Fit Index Values Research Articles

Study of Factors Influencing Consumer to Adopt Cryptocurrency

Cryptocurrencies have become one of the most traded financial assets in the last decade. The first half of 2022 will not be easily forgotten by the crypto faithful as it shifted investor sentiment after a monster cryptocurrency rally in 2021 that saw bitcoin (BTC) and altcoins scale multiple record peaks. Just as users were getting comfortable with their passive DeFi incomes, Terra and its non-collaterised stablecoin collapsed in a sensational turn of events. Three Arrows Capital (3AC), a crypto hedge fund that managed assets worth about $10bn at its peak, went bankrupt as falling crypto prices forced liquidations of collateralized loans and leveraged trading positions across the industry, aggravating the sell-off. Investor sentiment plummeted as crypto lending platforms like Celsius and Babel suspended withdrawals for clients. Investor sentiment plummeted as crypto lending platforms like Celsius and Babel suspended withdrawals for clients. The future of cryptocurrency still remains unclear. Given all these mess, we would like to know what factors could actually influence consumer adoption of cryptocurrency from here on out.The purpose of this research is to study factors influencing consumer to adopt cryptocurrency. These factors include seven independent variables: Convenience (CV), Popularity (PL), Usefulness (UF), Credibility (CD), Recommendations (RC), Price Stability (PS) and Risk (RK) and one dependent variable: Crypto Behavior (BH). 400 sample were collected using electronic questionnaire through social media. We used Structural Equation Models (SEM) for data analysis. The result shows that Since the RMSEA, which is an absolute fit index that assesses how far our hypothesized model is from a perfect model, for this model is .047 (<.05) which strongly indicates a “close fit” and the Goodness of Fit Index (GFI) value is .934 (>.90), the model seems to fit well according to the descriptive measures of fit. More importantly Popularity (PL), Usefulness (UF), Credibility (CD), Recommendations (RC) and Risk (RK) seem to have significant effects on influencing consumer to adopt cryptocurrency due to their p-values are both less than .05. That means as long as cryptocurrency is becoming more popular, useful, credible and highly recommended by key stakeholders (friends & family, professionals and influencers) with better risk management, consumer will be more welcome to adopt cryptocurrency as both day-to-day currency and investment alternative. One interesting finding is that Price Stability (PS) of cryptocurrency that we’ve seen over and over again especially post-covid doesn’t seem to significantly impact much of consumer adoption.

Study of Factors Influencing Consumers to adopt EVs (Electric Vehicles)

Statista market forecast has shown that revenue in the Electric Vehicles market is projected to reach US$457.60bn in 2023. Revenue is expected to show an annual growth rate (CAGR 2023-2027) of 17.02%, resulting in a projected market volume of US$858.00bn by 2027. Electric vehicles are gaining popularity and market share. In Q2 2022, EV sales accounted for 5.6% of the total auto market (up from 2.7% in Q2 of 2021). Clean energy and improved performance are driving people to make the switch to electric. Government incentives continue to buttress the future of all things electric. Between today and 2050, the electric vehicle market opportunity is slated to rise to $53 trillion. Additionally, global electricity demand in that same year is projected to increase by 27% even though KPMG reports in December 2022 that automotive executives are less bullish than they were last year about the adoption of electric vehicles. The survey found 76% are concerned that inflation and high interest rates will adversely affect their business in 2023. For the U.S., the median expectation for EV sales was 35% of the new vehicle market by 2030 — down from 65% a year earlier.The purpose of this research is to study factors influencing consumer to adopt Electric Vehicles. These factors include seven independent variables: Mileage (ML), Battery (BA), Charge station (CS), Price (PR), Maintenance (MT), At-home charger (HC), Government policy (GP), Promotion (PM), Brand (BR) and one dependent variable: Consumer Factor (CF). 387 sample were collected using electronic questionnaire through social media. We used Structural Equation Models (SEM) for data analysis. The result shows that since the RMSEA, which is an absolute fit index that assesses how far our hypothesized model is from a perfect model, for this model is .04 (<.05) which strongly indicates a “close fit” and the Goodness of Fit Index (GFI) value is .913 (>.90), the model seems to fit well according to the descriptive measures of fit. More importantly, Battery (BA), Charge station (CS), Price (PR), At-home charger (HC), Government policy (GP), and Brand (BR) are significantly defined as key success factors of electric vehicles (EV) from the consumer’s perspective due to their p-values are all less than .05. That means if these significant factors are taken good care of from having branded EV with quality battery at a competitive price offering with more charge stations available both in public and at home, all of which are deeply supported by government policy to encourage people to switch over to EV ASAP, EV will become much more successful and widely adopted from consumer standpoint much faster than what has been happening so far.

Study of Factors Influencing Sustainable Supply Chain Management (SSCM) in China

Sustainability in the transportation and supply chain industry has been a concern for decades. Conversations have been ongoing about how to reduce the carbon footprint, incorporate electric vehicles into fleets, and adopt alternative fuels. Now, however, we’re at a crossroad. The global climate crisis has reached a tipping point, highlighting transportation’s contribution to the problem in the boardrooms of most corporations. And for good reason. According to the U.S. Environmental Protection Agency, transportation is responsible for nearly a third (29%) of all greenhouse gas emissions. While passenger vehicles make up a significant portion of that number, ships, trains, planes and freight trucks are also in the mix.The purpose of this research is to study factors influencing Sustainable Supply Chain Management (SSCM) in China. These factors include seven first-order variables: independent variables: Carbon Footprint (CF), Organizational Practices (OP), Transportation Model (TM), Environmentally Responsible Packages (EP), Alternative Energy (AE), Partnership Initiative (PI), and Technology Development (TD); two second-order variables: Environmental, Social, and Governance (ESG) and Operating Model (OPER) and one dependent variable: Sustainable Supply Chain Management (SSCM). 400 sample were collected using electronic questionnaire through social media. We used Structural Equation Models (SEM) for data analysis. The result shows that since the RMSEA, which is an absolute fit index that assesses how far our hypothesized model is from a perfect model, for this model is .039 (<.05) which strongly indicates a “close fit” and the Goodness of Fit Index (GFI) value is .903 (>.90), the model seems to fit well according to the descriptive measures of fit. Moreover, CFI, which is incremental fit indices that compare the fit of our hypothesized model with that of a baseline model (i.e., a model with the worst fit), its value equals .956 indicating an acceptable fit.

Study of Factors Influencing Digital Transformation Process in Bangkok

Most digital transformations fail. Various studies from academics, consultants, and analysts indicate that the rate of digital transformations failing to meet their original objectives ranges from 70% to 95%, with an average at 87.5%. Yet, digital transformation has been at the top of corporate agendas for at least a decade and shows no sign of slowing down. On the contrary, many commentators have highlighted the accelerating impact of the Covid-19 period on digital transformation. Digital transformation is something no management team should attempt alone. It takes deep into reality and a sense of ownership among people across the enterprise to make transformation a reality.The purpose of this research is to study factors influencing digital transformation process in Bangkok, Thailand. These factors include seven first-order independent variables: Leadership (LD), Employee (EP), Culture (CT), Work Environment (WE), Mindset (MS), Organizational Friction (OF), Management of Transformation (MT), and Talent Acquisition (TA); three second-order variables: Leadership & Motivation (LDM), People (PPL), and Workplace Culture (WPC) and one dependent variable: Digital Transformation (DT). 400 sample were collected using electronic questionnaire through social media. We used Structural Equation Models (SEM) for data analysis. The result shows that since the RMSEA, which is an absolute fit index that assesses how far our hypothesized model is from a perfect model, for this model is .04 (<.05) which strongly indicates a “close fit” and the Goodness of Fit Index (GFI) value is .902 (>.90), the model seems to fit well according to the descriptive measures of fit. Moreover, CFI, which is incremental fit indices that compare the fit of our hypothesized model with that of a baseline model (i.e., a model with the worst fit), its value equals .903 indicating an acceptable fit.More importantly, Talent Acquisition (TA), Leadership & Motivation (LDM), and Workplace Culture (WPC) seem to have significant effects on Digital Transformation (DT) process due to their p-values are all less than .05. That means if corporates focus more on acquiring new talent and at the same time improve corporate leadership and motivation and workplace culture, they will be more likely to be successful in digital transformation which is necessary condition for all organizations to be competitively sustainable going forward.

Development and validation of an instrument to measure the Micro-Learning Environment of Students (MLEM)

BackgroundThere are multiple instruments to measure different learning environments but no valid and reliable instrument is present for measuring the micro-learning environment. This study aimed to develop and validate an instrument to measure the micro-learning environment of students. Measuring the micro-learning environment can give insight into the real-life experiences of students and enlighten us about the disparity between taught, delivered, and learned curricula.MethodsMulti-institutional Mixed methods study design with consecutive qualitative and, quantitative components was used based on information processing theory. Literature review, results of semi-structured interviews, and focus group discussion were combined to develop a questionnaire. Content and response process validity were established followed by pilot testing, reliability calculation, and exploratory and confirmatory factor analysis.ResultsA forty-nine-item preliminary draft instrument was reduced to a total of twenty-four items final instrument having five themes regarding teaching practices, learners support, competence in teaching, progressive faculty, and teaching environment. The values of SCVI/Ave and S-CVI/UA were calculated to be 0.92 and 0.62 respectively. Reliability was calculated to be 0.94. Fit indices values were within the normal range.ConclusionThe instrument for measuring the micro-learning environment has excellent content, construct, response process validity, and reliability.

Forecasting Lending Interest Rate and Deposit Interest Rate of Bangladesh Using Autoregressive Integrated Moving Average (ARIMA) Model

The purpose of this paper is to predict the lending interest rate and deposit interest rate of Bangladesh using the Autoregressive Integrated Moving Average (ARIMA) model by Box Jenkins. It has been found that ARIMA (1, 0, 1) model is appropriate in predicting both the lending and deposit interest rates from 2022 to 2026 using the data presented in the World Bank Open Data from 1976 to 2021. To test the goodness of fit, AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) index values have been calculated for six ARIMA models. Besides, Dickey-Fuller unit root test and Correlogram test have also been conducted for diagnostic tests.

The Relationship Between the Self-Recovery Power and the Nursing Care Perception and the Perceived Social Support of Psychiatric Patients: A Cross-Sectional Study

Objective: This research has been conducted to reveal the relationship between nursing care perceptions, self-recovery power and perceived social support on the self-recovery power of inpatients in psychiatry clinics and the factors affecting this relationship. Materials and Methods: This cross-sectional, descriptive, and relationship-seeking study was conducted with 172 patients hospitalized in psychiatry clinics. Research data were collected using the "Patient Information Collection Form", "Patient's Perception of Nursing Care Scale", "Self-Recovery Power Scale" and "Multidimensional Scale of Perceived Social Support". Results: It was found that there is a highly significant relationship between psychiatric patients’ ability to recover and the perceived social support and the nursing care perception (p <0.01). According to MANOVA results, gender and the number of hospitalizations were found to affect the perceived social support and the perception of nursing care, respectively (p <0.05). According to the regression coefficients, it was determined that the perception of nursing care and the perceived social support have a highly significant effect on the self-recovery power (p <0.001). According to the fit indices values of SEM results, GFI, TLI, and IFI indices are exactly 1; and AGFI, GFI, and NFI indices are greater than 0.90. RMSEA is near-zero and SRMR is considerably low. Conclusions: As a result of the study, it was determined that the high level of nursing care perceptions and the perceived social support of patients receiving treatment in psychiatry clinics contribute positively to the ability of patients to recover.

The Effect of Organizational Commitment as Mediator on Relationship between Training and Work Performance

This study aims to identify the effect of organizational commitment as a mediator on the relationship between training and work performance at Community Health Centers for midwives in Banyumas Regency, Central Java, Indonesia. A quantitative research design was selected to answer four research questions. Data collection uses a questionnaire with a five-point Likert scale. This study involved 243 midwives of Puskesmas in Banyumas Regency as a sample using a systematic random sampling method to calculate the sample size of Puskesmas. After that, proportional random sampling was used to determine the sample size of Puskesmas midwives. Data analysis used the Structural Equation Modeling method. The findings of the study show that based on the Measurement Model test, the Loading Factor value from all dimensions of the research construct is greater than 0.5. It means that they can be explained by each dimension of it. The results of the Structural Model exams show good results for absolute fit indices, incremental fit indices, and parsimonious fit indices values, which means that the measurement model and Structural Model used are built to fit. It is concluded that training has a significant positive effect on work performance, training has a significant positive effect on organizational commitment, organizational commitment has a significant positive effect on work performance, and organizational commitment moderates the relationship between training and work performance.

Turkish Adaptation of Dissociative Subtype of Post Traumatic Stress Disorder Scale

ABSTRACT After the changes in DSM-5, dissociative subtype was added to post-traumatic stress disorder. That caused a necessity for a scale to measure the mentioned change. A scale named Dissociative Subtype of Post-Traumatic Stress Disorder (DSPS) was developed to measure this subtype and help the diagnosis. The purpose of this study is to adapt the Dissociative Subtype of Post-Traumatic Stress Disorder to Turkish and examine its reliability and validity. The Dissociative Subtype of PTSD (DSPS) was translated into Turkish. DSPS, Turkish forms of The Posttraumatic Diagnostic Scale and Dissociative Experiences Scale were sent to participants via Google Forms and data from 279 people aged 18–45 were analyzed. Reliability tests and factor analysis were conducted. Factor analysis showed that scale has good model fit scores and items were loaded to the factors the same as the original study. Scales internal consistency was examined, and a good score was obtained (α=.84). Fit index values of confirmatory factor analysis were found as χ2/df = 2.51, GFI=.90, RMSEA=.07, RMR=.02. As a result of the high reliability scores and sufficient model fit scores, this scale is considered as a dependable measure to evaluate the dissociative subtype of PTSD.

Validation of Turkish Parental Perception on Antibiotics Scale

Objective: Antibiotic misuse is a significant public health problem worldwide. Parents’ perceptions of antibiotics are critical for the antibiotic intake of children. The study’s aim was to validate the Turkish Parental Perception on Antibiotics Scale. Methods: This is a scale validation study. The data were collected through a questionnaire that consisted of 15 questions about the demographic and socioeconomic characteristics of the family and the Turkish Parental Perception on Antibiotics Scale. The scale, developed by Alumran et al., is a 5-point Likert type and consists of 31 items. The high scores obtained from the non-cut-off scale indicate better antibiotics perception. Experts completed the language adaption and content validity of the scale. Confirmatory factor analysis was used for construct validity. Reliability was tested by internal consistency coefficients. Results: One thousand eight people participated in the study. 68.8% of the participants were mothers. The mean age of the mothers was 35.7±5.0, and the mean age of the fathers was 39.4±5.2 years. The percent of high school and above graduates was 51.2% among mothers and 56.0% among fathers. According to the confirmatory factor analysis, the fit index values were standardized root mean square residual (SRMR)=0.06, goodness-of-fit index (GFI)=0.90, root mean square error of approximation (RMSEA)=0.06, comparative fit index (CFI)=0.95, non-normed fit index (NNFI)=0.93. The fit index values were good or excellent and confirmed the 5-factor structure. It was found that the internal consistency coefficients calculated for reliability were 0.79 for the whole scale and ranged between 0.63 and 0.86 for the subscales. Conclusion: The Turkish Parental Perception on Antibiotics Scale is a valid and reliable measurement tool. Further research is needed to determine the current situation regarding antibiotic perception.

Psychological Climate and Employee Engagement at Workplace

Objectives: To determine the relationship between drivers of psychological climate and employee engagement considering the workforce who are a part of IT industries in Mysuru and Bengaluru region in India. Methodology: A cross-sectional survey method was adopted for obtaining the required data. Exploratory Factor Analysis, Confirmatory Factor Analysis, Structural Equation Modelling were adopted for examining and analyzing the data. Data was elicited through 445 respondents having their career in various IT industries in Mysuru and Bengaluru region between May 2022 to September 2022. Findings: Structural Equation Modelling analysis reveals that, the fit indices values were admissible. The model fit indices values that were recorded are: Chi- Square Statistics (CMIN/DF) = 2.845; Goodness of Fit index (GFI) = 0.982; Adjusted Goodness of Fit Index (AGFI) = 0.937; Incremental Fit Index (IFI) = 0.963; Tucker – Lewis’s Index (TLI) = 0.900; Comparative Fit Index (CFI) = 0.962; Root Mean Square Error of Approximation (RMSEA) = 0.073. The prominent drivers of Psychological Climate were identified as - Cooperative Work Environment (CWE); Supervisor Facilitation and Support (SS); Job Training and Support (JT) and Organizational Regulations (ROP). The identified factors resulted to have a relationship with Employee Engagement. Novelty: The important drivers of Psychological Climate essential at workplace were identified. The research outcome provides insight for the business managers to significantly focus on the psychological climate factors perceived by employees and build a better working environment. Keywords: Psychological Climate; Employee Engagement; Business Enterprises; Workforce; Structural Equation Modelling

Confirmatory Factor Analyses in Psychological Test Adaptation and Development

Confirmatory Factor Analyses in Psychological Test Adaptation and Development

Psychometric testing of a Danish version of the empowerment of parents in the intensive care - Neonatology questionnaire has confirmed validity.

Investigating parent satisfaction with care is important to guide quality development. In this study, we translated and validated a Danish version of the empowerment of parents in the intensive care - neonatology (EMPATHIC-N) questionnaire to determine validity in Danish contexts. A psychometric study design was applied. Translation was performed according to recommended international standards. Confirmatory factor analyses including standardised factor loadings, Cronbach's α reliability estimates, congruent validity and non-differential validity testing were applied. The study was performed from June 2017 to November 2019 at a 33-bed level IV neonatal intensive care unit. Participants were 311 parents (response rate=42,8%). Confirmative factor analyses disclosed a moderate model fit of the instrument with Comparative Fit Index (CFI) values of 0.83-0.92. Cronbach's α showed good reliability (0.82-0.93). Congruent validity showed good positive correlations (0.48-0.71) between the instrument domains and four overall satisfaction indicators. In search of improved model fit, a version including 27 items was tested. This version showed a better model fit with CFI values of 0.92-0.99 and satisfactory Cronbach's α values. Model fit for the Danish full EMPATIC-N was moderate. The shorter version showed better psychometric properties.

Factors influencing Consumer’s Driving Behavior of Most Preferred Luxury Car Brand in Bangkok Thailand

The luxury car market in Thailand is expected to keep expanding with double-digit growth this year (2022), despite the impact of lockdown measures implemented to contain the spread of COVID-19. Demand for cars and the purchasing power of prospective buyers remain strong in these segments, making Thailand a target market for upper-end car manufacturers. Revenue in the Luxury Cars market segment is projected to reach US$201m in 2022. The purpose of this research is to study factors influencing consumer’s driving behavior of his/her most preferred luxury car brand in Bangkok, Thailand. These factors include six independent first-order variables: Social Status (SS), Social Pressure (SP), Brand Personality (BP), Brand Image (BI), Brand Trust (BT), and Product (PD); three second-order latent variables: Product (PD), Brand (BRN) and Social (SOC) and one dependent variable: Car Usage Behavior (CU). 400 sample were collected using electronic questionnaire through social media. We used second-order Structural Equation Models (SEM) for data analysis. The result shows For data analysis, we employed second-order Structural Equation Models (SEM). The result shows that the RMSEA for this model is.049 (.05), which strongly implies a "near fit," and the Goodness of Fit Index (GFI) value is.968 (>. 90), indicating that the model fits well according to the descriptive measures of fit. CFI and TLI, which are incremental fit indices that compare the fit of our hypothesized model to that of a baseline model (i.e., the model with the worst fit), both have values more than.90 (CFI =.979, TLI =.900), indicating an acceptable fit. More importantly the second-order latent factors included in the model i.e. Product (PD) and Social (SOC) seem to have significant effects on influencing consumer’s driving behavior of his/her most preferred luxury car brand in Bangkok, Thailand due to their p-values are all both less than .05.

Study of the Future of Shopping Centers from the Consumer’s Perspective

According to Coresight Research, 25% of US malls are projected to close within the next five years. The coronavirus pandemic has accelerated a demise that was already underway. According to data pulled by Moody’s Analytics REIS, retail falls 15.7%. Demand for shopping mall is expected to shift noticeably because of the coronavirus pandemic, with more people now working from home, flocking to the suburbs for space and buying online things they used to browse for in stores. Nearly 200 department stores have disappeared in the past year alone, and another 800 or about half the country’s remaining mall-based locations are expected to be shuttered by the end of 2025, according to commercial real estate firm Green Street.
 The purpose of this research is study of the future of shopping centers from the consumer’s perspective. The variables include Entertainment Hub, Meeting Place, Food & Beverage, Experience Destination, Social Gathering, Education Center, Specific Segment, Service Center, Shopping Behavior. 400 sample were collected using electronic questionnaire through social media. For data analysis, we employed Structural Equation Models (SEM). The result shows that the RMSEA for this model is.040 (.05), which strongly implies a “near fit,” and the Goodness of Fit Index (GFI) value is.909 (>. 90), indicating that the model fits well according to the descriptive measures of fit. Furthermore, CFI, which is an incremental fit index that compares the fit of our hypothesized model to that of a baseline model (i.e., the model with the lowest fit), has a value of.901, indicating an adequate fit. More importantly, Experience Destination, Service Center, Specific Segment, and Food & Beverage seem to have significant effects on the future of shopping centers from the consumer’s perspective due to their p-values are all less than .05. That means if shopping malls can start transforming their business models and tenant mixes that’s in line with our research findings to become more experience destination, service-oriented, segment-focused with lots and varieties of F&B outlets such as restaurants, coffee shop, bistro, brasserie, café, dessert cafe, pub & bar, trendy food court, etc. that meet or exceed consumer expectation and satisfy customer needs in the catchment, those shopping malls will be more likely to stay and become sustainably profitable over time.

Adaptation and Psychometric Properties Testing of the Turkish Perception of Loneliness in Isolation Scale in COVID-19 Patients

The study was aimed to adapt the Perception of Loneliness in Isolation Scale (ISOLA) into Turkish and to examine the psychometric properties of the scale. The sample of the methodological and cross-sectional study consisted of 154 patients who were in isolation due to COVID-19. The psychometric characteristics of the scale were analyzed by using language equivalence, content validity, confirmatory factor analysis, criterion-related validity, internal consistency, and test-retest methods. The UCLA Loneliness Scale was used for criterion-related validity. As a result of the confirmatory factor analysis of the scale, the three-dimensional structure of 14 items was confirmed and the fit index values (χ2=90.874; χ2/sd=1.317; RMSEA=0.046; AGFI=0.88; CFI=0.97; GFI=0.92; NFI=0.90) were interpreted as "good fit" or "acceptable fit". It can be said that the Turkish version of ISOLA, which is thought to contribute to understanding the loneliness of patients in isolation and solving their problems, is a valid and reliable measurement tool.

Development of Teachers’ Views on Mixed and Single-Gender Education Scale

The aim of this study was to develop “Teachers’ Views on Mixed and Single-gender Education Scale”. The study group consisted of 718 teachers in 18 different schools who volunteered to participate in the study in Küçükçekmece District of İstanbul. Both Exploratory and Confirmatory Factor Analysis were carried out for the validity of the scale. With Exploratory Factor Analysis, it was found that the scale consisted of two factors (positive views on single-gender education and positive views on mixed-gender education) and 18 items and the scale explained 63% of the total variance. When the fit index values of the scale were examined, it was found that the model had a good fit [RMSEA=,05, SRMR=,05, CFI=0.98, GFI=0.93, AGFI=,91, NFI=,95 and IFI=0.98]. In order to calculate the discriminative values of the scale items, mean scores of upper and lower groups were examined with t-test and it was found that all of the items were discriminative. Cronbach Alpha values calculated for the scale reliability were found to vary between, 81 and ,89.

Adaptation of Parental Involvement Scale in Education to Sports: Validity and Reliability Study

Bu çalışmada, eğitimde veli katılımı ölçeğinin spora uyarlanarak psikometrik özelliklerinin geçerlik ve güvenirlik ölçütlerini sağlayıp sağlamadığı incelenmiştir. Orijinal ölçek Gürbüztürk ve Şad (2010a; 2010b) tarafından geliştirilmiştir. Veli Katılımı Ölçeği, 5 seçenekli (Her zaman-Hiçbir zaman) Likert tipi bir ölçek olup velilerin çocuklarının eğitimlerine katılım düzeylerini ölçmeyi amaçlayan toplam 8 alt ölçek ve 39 maddeden oluşmaktadır. Ölçeğin uyarlanmasında sırasıyla kapsam geçerliliği, yapı geçerliliği, yakınsak geçerlilik, ıraksak geçerlilik ve ölçüt geçerliliği analizlerine tabii tutulmuştur. Çalışmada NFI, CFI, GFI, RMSEA uyum indeks değerleri hesaplanmıştır. Ayrıca ölçeğin güvenirliliği iç tutarlılık katsayısı ve test tekrar test güvenirlik katsayısı hesaplanarak tespit edilmiştir. Sonuç olarak veri toplama aracının spora uyarlanmış versiyonunun uyum indeks değerlerine göre 36 madde ve 8 faktör olarak iyi uyum gösterdiği tespit edilmiştir.

Beden Eğitimi ve Spor Dersi Lise Değer Ölçeği: Geçerlik ve Güvenilirlik Çalışması

Bu araştırmada lise öğrencilerinin Beden Eğitimi ve Spor (BES) dersi değer düzeylerinin belirlenebilmesi amacıyla bir ölçme aracının geliştirilmesi amaçlanmıştır. Bu amaç doğrultusunda öncelikle literatür taranmış, ardından değerler ile ilgili anket ve ölçekler incelenmiştir. Sonrasında lise öğrencilerinin sahip olması gereken BES dersi değerlerinin nelerden oluşması gerektiğiyle ilgili, araştırmacılar tarafından hazırlanmış olan “yarı yapılandırılmış görüşme formu” ile 3 öğretim üyesi, 6 BES öğretmeni ve 30 lise öğrencisi ile yüz yüze görüşmeler yapılmıştır. Yapılan görüşmeler sonucunda hazırlanan ölçek taslak formu uzman görüşlerine sunulmuştur. Gelen dönütler sonucunda kapsam geçerliği belirlenerek .80’in altında olan değer maddelerinin çalışmadan çıkarılmasına karar verilmiştir. Oluşturulan taslak formu Türkiye’nin 7 farklı bölgesinde öğrenim gören öğrencilere uygulanmış ardından elde edilen verilerin analizi yapılmıştır. Yapılan Açımlayıcı faktör analizi sonucunda “Başarı”, “Saygı”, “Milli kültür ve beraberlik”, “Sportmenlik” ve “Spor kültürü” olmak üzere 5 boyuta ve toplam 28 maddelik bir yapıya ulaşılmıştır. Ölçekte yer alan 28 maddenin toplam varyans oranı %49.17 olarak tespit edilmiştir. Sonrasında yapılan Doğrulayıcı faktör analizi sonuçlarına bakıldığında modelin iyi uyum indeks değerlerine [χ2/sd (2.57), GFI (0.93), CFI (0.92), AGFI (0.92), NFI (0.89), IFI (0.91), RMSEA (.044)] sahip olduğu belirlenmiştir. Sonuç olarak BES derslerine yönelik lise öğrencilerinin değer düzeylerini belirlemede güvenilir ve geçerli bir ölçme aracı olarak kullanılabileceği sonucuna ulaşılmıştır.

Adaptation of teaching engineering self-efficacy scale into Turkish

By means of a good understanding of teachers’ motivational components in teaching, we are able to gain insight into their teaching performance. One of these personal components is self-efficacy. The aim of the study was to adapt the Teaching Engineering Self-Efficacy Scale (TESS) developed by Yoon (2014) into Turkish to measure the engineering teaching self-efficacy of K-12 teachers. The analysis of the data consisting of 439 science and technology design teachers from across Türkiye was performed using the Mplus program. According to the results obtained from this research, it was determined that the X2/sd ratio was 2.97, RMSEA was .07, CFI was .95, TLI was .94 and SRMR was .04. in the findings obtained from Model C, with the best fit index values. In addition, it was found that the Cronbach α reliability coefficients (.94 for engineering pedagogical content knowledge self-efficacy, .95 for engineering engagement self-efficacy, .93 for engineering discipline self-efficacy, and.87 for engineering outcome expectancy; .96 for the entire scale) were found to be at a high level. Consequently, the Turkish version of TESS is a valid and reliable scale with 23 items and a four-dimensional structure as in the original.