The Relation Between Autonomy and Well-Being in Higher Education Students During the COVID-19 Pandemic

During the COVID-19 pandemic, higher education has drastically moved online, which has increased the importance of autonomous learning by students. A decrease in students' well-being has meanwhile been registered across the globe. In this study, we examine which learning characteristics increase student well-being under the pandemic constraints. We investigate students' well-being, specifically burnout, amotivation, and study engagement, and their relation to learning autonomy. Two types of autonomy were included: autonomy at the student-level and autonomy at the instructor-level, measured via the instructors' communication and support provided for online learning. Our analyses show that amotivation and burnout correlated negatively with both kinds of autonomy. Similarly, student engagement correlated positively with both kinds of autonomy. A multiple regression showed that student-level autonomy was the only variable to significantly predict all three well-being variables, while instructor support predicted only study engagement and burnout. Instructor communication did not predict any well-being variables. Implications, limitations, and future directions for the role of autonomy in online learning are discussed

Methods for studying the writing time-course

The understanding of the cognitive processes that underlie written composition requires analysis of moment-by-moment fluctuation in the rate of output that go beyond traditional approaches to writing time-course analysis based on, for example, counting pauses. This special issue includes 10 papers that provide important new tools and methods for extracting and analyzing writing timecourse data that go beyond traditional approaches. The papers in this special issue divide into three groups: papers that describe methods for capturing and coding writing timecourse data from writers producing text either by hand or by keyboard, papers that describe new statistical approaches to describing and drawing inferences from these data, and papers that focus on analysis of how a text develops over time as the writer makes changes to what they have already written

Nitrous oxide emissions from grass–clover swards as influenced by sward age and biological nitrogen fixation

Grassland renovation by cultivation and reseeding has been shown to increase short‐term emissions of N2O, but there is uncertainty about long‐term effects, despite the potential impacts of reseeding on sward composition and soil functions. A field experiment was therefore carried out to determine how N2O emissions from previously renovated grasslands varied in the intermediate to long‐term, compared with an undisturbed permanent grassland (PG). Plots on the PG site were renovated, either two (G2) or five (G5) years prior to the two experimental years. In each sward age and experimental year, annual N2O‐measurements were conducted on a weekly basis and compared with the undisturbed PG. Plots were either unfertilized or were fertilized with slurry (240 kg N ha−1 year−1). On average, annual N2O emissions were 0.39 kg N/ha for the unfertilized swards, and 0.91 kg N/ha for slurry‐fertilized swards. Sward age had no effect on N2O emissions. With increasing sward age the proportion of legumes in the sward was reduced, but a minimum biological nitrogen fixation (BNF) of 88 kg N/ha was maintained even in the fertilized PG. Both sward age and BNF were of limited importance for the annual N2O emissions compared with the effects of soil carbon content and nitrogen surplus levels. However, measured N2O emissions were low in all sward age treatments, with a low risk of additional N2O emissions when BNF is taken into account in fertilizer planning

Are You Being Rhetorical? A Description of Rhetorical Move Annotation Tools and Open Corpus of Sample Machine-Annotated Rhetorical Moves

Writing analytics has emerged as a sub-field of learning analytics, with applications including the provision of formative feedback to students in developing their writing capacities. Rhetorical markers in writing have become a key feature in this feedback, with a number of tools being developed across research and teaching contexts. However, there is no shared corpus of texts annotated by these tools, nor is it clear how the tool annotations compare. Thus, resources are scarce for comparing tools for both tool development and pedagogic purposes. In this paper, we conduct such a comparison and introduce a sample corpus of texts representative of the particular genres, a subset of which has been annotated using three rhetorical analysis tools (one of which has two versions). This paper aims to provide both a description of the tools and a shared dataset in order to support extensions of existing analyses and tool design in support of writing skill development. We intend the description of these tools, which share a focus on rhetorical structures, alongside the corpus, to be a preliminary step to enable further research, with regard to both tool development and tool interaction</jats:p

Effectiveness of a web-based self-help smoking cessation intervention: protocol of a randomised controlled trial

BACKGROUND: Cigarette smoking is a major risk factor for many chronic and fatal illnesses. Stopping smoking directly reduces those risks. The aim of this study is to investigate the effectiveness of a web-based interactive self-help programme for smoking cessation, known as the StopSite, by comparing it to an online self-help guide. Both interventions were based on cognitive-behavioural and self-control principles, but the former provided exercises, feedback and interactive features such as one-to-one chatrooms and a user forum, which facilitated mutual support and experience sharing. METHODS AND DESIGN: We conducted a randomised controlled trial to compare the interactive intervention with the self-help guide. The primary outcome measure was prolonged abstinence from smoking. Secondary outcomes were point-prevalence abstinence, number of cigarettes smoked, and incidence of quit attempts reported at follow-up assessments. Follow-up assessments took place three and six months after a one-month grace period for starting the intervention after baseline. Analyses were based on intention-to-treat principles using a conservative imputation method for missing data, whereby non-responders were classified as smokers. DISCUSSION: The trial should add to the body of knowledge on the effectiveness of web-based self-help smoking cessation interventions. Effective web-based programmes can potentially help large numbers of smokers to quit, thus having a major public health impact. TRIAL REGISTRATION: ISRCTN7442376

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information