Affective learning: improving engagement and enhancing learning with affect-aware feedback

This paper describes the design and ecologically valid evaluation of a learner model that lies at the heart of an intelligent learning environment called iTalk2Learn. A core objective of the learner model is to adapt formative feedback based on students’ affective states. Types of adaptation include what type of formative feedback should be provided and how it should be presented. Two Bayesian networks trained with data gathered in a series of Wizard-of-Oz studies are used for the adaptation process. This paper reports results from a quasi-experimental evaluation, in authentic classroom settings, which compared a version of iTalk2Learn that adapted feedback based on students’ affective states as they were talking aloud with the system (the affect condition) with one that provided feedback based only on the students’ performance (the non-affect condition). Our results suggest that affect-aware support contributes to reducing boredom and off-task behavior, and may have an effect on learning. We discuss the internal and ecological validity of the study, in light of pedagogical considerations that informed the design of the two conditions. Overall, the results of the study have implications both for the design of educational technology and for classroom approaches to teaching, because they highlight the important role that affect-aware modelling plays in the adaptive delivery of formative feedback to support learning

Understanding Enrollment: Developing a Comprehensive Data File and Conducting Trend Analysis

The purpose of this project was to better understand enrollment trends related to first-year, direct-from-high school applicants for admissions to postsecondary education institutions. Analysis of this trend information could be used to evaluate program effectiveness, to assist in developing award allocation strategies, and to create a historical benchmark for future assessment projects or program evaluations. A secondary purpose of this project was to develop a model for use in conducting assessment and trend analysis projects using other institutions\u27 student populations. To complete this study, a comprehensive data file was developed with specifically selected information from students\u27 records in the admissions, registrar\u27s, and student financial aid offices

Combining Exploratory Learning With Structured Practice to Foster Conceptual and Procedural Fractions Knowledge

Robust domain knowledge consists of conceptual and procedural knowledge. The two types of knowledge develop together, but are fostered by different learning tasks. Exploratory tasks enable students to manipulate representations and discover the underlying concepts. Structured tasks let students practice problem-solving procedures step-by-step. Educational technology has mostly relied on providing only either task type, with a majority of learning environments focusing on structured tasks. We investigated in two quasi-experimental studies with 8-10 years old students from UK (N = 121) and 10-12 years old students from Germany (N = 151) whether a combination of both task types fosters robust knowledge more than structured tasks alone. Results confirmed this hypothesis and indicate that students learning with a combination of tasks gained more conceptual knowledge and equal procedural knowledge compared to students learning with structured tasks only. The results illustrate the efficacy of combining both task types for fostering robust fractions knowledge

Single-photon threshold photoionization of NO

Single‐photon threshold photoionization spectra for jet‐cooled NO have been measured for the v^+=0 and 1 vibrational levels of the X ^1Σ^+ ground state of NO^+. The NO^+ rotational state distribution for the v^+=0 level is shown to be perturbed by nearby autoionizing levels, whereas the v^+=1 level exhibits a cation rotational distribution which is in near quantitative agreement with calculated spectra near threshold. Only small changes in total angular momentum are observed (‖ΔJ‖=‖J^+ − J‘‖≤5/2) even though a wide range of photoelectron angular momenta (l=0–3) are predicted to contribute to the near‐threshold photoelectron continua. The present results are also discussed in light of recently published two‐photon threshold photoionization spectra of NO which exhibit nearly identical NO^+ rotational state distributions

Combining exploratory learning with structured practice educational technologies to foster both conceptual and procedural fractions knowledge

Educational technologies in mathematics typically focus on fostering either procedural knowledge by means of structured tasks or, less often, conceptual knowledge by means of exploratory tasks. However, both types of knowledge are needed for complete domain knowledge that persists over time and supports subsequent learning. We investigated in two quasi-experimental studies whether a combination of an exploratory learning environment, providing exploratory tasks, and an intelligent tutoring system, providing structured tasks, fosters procedural and conceptual knowledge more than the intelligent tutoring system alone. Participants were 121 students from the UK (aged 8–10 years old) and 151 students from Germany (aged 10–12 years old) who were studying equivalent fractions. Results confirmed that students learning with a combination of exploratory and structured tasks gained more conceptual knowledge and equal procedural knowledge compared to students learning with structured tasks only. This supports the use of different but complementary educational technologies, interleaving exploratory and structured tasks, to achieve a “combination effect” that fosters robust fractions knowledge

Метод CRAMM - комплексный подход к оценке рисков

The article shows the use of the method CRAMM for risk management and research of information security systems

Ion rotational distributions for near-threshold photoionization of H_2O

Ion rotational distributions for single‐photon VUV photoionization of the 1b_1 orbital of the X̃ ^1A_1 ground state of the jet‐cooled water are reported. These spectra reveal significant type a transitions which are seen to arise from odd angular momentum components of the photoelectron matrix element. The resulting photoionization dynamics are quite nonatomic‐like

Validation of flank-to-flank allometric equations in predicting weight of lactating sows and lactation weight change

The objectives of this study were to validate the use of flank-to-flank measurement in predicting weight of lactating sows and to determine the accuracy of the developed models in estimating lactation weight change. A total of 70 lactating sows (PIC Line 1050) were used in this study. Flank-to-flank measurement and body weight were measured on each individual sow after farrowing and at weaning. Flank-to-flank measurement and weight of lactating sows was positively correlated (R2 = 0.61; P<.0001) with the following equation: BW0.33, kg = 0.0371 x Flank-to-flank (cm) + 2.161. Weights of sows post-farrowing and at weaning were lower (P<0.03) when predicted with the previous allometric model developed from growing pigs and sows than their actual weights or weights predicted using the lactating sow model. Likewise, absolute residuals for post-farrowing and weaning weights using a previous allometric model developed from growing pigs and gestating sows were greater (P<0.02) than those of the lactating sow model. There were no differences (P<0.89) between the predicted weights using the lactating sow model and their actual weights. There also were no differences between the actual average weight loss (P<0.14) and the predicted loss using the lactating sow model. Using the model previously developed with growing pigs and gestating sows resulted in 15.5 lb (P<0.007) greater than the actual average weight loss. In conclusion, flank-to-flank measurement can be used as a predictor of weight of lactating sows, with the relationship having less accuracy than those used for growing-finishing pigs, gestating sows, and boars. The pig allometric equation cannot be used to estimate weights of lactating sows and lactation weight change. The developed lactating sow model was more appropriate in estimating weights and weight loss at the herd level, but needs to be validated on other sows before use can be recommended

Carbon footprints of cities and other human settlements in the UK

A growing body of literature discusses the CO2 emissions of cities. Still, little is known about emission patterns across density gradients from remote rural places to highly urbanized areas, the drivers behind those emission patterns and the global emissions triggered by consumption in human settlements—referred to here as the carbon footprint. In this letter we use a hybrid method for estimating the carbon footprints of cities and other human settlements in the UK explicitly linking global supply chains to local consumption activities and associated lifestyles. This analysis comprises all areas in the UK, whether rural or urban. We compare our consumption-based results with extended territorial CO2 emission estimates and analyse the driving forces that determine the carbon footprint of human settlements in the UK. Our results show that 90% of the human settlements in the UK are net importers of CO2 emissions. Consumption-based CO2 emissions are much more homogeneous than extended territorial emissions. Both the highest and lowest carbon footprints can be found in urban areas, but the carbon footprint is consistently higher relative to extended territorial CO2 emissions in urban as opposed to rural settlement types. The impact of high or low density living remains limited; instead, carbon footprints can be comparatively high or low across density gradients depending on the location-specific socio-demographic, infrastructural and geographic characteristics of the area under consideration. We show that the carbon footprint of cities and other human settlements in the UK is mainly determined by socio-economic rather than geographic and infrastructural drivers at the spatial aggregation of our analysis. It increases with growing income, education and car ownership as well as decreasing household size. Income is not more important than most other socio-economic determinants of the carbon footprint. Possibly, the relationship between lifestyles and infrastructure only impacts carbon footprints significantly at higher spatial granularity