17,840 results on '"Hypothesis testing"'
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2. EXPECTATIONS FOR THE SCHOOL BOARD ROLE AS RELATED TO LEVEL OF LOCAL FINANCIAL SUPPORT AND ALLOCATION OF EXPENDITURES.
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THORSON, JOHN R.
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TWO HYPOTHESES WERE TESTED--(1) NO SIGNIFICANT RELATIONSHIP EXISTS BETWEEN THE LEVEL OF EXPECTATIONS FOR THE FINANCIAL ASPECTS OF THE SCHOOL BOARD ROLE AND THE LEVEL OF LOCAL FINANCIAL SUPPORT, AND (2) NO SIGNIFICANT RELATIONSHIP EXISTS BETWEEN THE LEVEL OF EXPECTATIONS FOR SELECTED EXPENDITURES AND THE AMOUNT OF FUNDS ALLOCATED FOR THESE EXPENDITURES. EXPECTATIONS FOR THE SCHOOL BOARD ROLE WERE MEASURED BY AN INTERVIEW INSTRUMENT IN 12 WISCONSIN SCHOOL DISTRICTS. SUBJECTS OF THE STUDY WERE 150 CITIZENS, 20 TEACHERS, AND ALL SCHOOL AND MUNICIPAL OFFICIALS. THE FIRST HYPOTHESIS WAS SUBJECTED TO 16 SEPARATE TESTS, AND ONLY ONE PROVED SIGNIFICANT. THE SECOND, SUBJECTED TO 36 TESTS, RESULTED IN NINE SIGNIFICANT RELATIONSHIPS (NOT ENOUGH TO REJECT THE HYPOTHESIS). IMPLICATIONS AND CONCLUSIONS DRAWN FROM THE STUDY INCLUDED--(1) HOLDING PREFERENCES FOR PARTICULAR SCHOOL PROGRAMS MAY NOT BE THE SAME AS BEING WILLING TO PAY FOR THEM, (2) THERE MAY BE A DIFFERENCE BETWEEN RESPONDING FAVORABLY TOWARD FINANCIAL SUPPORT FOR SCHOOLS IN AN INTERVIEW AND ACTUAL FINANCIAL COMMITMENT, (3) EXPECTATIONS FOR EXPENDITURES MAY NOT EXIST AS A SINGLE IDENTIFIABLE CONCEPT, AND (4) THE SIGNIFICANT RELATIONSHIPS WHICH WERE FOUND WERE ACTUALLY INSIGNIFICANT ITEMS IN TERMS OF THE TOTAL SCHOOL BUDGET. (HW) more...
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- 2024
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3. The Impact of Digital Transformation and Leadership on Organizational Resilience in Distance Education Institution: Higher-Order SEM Approach
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Firmansyah, Gustriza Erda, and Arie Wibowo Khurniawan
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To overcome the difficulty and unprecedented suspensions due to the COVID-19 pandemic, every organization is required to consider strategic steps to sustain, one of which is by implementing digital transformation and developing leadership capability. This study aims to determine the impact of digital transformation and leadership capability in maintaining the organization, particularly in distance education. This study used questionnaires distributed to 402 students to obtain their opinions on digital transformation, leadership capability, and organizational resilience in Universitas Terbuka, a founder of distance education institutions in Indonesia. Data were analyzed using descriptive and Higher-Order Structural Equation Modeling analysis. Based on the modelling, it is shown that the modelling had a good value of the Goodness of Fit Indicator through a standardized loading factor (SLF) more than the tolerable loading factor limit (>0.50). The Variance Extracted (VE) and Construct Reliability (CR) values also showed that the questions on every indicator used in this study were sufficiently measurable and reliable. The results of hypothesis testing indicated that there was a positive and significant impact of digital transformation and leadership capability on the organizational resilience of Universitas Terbuka. more...
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- 2024
4. Attitudes in Mathematical Discovery Processes: The Case of Alex and Milo
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Carolin Danzer
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This paper's purpose is to investigate the attitude of students in mathematical discovery processes in terms of the handling of counterexamples. By understanding this attitude as a kind of scientific attitude, it consists of different aspects that become visible in the behaviour during a mathematical discovery process. Since such a process is particularly complex, the author's interest is to use the concept of attitude as an explanation for students' behaviour that occurs when dealing with conflicts such as counterexamples. Semi-structured interviews with sixth graders of a German Gymnasium were conducted and analysed in a qualitative and interpretative way. As a result, the case study of Alex and Milo is presented. Based on the framework that observable behaviour is influenced by an underlying attitude, there are drawn conclusions about Alex's and Milo's attitudes adopted in the mathematical discovery process and their impact on the process is elaborated. more...
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- 2024
5. Concrete Counterfactual Tests for Process Tracing: Defending an Interventionist Potential Outcomes Framework
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Rosa W. Runhardt
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This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to corroborate process tracing claims. In particular, three steps are prescribed for an interventionist investigation, and each step in turn is shown to make the causal analysis more robust, amongst others by disambiguating causal claims and clarifying or strengthening the existing methodological advice on counterfactual analysis. The article's claims are then illustrated using a concrete example, Haggard and Kaufman's analysis of the Argentinian transition to democracy. It is shown that interventionism could have strengthened the authors' conclusions. The article concludes with a short Bayesian analysis of its key methodological proposals. more...
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- 2024
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6. A Tutorial on Aggregating Evidence from Conceptual Replication Studies Using the Product Bayes Factor
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Caspar J. Van Lissa, Eli-Boaz Clapper, and Rebecca Kuiper
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The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and measures used. PBF shines as a solution for small sample meta-analyses, where the number of between-study differences is often large relative to the number of studies, precluding the use of meta-regression to account for these differences. Users should be mindful of the fact that the PBF answers a qualitatively different research question than other evidence synthesis methods. For example, whereas fixed-effect meta-analysis estimates the size of a population effect, the PBF quantifies to what extent an informative hypothesis is supported in all included studies. This tutorial paper showcases the user-friendly PBF functionality within the bain R-package. This new implementation of an existing method was validated using a simulation study, available in an Online Supplement. Results showed that PBF had a high overall accuracy, due to greater sensitivity and lower specificity, compared to random-effects meta-analysis, individual participant data meta-analysis, and vote counting. Tutorials demonstrate applications of the method on meta-analytic and individual participant data. The example datasets, based on published research, are included in bain so readers can reproduce the examples and apply the code to their own data. The PBF is a promising method for synthesizing evidence for informative hypotheses across conceptual replications that are not suitable for conventional meta-analysis. more...
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- 2024
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7. Inquiry-Guided Learning in Statistics Education: Enhancing Student Understanding of Type I Error through the Use of an Animated Space Exploration Video
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Kevin L. Sager, Miho Aoki, and Scott D. Goddard
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We tested the educational effectiveness of an inquiry-guided approach (Lee et al., 2004; Prince & Felder in "Journal of Engineering Education, 95," 123-138, 2006) to teaching a possible outcome of statistical hypothesis testing known as type 1 error. The approach consisted of showing participants an animated space exploration video. In the video, the commander of a spaceship set out to determine whether the concentration of carbon dioxide on a distant planet exceeded the concentration found on Earth. To make this determination, the commander conducted a series of hypothesis tests. One of the tests suggested that the concentration of carbon dioxide was significantly higher than that on Earth. However, when juxtaposed with the results of the other hypothesis tests, the lone decision to reject the null hypothesis appeared to be a type 1 error. The video's educational effectiveness was evaluated in two ways. First, participants responded to a set of multiple-choice questions on type 1 error, both before and after watching the video. Participants' scores on the multiple-choice test increased significantly from pre-test to post-test. Second, participants rated the video on a set of semantic differential items that tapped its educational effectiveness. On average, participants found the video to be educationally effective. The article concludes with an evaluation of the video's features based on established best practices in statistics education (GAISE College Report ASA Revision Committee, 2016). more...
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- 2024
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8. Conceptual Modeling Enables Systems Thinking in Sustainable Chemistry and Chemical Engineering
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Leonie E. Krab-Hu¨sken, Linlin Pei, Pepijn G. de Vries, Saskia Lindhoud, Jos M. J. Paulusse, Pascal Jonkheijm, and Albert S. Y. Wong
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This study aims to equip students with conceptual modeling skills to address compelling 21st-century challenges in chemistry and chemical engineering education. System-based concept mapping is a critical competence for analyzing global, often complex, problems. We examined how conceptual modeling could scaffold practical experimental design, transitioning from problem identification to testable hypotheses. We set up a project in which first-year undergraduates in chemical engineering work in groups of 5-6 students. Their task was to develop concrete hypotheses for assignments that center on finding sustainable solutions for polluted environments. A set of educational roles (i.e., lecturers, tutors, learning assistants, educational specialist, and project coordinator) were implemented to ensure that students could accomplish their main learning outcome; that is, to become familiar with the academic way of thinking and apply critical thinking skills as a team. Interviews were conducted after the project was finished and revealed that, while conceptual modeling helped students to structure their ideas (i.e., to learn how to design research questions, incorporate interventions, and test models), developing hypotheses remains a challenging task. Our findings brought us to the recommendations for teaching conceptual modeling in the curriculum rather than at the project level, allowing students to progressively transition from understanding and applying concept mapping in their first year into creating solutions within the context of solving complex real-world problems in the final year of their bachelor's degree. The collaborative learning environment and project format employed in this work could spark new ways to teach science that facilitates systems thinking in chemistry. more...
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- 2023
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9. Analysing Students' Concept Mapping Style and Its Association with Task Performance in Computer-Based Inquiry Learning
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Juanjuan Chen, Minhong Wang, Tina A. Grotzer, and Chris Dede
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Background: In scientific inquiry learning, students often have difficulties conducting hypothetical reasoning with multiple intertwined variables. Concept maps have a potential to facilitate complex thinking and reasoning. However, there is little investigation into the content of student-constructed concept maps and its association with inquiry task performance. Objectives: This study explored students' concept mapping style and its association with task performance in computer-based inquiry learning. Methods: An exploratory study was conducted with 80 Grade 11 students, who collaboratively constructed concept maps in a free style to support inquiry learning with a virtual ecosystem. Student-constructed concept maps was analysed by firstly identifying different types of propositions formed in the maps and then determining the style of each concept map based on the dominant type of propositions in the map. Finally, the association between the concept map style and inquiry task performance was explored. Results and Conclusions: Two major concept map styles were identified: (1) knowledge-oriented concept maps (KCMs) mainly representing problem-related subject knowledge as a set of concepts and their relationships, and (2) problem-oriented concept maps (PCMs) mainly representing problem situation as a sequence of changes and their causal relationships. Compared with those constructing KCMs, the students constructing PCMs formed higher-quality propositions in their maps and performed better in hypothesising, reasoning, and drawing conclusions in the inquiry task. Implications: Besides KCMs, students in inquiry learning can be encouraged to construct PCMs to foster effective thinking and reasoning; that is, constructing a concept map to represent the problem situation as a sequence of changes and the causal relationships between the changes. more...
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- 2024
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10. Modeling Nonlinear Effects of Person-by-Item Covariates in Explanatory Item Response Models: Exploratory Plots and Modeling Using Smooth Functions
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Sun-Joo Cho, Amanda Goodwin, Matthew Naveiras, and Paul De Boeck
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Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are linear. However, this linearity assumption obscures the differential effects of covariates over their range in the presence of nonlinearity. Therefore, this paper presents exploratory plots that describe the potential nonlinear effects of person and item covariates on binary outcome variables. This paper also illustrates the use of EIRMs with smooth functions to model these nonlinear effects. The smooth functions examined in this study include univariate smooths of continuous person or item covariates, tensor product smooths of continuous person and item covariates, and by-variable smooths between a continuous person covariate and a binary item covariate. Parameter estimation was performed using the mgcv R package through the maximum penalized likelihood estimation method. In the empirical study, we identified a nonlinear effect of the person-by-item covariate interaction and discussed its practical implications. Furthermore, the parameter recovery and the model comparison method and hypothesis testing procedures presented were evaluated via simulation studies under the same conditions observed in the empirical study. [This is the online first version of an article published in "Journal of Educational Measurement" (ISSN 1745-3984).] more...
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- 2024
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11. Use of the Model Statement in Determining the Veracity of Opinions
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Samantha Mann, Aldert Vrij, and Haneen Deeb
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We examined the efficacy of a Model Statement to detect opinion lies. A total of 93 participants discussed their opinion about the recent strikes on two occasions, 1 week apart. In one interview they told the truth and in the other interview they lied. Each interview consisted of two phases. In Phase 1 they discussed their alleged opinion (truth or lie as appropriate). They then either listened to a Model Statement (a detailed account of someone discussing an opinion about a topic unrelated to strike actions) and expressed their opinion again in Phase 2 (Model Statement present condition) or they discussed their opinion again without listening to a Model Statement (Model Statement absent condition). The verbal cues examined were pro-opinion arguments, anti-opinion arguments, plausibility, immediacy, directness, clarity, and predictability. The truthful statements sounded more plausible in Phases 1 and 2 than the deceptive statements, providing further evidence that plausibility is a strong veracity indicator. The truthful statements included more pro-arguments and sounded more immediate and direct than the deceptive statements, but only in Phase 2. The Model Statement had no effect. Reasons for the Model Statement null-effect are discussed. more...
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- 2024
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12. An Improved Inferential Procedure to Evaluate Item Discriminations in a Conditional Maximum Likelihood Framework
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Clemens Draxler, Andreas Kurz, Can Gürer, and Jan Philipp Nolte
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A modified and improved inductive inferential approach to evaluate item discriminations in a conditional maximum likelihood and Rasch modeling framework is suggested. The new approach involves the derivation of four hypothesis tests. It implies a linear restriction of the assumed set of probability distributions in the classical approach that represents scenarios of different item discriminations in a straightforward and efficient manner. Its improvement is discussed, compared to classical procedures (tests and information criteria), and illustrated in Monte Carlo experiments as well as real data examples from educational research. The results show an improvement of power of the modified tests of up to 0.3. more...
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- 2024
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13. Unraveling Temporal Dynamics of Multidimensional Statistical Learning in Implicit and Explicit Systems: An X-Way Hypothesis
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Stephen Man-Kit Lee, Nicole Sin Hang Law, and Shelley Xiuli Tong
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Statistical learning enables humans to involuntarily process and utilize different kinds of patterns from the environment. However, the cognitive mechanisms underlying the simultaneous acquisition of multiple regularities from different perceptual modalities remain unclear. A novel multidimensional serial reaction time task was developed to test 40 participants' ability to learn simple first-order and complex second-order relations between uni-modal visual and cross-modal audio-visual stimuli. Using the difference in reaction times between sequenced and random stimuli as the index of domain-general statistical learning, a significant difference and dissociation of learning occurred between the initial and final learning phases. Furthermore, we used a negative and positive occurrence-frequency-and-reaction-time correlation to indicate implicit and explicit learning, respectively, and found that learning simple uni-modal patterns involved an implicit-to-explicit segue, while acquiring complex cross-modal patterns required an explicit-to-implicit segue, resulting in a X-shape crossing of regularity learning. Thus, we propose an X-way hypothesis to elucidate the dynamic interplay between the implicit and explicit systems at two distinct stages when acquiring various regularities in a multidimensional probability space. more...
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- 2024
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14. First Year University Students Ways of Reasoning and Argumentation in Problem-Solving Activities = Formas de razonar y argumentar en actividades de resolución de problemas de estudiantes de primer año de universidad
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Tania Azucena Chicalote Jiménez and Daniel José Ortiz May
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The aim of this study is to characterize ways of reasoning and arguing that first year university mathematics students exhibit in problem-solving activities from a course that emphasizes the importance of formulating conjectures and the search for different ways to support or validate them. The use of a Dynamic Geometry System in the representation of problems and in the formulation of conjectures or relationships that are important in the solution processes is highlighted. In this context, students have the opportunity to look for different ways to argue and support the relevance and validity of the conjectures. Results indicate that students extend their ways of reasoning so that allows them to move from empirical to formal arguments within problem solutions. [For the complete proceedings, see ED657822.] more...
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- 2023
15. Pre-Service Mathematics Teachers Investigating the Attributes of Inscribed Circles by Technological and Theoretical Scaffolding
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Segal, Ruti and Stupel, Moshe
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The benefits of technological and theoretical scaffolding were observed when pre-service teachers aiming to teach upper elementary grades were given three learning-based geometrical inquiry tasks involving inscribed circles. They were asked to collaboratively examine the accompanying geometrical illustration and data for some new or interesting feature and then propose a hypothesis resulting from their observations and prove them. Due to the difficulty generally involved in proposing and proving geometrical hypotheses, two forms of scaffolding were provided: theoretical scaffolding based on revising previous learning or specific attributes of the given data and technological scaffolding in the form of specifically designed GeoGebra applets that allowed dynamic observation of the attributes of the geometrical shapes and the changes they underwent during modification. We found that the two forms of scaffolding led to relatively pre-service teachers' high levels of success. They exhibited high levels of interest and participation, were engaged in the tasks, and underwent high-quality learning processes. In follow-up interviews, they confirmed that the exercise improved their inquiry skills, and developed their pedagogical and technological knowledge. more...
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- 2023
16. Informative Hypothesis for Group Means Comparison
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Tan, Teck Kiang
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Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons if the null hypothesis is rejected. As this approach is not able to incorporate order, inequality, and direction into hypothesis testing, and neither does it able to specify multiple hypotheses, this paper introduces the informative hypothesis that allows more flexibility in stating hypothesis testing and is directly targeted to address and state the researcher's study concern. The two new hypothesis terms under the informative hypothesis framework, the unconstrained and complementary hypotheses are introduced, and the approaches to state the level of evidence using the Bayes factor and Generalization AIC are elaborated. As this hypothesis conception is relatively new and the literature was mostly technical, the main aims of the paper are to introduce this conception, offer a general guideline, and provide an easy-to-read approach to the procedure with practical examples of carrying out this hypothesis approach and contrast it to the frequentist, using the R package. more...
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- 2023
17. A Corpus-Driven Approach on Learning near Synonyms of Pain in Indonesian
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Leo, Haniva Yunita
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Pain is human-universal since it is experienced by people across the world. However, since it is related to personal feelings, different people may feel it in a different way and rely on language to communicate. This paper presents a cross-cultural comparison of the study of the emotion of pain in Indonesian by examining the usage of two near-synonyms: "sakit" and "nyeri." This study aims to provide a new insight for L2 learners of Indonesian regarding the study of emotion. A corpus-driven method by using the usage-feature analysis (Glynn, 2010b) is employed to test the hypothesis on the semasiological structure of pain from Indonesian dictionary. The corpus data of Indonesian News 2020 with a total of 15,206,710 tokens were extracted from the Leipzig Corpora Data Collection of Indonesian (Goldhahn et al., 2012). A total of 400 examples of "sakit" and "nyeri" were extracted from the corpus data using AntConc version 4.1.2 (Laurence, 2022) for manual annotation. The manual coding of the lexemes was conducted based on cross-linguistic dimensions of pain proposed by Wierzbicka (2016). After manual annotation, two statistical analyses were conducted in R (R Core Team, 2022), namely Binary Correspondence Analysis (Glynn, 2014) and Binomial Regression Analysis (Levshina, 2015). The result of exploratory analysis shows that "sakit" and "nyeri" can be distinguished by bodily focus and intensity. However, the confirmatory analysis confirms bodily focus as the significant predictor. It means "nyeri" is strongly associated with pain on the part of body relative to "sakit." The finding of the current study may have an implication for the possibility of combining cross-cultural competence with L2 vocabulary learning by making use of corpora in L2 learning design. more...
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- 2023
18. What Enabled the Production of Mathematical Knowledge in Complex Analysis?
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Piña-Aguirre, José Gerardo and Farfán Márquez, Rosa María
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With the objective of identifying intrinsic forms of mathematical production in complex analysis (CA), this study presents an analysis of the mathematical activity of five original works that contributed to the development of Cauchy's integral theorem. The analysis of the mathematical activity was carried out through the identification of the types of expressions used and the way they were used by the historical subjects when communicating their results, to subsequently identify transversal elements of knowledge production. The analysis was refined by the notion of confrontation, which depicts the development of mathematical knowledge through the idea of building knowledge against previous knowledge. As a result of the study we established epistemological hypothesis, which are conceived as conjectures that reveal ways in which mathematical knowledge was generated in CA. more...
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- 2023
19. Design Principles for Simulation-Based Learning of Hypothesis Testing in Secondary School
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Per Nilsson and Andreas Eckert
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This study contributes to the call for influencing practice by increasing attention to how learning environments can be designed to support learning in statistical inference. We report on a design experiment in secondary school (students 14-16 years old), that resulted in a set of lessons with the learning goal of teaching students how to apply concepts and principles of hypothesis testing for making an inference as to whether or not students in secondary school can taste the difference between two brands of cola soda. The design experiment resulted in four design principles for a simulation-based approach for learning hypothesis testing in secondary school. The design principles highlight the combination of practical and digital simulations of samplings. They stress the need for using random generators that allow for high reliability in collecting sample data and introduce a simulation-based method for determining p-values, i.e. to quantify how likely or surprising a sample result, or a result more extreme, is under a null hypothesis. more...
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- 2024
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20. The Psychological Reality of the Learned 'P < .05' Boundary
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V. N. Vimal Rao, Jeffrey K. Bye, and Sashank Varma
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The 0.05 boundary within Null Hypothesis Statistical Testing (NHST) "has made a lot of people very angry and been widely regarded as a bad move" (to quote Douglas Adams). Here, we move past meta-scientific arguments and ask an empirical question: What is the psychological standing of the 0.05 boundary for statistical significance? We find that graduate students in the psychological sciences show a "boundary effect" when relating p-values across 0.05. We propose this psychological boundary is learned through statistical training in NHST and reading a scientific literature replete with "statistical significance". Consistent with this proposal, undergraduates do not show the same sensitivity to the 0.05 boundary. Additionally, the size of a graduate student's boundary effect is not associated with their explicit endorsement of questionable research practices. These findings suggest that training creates distortions in initial processing of p-values, but these might be dampened through scientific processes operating over longer timescales. more...
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- 2024
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21. Repurposing Video Games as Discussion Tools
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Joshua M. Patterson
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Numerous video games marketed entirely for entertainment purposes, also known as commercial, off-the-shelf (COTS) titles, can serve as an effective tool for teaching students complicated skills such as executive functioning, hypothesis testing, and critical analysis. In this phenomenological case study, I outline a pedagogical approach that harnesses the trinity of content knowledge, discursive prowess, and video game aptitude by capitalizing on pupils' preference for digital integration. Video game titles were selected according to their scores on Rice's (2007) "Video Game Higher-Order Thinking Evaluation Rubric" and "Video Game Cognitive Viability Scale," with lessons tied to Florida's Next Generation Sunshine State Standards for social studies. The implication of this study is that COTS titles offer an alternative curricular entry point, which can elicit higher-order discussions when paired with pointed, teacher-led inquiry. This methodology, if properly harnessed, could transmit subject manner more effectively and create critically reflective, game-based learning cohorts. more...
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- 2024
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22. Exploring the Fetal Origins Hypothesis Using Genetic Data
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Sam Trejo
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Birth weight is a robust predictor of valued life course outcomes, emphasizing the importance of prenatal development. But does birth weight act as a proxy for environmental conditions in utero, or do biological processes surrounding birth weight themselves play a role in healthy development? To answer this question, we leverage variation in birth weight that is, within families, orthogonal to prenatal environmental conditions: one's genes. We construct polygenic scores in two longitudinal studies (Born in Bradford, N = 2008; Wisconsin Longitudinal Study, N = 8488) to empirically explore the molecular genetic correlates of birth weight. A 1 standard deviation increase in the polygenic score is associated with an ~100-grams increase in birth weight and a 1.4 pp (22 percent) decrease in low birth weight probability. Sibling comparisons illustrate that this association largely represents a causal effect. The polygenic score-birth weight association is increased for children who spend longer in the womb and whose mothers have higher body mass index, though we find no differences across maternal socioeconomic status. Finally, the polygenic score affects social and cognitive outcomes, suggesting that birth weight is itself related to healthy prenatal development. [This is the online first version of an article published in "Social Forces."] more...
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- 2024
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23. Presenting Domain Information or Self-Exploration to Foster Hypothesis Generation in Simulation-Based Inquiry Learning
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Xiulin Kuang, Tessa H. S. Eysink, and Ton de Jong
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This study investigated the effects of presenting domain information (basic information about the domain) either together with or instead of offering exploratory practice (an exploratory opportunity in a simulation-based representation of the learning domain) prior to inquiry learning for facilitating students' hypothesis generation and subsequent inquiry processes and their knowledge acquisition. Secondary school students (n = 118) completed a simulation-based inquiry task on force and motion. They were randomly assigned to one of four conditions: the D + E condition (n = 29), in which domain information and exploratory practice were available; the D condition (n = 30), in which only domain information was available; the E condition (n = 32), in which only exploratory practice was available; or the C condition (n = 27), with no support at all. Students' knowledge was measured with a pre- and posttest and a test on knowledge of variables. Inquiry processes were inferred from information students entered in a Hypothesis Scratchpad and an Observation tool, and from a final summary that they had to write. Results indicated that providing students with domain information alone helps to foster their knowledge of variables before generating hypotheses and leads to knowledge acquisition. The results also showed that the opportunity to explore before experimenting does not affect students' inquiry behavior or learning performance, even when combined with providing students with domain information. more...
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- 2024
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24. Emergent Learning about Measurement and Uncertainty in an Inquiry Context: A Case from an Elementary Classroom
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Tang, Xiaowei, Shu, Gang, Wei, Bing, and Levin, Daniel
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Students often learn about measurement uncertainty as an isolated topic, with a focus on generalizable strategies to manage uncertainty in scientific investigation. In this study, we report and analyze a case of emergent learning about measurement and uncertainty, in which students in a Chinese elementary school science class explored and reconciled discrepancies in hypotheses by constructing and using measures and making inferences. Adopting a model-based view of measurement, we show that when allowed to take on emergent measurement uncertainty while inquiring into causes for phenomena, late elementary students with no prior experience can engage in sophisticated reasoning characterized by a variety of theoretical modeling practices. Developing and aligning models of the phenomenon, the measure and the measurement data supported students in constructing an intuitive solution to their discrepancies. Our analysis also identified (1) a pattern of thinking and some common assumptions students adopted in their modeling practice that were productive, and (2) contextual elements affording and constraining emergent learning on measurement and uncertainty. In our discussion, we reflect on the educational potential of adopting a model-based account of measurement and of treating measurement and uncertainty as integrated into investigative practice. We also discuss the necessary contexts for realizing the potential of the model-based account. more...
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- 2024
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25. Overall Model Fit Does Not Imply Linearity in Longitudinal Structural Equation Models: Examining Linear Change over Time Using Latent Variable Modeling
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Tenko Raykov, Christine DiStefano, and Natalja Menold
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This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal structural models with covariates, or models for the study of predictors and correlates of change. In empirical research applications, currently behavioral and social scientists typically evaluate only overall goodness of fit for a considered model. However, this omnibus fit assessment may miss violations of the underlying linearity assumption. To respond to this limitation, the present article discusses a testing procedure for examining the hypothesis of linear growth or decline separately from the widely used overall fit evaluation process. The method is readily utilized with popular latent variable modeling software and is illustrated using a numerical example. more...
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- 2024
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26. Minimal-Effect Testing, Equivalence Testing, and the Conventional Null Hypothesis Testing for the Analysis of Bi-Factor Models
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Shunji Wang, Katerina M. Marcoulides, Jiashan Tang, and Ke-Hai Yuan
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A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes using minimal-effect testing (MET) and equivalence testing (ET) to analyze bi-factor models. A key element in conducting MET and ET is the minimal size of factor loadings that can be regarded as noteworthy in practice, termed as "minimal noteworthy size." This article presents two approaches to formulating the minimal noteworthy size and compares the pros and cons of MET, ET, and the conventional NHT. Analysis shows that MET, ET, and the conventional NHT are complementary. Combining them to test the noteworthiness of domain loadings can help researchers make a comprehensive judgment. Real and simulated datasets illustrate the applications of the three methods. Monte Carlo results show that MET and ET can control type I errors reasonably well while maintaining good statistical power. more...
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- 2024
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27. Effects of Task Structure and Confirmation Bias in Alternative Hypotheses Evaluation
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Mandeep K. Dhami, Ian K. Belton, Peter De Werd, Velichka Hadzhieva, and Lars Wicke
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We empirically examined the effectiveness of how the Analysis of Competing Hypotheses (ACH) technique structures task information to help reduce confirmation bias (Study 1) and the portrayal of intelligence analysts as suffering from such bias (Study 2). Study 1 (N = 161) showed that individuals presented with hypotheses in rows and evidence items in columns were significantly less likely to demonstrate confirmation bias, whereas those presented with the ACH-style matrix (with hypotheses in columns and evidence items in rows) or a paragraph of text (listing the evidence for each hypothesis) were not less likely to demonstrate bias. The ACH-style matrix also did not confer any benefits regarding increasing sensitivity to evidence credibility. Study 2 showed that the majority of 62 Dutch military analysts did not suffer from confirmation bias and were sensitive to evidence credibility. Finally, neither judgmental coherence nor cognitive reflection differentiated between better or worse performers in the hypotheses evaluation tasks. more...
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- 2024
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28. Piloting a Decision Tool to Guide Individualized Hypothesis Testing for Students with Severe and Complex Challenging Behavior
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Blair P. Lloyd, Jessica N. Torelli, Marney S. Pollack, and Emily S. Weaver
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For students with severe or complex challenging behavior, incorporating hypothesis testing as a component of functional behavior assessment (FBA) is often warranted. Several hypothesis testing strategies (i.e., functional analysis, antecedent analysis, concurrent operant analysis) can confirm whether and how features of a student's environment impact their behavior to then inform effective intervention. Yet practitioners have limited guidance on how to select and individualize best-fit strategies for a given student and context. We developed a decision tool for behavior specialists and classroom teachers to collaboratively plan and implement individualized hypothesis testing strategies for students whose initial FBA was inconclusive. We piloted this tool with 12 practitioner teams and students, aiming to (a) identify which assessment strategies were indicated based on practitioner responses; (b) evaluate whether indicated assessments produced conclusive results; and (c) explore practitioner perceptions of the individualized assessment process. The most commonly indicated hypothesis testing strategy was functional analysis. Across teams, one or more hypothesis was successfully confirmed on the first or second assessment iteration. The assessment process was perceived positively by practitioners. Yet they reported feeling ill-equipped to complete the process independently, highlighting important next steps for training and technical assistance work. more...
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- 2024
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29. Hypothesis Testing for Hierarchical Structures in Cognitive Diagnosis Models
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Chenchen Ma and Gongjun Xu
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Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models widely used in educational, psychological and social sciences. In many applications of CDMs, certain hierarchical structures among the latent attributes are assumed by researchers to characterize their dependence structure. Specifically, a directed acyclic graph is used to specify hierarchical constraints on the allowable configurations of the discrete latent attributes. In this paper, we consider the important yet unaddressed problem of testing the existence of latent hierarchical structures in CDMs. We first introduce the concept of testability of hierarchical structures in CDMs and present sufficient conditions. Then we study the asymptotic behaviors of the likelihood ratio test (LRT) statistic, which is widely used for testing nested models. Due to the irregularity of the problem, the asymptotic distribution of LRT becomes nonstandard and tends to provide unsatisfactory finite sample performance under practical conditions. We provide statistical insights on such failures, and propose to use parametric bootstrap to perform the testing. We also demonstrate the effectiveness and superiority of parametric bootstrap for testing the latent hierarchies over non-parametric bootstrap and the naïve Chi-squared test through comprehensive simulations and an educational assessment dataset. more...
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- 2022
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30. Piloting a Decision Tool to Guide Individualized Hypothesis Testing for Students with Severe and Complex Challenging Behavior
- Author
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Blair P. Lloyd, Jessica N. Torelli, Marney S. Pollack, and Emily S. Weaver
- Abstract
For students with severe or complex challenging behavior, incorporating hypothesis testing as a component of functional behavior assessment (FBA) is often warranted. Several hypothesis testing strategies (i.e., functional analysis, antecedent analysis, concurrent operant analysis) can confirm whether and how features of a student's environment impact their behavior to then inform effective intervention. Yet practitioners have limited guidance on how to select and individualize best-fit strategies for a given student and context. We developed a decision tool for behavior specialists and classroom teachers to collaboratively plan and implement individualized hypothesis testing strategies for students whose initial FBA was inconclusive. We piloted this tool with 12 practitioner teams and students, aiming to (a) identify which assessment strategies were indicated based on practitioner responses; (b) evaluate whether indicated assessments produced conclusive results; and (c) explore practitioner perceptions of the individualized assessment process. The most commonly indicated hypothesis testing strategy was functional analysis. Across teams, one or more hypothesis was successfully confirmed on the first or second assessment iteration. The assessment process was perceived positively by practitioners. Yet they reported feeling ill-equipped to complete the process independently, highlighting important next steps for training and technical assistance work. [This paper was published in "Journal of Behavioral Education" v33 p208-232 2024.] more...
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- 2022
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31. The BASIE (BAyeSian Interpretation of Estimates) Framework for Interpreting Findings from Impact Evaluations: A Practical Guide for Education Researchers. Toolkit. NCEE 2022-005
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National Center for Education Evaluation and Regional Assistance (NCEE) (ED/IES), Mathematica, Deke, John, Finucane, Mariel, and Thal, Daniel
- Abstract
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide also provides conceptual and technical details for evaluation methodologists. more...
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- 2022
32. Teaching Descriptive Statistics and Hypothesis Tests Measuring Water Density
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Roberto Silva de Souza and Endler Marcel Borges
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This laboratory experiment was divided into four parts. In the first part, students evaluate previously published data and check their normality using histograms, Q-Q plots, the Shapiro-Wilk test, and boxplots. In the second part, two different groups were compared. First, data normality and homoskedasticity were checked by using the Shapiro-Wilk test and Levene's test, respectively. Then the group mean was compared using the Student, Welch, and Mann-Whitney tests. In the third part, the famous Iris flower data set was analyzed, where data normality and homoskedasticity were checked. Then, three independent groups were compared using ANOVA, without correction, and using the Welch and Brown-Forsythe corrections. The Iris flowers data set was also compared using the nonparametric version of ANOVA (Kruskal-Wallis test) and post hoc tests such as the Tukey test (parametric) and Dunn's test (nonparametric). In the fourth part, students measured the density of water using four pieces of glassware (a beaker, a graduated cylinder, a volumetric pipet, and a graduated pipet). After the experiment, the data' normality and homoskedasticity were checked. Then, the data was compared using ANOVA and post hoc tests. The results of these tests were visually interpreted using raincloud and discriminant plots. These data provide a starting point for teaching precision, accuracy, descriptive statistics, and hypothesis tests. Statistical analysis was carried out using Jeffreys's Amazing Statistics Program (JASP), which is free and open-source software that provides several graphical interpretations of the hypothesis test. more...
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- 2023
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33. A Design Case for Utilizing Theories as a Heuristic Thinking Device to Create Empathy in [Interior] Design Studios
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Patel, Tina and Alfaro, Sarah Angne
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This design case introduces a design and development process of theories from environmental psychology, humanities, and social sciences as heuristic thinking devices to measure human-centered design solutions. The pedagogical review of the traditional studio design process revealed obstacles as students translated their research and program to the development of the design. They created the latter without applying their theoretical understanding of research conducted on the human-environment relationship. Given this challenge, the authors evolved a revised design method utilizing theories to afford an empathetic design response. Students in two interior design studios adopted this approach to develop hypotheses for the design problem, and later the theories informed guidelines for cultivating a more empathetic design response. Project analysis by authors, and reflection statements from the students, capture the value of theory as thinking devices to assist directly in their work by improving their position and power, prompting a more imaginative and generative ideation process. The role of this design case is to acknowledge the role of theory as a heuristic device in order to generate, develop, and support the advancement of interior design as a discipline through interaction, mediation, and discourse. more...
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- 2022
34. A Model of Scientific Data Reasoning
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Masnick, Amy M. and Morris, Bradley J.
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Data reasoning is an essential component of scientific reasoning, as a component of evidence evaluation. In this paper, we outline a model of scientific data reasoning that describes how data sensemaking underlies data reasoning. Data sensemaking, a relatively automatic process rooted in perceptual mechanisms that summarize large quantities of information in the environment, begins early in development, and is refined with experience, knowledge, and improved strategy use. Summarizing data highlights set properties such as central tendency and variability, and these properties are used to draw inferences from data. However, both data sensemaking and data reasoning are subject to cognitive biases or heuristics that can lead to flawed conclusions. The tools of scientific reasoning, including external representations, scientific hypothesis testing, and drawing probabilistic conclusions, can help reduce the likelihood of such flaws and help improve data reasoning. Although data sensemaking and data reasoning are not supplanted by scientific data reasoning, scientific reasoning skills can be leveraged to improve learning about science and reasoning with data. more...
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- 2022
35. An Analysis of Turkish and Russian Teachers' of English Approaches to Effective Instructional Strategies
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Celik, Aleksandra and Bay, Erdal
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The purpose of this study was to determine teachers' approaches to Marzano's effective instructional strategies (MEISs), as defined by Marzano, Pickering and Pollack (2001) in the secondary schools in Turkey and Russia and tell whether they differ or not. In this study survey research - one of the quantitative approaches -- was carried out. The participants for the study were 54 teachers of English in Turkey and 40 teachers of English in Russia. "The Effective Instructional Strategies Questionnaire" and an open-ended questionnaire were used to gather data. Data was generated utilizing content analysis and non-parametric Mann-Whitney U test. The results related to the first and second research questions revealed that there were partial differences between Turkish and Russian teachers' approaches to Marzano's nine effective instructional strategies and to usage of these strategies. Turkish teachers place less importance than Russian teachers on such strategies as summarizing and note taking, homework and practice, generating and testing hypothesis. As to Russian teachers, they do not espouse strategies in the category of non-linguistic representations as much as Turkish teachers do. The results of the study showed that Turkish and Russian teachers' approaches and the usage of the strategies differ. more...
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- 2021
36. The Lack of Robustness of a Statistic Based on the Neyman-Pearson Lemma to Violations of Its Underlying Assumptions
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Sinharay, Sandip
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Drasgow, Levine, and Zickar (1996) suggested a statistic based on the Neyman-Pearson lemma (e.g., Lehmann & Romano, 2005, p. 60) for detecting preknowledge on a known set of items. The statistic is a special case of the optimal appropriateness indices of Levine and Drasgow (1988) and is the most powerful statistic for detecting item preknowledge when the assumptions underlying the statistic hold for the data (e.g., Belov, 2016; Drasgow et al., 1996). This paper demonstrated using real data analysis that one assumption underlying the statistic of Drasgow et al. (1996) is often likely to be violated in practice. This paper also demonstrated, using simulated data, that the statistic is not robust to realistic violations of its underlying assumptions. Together, the results from the real data and the simulations demonstrate that the statistic of Drasgow et al. (1996) may not always be the optimum statistic in practice and occasionally has smaller power than another statistic for detecting preknowledge on a known set of items, especially when the assumptions underlying the former statistic do not hold. The findings of this paper demonstrate the importance of keeping in mind the assumptions underlying and the limitations of any statistic or method. [This paper will be published in "Applied Psychological Measurement."] more...
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- 2021
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37. Taking Causal Heterogeneity Seriously: Implications for Case Choice and Case Study-Based Generalizations
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Hertog, Steffen
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In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect sizes in individual cases--even if we choose "onlier" cases as is usually suggested. Contrary to established practice, we show that choosing "reinforcing" outlier cases--where outcomes are stronger than predicted in the statistical model--is appropriate for testing preexisting hypotheses on causal mechanisms, as this reduces the risk of false negatives. When investigating mechanisms inductively, researchers face a choice between "onlier" and reinforcing outlier cases that represents a trade-off between false negatives and false positives. We demonstrate that the inferential power of nested research designs can be much increased through paired comparisons of cases. More generally, this article provides a new conceptual framework for understanding the limits to and conditions for causal generalization from case studies. more...
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- 2023
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38. Using Theoretical Models in Mixed Methods Research: An Example from an Explanatory Sequential Mixed Methods Study Exploring Teachers' Beliefs and Use of Technology
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Haynes-Brown, Tashane K.
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The purpose of this article is to illustrate the dynamic process involved in developing and utilizing a theoretical model in a mixed methods study. Specifically, I illustrate how the theoretical model can serve as the starting point in framing the study, as a lens for guiding the data collection and analysis, and as the end point in explaining the integrated findings. The article is based on an explanatory sequential mixed methods study conducted with 248 teachers in Jamaican secondary schools that sought to understand how beliefs shaped their use of technology. This article contributes to mixed methods research by providing illustrations and analytical insights into the role of a theoretical model in enhancing rigor in designing and conducting mixed methods research. more...
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- 2023
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39. Increasing Participation in Psychological Science by Using Course-Based Research Projects: Testing Theory, Using Open-Science Practices, and Professionally Presenting Research
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Frankowski, Scott D.
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Introduction: Undergraduate research experiences prepare students for graduate training or employment. Statement of problem: At many teaching-intensive universities, there is a greater demand for research experiences than there are independent study opportunities. Students from typically underrepresented backgrounds may also be unaware of a department's undergraduate research pipeline of independent study, honor's theses, and internal research funding. Literature review: Course-based research contributes to diversity and inclusivity in access to undergraduate research experiences, especially at teaching-intensive universities. Course-based research is often integrated into methods courses, but not content courses. Teaching implications: I present practical ways to integrate research projects into courses. I stress the importance of testing theory, teaching open-science practices, and providing opportunities for students to present professionally. I also provide examples of implementing group research projects in content courses. Conclusion: Implementing course-based research projects, especially at teaching-intensive universities, can expand access to psychological science by providing valuable research opportunities for many students. Instructors can also benefit by intertwining their teaching, mentoring, and research goals. Future research should focus on experimentally testing learning outcomes. more...
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- 2023
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40. Evidence-Based Assessment in Special Education Research: Advancing the Use of Evidence in Assessment Tools and Empirical Processes
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Talbott, Elizabeth, De Los Reyes, Andres, Kearns, Devin M., Mancilla-Martinez, Jeannette, and Wang, Mo
- Abstract
Evidence-based assessment (EBA) requires that investigators employ scientific theories and research findings to guide decisions about what domains to measure, how and when to measure them, and how to make decisions and interpret results. To implement EBA, investigators need high-quality assessment tools along with evidence-based processes. We advance EBA in three sections in this article. First, we describe an empirically grounded framework, the Operations Triad Model (OTM), to inform EBA decision-making in the articulation of relevant educational theory. Originally designed for interpreting mental health assessments, we describe features of the OTM that facilitate its fusion with educational theory, namely its falsifiability. In turn, we cite evidence to support the OTM's ability to inform hypothesis generation and testing, study design, instrument selection, and measurement validation. Second, we describe quality indicators for interpreting psychometric data about measurement tools, which informs both the development and selection of measures and the process of measurement validation. Third, we apply the OTM and EBA to research in special education in two contexts: (a) empirical research for causal explanation and (b) implementation science research. We provide open data resources to advance measurement validation and conclude with future directions for research. more...
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- 2023
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41. Short-Term and Long-Term Educational Outcomes of Infants Born Moderately and Late Preterm
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Townley Flores, Carrie, Gerstein, Amy, Phibbs, Ciaran S., and Sanders, Lee M.
- Abstract
Objective: To assess the relationship of moderate and late preterm birth (32[superscript 0/7]-36 [superscript 6/7] weeks) to long-term educational outcomes. Study Design: We hypothesized that moderate and late preterm birth would be associated with adverse out- comes in elementary school. To test this, we linked vital statistics patient discharge data from the Office of Statewide Health Planning and Development including birth outcomes, to the 2015-2016 school year administrative data of a large, urban school district (n = 72,316). We compared the relative risk of moderate and late preterm and term infants for later adverse neurocognitive and behavioral outcomes in kindergarten through the 12th grade. Results: After adjusting for socioeconomic status, compared with term birth, moderate and late preterm birth was associated with an increased risk of low performance in mathematics and English language arts, chronic absenteeism, and suspension. These risks emerged in kindergarten through grade 2 and remained in grades 3-5, but seemed to wash out in later grades, with the exception of suspension, which remained through grades 9-12. Conclusions: Confirming our hypothesis, moderate and late preterm birth was associated with adverse educational outcomes in late elementary school, indicating that it is a significant risk factor that school districts could leverage when targeting early intervention. Future studies will need to test these relations in geographically and socioeconomically diverse school districts, include a wider variety of outcomes, and consider how early interventions moderate associations between birth outcomes and educational outcomes. more...
- Published
- 2021
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42. Investigating Preservice Chemistry Teachers' Understanding and Views about the Diversity of Scientific Methods
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Huinan Liu, Bo Chen, Kai Chen, and Yanting Jing
- Abstract
The diversity of scientific methods has received increasing attention in the field of science education. This paper aimed to investigate how preservice chemistry teachers perceive scientific methods and their diversity. Based on the theoretical framework of Brandon's Matrix and previous research, two tasks (i.e., Task 1 "understanding of the components of Brandon's Matrix" and Task 2 "views on the diversity of scientific methods") and follow-up interview questions were developed in this study as research instruments. 130 preservice chemistry teachers from two universities in China were selected as participants. The statistical results of the questionnaire survey revealed that the participants showed a relatively satisfactory understanding of the components of Brandon's Matrix, and they judged the hypothesis testing more accurately than variable manipulation. However, the majority of participants held relatively naive views on the diversity of scientific methods, suggesting that they endorsed the idea of "the scientific method". Moreover, it was found by in-depth interviews that four typically held reasons led to the misunderstanding of scientific methods by preservice chemistry teachers, namely, misinterpreting the liberal meaning of item scenarios, misconceptions in identifying the "variable manipulation", grade disparity in the scientificity, and past learning experience in chemistry. At the end of this paper, the implications of the findings and the suggestions for further research were discussed. more...
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- 2023
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43. Whey Protein Analysis Using the Lowry Assay and 96-Well-Plate Digital Images Acquired Using Smartphones
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Eder José Assink Junior, Paulo Cesar de Jesus, and Endler Marcel Borges
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Here, students determine the total protein content in whey protein samples using the Lowry assay. Quantitative analysis was carried out using absorbance measured at 750 nm (standard method) and 96-well-plate digital images obtained using smartphones (proposed method). The proposed method was carried out using two smartphones (1 and 2). Smartphone 1 had a higher resolution than smartphone 2. The statistical evaluation of the data set produced by the students was carried out using JASP (Jeffreys's Amazing Statistics Program), and it was a valuable tool to teach descriptive statistics and hypothesis tests. We chose JASP because it is free and open-source software with a graphical user interface. The protein percentage found in five whey protein samples using the standard method during three lab classes was compared using one-way and two-way ANOVA. Five whey protein samples were analyzed using the standard method and the proposed methods (smartphones 1 and 2). The results were compared using one-way repeated measure ANOVA (RMANOVA) and mixed-factor ANOVA. During the statistical analysis of the data set, students identified outlier results using boxplots and checked data normality using the Shapiro-Wilk test, histograms, and boxplots. They learned the difference between dependent and independent variables and compared variances using Levene's test (dependent variables) and Mauchly's test (independent variables). The interpretation of statistical tests was also carried out using descriptives plots, boxplots, and raincloud plots. more...
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- 2023
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44. Integrative Evaluation
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Feinstein, Osvaldo
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"Integrative evaluation" is an approach with two main phases: identification of plausible rival hypotheses and integration of rival hypotheses. The first phase may correspond to traditional adversary evaluation, whereas the second phase, that is not included in adversary evaluation, requires integrative thinking which can be applied when they are compatible and complementary. Integrative evaluation may facilitate "evaluative thinking" and contribute to deliberative or integrative democracy. more...
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- 2023
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45. Student-Focused, Career-Driven Exploration in Natural History Museums through Experiential Education and Mentorship: A Model to Intentionally Increase the Racial and Ethnic Diversity of Students
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Flemming, Adania D. C.
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Being immersed in the processes of research can develop undergraduate students' science identities and support their persistence in pursuing science careers. However, it can be difficult for students to find opportunities for engaging in authentic scientific research. The professional staff and scientific objects in natural history museums provide such an opportunity that can create relationships through which both undergraduate students and museums benefit. Students require authentic practical experiences to better understand their academic fields and career trajectories, and museums require assistance curating and managing collections. This can be accomplished through mentorship, training, and research experience in a formal course. At the University of Florida, I developed and taught a course titled "Introduction to Natural History" that engaged students in projects in museum collections. Discussion sessions replaced lectures by introducing topics such as the concept of research, distinction between predictions and hypotheses, understanding of the nature of science, and how to conduct literature reviews. In 2019 and 2020, students completed a pre- and postcourse survey to gauge their understanding of science and their anticipated career trajectory. My results demonstrate that mentorship and authentic experiential science opportunities using museum collections enable students to realize a passion, sense of purpose, and better understanding of science and careers in science. more...
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- 2023
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46. Methodological Issues When Interpreting Changes in Social Phenomena over Time: Perceptions of Relative Difference, Absolute Difference, and Time Distance
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Prevodnik, Katja and Vehovar, Vasja
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When comparing social science phenomena through a time perspective, absolute and relative difference (RD) are the two typical presentation formats used to communicate interpretations to the audience, while time distance (TD) is the least frequently used of such formats. This article argues that the chosen presentation format is extremely important because the various formats suggest different substantive interpretations. To elaborate upon this issue, researchers from the National Statistical Office, National Health Institute, and general academia were invited to participate in an experiment with alternative presentation formats that describe changes in certain social science phenomena over time. The results revealed a prevailing tendency of respondents to rely on interpretations related to absolute differences, which was additionally reinforced with graphical presentation formats. Therefore, whenever RD or TD is more proper for substantive interpretations, the corresponding presentation format must be designed with special attention. more...
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- 2023
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47. Metacognitive Errors in the Classroom: The Role of Variability of Past Performance on Exam Prediction Accuracy
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Geraci, Lisa, Kurpad, Nayantara, Tirso, Robert, Gray, Kathryn N., and Wang, Yan
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Students often make incorrect predictions about their exam performance, with the lowest-performing students showing the greatest inaccuracies in their predictions. The reasons why low-performing students make inaccurate predictions are not fully understood. In two studies, we tested the hypothesis that low-performing students erroneously predict their exam performance in part because their past performance varies considerably, yielding unreliable data from which to make their predictions. In contrast, high-performing students tend to have consistently high past performance that they can rely on to make relatively accurate predictions of future test performance. Results showed that across different exams (Study 1) and different courses (Study 2), low-performing students had more variable past performance than high-performing students. Further, results from Study 2 showed that variability in past course performance (but not past exam performance) was associated with poor calibration. Results suggest that variability in past performance may be one factor that contributes to low-performing students' erroneous performance predictions. more...
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- 2023
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48. Can You Predict the Money Laundering Cases?
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McCarthy, Richard V., Ceccucci, Wendy, McCarthy, Mary, and Sugurmar, Nirmalkumar
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This case is designed to be used in business analytics courses; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People's United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize predictive models, and then score the models. Students are challenged to develop a better baseline model than what is currently being used by People's United Bank. more...
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- 2021
49. Beyond p-Values: Using Bayesian Data Analysis in Science Education Research
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Kubsch, Marcus, Stamer, Insa, Steiner, Mara, Neumann, Knut, and Parchmann, Ilka
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In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community often relies on quantitative statistical approaches, the challenges the replication crisis poses to these approaches need to be considered. "p"-values suffer primarily from the fact that they carry little information by themselves and lend themselves to misinterpretations. As one alternative, Bayesian approaches have become increasingly popular as the posterior distributions they provide carry more relevant information than "p"-values. In this paper, we discuss practical issues related to "p-values" with respect to interpreting and communicating results and how these issues can be addressed using a Bayesian approach. Drawing on a science education data set, we demonstrate how Bayesian data analysis methods go beyond p-values and can help to make more valid conclusions and to communicate them more easily in a manner that lends itself to less misinterpretations. more...
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- 2021
50. AutoML Feature Engineering for Student Modeling Yields High Accuracy, but Limited Interpretability
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Bosch, Nigel
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Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The methods we compare, Featuretools and TSFRESH (Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests), have rarely been applied in the context of student interaction log data. Thus, we address research questions regarding the accuracy of models built with AutoML features, how AutoML feature types compare to each other and to expert-engineered features, and how interpretable the features are. Additionally, we developed a novel feature selection method that addresses problems applying AutoML feature engineering in this context, where there were many heterogeneous features (over 4,000) and relatively few students. Our entry to the NAEP competition placed 3rd overall on the final held-out dataset and 1st on the public leaderboard, with a final Cohen's kappa = 0.212 and area under the receiver operating characteristic curve (AUC) = 0.665 when predicting whether students would manage their time effectively on a math assessment. We found that TSFRESH features were significantly more effective than either Featuretools features or expert-engineered features in this context; however, they were also among the most difficult features to interpret based on a survey of six experts' judgments. Finally, we discuss the tradeoffs between effort and interpretability that arise in AutoML-based student modeling. more...
- Published
- 2021
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