Evaluation of Chemical Control of Botrytis Cinerea in Relation to Covering Red Current Shrubs

Covering red currant during the development of the fruits guarantees high quality fruits and delays picking time. Because of these reasons, the number of fruit growers using cover production system is increasing. Covering red currant affects fungicide action and efficacy. Furthermore the climate conditions are altered in the shrub resulting in a different infection risk/pressure for certain fungal diseases. The effect of the timing of covering on the control of Botrytis cinerea which is the cause of the mayor fruit rot disease of red currants was studied. The results from the trials clearly show the positive effect of covering during bloom on the chemical control of Botrytis on red currant. The chemical control of plants during bloom which were covered from bloom equals that of a full season chemical control of uncovered plants or plants covered after fruit set. The full season chemical control of plants covered from bloom was only statistically better then all other objects tested in one of the two trials. Covering alone without chemical control had only a limited effect

III/V-on-lithium niobate amplifiers and lasers

We demonstrate electrically pumped, heterogeneously integrated lasers on thin-film lithium niobate, featuring electro-optic wavelength tunability. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA

Purpose: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. Methods: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Results: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0–1.00) and 85.9% (75.4–92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20–2.92) or receiving a written TLD (HR 2.32, CI 1.11–4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Conclusion: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Adults’ self-regulatory behaviour profiles in blended learning environments and their implications for design

Blended forms of learning have become increasingly popular. However, it remains unclear under what circumstances blended learning environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit in such environments. This limited understanding is problematic since this insight is needed for effective designs. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate them to designs of blended learning environments. Learners’ (n = 120) self-regulatory behaviour in six ecologically valid blended learning courses was captured. Log files were analysed in a learning analytics fashion for frequency, diversity, and sequence of events. Three main user profiles were identified. The designs were described using a descriptive framework containing attributes that support self-regulation in blended learning environments. Results indicate fewer mis-regulators when more self-regulatory design features are integrated. These finding highlights the value of integrating features that support self-regulation in blended learning environmentsstatus: Published onlin

Learners’ self-regulatory behavior in blended learning environments: Towards design guidelines for supporting self-regulation

In response to the need for design guidelines to support learners’ self-regulation in blended learning environments, six blended learning environments were compared and linked to learners’ self-regulatory behavior (n=137). A dedicated framework was developed to describe these environments and trace data was used to identify learner self-regulatory behavior profiles. We found that when more self-regulation supporting attributes were integrated, fewer poor self-regulating learners were observed. Finally, gaps were identified and design guidelines proposed.status: publishe

Uncovering the relationship between learners' self-regulatory behaviour profiles and designs of blended learning environments

The analysis of behavioural data provides new avenues for investigating the sequential nature of self-regulation. This contribution describes the data-driven approach used in a study that aimed to identify the relationship between learners’ characteristics and their self-regulatory behaviour by performing event sequence analysis on log files extracted from ecologically valid online learning environments. In the first phase of the study, we described the instructional context as an external condition in order to map any aspects that might support self-regulation. We collected data on relevant learner characteristics as internal conditions and extracted timestamped log-file data as indicators of learners’ self-regulatory behaviour. Next, the data was cleaned and recoded using an action library. The third phase focused on discovering event patterns using the TraMineR package in R to identify frequent sub-sequences (Levenshtein distance) (Gabadinho, Ritschard, Studer, & Müller, 2009). Finally, significant discriminant sub-sequences were described in relation to various learner characteristics (Pearson’s Chi-square test). The results demonstrate how the design of an online learning environment triggers different event sequences — and hence different self-regulatory behaviour — in learners with different characteristics. The study offers a starting point for discussing sequence analysis of log files extracted from ecologically valid environments, as well as the conceptual and methodological issues related to this type of research.status: publishe

The effect of cues for calibration on learners' self-regulated learning through changes in learners’ learning behaviour and outcomes

Literature on blended learning emphasizes the importance of self-regulation for learning in blended learning environments and the role of learners’ calibration. Although literature on calibration is clear on its importance for self-regulated learning, it provides inconclusive insight in the effect of support for calibration on learners’ self-regulated learning. One under-investigated avenue might be learners’ ability to enact on the cues provided. In order to establish a more accurate picture of the effect of support for calibration on self-regulated learning, our study investigates whether providing cues for calibration affect learners’ self-regulated learning, and whether this effect is different for learners with different metacognitive abilities. We investigate this effect by examining changes in learners’ learning behaviour and outcomes. A pre-post design with one control and two experimental conditions was applied in a blended learning environment. Learners in the experimental conditions received either functional validity feedback (F-condition) or functional and cognitive validity feedback (FC-condition). Learners in the control condition did not receive any cues. Learners’ behaviour was analysed using event sequence analysis. Learners’ post-test learning scores were subjected to multivariate analysis of covariance, with condition and learners’ metacognitive ability as independent variables. The results show a significant and unexpected impact of condition and learners’ metacognitive abilities on learners’ learning behaviour and outcomes. This manuscript discusses the unexpected results in terms of their theoretical and practical implications and provides recommendations for future research. We conclude that when cues for calibration are provided through functional and cognitive validity feedback, learners’ calibration capabilities will increase. Yet for this to result in goal-directed self-regulated learning, we hypothesize learners’ might need to be supported on how to apply the cognitive and metacognitive strategies needed.status: Published onlin

Adults’ self-regulatory behaviour profiles in blended learning environments and their implications for design

Blended forms of learning have become increasingly popular. Learning activities within these environments are supported by large varieties of online and face-to-face interventions. However, it remains unclear whether these environments are successful, and if they are, what makes them successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit within these learning environments. This limited understanding is problematic since this insight is needed to be able to make an effective design, suitable for its target group. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate these profiles to the design of these environments. To do this, we first captured learners’ (n=120) self-regulatory behaviour in six blended learning courses from two institutions. As self-regulation in this study was seen as a continuously evolving event, ecological trace data was used to describe learners’ behaviour. The trace files were analysed for frequency, timing, patterns, and sequence of events. Three main user profiles were identified (internal regulator, external regulator, and miss-regulator). We described the design of each of the learning environments, using a framework consisting of seven blended learning environment attributes that support self-regulation. Although this study focuses mainly on the online component of the learning environment, the results do indicate that fewer miss-regulators are identified in courses, which have more integrated self-regulatory design features. This finding highlights the value to integrate features that support self-regulation in the design of blended learning environments. The contribution will elaborate further on the roles identified and their relation to the design of blended learning environments.status: publishe