Software engineering education: some important dimensions

Software engineering education has been emerging as an independent and mature discipline. Accordingly, various studies are being done to provide guidelines for curriculum design. The main focus of these guidelines is around core and foundation courses. This paper summarizes the current problems of software engineering education programs. It also proposes some important dimensions as integral parts of software engineering education: interdisciplinary skills, practice experience, communication, skills on continuing education and professionalism. In the current guidelines and studies these dimensions are not addressed specifically. Although there could be other dimensions to be considered in software engineering education, we believe that the proposed ones are very crucial as software engineering is evolving more rapidly than any other engineering discipline. This study also provides a survey of some major universities’ undergraduate software engineering programs to evaluate these dimensions.     

Movement and engagement in flexible,technology-enhanced classrooms: investigating cognitive and emotional engagement from the faculty perspective

Learning Environments Research - The main objective of the study was to understand specific ways in which a flexible, technology-enhanced space can create opportunities for student engagement....     

Collaborative risk method for information security management practices: A case context within Turkey

In this case study, a collaborative risk method for information security management has been analyzed considering the common problems encountered during the implementation of ISO standards in eight Turkish public organizations. This proposed risk method has been applied within different public organizations and it has been demonstrated to be effective and problem-free. The fundamental issue is that there is no legislation that regulates the information security liabilities of the public organizations in Turkey. The findings and lessons learned presented in this case provide useful insights for practitioners when implementing information security management projects in other international public sector organizations.     

Are we wasting our children's time by giving them more homework?

Following an identification strategy that allows us to largely eliminate unobserved student and teacher traits, we examine the effect of homework on math, science, English and history test scores for eighth grade students in the United States. Noting that failure to control for these effects yields selection biases on the estimated effect of homework, we find that math homework has a large and statistically meaningful effect on math test scores throughout our sample. However, additional homework in science, English and history are shown to have little to no impact on their respective test scores.     

e-Government adoption model based on theory of planned behavior: Empirical validation

The e-Government phenomenon has become more important with the ever increasing number of implementations worldwide. A model explaining the e-Government adoption and the related measurement instrument – a survey – had been developed and validated in this study. In a post Technology Acceptance Model (TAM) approach, theory of planned behavior (TPB) was extended to fit the requirements of e-Government context. The adoption of student loans service of the higher education student loans and accommodation association of Turkey (KYK) was investigated to obtain data for empirical validation. The instrument was administered to over four-hundred students and partial least squares path modeling was employed to analyze the data. The results indicate that the model was an improvement over TAM in terms of predictive power. The constructs trust, perceived behavioral control and attitudes successfully explained the intention to use an e-Government service. The findings presented in this study provide useful insights for researchers and policy makers when dealing with e-Government services.     

Effects of Model‐based Teaching on Pre‐service Physics Teachers’ Conceptions of the Moon,Moon Phases,and Other Lunar Phenomena

The purpose of this study was twofold. First, it was aimed to identify Turkish pre‐service physics teachers’ knowledge and understanding of the Moon, Moon phases, and other lunar phenomena. Second, the effects of model‐based teaching on pre‐service teachers’ conceptions were examined. Conceptions were proposed as mental models in this study. Four different questionnaires including 22 generative, explanation, and factual questions were used through the study. The pre‐service physics teachers’ mental models generated in response to lunar phenomena might be representations of their naïve knowledge as a result of their causal observations and experiences with the world, and their misconceptions as a result of inconsistencies between their naïve knowledge and scientific knowledge. Therefore, the pre‐service teachers’ mental models were categorized based on the work by Chi and Roscoe. Some of the pre‐service teachers’ mental models shifted from flawed or incomplete mental models to correct mental models of the Moon and lunar phenomena with the facilitation of model‐based teaching. The conclusions of the study carry implications for curriculum developers and teacher education.     

Evaluation of treatment effect estimates in single‐case experimental research: comparison of twelve overlap methods and visual analysis

The purpose of this study was to compare 12 commonly‐used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema‐based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each graph by hand or using an online calculator. Five experts conducted visual analysis of each graph. Results showed that strong agreements existed between visual analysis and PND, Tau_NOVLAP and Tau‐U when raw data were analysed, and PND, PNCD and PEM‐T when categorised data were analysed. Of the 12 methods investigated, PND had the highest agreement rate with visual analysis, followed by PEM‐T, PAND, PNCD, IRD, NAP and Tau_NOVLAP. Overall, visual analysis appeared to be more conservative, as most nonoverlap methods overestimated the treatment effect. Additional research is needed to replicate and potentially validate the findings of this study.     

On constituent chunking for Turkish

Chunking is a task which divides a sentence into non-recursive structures. The primary aim is to specify chunk boundaries and classes. Although chunking generally refers to simple chunks, it is possible to customize the concept. A simple chunk is a small structure, such as a noun phrase, while constituent chunk is a structure that functions as a single unit in a sentence, such as a subject. For an agglutinative language with a rich morphology, constituent chunking is a significant problem in comparison to simple chunking. Most of Turkish studies on this issue use the IOB tagging schema to mark the boundaries.In this study, we proposed a new simpler tagging schema, namely OE, in constituent chunking for Turkish. “E” represents the rightmost token of a chunk, while “O” stands for all other items. In reference to OE, we also used a schema called OB, where “B” represents the leftmost token of a chunk. We aimed to identify both chunk boundaries and chunk classes using the conditional random fields (CRF) method. The initial motivation was to employ the fact that Turkish phrases are head-final for chunking. In this context, we assumed that marking the end of a chunk (OE) would be more advantageous than marking the beginning of a chunk (OB). In support of the assumption, the test results reveal that OB has the worst performance and OE is significantly a more successful schema in many cases. Especially in long sentences, this contrast is more obvious. Indeed, using OE means simply marking the head of the phrase (chunk). Since the head and the distinctive label “E” are aligned, CRF finds the chunk class more easily by using the information contained in the head. OE also produced more successful results than the schemas available in the literature.In addition to comparing tagging schemas, we performed four analyses. Along with the examination of window size, which is a parameter of CRF, it is adequate to select and accept this value as 3. A comparison of the evaluation measures for chunking revealed that F-score was a more balanced measure in contrast to token accuracy and sentence accuracy. As a result of the feature analysis, syntactic features improves chunking performance significantly under all conditions. Yet when withdrawing these features, a pronounced difference between OB and OE is forthcoming. In addition, flexibility analysis shows that OE is more successful in different data.     

Clinical biochemistry laboratory rejection rates due to various types of preanalytical errors

Introduction:

Preanalytical errors, along the process from the beginning of test requests to the admissions of the specimens to the laboratory, cause the rejection of samples. The aim of this study was to better explain the reasons of rejected samples, regarding to their rates in certain test groups in our laboratory.

Materials and methods:

This preliminary study was designed on the rejected samples in one-year period, based on the rates and types of inappropriateness. Test requests and blood samples of clinical chemistry, immunoassay, hematology, glycated hemoglobin, coagulation and erythrocyte sedimentation rate test units were evaluated. Types of inappropriateness were evaluated as follows: improperly labelled samples, hemolysed, clotted specimen, insufficient volume of specimen and total request errors.

Results:

A total of 5,183,582 test requests from 1,035,743 blood collection tubes were considered. The total rejection rate was 0.65 %. The rejection rate of coagulation group was significantly higher (2.28%) than the other test groups (P < 0.001) including insufficient volume of specimen error rate as 1.38%. Rejection rates of hemolysis, clotted specimen and insufficient volume of sample error were found to be 8%, 24% and 34%, respectively. Total request errors, particularly, for unintelligible requests were 32% of the total for inpatients.

Conclusions:

The errors were especially attributable to unintelligible requests of inappropriate test requests, improperly labelled samples for inpatients and blood drawing errors especially due to insufficient volume of specimens in a coagulation test group. Further studies should be performed after corrective and preventive actions to detect a possible decrease in rejecting samples.