Moving Toward Blended Learning: A Multiple Case Design Based Research Study In Higher Education

The purpose of this multiple case design-based research study was to determine what elements were needed to assist two higher education instructors inexperienced in designing and teaching a blended learning course to successfully create and implement it, to document the instructors’ perceptions about their first experience of teaching a blended learning course, and to reveal how this blended learning course influenced student satisfaction. The goal of the study was to iteratively design, develop, implement, evaluate and redesign a desired blended learning course based on constructivist design theory, cognitive learning theory, and ARCS motivational design theory over the three iterative phases. This design-based research approach used a mixed study of quantitative and qualitative research methods including student surveys, instructor interviews, learning environment and observations. Quantitative data in terms of determining any change in the level of students’ motivation between the beginning of the semester and the end of the semester, and students’ motivational attitude toward the use of instructional activities and tools at the fifth and tenth week of the semester was collected. Multiple choice comprehensive pretest and posttest surveys were given to students to detect changes in their motivation level, and a multiple choice comprehensive survey was given to students to detect their motivational attitude. Qualitative data in terms of identifying the need of appropriate technological processes and resources to create a desired blended learning course, enhancing the effectiveness and efficiency of the blended learning course, and revealing instructor perceptions about teaching a blended learning course was collected over the three iterative designed intervention phases. Instructor perceptions were captured through in-depth interviews, and the strengths and weaknesses of the blended learning environment were ascertained through observations. The results of this study demonstrated Blackboard Learn (Learning Management System) and Google Documents were two beneficial learning resources to create a desired blended learning environment. The design and implementation of these learning resources enabled the instructors to shift from a passive teaching style to an active teaching style. Students became active and interactive learners through the adoption of active learning approaches and transactional collaborative learning approaches in the designed blended learning environments. Through the process of three iterative design cycles, the blended learning environments were modified to optimize the efficiency and effectiveness of learning activities and maximize the quality of learning and teaching experiences. The results also revealed that the instructors’ overall perception was positive toward taking part in combining online and face-to-face learning and they were satisfied with teaching a blended learning course. Lastly, findings from the paired t-test completed in SPSS which compared the students’ motivation level in the beginning of the semester and the end of the semester were not statistically significant in both cases

Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability

Post-hoc model-agnostic interpretation methods such as partial dependence plots can be employed to interpret complex machine learning models. While these interpretation methods can be applied regardless of model complexity, they can produce misleading and verbose results if the model is too complex, especially w.r.t. feature interactions. To quantify the complexity of arbitrary machine learning models, we propose model-agnostic complexity measures based on functional decomposition: number of features used, interaction strength and main effect complexity. We show that post-hoc interpretation of models that minimize the three measures is more reliable and compact. Furthermore, we demonstrate the application of these measures in a multi-objective optimization approach which simultaneously minimizes loss and complexity

Improving Phrap-Based Assembly of the Rat Using “Reliable” Overlaps

The assembly methods used for whole-genome shotgun (WGS) data have a major impact on the quality of resulting draft genomes. We present a novel algorithm to generate a set of “reliable” overlaps based on identifying repeat k-mers. To demonstrate the benefits of using reliable overlaps, we have created a version of the Phrap assembly program that uses only overlaps from a specific list. We call this version PhrapUMD. Integrating PhrapUMD and our “reliable-overlap” algorithm with the Baylor College of Medicine assembler, Atlas, we assemble the BACs from the Rattus norvegicus genome project. Starting with the same data as the Nov. 2002 Atlas assembly, we compare our results and the Atlas assembly to the 4.3 Mb of rat sequence in the 21 BACs that have been finished. Our version of the draft assembly of the 21 BACs increases the coverage of finished sequence from 93.4% to 96.3%, while simultaneously reducing the base error rate from 4.5 to 1.1 errors per 10,000 bases. There are a number of ways of assessing the relative merits of assemblies when the finished sequence is available. If one views the overall quality of an assembly as proportional to the inverse of the product of the error rate and sequence missed, then the assembly presented here is seven times better. The UMD Overlapper with options for reliable overlaps is available from the authors at http://www.genome.umd.edu. We also provide the changes to the Phrap source code enabling it to use only the reliable overlaps

Developing Core Sets for Persons With Traumatic Brain Injury Based on the International Classification of Functioning, Disability, and Health

The authors outline the process for developing the International Classification of Functioning, Disability, and Health (ICF) Core Sets for traumatic brain injury (TBI). ICF Core Sets are selections of categories of the ICF that identify relevant categories of patients affected by specific diseases. Comprehensive and brief ICF Core Sets for TBI should become useful for clinical practice and for research. The final definition of the ICF Core Sets for TBI will be determined at an ICF Core Sets Consensus Conference, which will integrate evidence from preliminary studies. The development of ICF Core Sets is an inclusive and open process and rehabilitation professionals are invited to participate

Prevalence of Depression among Households in Three Capital Cities of Pakistan: Need to Revise the Mental Health Policy

BACKGROUND: Pakistan, among the other developing countries, has a higher prevalence rate of depression because of the current social adversities. There is, thus, a great need for systematic studies on prevalence of depression. The current study aims at exploring the prevalence of depression among households in three capital cities of Pakistan. METHODOLOGY AND PRINCIPAL FINDINGS: A sample of N = 820 was randomly selected, and a cross sectional telephone-based study was conducted for a duration of six months. It was found that there was a regional variation in prevalence rates for depression among the three cities. Lahore had the highest number of depressives (53.4%), as compared to Quetta (43.9%) and Karachi (35.7%). Middle age, female gender and secondary school level of education were significantly associated with depression among the study group. CONCLUSIONS/SIGNIFICANCE: The different rates of prevalence among the three cities could be attributed to local cultural influence, geographical locations and social adversities. There is a need for revision of existing health policy by the government

Explanations of Black-Box Model Predictions by Contextual Importance and Utility

The significant advances in autonomous systems together with an immensely wider application domain have increased the need for trustable intelligent systems. Explainable artificial intelligence is gaining considerable attention among researchers and developers to address this requirement. Although there is an increasing number of works on interpretable and transparent machine learning algorithms, they are mostly intended for the technical users. Explanations for the end-user have been neglected in many usable and practical applications. In this work, we present the Contextual Importance (CI) and Contextual Utility (CU) concepts to extract explanations that are easily understandable by experts as well as novice users. This method explains the prediction results without transforming the model into an interpretable one. We present an example of providing explanations for linear and non-linear models to demonstrate the generalizability of the method. CI and CU are numerical values that can be represented to the user in visuals and natural language form to justify actions and explain reasoning for individual instances, situations, and contexts. We show the utility of explanations in car selection example and Iris flower classification by presenting complete (i.e. the causes of an individual prediction) and contrastive explanation (i.e. contrasting instance against the instance of interest). The experimental results show the feasibility and validity of the provided explanation methods

Pre-existing invasive fungal infection is not a contraindication for allogeneic HSCT for patients with hematologic malignancies: a CIBMTR study.

Patients with prior invasive fungal infection (IFI) increasingly proceed to allogeneic hematopoietic cell transplantation (HSCT). However, little is known about the impact of prior IFI on survival. Patients with pre-transplant IFI (cases; n=825) were compared with controls (n=10247). A subset analysis assessed outcomes in leukemia patients pre- and post 2001. Cases were older with lower performance status (KPS), more advanced disease, higher likelihood of AML and having received cord blood, reduced intensity conditioning, mold-active fungal prophylaxis and more recently transplanted. Aspergillus spp. and Candida spp. were the most commonly identified pathogens. 68% of patients had primarily pulmonary involvement. Univariate and multivariable analysis demonstrated inferior PFS and overall survival (OS) for cases. At 2 years, cases had higher mortality and shorter PFS with significant increases in non-relapse mortality (NRM) but no difference in relapse. One year probability of post-HSCT IFI was 24% (cases) and 17% (control, P<0.001). The predominant cause of death was underlying malignancy; infectious death was higher in cases (13% vs 9%). In the subset analysis, patients transplanted before 2001 had increased NRM with inferior OS and PFS compared with later cases. Pre-transplant IFI is associated with lower PFS and OS after allogeneic HSCT but significant survivorship was observed. Consequently, pre-transplant IFI should not be a contraindication to allogeneic HSCT in otherwise suitable candidates. Documented pre-transplant IFI is associated with lower PFS and OS after allogeneic HSCT. However, mortality post transplant is more influenced by advanced disease status than previous IFI. Pre-transplant IFI does not appear to be a contraindication to allogeneic HSCT

Data Standardization for Smart Infrastructure in First-Access Electricity Systems

Recent developments in renewable energy and Information Technology (IT) fields made it easier to set up power systems at a smaller scale. This proved to be a turning point for developing First-Access Electricity Systems for the underserved locations around the world. However, there are planning and operation challenges due to lack of past data on such places. Deployment of IoT devices and proliferation of smart infrastructures with additional sensors will lead to tremendous opportunities for gathering very useful data. For different stakeholders to access and manage this data, trusted and standardized mechanisms need to be in place. Storing proper data in a well-structured common format allows for collaborative research across disciplines, large-scale analytics, and sharing of algorithms and methodologies, in addition to improved customer service. Data standardization plays a more vital role in the context of electricity access in underdeveloped countries, where there is no past data on generation or consumption as in utility grids. Data collected in a standard structure, be it for a short period of time, facilitates learning from the past experiences, monitoring the current projects and delivering better results in future endeavors. It will result in ways to better assist consumers and help the industry operate more efficiently by sharing data with different stakeholders. It can also enhance competition, thus making electricity accessible faster and to more people. The focus of this paper is data standardization for first-access electricity systems, in general, and renewable energy based microgrids, in particular, different data sources and ways the corresponding data can be exploited, technological and capacity constraints for storage of data, political and governance implications, as well as data security and privacy issues, are examined. The work presented here is relevant to different stake holders such as investors, public utilities, non-governmental organizations (NGOs) and communities. Using the data standardization approach developed here, it is possible to create a much-needed first-access electricity system database. This will provide an important resource for project developers and energy companies to assess the potential of a certain unelectrified site, estimating its demand growth in time and establishing universal control systems that can seamlessly communicate with different components

Estimated Risk of HIV Acquisition and Practice for Preventing Occupational Exposure: A Study of Healthcare Workers at Tumbi and Dodoma Hospitals, Tanzania.

Health care workers (HCWs) are at risk of acquiring human immuno-deficiency virus (HIV) and other infections via exposure to infectious patients' blood and body fluids. The main objective of this study was to estimate the risk of HIV transmission and examine the practices for preventing occupational exposures among HCWs at Tumbi and Dodoma Hospitals in Tanzania. This study was carried out in two hospitals, namely, Tumbi in Coast Region and Dodoma in Dodoma Region. In each facility, hospital records of occupational exposure to HIV infection and its management were reviewed. In addition, practices to prevent occupational exposure to HIV infection among HCWs were observed. The estimated risk of HIV transmission due to needle stick injuries was calculated to be 7 cases per 1,000,000 HCWs-years. Over half of the observed hospital departments did not have guidelines for prevention and management of occupational exposure to HIV infections and lacked well displayed health and safety instructions. Approximately, one-fifth of the hospital departments visited failed to adhere to the instructions pertaining to correlation between waste materials and the corresponding colour coded bag/container/safety box. Seventy four percent of the hospital departments observed did not display instructions for handling infectious materials. Inappropriate use of gloves, lack of health and safety instructions, and lack of use of eye protective glasses were more frequently observed at Dodoma Hospital than at Tumbi Hospital. The poor quality of the hospital records at the two hospitals hampered our effort to characterise the risk of HIV infection acquisition by HCWs. Greater data completeness in hospital records is needed to allow the determination of the actual risk of HIV transmission for HCWs. To further reduce the risk of HIV infection due to occupational exposure, hospitals should be equipped with sufficient personal protective equipment (PPE) and HCWs should be reminded of the importance of adhering to universal precautions