was also investigated; we found that substantial word timing information can be extracted using fast TRs, with diminishing benefits beyond TRs of 1000 ms.

| S-EPMC5226857 | biostudies-literature

How to make causal inferences using texts.

Project description:Text as data techniques offer a great promise: the ability to inductively discover measures that are useful for testing social science theories with large collections of text. Nearly all text-based causal inferences depend on a latent representation of the text, but we show that estimating this latent representation from the data creates underacknowledged risks: we may introduce an identification problem or overfit. To address these risks, we introduce a split-sample workflow for making rigorous causal inferences with discovered measures as treatments or outcomes. We then apply it to estimate causal effects from an experiment on immigration attitudes and a study on bureaucratic responsiveness.

| S-EPMC9581481 | biostudies-literature

Exploring Topics in Bibliometric Research Through Citation Networks and Semantic Analysis.

Project description:This article surveys topic distributions of the academic literature that employs the terms bibliometrics, scientometrics, and informetrics. This exploration allows informing on the adoption of those terms and publication patterns of the authors acknowledging their work to be part of bibliometric research. We retrieved 20,268 articles related to bibliometrics and applied methodologies that exploit various features of the dataset to surface different topic representations. Across them, we observe major trends including discussions on theory, regional publication patterns, databases, and tools. There is a great increase in the application of bibliometrics as science mapping and decision-making tools in management, public health, sustainability, and medical fields. It is also observed that the term bibliometrics has reached an overall generality, while the terms scientometrics and informetrics may be more accurate in representing the core of bibliometric research as understood by the information and library science field. This article contributes by providing multiple snapshots of a field that has grown too quickly beyond the confines of library science.

| S-EPMC8498340 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data