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An International Comparative Study of Students' Scientific Explanation Based on Cognitive Diagnostic Assessment.

ABSTRACT: Scientific explanation is one of the most core concepts in science education, and its mastery level is crucial for a deep understanding of the nature of science. As a new generation of assessment theory, cognitive diagnostic assessment (CDA) can get the knowledge of students' mastery of fine-grained knowledge. Based on the extant research, this research has formed eight attributes of scientific explanation concepts. By coding the Trends in International Mathematics and Science Study (TIMSS) test items, a CAD tool was formed. Data collected from 574 Grade 4 students in Hangzhou, China, combined with the data of the United States, Singapore, Australia, the United Kingdom, and Russia, were used in our study. The Deterministic Inputs, Noisy "And" gate (DINA) model was used to analyze the results from three aspects: the probability of mastery of attributes, the international comparison of knowledge states, and the analysis of learning paths. This study provided a new perspective from a CDA approach on the assessment of scientific explanation.

SUBMITTER: Hu T

PROVIDER: S-EPMC8718451 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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An International Comparative Study of Students' Scientific Explanation Based on Cognitive Diagnostic Assessment.

Hu Tao T Yang Jing J Wu Rongxiu R Wu Xiaopeng X

Frontiers in psychology 20211217

Scientific explanation is one of the most core concepts in science education, and its mastery level is crucial for a deep understanding of the nature of science. As a new generation of assessment theory, cognitive diagnostic assessment (CDA) can get the knowledge of students' mastery of fine-grained knowledge. Based on the extant research, this research has formed eight attributes of scientific explanation concepts. By coding the Trends in International Mathematics and Science Study (TIMSS) test ...[more]

PMID: 34975697

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Project description:As one of the most influential international large-scale educational assessments, the Program for International Student Assessment (PISA) provides a valuable platform for the horizontal comparisons and references of international education. The cognitive diagnostic model, a newly generated evaluation theory, can integrate measurement goals into the cognitive process model through cognitive analysis, which provides a better understanding of the mastery of students of fine-grained knowledge points. On the basis of the mathematical measurement framework of PISA 2012, 11 attributes have been formed from three dimensions in this study. Twelve test items with item responses from 24,512 students from 10 countries participated in answering were selected, and the analyses were divided into several steps. First, the relationships between the 11 attributes and the 12 test items were classified to form a Q matrix. Second, the cognitive model of the PISA mathematics test was established. The liner logistic model (LLM) with better model fit was selected as the parameter evaluation model through model comparisons. By analyzing the knowledge states of these countries and the prerequisite relations among the attributes, this study explored the different learning trajectories of students in the content field. The result showed that students from Australia, Canada, the United Kingdom, and Russia shared similar main learning trajectories, while Finland and Japan were consistent with their main learning trajectories. The primary learning trajectories of the United States and China were the same. Furthermore, the learning trajectory for Singapore was the most complicated, as it showed a diverse learning process, whereas the trajectory in the United States and Saudi Arabia was relatively simple. This study concluded the differences of the mastery of students of the 11 cognitive attributes from the three dimensions of content, process, and context across the 10 countries, which provided a reference for further understanding of the PISA test results in other countries and shed some evidence for a deeper understanding of the strengths and weaknesses of mathematics education in various countries.

Project description:BackgroundPreoperative assessment of whether a melanoma is invasive or in situ (MIS) is a common task that might have important implications for triage, prognosis and the selection of surgical margins. Several dermoscopic features suggestive of melanoma have been described, but only a few of these are useful in differentiating MIS from invasive melanoma.ObjectiveThe primary aim of this study was to evaluate how accurately a large number of international readers, individually as well as collectively, were able to discriminate between MIS and invasive melanomas as well as estimate the Breslow thickness of invasive melanomas based on dermoscopy images. The secondary aim was to compare the accuracy of two machine learning convolutional neural networks (CNNs) and the collective reader response.MethodsWe conducted an open, web-based, international, diagnostic reader study using an online platform. The online challenge opened on 10 May 2021 and closed on 19 July 2021 (71 days) and was advertised through several social media channels. The investigation included, 1456 dermoscopy images of melanomas (788 MIS; 474 melanomas ≤1.0 mm and 194 >1.0 mm). A test set comprising 277 MIS and 246 invasive melanomas was used to compare readers and CNNs.ResultsWe analysed 22 314 readings by 438 international readers. The overall accuracy (95% confidence interval) for melanoma thickness was 56.4% (55.7%-57.0%), 63.4% (62.5%-64.2%) for MIS and 71.0% (70.3%-72.1%) for invasive melanoma. Readers accurately predicted the thickness in 85.9% (85.4%-86.4%) of melanomas ≤1.0 mm (including MIS) and in 70.8% (69.2%-72.5%) of melanomas >1.0 mm. The reader collective outperformed a de novo CNN but not a pretrained CNN in differentiating MIS from invasive melanoma.ConclusionsUsing dermoscopy images, readers and CNNs predict melanoma thickness with fair to moderate accuracy. Readers most accurately discriminated between thin (≤1.0 mm including MIS) and thick melanomas (>1.0 mm).

Project description:BackgroundSelf-explanation without feedback has been shown to improve medical students' diagnostic reasoning. While feedback is generally seen as beneficial for learning, available evidence of the value of its combination with self-explanation is conflicting. This study investigated the effect on medical students' diagnostic performance of adding immediate or delayed content-feedback to self-explanation while solving cases.MethodsNinety-four 3rd-year students from a Canadian medical school were randomly assigned to three experimental conditions (immediate-feedback, delayed-feedback, control). In the learning phase, all students solved four clinical cases by giving i) the most likely diagnosis, ii) two main arguments supporting this diagnosis, and iii) two plausible alternative diagnoses, while using self-explanation. The immediate-feedback group was given the correct diagnosis after each case; delayed-feedback group received the correct diagnoses only after the four cases; control group received no feedback. One week later, all students solved four near-transfer (i.e., same final diagnosis as the learning cases but different scenarios) and four far-transfer cases (i.e., different final diagnosis from the learning cases and different scenarios) by answering the same three questions. Students' diagnostic accuracy (score for the response to the first question only) and diagnostic performance (combined score of responses to the three questions) scores were assessed in each phase. Four one-way ANOVAs were performed on each of the two scores for near and far-transfer cases.ResultsThere was a significant effect of experimental condition on diagnostic accuracy on near-transfer cases (p < .05). The immediate-feedback and delayed-feedback groups performed equally well, both better than control (respectively, mean = 90.73, standard deviation =10.69; mean = 89.92, standard deviation = 13.85; mean = 82.03, standard deviation = 17.66). The experimental conditions did not significantly differ on far-transfer cases.ConclusionsProviding feedback to students in the form of the correct diagnosis after using self-explanation with clinical cases is potentially beneficial to improve their diagnostic accuracy but this effect is limited to similar cases. Further studies should explore how more elaborated feedback combined with self-explanation may impact students' diagnostic performance on different cases.

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An International Comparative Study of Students' Scientific Explanation Based on Cognitive Diagnostic Assessment.

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An International Comparative Study of Students' Scientific Explanation Based on Cognitive Diagnostic Assessment.

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