An Examination of Abstraction in K-12 Computer Science Education

Computer scientists have been working towards a common definition of abstraction; however, the instruction and assessment of abstraction remain categorically underresearched. Because abstraction is often cited as a component of computational thinking, abstraction has been summarily likened to a higher order thinking skill. A broad conceptual framework including philosophy, psychology, constructionism, and computational thinking was aligned with the descriptive qualitative design and guided the literature review and data analysis. This qualitative examination of how teachers determine curriculum, deliver instruction, and design assessments in K-12 computer science education provides insight into best practices and variables for future quantitative study. The instructional strategies, objectives, and assessments of twelve K-12 computer science teachers from 3 states were examined in this descriptive qualitative examination of instruction using thematic coding analysis. The majority of teachers had little to no professional development regarding teaching abstraction. All teachers in the study were unsure what student abstraction abilities should be according to grade level. Teachers\u27 understanding of abstraction ranged from very little knowledge to very knowledgeable. The majority of teachers did not actively assess abstraction. Teachers described successfully teaching abstraction through multiple instructional practices and spiraling curriculum. Practical descriptive insights illuminate additional variables to research the instruction of abstraction qualitatively and quantitatively, as well as provide anecdotal instructional successes

Bayesian retrieval of complete posterior PDFs of oceanic rain rate from microwave observations

A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain-rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes’s theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance the understanding of theoretical benefits of the Bayesian approach, sensitivity analyses have been conducted based on two synthetic datasets for which the “true” conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism, but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak owing to saturation effects. It is also suggested that both the choice of the estimators and the prior information are crucial to the retrieval. In addition, the performance of the Bayesian algorithm herein is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate

An International Pilot Study of K-12 Teachers’Computer Science Self-Esteem

Computer Science (CS) is a new subject area for many K-12 teachersaround the world, requiring new disciplinary knowledge and skills.Teacher social-behavioral factors (e.g. self-esteem) have been foundto impact learning and teaching, and a key part of CS curriculumimplementation will need to ensure teachers feel confident to de-liver CS. However, studies about CS teacher self-esteem are lacking.This paper presents an analysis of publicly available data (n=219)from a pilot study using a Teacher CS Self-Esteem scale. Analy-sis revealed significant differences, including 1) females reportedsignificantly lower CS self-esteem than males, 2) primary teachersreported lower levels of CS self-esteem than secondary teachers, 3)those with no CS teaching experience reported significantly lowerCS self-esteem, 4) teachers with 0-3 years experience had a neg-ative CS self-esteem, but after four years, teachers had a positiveCS self-esteem, and 5) teachers who lived further from metropol-itan areas and in some countries reported lower CS self-esteem.These initial findings suggest a pressing need for future researchto look further into teacher CS self-esteem to inform teacher CSprofessional development

Using Factorial Survey Experiments to Measure Attitudes, Social Norms, and Fairness Concerns in Developing Countries

Survey-based experimental methods are increasingly used in the social sciences to study, among others, attitudes, norms, and fairness judgments. One of these methods is the factorial survey experiment (FSE or vignette experiment) in which respondents are confronted with various descriptions of situations that differ in a discrete number of attributes (or factors), and they are asked to evaluate those situations according to criteria such as agreement, approval, and fairness. Due to the systematic experimental variation of the presented situations, an FSE can separate effects of single situational attributes, allowing the causal influence of relevant situationalattributes to be determined. This is the key advantage over simple survey items. While most studies using FSEs are carried out in developed countries in which respondents are familiar with surveys, we add further evidence that this method can also unfold its power in a developing context. Building on previous applications of FSEs in Africa, we demonstrate the usefulness of this method in four novel studies on social norms regarding the physical punishment of children and the social approval of technology adoption in Benin as well as judgments of just earnings in Rwanda. We also test for the first time the applicability of multiple vignettes per respondents in a Global South/remote area context. The results of these studies are theoretically meaningful and the overwhelming majority of respondents discriminate between vignettes. This supports the validity of FSEs. However, conducting survey experiments in developing countries is different from similar experimental research in developed countries and, therefore, we also discuss some of these differences and corresponding challenges. Last but not least, our article shows, provided a few precautions are heeded, that FSEs could be used as a vehicle to innovate social science research in a Global South/remote area context

Using factorial survey experiments to measure attitudes, social norms, and fairness concerns in developing countries

Survey-based experimental methods are increasingly used in the social sciences to study, among others, attitudes, norms, and fairness judgments. One of these methods is the factorial survey experiment (FSE or vignette experiment) in which respondents are confronted with various descriptions of situations that differ in a discrete number of attributes (or factors), and they are asked to evaluate those situations according to criteria such as agreement, approval, and fairness. Due to the systematic experimental variation of the presented situations, an FSE can separate effects of single situational attributes, allowing the causal influence of relevant situational attributes to be determined. This is the key advantage over simple survey items. While most studies using FSEs are carried out in developed countries in which respondents are familiar with surveys, we add further evidence that this method can also unfold its power in a developing context. Building on previous applications of FSEs in Africa, we demonstrate the usefulness of this method in four novel studies on social norms regarding the physical punishment of children and the social approval of technology adoption in Benin as well as judgments of just earnings in Rwanda. We also test for the first time the applicability of multiple vignettes per respondents in a Global South/remote area context. The results of these studies are theoretically meaningful and the overwhelming majority of respondents discriminate between vignettes. This supports the validity of FSEs. However, conducting survey experiments in developing countries is different from similar experimental research in developed countries and, therefore, we also discuss some of these differences and corresponding challenges. Last but not least, our article shows, provided a few precautions are heeded, that FSEs could be used as a vehicle to innovate social science research in a Global South/remote area context

An International Benchmark Study of K-12 Computer Science Education in Schools

There has been a growing interest and increase in work shared about national K-12 Computer Science Education (CSED) curriculum and implementation efforts around the world. Much of this work focuses on curriculum analysis, country reports, experience reports and case studies. The K-12 CSED community would benefit from an international strategic effort to compare, contrast and monitor K-12 CSED over time, across multiple countries and regions, to understand pedagogy, practice, resources and experiences from the perspective of teachers working in classrooms. Furthermore, there is a need for validated and robust instruments that can support comparable investigations into the current state of K-12 CSED in schools around the world. Through a collaborative effort, this Working Group will develop a validated teacher survey instrument and collect data about CSED implementation and practice in K-12 classrooms. The authors will pilot the survey with K-12 teacher cohorts and analyse, compare and contrast survey findings across countries

An International Comparison of K-12 Computer Science Education Intended and Enacted Curricula

This paper presents an international study of K-12 Computer Science implementation across Australia, England, Ireland, Italy, Malta, Scotland and the United States. We present findings from a pilot study, comparing CS curriculum requirements (intended curriculum) captured through country reports, with what surveyed teachers (n=244) identify as enacting in their classroom (the enacted curriculum). We address the extent that teachers are implementing the intended curriculum as enacted curriculum, exploring specifically country differences in terms of programming languages and CS topics implemented. Our findings highlight the similarities and differences of intended and enacted CS curriculum within and across countries and the value of such comparisons