Developing an understanding of repeating patterning

The aim of the present study was to examine Turkish teacher candidates’ competency levels in writing different types of test items by utilizing Rasch analysis. In addition, the effect of the expertise of the raters scoring the items written by the teacher candidates was examined within the scope of the study. 84 Turkish teacher candidates participated in the present study, which was conducted using the relational survey model, one of the quantitative research methods. Three experts participated in the rating process: an expert in Turkish education, an expert in measurement and evaluation, and an expert in both Turkish education and measurement and evaluation. The teacher candidates wrote true-false, short response, multiple choice and open-ended types of items in accordance with the Test Item Development Form, and the raters scored each item type by designating a score between 1 and 5 based on the item evaluation scoring rubric prepared for each item type. The study revealed that Turkish teacher candidates had the highest level of competency in writing true-false items, while they had the lowest competency in writing multiple-choice items. Moreover, it was revealed that raters’ expertise had an effect on teacher candidates’ competencies in writing different types of items. Finally, it was found that the rater who was an expert in both Turkish education and measurement and evaluation had the highest level of scoring reliability, while the rater who solely had expertise in measurement and evaluation had the relatively lowest level of scoring reliability.

This paper looks at a question that has up to now not yet been put, namely which textual dictionary structure elements with which features, by the use of which the user can find semantic and pragmatic knowledge within an article can systematically be differentiated. In order to do this the following four dictionary structure elements are introduced: items, item texts, functional item additions and item symbols. Then the dictionary structure elements for enabling knowledge regarding meaning are treated by means of examples, e.g. different types of items giving the meaning, different types of items giving semantically related expressions, different types of pragmatically enriched items giving the paraphrase of meaning, etc. Finally, the dictionary structure elements enabling pragmatic knowledge are discussed, e.g. different types of diasystematic labelling items and pragmatic labelling symbols. In conclusion, a brief perspective is given on the relevant approach to meaning.

BackgroundImproving engagement in medical care among persons living with human immunodeficiency virus (HIV) is critical to optimizing clinical outcomes and reducing onward transmission of HIV. However, a clear conceptualization of what it means to be engaged in HIV care is lacking, and thus efforts to measure and enhance engagement in care are limited.ObjectiveThis paper describes the use of a modified online Delphi process of consensus building to solicit input from a range of HIV and non-HIV researchers and providers, and to integrate that input with focus group data conducted with HIV-infected patients. The overarching goal was to generate items for a patient-centered measure of engagement in HIV care for use in future research and clinical practice.MethodsWe recruited 66 expert panelists from around the United States. Starting with six open-ended questions, we used four rounds of online Delphi data collection in tandem with 12 in-person focus groups with patients and cognitive interviews with 25 patients.ResultsWe recruited 66 expert panelists from around the United States and 64 (97%) were retained for four rounds of data collection. Starting with six open-ended questions, we used four rounds of online Delphi data collection in tandem with 12 in-person focus groups with patients and cognitive interviews with 25 patients. The process resulted in an expansion to 120 topics that were subsequently reduced to 13 candidate items for the planned assessment measure.ConclusionsThe process was an efficient method of soliciting input from geographically separated and busy experts across a range of disciplines and professional roles with the aim of arriving at a coherent definition of engagement in HIV care and a manageable set of survey items to assess it. Next steps are to validate the utility of the new measure in predicting retention in care, adherence to treatment, and clinical outcomes among patients living with HIV.

To introduce the topic of this chapter, let us consider a test developed with the goal of measuring writing proficiency. Ultimately, the test will be used to produce test scores reflecting each examinee’s level of writing proficiency, and to do so the test must elicit examinee responses to generate evidence of writing proficiency. To this end, the test developer is faced with a decision concerning the type of items or tasks to be used to elicit examinee responses. The test developer may opt to use multiple-choice (MC) items. Although cost-effective and efficient, MC items are indirect measures of writing proficiency and may not yield inferences about an examinee’s writing skills that rise to the same level of validity as those offered by more authentic writing tasks. To overcome limitations of MC items, the test developer may choose to employ constructed-response (CR) items consisting of a series of prompts used to elicit written responses from examinees, and have human-raters score the written responses using scoring rubrics. The resulting test may be comprised entirely of CR items or a combination of CR and MC items. While the CR item format offers a much more authentic assessment context, human-rater scoring suffers from several drawbacks, including inconsistency (e.g., due to rater severity/leniency, fatigue, etc.) and a high expense due to the time and resources required to train raters and conduct the scoring process (see Zhang, 2013). The test developer can avoid the drawbacks of human-rater scoring by using CR items that are scored by a computer-automated scoring engine (referred to as automated scoring hereafter), which applies a set of predefined decision rules to assign a score to a CR item based on particular features of the examinee’s response. Automated scoring has the advantageous properties of being perfectly consistent across examinees and being highly efficient from a resource perspective, but these scores may yield biased estimates of scores assigned by human raters.

Best Practices Related to Examination Item Construction and Post-hoc Review

This study aims to determine the distribution of higher-order mathematical thinking skills of students of state senior high schools in Tasikmalaya City in the academic year 2018/2019, to find out whether there is a relationship between mathematical critical thinking abilities with students' mathematical creative thinking skills High School in Tasikmalaya City 2018/2019 academic year. This research is a type of descriptive research using quantitative descriptive methods. The population in this study were all students of Tasikmalaya City Senior High School in class X, class XI, and class XII, ranging in age from 16-18 years. The sampling technique in this study uses a probability sampling technique that is Proportionate Stratified Random Sampling, by taking 2 classes each school. The research instrument used in this study was a matter of high-level mathematical thinking ability tests which are slices of the cognitive dimension of Bloom's Taxonomy with the 2013 Curriculum Dimension dimension consisting of questions of critical and creative thinking skills. The results showed that the distribution of mathematical thinking ability levels in high school students in the City of Tasikmalaya academic year 2018/2019 as follows: a) mathematical HOTS ability with a very good category was obtained by 2 Schools or 20% of all High School Schools in Tasikmalaya City, the ability Mathematical HOTS with the good category is obtained by 7 Schools or 70% of all High Schools in Tasikmalaya City, Mathematical HOTS ability with a pretty good category is obtained by 1 School, namely SMAN J or 10% of all Public High Schools in Tasikmalaya City. There is a significant relationship between students' mathematical critical thinking skills with the mathematical creative thinking abilities of high school students in the City of Tasikmalaya 2018/2019 academic year. with the degree of correlation obtained a correlation coefficient of 0.283 or are in a low category. Keywords: Higher Order Mathematical Thinking Skills, mathematical critical thinking skills, mathematical creative thinking skills.

Given the success of online shopping platforms and e-commerce technology, there is an increasing necessity to quickly and safely package different types of items. Addressing this necessity requires technology to accurately measure items at a high speed. Existing studies, however, lack in terms of reproducibility and the diversity of the items measured. In this paper, we present a novel approach for item measurement, targeting automated packaging systems that make use of belt conveyors. In particular, leveraging a scenario-driven approach and an automata-based control design, we describe in detail the creation of a real-world prototype for belt conveyor-based item measurement. Experimental results obtained for this prototype demonstrate that it is possible to measure different types of items (boxes, books, household items) with a mean error of less than 3.02mm and a standard deviation of less than 2.34mm, for a maximum conveyor belt speed that is less than 0. 5m /s and a maximum calculation time of 20ms.

Human beings are creatures of habit. In their daily life, people tend to repeatedly consume similar types of food items over several days and occasionally switch to consuming different types of items when the consumptions become overly monotonous. However, the novel and repeat consumption behaviors have not been studied in food recommendation research. More importantly, the ability to predict daily eating habits of individuals is crucial to improve the effectiveness of food recommender systems in facilitating healthy lifestyle change. In this study, we analyze the patterns of repeat food consumptions using large-scale consumption data from a popular online fitness community called MyFitnessPal (MFP), conduct an offline evaluation of various state-of-the-art algorithms in predicting the next-day food consumption, and analyze their performance across different demographic groups and contexts. The experiment results show that algorithms incorporating the exploration-and-exploitation and temporal dynamics are more effective in the next-day recommendation task than most state-of-the-art algorithms.

Dynamic scheduling for production systems operating in a random environment

Examining the Language Factor in Mathematics Assessments Adnan Kan, Okan Bulut Abstract In educational testing, assessment specialists typically create multiple forms of a test for different purposes, such as increasing test security or developing an item bank. Using different types of items across test forms is also a common practice to create alternative test forms.This study investigates whether word problems and mathematically expresseditems can be used interchangeably regardless of their linguistic complexities. A sample of sixth grade students was given two forms of a mathematics assessment. The first form included mathematicsitems based onmathematical terms, expressions, and equations. The second form included the same items as word problems. The underlying tasks and solutions of the items in the first test form were the same as the corresponding items in the second form. Explanatory item response modeling was used for examining the impact of item type and genderon difficulty levels of items and students’ test scores. The results showed that word problems were easier than mathematically expressed items. Gender and its interaction with the linguistic complexity of mathematics items did not seem to have any impact on student performance on the test. Full Text: PDF DOI: 10.15640/jehd.v4n1a13

The flipped learning approach of instruction sees classroom lectures moved outside of classrooms through devices and technology. Homework is moved inside classrooms as learning activities. Due to the COVID-19 outbreak, cloud-based education platforms - the organization of the educational environment in the cloud as a tool to enable teaching and learning - have been widely deployed to support online instruction. In this study, flipped cloud learning, incorporating approach of advancing mathematical thinking, were conducted in Mathematical Analysis course to study students’ mathematical critical thinking. A quantitative method, using a pre-test-post-test design, was employed with a group of 56 undergraduate mathematics students. The research instrument was a mathematical critical thinking ability test. The quantitative data were analyzed using the descriptive analysis, n-gain and t-test. The findings revealed that students had statistically significant mathematical critical thinking of higher than 60% of the full score at the .05 level. There was an increase in students’ mathematical critical thinking abilities with a mean n-gain of .64, which was moderate. The findings also show that the students’ mathematical critical thinking was significantly enhanced by this approach at .05 level. Thus, it could be summarized that integrating strategy for advancing mathematical thinking into flipped cloud learning positively affected students’ mathematical critical thinking. The results also suggest that this reformed learning approach might be usefully employed as an instruction model in the new normal context.

The Millennial Generation has been phasing out of undergraduate classrooms since 2013 and is being replaced by the technologically savvy and visual learners of Generation Z. To help to increase our understanding of the learning needs and attitudes of this new population of students, a two-fold data collection design has been implemented in undergraduate statistics classes at the University of Rhode Island. In the first round of data collection during the spring 2016 semester, survey and grade data was collected from an introductory biostatistics class pertaining to 146 students. Results from the analysis including the use of longitudinal generalized linear mixed models, hierarchical linear models and regression trees indicated a relationship between time and student performance throughout the semester, as well as a relationship between students starting attitudes and their performance and a potential group structure in the class based on their attitudes. This first round of data collection and analysis lead to interesting results about students starting attitudes and the effect on their performance. To further explore these results and extend them to more than one course, a second round of data collection was completed during the spring 2017 semester. Principal component analysis in connection with regression analysis indicated a relationship between students starting attitudes and their course performance. Cluster analysis indicated a two group structure in starting attitudes of the students in each course, with each cluster showing different achievement and learning preferences.

Area-based sampling approaches designed to capture pharmacies, drug shops, and other non-facility service delivery outlets are critical for accurately measuring the contraceptive service environment in contexts of increasing de-medicalization of contraceptive commodities and services. Evidence from other disciplines has demonstrated area-based estimates may be biased if there is spatial heterogeneity in product distribution, but this bias has not yet been assessed in the context of contraceptive supply estimates. The Consumer's Marker for Family Planning (CM4FP) study conducted censuses and product audits of contraceptive outlets across 12 study sites and 2-3 rounds of quarterly data collection in Kenya, Nigeria, and Uganda. We assessed bias in estimates of contraceptive product availability by comparing estimates from simulations of area-based sampling approaches with census counts among all audited facilities for each study site and round of data collection. We found evidence of bias in estimates of contraceptive availability generated from simulated area-based sampling. Within specific study sites and rounds, we observed biased sampling estimates for several but not all contraceptive method types, with bias more likely to occur in sites with heterogeneity in both spatial distribution of outlets and product availability within outlets. In simulations varying size of enumeration areas (EA) and number of outlets sampled per EA, we demonstrated that the likelihood of substantial bias decreases as EA size decreases and as the number of outlets sampled per EA increases. Straightforward approaches such as increasing sample size per EA or applying statistical weights may be used to reduce area-based sampling bias, indicating a pragmatic way forward to improve estimates where design-based sampling is infeasible. Such approaches should be considered in development of improved methods for area-based estimates of contraceptive supply-side environments.

A major part of the HEALing Communities Study (HCS), launched in 2019 to address the growing opioid epidemic, is evaluating the study's intervention implementation process through an implementation science (IS) approach. One component of the IS approach involves teams with more than 20 researchers collaborating across four research sites to conduct in-depth qualitative interviews with over 300 participants at four time points. After completion of the first two rounds of data collection, we reflect upon our qualitative data collection and analysis approach. We aim to share our lessons learned about designing and applying qualitative methods within an implementation science framework. The HCS evaluation is based on the RE-AIM/PRISM framework and incorporates interviews at four timepoints. At each timepoint, the core qualitative team of the Intervention Work Group drafts an interview guide based on the framework and insights from previous round(s) of data collection. Researchers then conduct interviews with key informants and coalition members within their respective states. Data analysis involves drafting, iteratively refining, and finalizing a codebook in a cross-site and within-site consensus processes. Interview transcripts are then individually coded by researchers within their respective states. Successes in the evaluation process includes having structured procedures for communication, data collection, and analysis, all of which are critical for ensuring consistent data collection and for achieving consensus during data analysis. Challenges include recognizing and accommodating the diversity of training and knowledge between researchers, and establishing reliable ways to securely store, manage, and share the large volumes of data. Qualitative methods using a team science approach have been limited in their application in large, multi-site randomized controlled trials of health interventions. Our experience provides practical guidance for future studies with large, experientially and disciplinarily diverse teams, and teams seeking to incorporate qualitative or mixed-methods components for their evaluations.

Area-based sampling approaches designed to capture pharmacies, drug shops, and other non-facility service delivery outlets are critical for accurately measuring the contraceptive service environment in contexts of increasing de-medicalization of contraceptive commodities and services. Evidence from other disciplines has demonstrated area-based estimates may be biased if there is spatial heterogeneity in product distribution, but this bias has not yet been assessed in the context of contraceptive supply estimates. The Consumer’s Marker for Family Planning (CM4FP) study conducted censuses and product audits of contraceptive outlets across 12 study sites and 2–3 rounds of quarterly data collection in Kenya, Nigeria, and Uganda. We assessed bias in estimates of contraceptive product availability by comparing estimates from simulations of area-based sampling approaches with census counts among all audited facilities for each study site and round of data collection. We found evidence of bias in estimates of contraceptive availability generated from simulated area-based sampling. Within specific study sites and rounds, we observed biased sampling estimates for several but not all contraceptive method types, with bias more likely to occur in sites with heterogeneity in both spatial distribution of outlets and product availability within outlets. In simulations varying size of enumeration areas (EA) and number of outlets sampled per EA, we demonstrated that the likelihood of substantial bias decreases as EA size decreases and as the number of outlets sampled per EA increases. Straightforward approaches such as increasing sample size per EA or applying statistical weights may be used to reduce area-based sampling bias, indicating a pragmatic way forward to improve estimates where design-based sampling is infeasible. Such approaches should be considered in development of improved methods for area-based estimates of contraceptive supply-side environments.