Yoxas/statistical_literacy huggingface dataset:
Learning to interpret data in context is an important educational outcome. To assess students' attainment of this outcome, it is necessary to examine the interplay between their contextual and statistical reasoning. We describe a research method designed to do so. The method draws upon Toulmin's (1958, 2003) model of argumentation for the first stage of qualitative data analysis and the Structure of the Observed Learning Outcome (SOLO) (Biggs & Collis, 1991) model for the second stage. Toulmin analyses help identify the justifications and expressions of uncertainty students provide in their interpretive arguments. Subsequent analyses based on the multi-modal conceptualization of SOLO help characterize the quality of student arguments relative to one another. Existing literature and an empirical example are drawn upon to explain how the Toulmin and SOLO models can be used in tandem to analyze students' interpretations of contextualized data. We also explain how pairing Toulmin and SOLO can address theoretical and practical limitations that arise when using just one of the two models on its own.
Learning to synthesize free-hand sketches controllably according to specified categories and sketching styles is a challenging task, due to the lack of training data with category labels and style labels. One choice to control the synthesis is by self-organizing a latent coding space to preserve the similarity of structural patterns of the observed data. A practical way is introducing a Gaussian mixture prior over the latent codes, where each Gaussian component represents a specific categorical or stylistic pattern. As a result, we can generate sketches by sampling the latent variables from the Gaussian components or continuously manipulating the latent representations by interpolation. To achieve robust controllable sketch synthesis, it is critical to determine an appropriate Gaussian number. An underestimated Gaussian number cannot fully represent all the sketch patterns, i.e., some clusters have to contain sketches with more than one pattern. An overestimated one introduces redundant components, usually representing a chaotic collection of sketches with diverse patterns featured by other components. Both cases disturb pattern clustering over the coding space and make the internal code generation difficult to control for specific patterns. However, the Gaussian number is unavailable in this unsupervised task. In this paper, we present Rival Penalized Competitive Learning pixel to sequence (RPCL-pix2seq) to automatically determine the Gaussian number. Both quantitative and qualitative experimental results show RPCL-pix2seq can partition the codes for the sketches into an approximate stable number of clusters. Hence, we are able to do synthesis reasoning over the latent space, generating novel but reasonable sketches which neither appear in the training dataset nor exist in real life.
Learning trajectory describes the student's learning progress or steps in one area through which teaching and learning can be linked. The cognitive diagnostic model (CDM) is an emerging evaluation theory in education measures. Researchers can determine students' mastery of fine-grained knowledge points by describing the learning trajectory based on CDM. The present study is based on the Trends in International Mathematics and Science Study (TIMSS) 2019, particularly, 21 mathematical items in the fourth grade. It analyzes the response data of 2,854 students from 17 countries from 10 attributes based on CDM. This study explores students' different learning trajectories in the content field by analyzing the relationships between knowledge states and attribute patterns. The study found that the 17 countries differ in learning trajectories but have commonalities. The learning starting points of 17 countries can be roughly divided into two categories and geometry attribute and fractions and decimals attribute are the last two attributes to master.
Lee and Schwarz (L&S) suggest that separation is the grounded procedure underlying cleansing effects in different psychological domains. Here, we interpret L&S's account from a hierarchical view of cognition that considers the influence of physical properties and sensorimotor constraints on mental representations. This approach allows theoretical integration and generalization of L&S's account to the domain of formal quantitative reasoning.
Left brain damage (LBD) can impair the ability to use familiar tools (apraxia of tool use) as well as novel tools to solve mechanical problems. Thus far, the emphasis has been placed on quantitative analyses of patients' performance. Nevertheless, the question still to be answered is, what are the strategies employed by those patients when confronted with tool use situations? To answer it, we asked 16 LBD patients and 43 healthy controls to solve mechanical problems by means of several potential tools. To specify the strategies, we recorded the time spent in performing four kinds of action (no manipulation, tool manipulation, box manipulation, and tool-box manipulation) as well as the number of relevant and irrelevant tools grasped. We compared LBD patients' performance with that of controls who encountered difficulties with the task (controls-) or not (controls+). Our results indicated that LBD patients grasped a higher number of irrelevant tools than controls+ and controls-. Concerning time allocation, controls+ and controls- spent significantly more time in performing tool-box manipulation than LBD patients. These results are inconsistent with the possibility that LBD patients could engage in trial-and-error strategies and, rather, suggest that they tend to be perplexed. These findings seem to indicate that the inability to reason about the objects' physical properties might prevent LBD patients from following any problem-solving strategy.
Lego construction ability is associated with a variety of spatial skills and mathematical outcomes. However, it is unknown whether these relations are causal. We aimed to establish the causal impact of Lego construction training on: Lego construction ability; a broad range of spatial skills; and on mathematical outcomes in 7-9-year-olds. We also aimed to identify how this causal impact differs for digital versus physical Lego construction training. One-hundred and ninety-eight children took part in a six-week training programme, delivered twice weekly as a school lunch time club. They completed either physical Lego training (N = 59), digital Lego training (N = 64), or an active control condition (crafts; N = 75). All children completed baseline and follow-up measures of spatial skills (disembedding, visuo-spatial working memory, spatial scaling, mental rotation, and performance on a spatial-numerical task, the number line task), mathematical outcomes (geometry, arithmetic, and overall mathematical skills) and Lego construction ability. Exploratory analyses revealed evidence for near transfer (Lego construction ability) and some evidence for far transfer (arithmetic) of Lego training, but overall transfer was limited. Despite this, we identified key areas for further development (explicit focus on spatial strategies, training for teachers, and embedding the programme within a mathematical context). The findings of this study can be used to inform future development of Lego construction training programmes to support mathematics learning.
Leishmaniasis is an overlooked, poverty-stricken, and complex disease with growing social and public health problems. In general, leishmaniasis is a curable disease; however, there is an expansion of unresponsive cases to treatment in cutaneous leishmaniasis (CL). One of the effective and ignored determinants in the treatment outcome of CL is poor treatment adherence (PTA). PTA is an overlooked and widespread phenomenon to proper Leishmania treatment. This study aimed to explore the effect of poor adherence in unresponsiveness to treatment in patients with anthroponotic CL (ACL) by comparing conventional statistical modalities and machine learning analyses in Iran. Overall, 190 cases consisting of 50 unresponsive patients (case group), and 140 responsive patients (control group) with ACL were randomly selected. The data collecting form that included 25 queries (Q) was recorded for each case and analyzed by R software and genetic algorithm (GA) approaches. Complex treatment regimens (Q11), cultural and lay views about the disease and therapy (Q8), life stress, hopelessness and negative feelings (Q22), adverse effects of treatment (Q13), and long duration of the lesion (Q12) were the most prevalent significant variables that inhibited effective treatment adherence by the two methods, in decreasing order of significance. In the inherent algorithm approach, similar to the statistical approach, the most significant feature was complex treatment regimens (Q11). Providing essential knowledge about ACL and treatment of patients with chronic diseases and patients with misconceptions about chemical drugs are important issues directly related to the disease's unresponsiveness. Furthermore, early detection of patients to prevent the long duration of the disease and the process of treatment, efforts to minimize side effects of treatment, induction of positive thinking, and giving hope to patients with stress and anxiety by medical staff, and family can help patients adhere to the treatment.
Lentiviral vectors (LVVs) are used as a starting material to generate chimeric antigen receptor (CAR) T cells. Therefore, LVVs need to be carefully analyzed to ensure safety, quality, and potency of the final product. We evaluated orthogonal and complementary analytical techniques for their suitability to characterize particulate matter (impurities and LVVs) in pharmaceutical LVV materials at development stage derived from suspension and adherent manufacturing processes. Microfluidic resistive pulse sensing (MRPS) with additional manual data fitting enabled the assessment of mode diameters for particles in the expected LVV size range in material from adherent production. LVV material from a suspension process, however, contained substantial amounts of particulate impurities which blocked MRPS cartridges. Sedimentation-velocity analytical ultracentrifugation (SV-AUC) resolved the LVV peak in material from adherent production well, whereas in more polydisperse samples from suspension production, presence of particulate impurities masked a potential signal assignable to LVVs. In interferometric light microscopy (ILM) and nanoparticle tracking analysis (NTA), lower size detection limits close to ∼ 70 nm resulted in an apparent peak in particle size distributions at the expected size for LVVs emphasizing the need to interpret these data with care. Interpretation of data from dynamic light scattering (DLS) was limited by insufficient size resolution and sample polydispersity. In conclusion, the analysis of LVV products manufactured at pharmaceutical scale with current state-of-the-art physical (nano)particle characterization techniques was challenging due to the presence of particulate impurities of heterogeneous size. Among the evaluated techniques, MRPS and SV-AUC were most promising yielding acceptable results at least for material from adherent production.
Leptomeningeal carcinomatosis (LMC), the metastatic spread of cancer to the leptomeninges, is a rare complication and has a dismal prognosis. Due to limited data available on LMC from India, we conducted a country-wise audit of LMC across 15 centres in India. The current study conducted in 2020, was a retrospective, multicentric audit of adult patients (aged ≥18 years) with diagnosis of LMC and who received treatment during 2010-2020. Baseline characteristics, details related to previous treatments, cancer sites, LMC diagnosis, treatment pattern and overall survival (OS) were collected. Descriptive statistics were performed, and Kaplan Meier analysis was performed for the estimation of OS. Among the patients diagnosed with LMC (n = 84), diagnosis was confirmed in 52 patients (61.9%) and 'probable' in 32 (38.1%) patients. The three most common cause of malignancy were non-small cell lung cancer (NSCLC), breast cancer and gastrointestinal cancer with 45 (53.6%), 22 (26.1%) and 9 (10.7%) patients respectively. Intrathecal therapy was offered in 33 patients (39.3%). The most common intrathecal agent was methotrexate in 23 patients (27.4%). The median OS was 90 days (95% CI 48-128). Among tested variables, intrathecal therapy administration (hazard ratio [HR] = 0.36, 95% CI 0.19-0.68) and primary in lung (HR = 0.43, 95% CI 0.23-0.83) had a favourable impact on OS. Prognosis with leptomeningeal carcinomatosis is poor with a significant burden of morbidity and mortality in India. This data aims to highlight the current outcomes and facilitate further research on LMC. None.
Lesbian, gay and bisexual people are disadvantaged in terms of health and socio-economic status compared with heterosexual people, yet findings pertaining to educational outcomes vary depending on the specific identity and gender considered. This study delves into these unexplained findings by applying a social-stratification lens, thereby providing an account of how intergenerational educational mobility varies by sexual identity. To accomplish this, we use representative data from five OECD countries and a regression-based empirical specification relying on coarsened exact matching. We find that gay and lesbian people have higher educational attainment than heterosexual people in all five countries and that these higher levels of education stem from greater rates of upward educational mobility among gay/lesbian people. There were, however, few differences between heterosexual and bisexual people. Variation across countries emerged when analyses were stratified by gender, with higher rates of upward mobility observed for gay men in Australia, Chile, the United Kingdom, and the United States and lesbian women in Australia and Germany. Overall, our results align with previous claims that education can be a strategy for gay/lesbian people to avoid actual or anticipated discrimination. However, variation in these patterns across groups suggests that other mechanisms may also be at play.
Lesbian, gay, bisexual, transgender, and queer plus (LGBTQ+) students in undergraduate science, technology, engineering, and math (STEM) majors are more likely to drop out than their cisgender, heterosexual peers despite having equivalent grades and research exposure. It has been demonstrated that a sense of belonging, a very strong predictor of student retention, is low in LGBTQ+-identified STEM undergraduates. It has further been posited that faculty openness and authenticity can enhance a sense of belonging for LGBTQ+ students through the creation of an inclusive classroom culture. The authors of this article, three LGBTQ+-identified faculty in the health sciences department at Boston University, surveyed students enrolled in their courses to elicit student thoughts, feelings, and behaviors regarding the effect of faculty 1) sharing their identity openly in the classroom, and 2) actively working to create open, inclusive dialogue and space in their classrooms. Of 86 student participants across multiple classes, the large majority of students, both LGBTQ+-identified and non-LGBTQ+-identified, described feeling safe, included, and welcomed in the classroom. They described engaging more in peer-to-peer education and felt that instructor authenticity created a safe and inclusive classroom. A minority of LGBTQ+-identified students and non-LGBTQ+-identified students reported feeling unsure of voicing their opinions, for the former related to insecurity about being LGBTQ+ and the latter feeling a liberal bias existed in the classroom. Altogether, these results suggest a positive effect on student sense of belonging when faculty authenticity and intentionality create inclusive classroom environments in the health sciences.NEW & NOTEWORTHY Openness and authenticity of lesbian, gay, bisexual, transgender, and queer plus (LGBTQ+)-identified faculty in the health sciences positively affect students by helping them feel seen, welcomed, and included for both students who identify as LGBTQ+ and those who do not. Moreover, faculty openness fostered student action by encouraging them to have peer-to-peer discussions about inclusive language and engage more openly in classroom discussions. Creating academic job security for LGBTQ+-identified faculty to be open can enhance classroom culture, student engagement, and learning.
Lesson planning is of central importance to the teaching of all subjects in school. However, despite its high relevance, there is still a substantial need for a comprehensive review of factors affecting lesson planning. Empirical evidence on how teachers' competence in lesson planning can be developed, what challenges may be encountered during the lesson planning process, and successful lesson planning designs and practices should come to light on. To close this gap the current paper presents the results of a systematic review of 20 empirical research studies on teacher competence in mathematics lesson planning. For detailed insight into the most recent contributions of the reviewed studies on mathematics lesson planning, we analyzed studies conducted during the past decade, adapting the "process model of lesson planning" and the model of "competence as continuum" as a heuristic for approaching lesson planning. We present key results of the studies related to four major themes: (1) dispositions and their influence on developing and implementing lesson plans, (2) quality aspects of lesson plans and the development of lesson planning skills, (3) difficulties in lesson planning, and (4) the relationship between lesson planning skills and performance in implementation of lesson plans. The results of our literature review reveal that teachers (especially novice teachers) face difficulties in lesson planning and their overall competence (and knowledge) are not at an expert level. However, as the results of the examined studies pointed out, teachers can acquire such competence and knowledge through training within initial teacher education and professional development. Overall, teachers need support in planning mathematics lessons by delineating their lesson plan to improve their awareness of students' thinking, possible learning trajectories, effective usage of the curriculum and teaching resources, and the potential of innovative pedagogies that incorporate new technology.
Letters of recommendation (LOR) are an integral component of physical therapy residency applications. Identifying the influence of applicant and writer gender in LOR will help identify whether potential implicit gender bias exists in physical therapy residency application processes. Several medical and surgical residency education programs have reported positive, neutral, or negative LOR female gender bias among applicants and writers. Little research exists on gender differences in LOR to physical therapy education programs or physical therapy residency programs. Seven hundred sixty-eight LOR were analyzed from 256 applications to 3 physical therapy residency programs (neurologic, orthopaedic, sports) at one institution from 2014 to 2020. Thematic categories were developed to identify themes in a sample of LOR. Associations between writer and applicant gender were analyzed using summary statistics, word counts, thematic and psycholinguistic extraction, and rule-based and deep learning Natural Language Processing . No significant difference in LOR word counts were found based on writer or applicant gender. Increased word counts were seen in sports residency LOR compared with the orthopaedic residency. Thematic analysis showed LOR gender differences with male applicants receiving more positive generalized recommendations and female applicants receiving more comments regarding interpersonal relationship skills. No thematic or psycholinguistic gender differences were seen by LOR writer. Male applicants were 1.9 times more likely to select all male LOR writers, whereas female applicants were 2.1 times more likely to choose all female LOR writers. Gender differences in LORs for physical therapy residencies were found using a comprehensive Natural Language Processing approach that identified both a positive recommendation male applicant gender bias and a positive interpersonal relationship skill female applicant gender bias. Applicants were not harmed nor helped by selecting LOR writers of the opposite gender. Admissions committees and LOR writers should be mindful of potential implicit gender biases in LOR submitted to physical therapy residency programs.
Leucocyte telomere length (LTL) is linked to accelerate aging and premature mortality. In this research, we aimed to explore the relations between biochemical and anthropometry markers and LTL in Asian Indian women with abnormal fasting glycemia (impaired fasting glucose). In this study, 797 pre-diabetic women (obese, 492; non-obese, 305) were recruited. Demographic and clinical profiles, anthropometry, and fasting blood glucose were evaluated. LTL was quantified by a quantitative PCR. LTL was expressed as the relative telomere length or telomere repeat:single copy gene (T:S) ratio. The subjects were separated into quartiles according to the LTL. The average LTL was significantly decreased with increasing age. The average LTL was significantly shorter in obese women with abnormal fasting glycemia (p<0.05). R-squared (R2) statistic for multivariable linear model after adjusted for age, family income, education and hypertension showed that LTL was inversely correlated with body mass index (BMI), waist and hip circumference, waist-hip and waist-to-height ratio, truncal skinfolds (subscapular, and subscapular/triceps ratio, central and total skinfolds), fat mass (kg) and % body fat. The relationship between obesity measures and LTL (using the LTL quartile 1 as reference) identified central skinfolds (R2=0.92, p<0.0001), Σ4SF (R2=0.90, p<0.0001), BMI (R2=0.93, p<0.0001) and % body fat (R2=0.91, p<0.0001) as independent predictors of LTL. Besides age, obesity and subcutaneous adiposity (predominantly truncal) are major contributors to telomere shortening in Asian Indian women with abnormal fasting glycemia (impaired fasting glucose).