134,772 research outputs found
Validation of Diabetes Mellitus Patient Behavior Questionnaire in Primary Health Care Service
This study aimed to develop and validation a questionnaire as measurement instrument for knowledge and adherence behavior of DM patients in primary health care. Cross sectional study design was conducted in diabetes mellitus patient. Inclusion criteria were patients in the age group 18-65 years, diagnosed with DM, receiving at least one oral antidiabetic medication. Questionnaire questions for behavioral item were developed based on Diabetes Mellitus management guidelines and references to previous studies. Evaluation and validation by expert was carried out on diabetes mellitus experts and clinical psychologists. The pilot study was conducted on 10 healthy patients and 10 patients with diabetes who enrolled inclusion criteria. Questionnaire validation test was conducted with 41 DM outpatient at PKU Muhammadiyah Hospital in Yogyakarta. Collecting data by interviewing patients based on questionnaire. Statistical analysis was performed using SPSS with Pearson correlation coefficients for validation test and Cronbach alpha coefficients for reliability test of the questionnaire. Adherence behavior questionnaire consists of 12 question items, which are divided into three domains: cognitive, affective, and psychomotor domains. Validation results showed 12 valid items where the pearson correlation value was>0.308 (n=41). Cronbach alpha as reliability test results showed 0.78. This result showed a questionnaire were valid and reliable in Diabetes Mellitus patients. This instrument would be use in primary health care for measuring adherence behavior of DM patients
Dynamic Key-Value Memory Networks for Knowledge Tracing
Knowledge Tracing (KT) is a task of tracing evolving knowledge state of
students with respect to one or more concepts as they engage in a sequence of
learning activities. One important purpose of KT is to personalize the practice
sequence to help students learn knowledge concepts efficiently. However,
existing methods such as Bayesian Knowledge Tracing and Deep Knowledge Tracing
either model knowledge state for each predefined concept separately or fail to
pinpoint exactly which concepts a student is good at or unfamiliar with. To
solve these problems, this work introduces a new model called Dynamic Key-Value
Memory Networks (DKVMN) that can exploit the relationships between underlying
concepts and directly output a student's mastery level of each concept. Unlike
standard memory-augmented neural networks that facilitate a single memory
matrix or two static memory matrices, our model has one static matrix called
key, which stores the knowledge concepts and the other dynamic matrix called
value, which stores and updates the mastery levels of corresponding concepts.
Experiments show that our model consistently outperforms the state-of-the-art
model in a range of KT datasets. Moreover, the DKVMN model can automatically
discover underlying concepts of exercises typically performed by human
annotations and depict the changing knowledge state of a student.Comment: To appear in 26th International Conference on World Wide Web (WWW),
201
Application of Qualitative Methods in Health Research: An Overview
Qualitative research is type of formative research that includes specialized techniques for obtaining in-depth responses about what people think and how they feel. It is seen as the research that seeks answer to the questions in the real world. Qualitative researchers gather what they see, hear, read from people and places, from events and activities, with the purpose to learn about the community and to generate new understanding that can be used by the social world. Qualitative research have often been conducted to answer the question âwhyâ rather than âwhatâ. A purpose of qualitative research is the construction of new understanding. Here, we present an overview of application of qualitative methods in health research. We have discussed here the different types of qualitative methods and how we and others have used them in different settings/scenarios; sample size and sampling techniques; analysis of qualitative data; validity in qualitative research; and ethical issues
Innovative teaching of IC design and manufacture using the Superchip platform
In this paper we describe how an intelligent chip architecture has allowed a large cohort of undergraduate students to be given effective practical insight into IC design by designing and manufacturing their own ICs. To achieve this, an efficient chip architecture, the âSuperchipâ, has been developed, which allows multiple student designs to be fabricated on a single IC, and encapsulated in a standard package without excessive cost in terms of time or resources. We demonstrate how the practical process has been tightly coupled with theoretical aspects of the degree course and how transferable skills are incorporated into the design exercise. Furthermore, the students are introduced at an early stage to the key concepts of team working, exposure to real deadlines and collaborative report writing. This paper provides details of the teaching rationale, design exercise overview, design process, chip architecture and test regime
On Using Active Learning and Self-Training when Mining Performance Discussions on Stack Overflow
Abundant data is the key to successful machine learning. However, supervised
learning requires annotated data that are often hard to obtain. In a
classification task with limited resources, Active Learning (AL) promises to
guide annotators to examples that bring the most value for a classifier. AL can
be successfully combined with self-training, i.e., extending a training set
with the unlabelled examples for which a classifier is the most certain. We
report our experiences on using AL in a systematic manner to train an SVM
classifier for Stack Overflow posts discussing performance of software
components. We show that the training examples deemed as the most valuable to
the classifier are also the most difficult for humans to annotate. Despite
carefully evolved annotation criteria, we report low inter-rater agreement, but
we also propose mitigation strategies. Finally, based on one annotator's work,
we show that self-training can improve the classification accuracy. We conclude
the paper by discussing implication for future text miners aspiring to use AL
and self-training.Comment: Preprint of paper accepted for the Proc. of the 21st International
Conference on Evaluation and Assessment in Software Engineering, 201
Assessments in Mathematics, undergraduate degree
In the sequel, we question the validity of multiple choice questionnaires for
undergraduate level math courses. Our study is based on courses given in major
French universities, to numerous audiences
Perceived Environmental Supportiveness Scale: Portuguese Translation, Validation and Adaptation to the Physical Education Domain
Aim: Grounded on Self-Determination Theory, this study aimed to translate, adapt and validate the
Perceived Environmental Supportiveness Scale (PESS) in a sample of Portuguese physical education students.
Methods: The global sample was comprised of 964 students (518 females), divided in two groups: the calibration (n
= 469) and the validation one (n = 483), all of them enrolled in two Physical Education (PE) classes/week. Results: The analysis provided support for a one factor and 12 items model, which are in line with the values adopted in the methodology (ÏÂČ = 196.123, df = 54, p = <.001, SRMR = .035, NNFI = .943, CFI = .954, RMSEA = .074, 90% CI .063-.085). Results express that the models are invariant in all analysis (i.e., calibration vs. validation, male vs. female,and 3rd vs. secondary cycle; three and single factor models). Conclusion: The present study suggests that the PESS with one factor and 12 items has good psychometric properties and can be used to assess perceived need supportive motivational environments provided by PE teachers. Additionally, invariance analysis showed support for the use of the scale in both genders and in the 3rd and secondary cycles.info:eu-repo/semantics/publishedVersio
Zooming into daily life : Within-person associations between physical activity and affect in young adults
Funding The first author was funded by the LEAD Graduate School & Research Network [GSC1028], a project of the Excellence Initiative of the German federal and state governments. Acknowledgements We thank Laura Grube, Leona Hellwig, Parvin Nemati, and Sarah Schmid for their study assistance and all the individuals who participated and made this research feasible.Peer reviewedPostprin
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