Software development requires understanding and navigating complex software spaces. Developers frequently utilize annotations in source code to help them externalize information they need to remember, such as tasks and implementation details. Although some tool support exists in modern integrated development environments for authoring and navigating these annotations, we have observed that they often fail to remind developers about tasks that need to be performed and are sometimes difficult to find. We present the results from four empirical studies designed to better understand how developers create and manage their information using annotations. We also explore the use of hierarchical tagging capabilities to enhance these annotations. Based on the findings from these studies, we provide suggestions on how annotation tools may be improved.

In the field of second language acquisition, there are few studies focusing on Chinese English-as-an-additional-language (EAL) graduate students’ communication strategy use, strategy use across different disciplines, and the relationships between communication strategy use and learners’ speaking performance. To fill the gap identified in the literature reviewed, this study examined the communication strategies used by 11 Chinese EAL graduate students from the Departments of Electrical Engineering and Education in the completion of two informal debate tasks with a questionnaire adapted from Nakatani’s (2006) Oral Communication Strategy Inventory and two post-task communication strategy recall questionnaires. Results from the study indicate that participants used eight categories of communication strategies, with fluency-oriented strategies the most frequently used strategy category and translation the least frequently used strategy category. Advanced English-language proficiency level learners used more social affective, message reduction and alteration, and negotiation of meaning strategies than learners at high-intermediate proficiency levels, to a degree that was statistically significant. No significant difference was identified in the overall communication strategy use but in one instance of individual strategy use (i.e., clarifying stance) across two disciplines. Significantly positive relationships were identified among certain categories of communication strategies (i.e., social affective, negotiation of meaning, accuracy-oriented strategies, and message reduction and alteration strategies), individual strategies (i.e., turn yielding, exemplifying, clarifying meaning, correcting others, referring to notes for accuracy/fluency, message reduction and alteration), and participants’ speaking performance. In addition, the retrospective results from the post-task strategy recall questionnaires suggest that participants in this study are not fully aware of their communication strategy use. The findings in this study can inform language practitioners’ of communication strategies used by Chinese graduate students majoring in Electrical Engineering and Education. Implications and future research directions are discussed in light of the findings derived from the present study that can further contribute to research about EAL learners’ communication strategies used at the graduate level. / Graduate / 0290 / cihangzh@uvic.ca

Background Nurses complete tasks during patient care to promote the recovery, or to maintain the health, of patients. These tasks can be routine or non-routine to the nurse. Non-routine tasks are characterized by unfamiliarity, requiring nurses to seek additional information from a variety of sources to effectively complete the tasks. Nurses’ perception of their problem-solving skills, as characterized by the attributes of personal control, problem-solving confidence, and avoidance-approach style, influences how information is sought. Objectives/Research Questions Guided by the information-seeking behaviour model, this study was designed to: (1) examine how the non-routineness of the task affects nurses’ information-seeking behaviour and the use of accumulated knowledge; and, (2) explore nurses’ perception of their problem-solving abilities. Methods An exploratory cross-sectional survey design was used. A random sample of critical care nurses who worked in a hospital setting were selected from the College of Nurses of Ontario (CNO) research participant database. Multiple regression analysis was used to examine the proposed relationships. Results Avoidance-approach style and, problem-solving confidence did not have a significant relationship with nurses’ information-seeking behaviour. None of the variables explained use of accumulated knowledge (F = 0.902, p > 0.05). Previous training (p = 0.008), Non-routineness of the task (p = 0.018), and Personal control (p = 0.040) had a positive relationship with information-seeking behaviour (Adjusted R2 = 0.136). Implications The study results provide evidence that problem-solving ability, and in particular the attribute of personal control, influences nurses’ information-seeking behaviour during the completion of nursing tasks. They reveal how information is sought from resources, and what specific information resources are necessary to promote access to, and use of, evidence-based information. The results also help direct efforts towards training nurses in issues related to problem-solving and information-seeking by targeting the development of personal control and retrieving evidence-based information.

The article deals with a special kind of modelling tass. These problems are used for learning and researching as well. So the results of an empirical study on mathematical modelling of pupils in secondary schools are presented. Pupils of forms 8-10 were observed working on open, realistic problems. These observations were recorded and evaluated. The goal of the presented part of the study is a detailed look at the control processes of modelling problems. In this context changes between real life control and mathematical control during the control phases are studied and evaluated. We describe in detail the sub phases of controlling and explain their connection with modelling process. The problems used in this project can also be used in math lessons, so this kind of research can put teachers and researchers together. These tasks are suitable to support ongoing in-service development and teacher education.

Type 2 diabetes mellitus (T2DM) is now increasingly diagnosed in children and adolescents at an alarming rate, especially in youth from diverse ethnic backgrounds. Youth diagnosed with T2DM and their families face many challenges associated with the illness and its complications. Given that the prevalence of T2DM in youth is a recent trend, most of the studies examining T2DM have been conducted with adults. The current study expands the literature base of youth with T2DM by collecting demographic and clinical data of youth with T2DM and their families. Regression analyses were used to investigate the relationship among youth's executive function, their body mass index (BMI) and glycosylated hemoglobin (HbA1c) level. Furthermore, the study analyzed the relationship among depressive symptoms and health related quality of life (HRQOL) in youth, and the role of family members in sharing of tasks related to T2DM care and the youth's HRQOL. Results of this study demonstrated that executive function does not predict a youth's HbA1c, nor their BMI. Interestingly, one of the more significant findings to emerge from this study is that youth's rating of their ability to adjust to changes in routine or task demands and their ability to modulate emotions significantly correlated with their BMI. Results also demonstrated that HbA1c does not mediate the relationship between depressive symptoms and HRQOL, nor the relationship between the family sharing of responsibilities related to T2DM tasks and HRQOL. Future research examining the relationship among psychological and family characteristics can aid the development of diabetes prevention and treatment management.

The purpose of this study was to evaluate the utility of the Adaptive Tasks Framework for assessing parental needs when providing primary care for their child with a chronic health condition. A qualitative descriptive methodology framed the study and two methods were employed to collect data: a secondary analysis of existing interview data from seven parents of children with chronic health conditions and interviews with four parents who were currently providing primary care for their child with a chronic health condition. The data was analyzed using content analysis, whereby interview data was explored to determine if it fit into one or more of the eight adaptive tasks categories. Parents reported needs in all of the eight adaptive tasks categories, with the need for information regarding their child's chronic health condition being the foremost concern among parents. The need for caring, empathetic, and patient health care professionals who are sympathetic to the informational needs of parents, while at the same time acknowledging their expertise, was the second need expressed by the parents in this study. Implications of these findings for nurses is that the Adaptive Tasks Framework provides a useful tool for assessing parental needs when managing their child's chronic health condition and for determining areas in which the parents may require support.

Real-world learning tasks present a range of issues for learning systems. Learning tasks can be complex and the training data noisy. When operating as part of a larger system, there may be limitations on available memory and computational resources. Learners may also be required to provide results from a stream. This thesis investigates the problem of incremental, relational learning from imperfect data with constrained time and memory resources. The learning process involves incremental update of a theory when an example is presented that contradicts the theory. Contradictions occur if there is an incorrect theory or noisy data. The learner cannot discriminate between the two possibilities, so both are considered and the better possibility used. Additionally, all changes to the theory must have support from multiple examples. These two principles allow learning from imperfect data. The Minimum Description Length principle is used for selection between possible worlds and determining appropriate levels of additional justification. A new encoding scheme allows the use of MDL within the framework of Inductive Logic Programming. Examples must be stored to provide additional justification for revisions without violating resource requirements. A new algorithm determines when to discard examples, minimising total usage while ensuring sufficient storage for justifications. Searching for revisions is the most computationally expensive part of the process, yet not all searches are successful. Another new algorithm uses a notion of theory stability as a guide to occasionally disallow entire searches to reduce overall time. The approach has been implemented as a learner called NILE. Empirical tests include two challenging domains where this type of learner acts as one component of a larger task. The first of these involves recognition of behavior activation conditions in another agent as part of an opponent modeling task. The second, more challenging task is learning to identify objects in visual images by recognising relationships between image features. These experiments highlight NILE'S strengths and limitations as well as providing new n domains for future work in ILP.

The effects of caffeine (250 mg) and placebo on healthy controls were studied in a double-blind, cross over study on 24 healthy subjects who performed a working memory n-back task. Reaction time and accuracy levels were tested using the n-back working memory measure in cognitive neuroscience. An experimental study tested on the 1, 2 and 3-back tasks under the placebo/coffee condition. Based on the empirical results obtained in this thesis it can be concluded that changes produced by caffeine ingestion support the hypothesis that caffeine acts as a stimulant. However, it cannot be proven that the stimulant translates into enhanced motor processes with an improvement in performance.

Software development requires understanding and navigating complex software spaces. Developers frequently utilize annotations in source code to help them externalize information they need to remember, such as tasks and implementation details. Although some tool support exists in modern integrated development environments for authoring and navigating these annotations, we have observed that they often fail to remind developers about tasks that need to be performed and are sometimes difficult to find. We present the results from four empirical studies designed to better understand how developers create and manage their information using annotations. We also explore the use of hierarchical tagging capabilities to enhance these annotations. Based on the findings from these studies, we provide suggestions on how annotation tools may be improved.

In many early intensive behavioural intervention (EIBI) programs, such as the St.Amant Autism Programs in Manitoba, the Assessment of Basic Language and Learning Skills-Revised (ABLLS-R) is used as an assessment guide, a curriculum guide, and a skills tracking system. The ABLLS-R lists a total of 544 potential training tasks. In the St.Amant Autism Programs, the Assessment of Basic Learning Abilities-Revised (ABLA-R) is also used to assess a child’s ability to learn to perform 6 tasks, called levels, which are hierarchical in difficulty. Research has demonstrated that training tasks comparable to failed ABLA-R levels are very difficult to teach using standard prompting and reinforcement procedures, and training tasks that are mismatched to a client’s highest-passed ABLA-R level result in more aberrant behaviours than matched tasks. The purpose of this study was to evaluate whether the difficulty of the training tasks taught to children enrolled in the St.Amant Autism Early Learning Program matched the learning abilities of the children. In order to do so, five questions were examined based on the ABLLS-R, the ABLA-R, and archival data from the St.Amant Autism Programs. The results reveal several potentially important findings. First, observers who were knowledgeable about the ABLA-R reliably categorized 99 of the 544 ABLLS-R tasks into individual ABLA-R levels. Second, for a random sample of those 99 ABLLS-R tasks, Autism Consultants from the St.Amant Autism Programs averaged 90.5% agreement that those tasks were taught at the categorized ABLA-R levels. Third, across a sample of 14 children, 81% of their training tasks were mismatched to each child’s highest-passed ABLA-R level. Fourth, for that sample of 14 children and across their 31 maladaptive behaviour assessments, 61% of the assessments had a score representative of maladaptive behaviours. Fifth, for that same sample of children, their rates of acquisition of new training tasks were lower for mismatched tasks than for matched tasks. These findings have important implications for potentially improving the services that children with ASD are receiving from the St.Amant Autism Programs and other EIBI programs. / February 2016