Prof. Ibrahim ARPACI - Academia.edu (original) (raw)

Papers by Prof. Ibrahim ARPACI

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Sustainability, 2023

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Sustainability, 2023

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Computers in Human Behavior, 2023

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Interactive Learning Environments, 2023

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Current Psychology, 2023

The study investigated the moderating role of exhibitionism in the relationship between psycholog... more The study investigated the moderating role of exhibitionism in the relationship between psychological needs (i.e., autonomy, competence, and relatedness) and selfie-posting behavior. The study proposed a research model by extending the “self-determination theory” with exhibitionism to better explain selfie-posting behavior. Structural equation modeling (SEM) approach was employed to test the proposed model based on data obtained from 316 social media users in New Delhi, India. Results indicated that psychological needs for relatedness, competence, and autonomy significantly predict selfie-posting behavior. Further, results of the multi-group analysis indicated that level of exhibitionism plays a moderating role in the relationship between psychological needs and selfie-posting behavior. The findings suggested that individuals with a higher level of exhibitionism more tend to post selfies on social media to satisfy their needs for competence and relatedness.

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Interactive Learning Environments

attention during the last few years. However, little is known concerning what affects their use f... more attention during the last few years. However, little is known concerning what affects their use for educational purposes. This research, therefore, develops a theoretical model based on extracting constructs from the expectation confirmation model (ECM) (expectation confirmation, perceived usefulness, and satisfaction), combined with the knowledge management (KM) factors (knowledge sharing, knowledge acquisition, and knowledge application) to understand the sustainable use of chatbots. The developed model was then tested based on data collected through an online survey from 448 university students who used chatbots for learning purposes. Contrary to the prior literature that mainly relied on structural equation modeling (SEM) techniques, the empirical data were analyzed using a hybrid SEM-artificial neural network (SEM-ANN) approach. The hypotheses testing results reinforced all the suggested hypotheses in the developed model. The sensitivity analysis results revealed that knowledge application has the most considerable effect on the sustainable use of chatbots with 96.9% normalized importance, followed by perceived usefulness (70.7%), knowledge acquisition (69.3%), satisfaction (61%), and knowledge sharing (19.6%). Deriving from these results, the study highlighted a number of practical implications that benefit developers, designers, service providers, and instructors.

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Studies in Systems, Decision and Control, 2021

Technology acceptance is one of the most dynamic research areas in the field of Information Syste... more Technology acceptance is one of the most dynamic research areas in the field of Information Systems (IS). This chapter provides a systematic overview of technology acceptance theories by clarifying the relations among the theories and models. The chapter developed a theoretical model by extending the "Technology Acceptance Model" (TAM) to better explain adoption of visual programming languages by engineering students. The proposed model was tested by using a "structural equation modelling" approach. Results indicated that "perceived enjoyment" was significantly related with perceived usefulness and attitude. Further, the results indicated that "self-efficacy" was significantly related with perceived ease of use. The proposed model better explained the adoption of Scratch by predicting 75% of the variance in continuous use intention.

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Information Development, 2021

This study aimed to develop a cybersecurity scale to measure individuals’ practices and perceptio... more This study aimed to develop a cybersecurity scale to measure individuals’ practices and perceptions regarding cybersecurity. The study tested psychometric properties of the Cybersecurity Scale (CS-S) by employing a multi-stage research design. In the first study, an Exploratory-Factor-Analysis (EFA) was conducted to explore the underlying factor structure and evaluate internal consistency reliability of the CS-S. The EFA results showed good internal consistency reliability (α = .88) and a six-factor structure. In the second study, a Confirmatory-Factor-Analysis (CFA) was conducted to verify the factor structure. The CFA results indicated that the six-factor model (i.e., confidentiality, control/possession, integrity, authenticity, availability, and utility) fits the data well. Significant individual differences were observed in each dimension of the CS-S. Results indicated that the CS-S has evidence of convergent, discriminant, and construct validity along with internal consistency ...

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International Journal of Mental Health and Addiction, 2021

The purpose of this study is to investigate the gaming habits, personality traits, and Internet g... more The purpose of this study is to investigate the gaming habits, personality traits, and Internet gaming disorder (IGD) of Kyrgyz adolescents. Sociodemographic questions, gaming-related questions, Internet Gaming Disorder Test (IGD-10), and Big Five Inventory (BFI-10) were used to collect data from 248 Kyrgyz adolescents between the ages of 11 and 21 years. The study revealed that most of the participants play digital games for 1 to 10 h a week. Among the game categories, action games are the most preferred one by the participants. Structural equation modelling (SEM) was used to investigate the relationship between Big Five personality traits and IGD. The results indicated that neuroticism has a positive and significant relationship with IGD. On the other hand, agreeableness has a negative and significant relationship with IGD. The results indicated that some personality traits have substantial predictive power in determining IGD among Kyrgyz adolescents.

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Proceedings of International Conference on Emerging Technologies and Intelligent Systems, 2021

This study aimed to develop and validate a short form of the Smartphone Addiction Inventory (SPAI... more This study aimed to develop and validate a short form of the Smartphone Addiction Inventory (SPAI) and determine the cutoff point for smartphone addiction based on a psychiatric interview. A sample of 281 Iranian undergraduate students from Mazandaran University of Medical Sciences completed the 26-item SPAI and psychologist interview. Stepwise multiple linear regression identified 10 items for the short-form of the SPAI, consisting of compulsive behavior (four items), functional impairment (three items), withdrawal (two items), and tolerance (one item) with an explained variance of 96%. Exploratory factor analysis revealed a two-factor structure that labeled Compulsive behavior and Functional impairment (47.99 variance) and Withdrawal and Tolerance (11.57 variance). Confirmatory factor analysis (CFA) verified the structure by excellent goodness of fit indices (p-value = 0.061, x 2 /df = 1.43, CFI = 0.99, GFI = 0.97, and RMSEA = 0.039). The inter-item and item-total correlations of the SPAI-SF were positively significant and confirmed the convergent validity. Internal consistency verified by Cronbach's alpha of 0.875 (CI: 0.852 − 0.896). The area under the curve (AUC) was 0.876 (95% CI = 0.833 − 0.919, p < 0.001), indicating a good diagnostic efficiency. The best cutoff point to discriminate diagnostic negatives was 23, with a sensitivity of 79.19%, a specificity of 83.33%, and an accuracy of 80.43%. The results indicated acceptable reliability, validity, and AUC for the SPAI-SF for smartphone addiction screening and studies.

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Emerging Technologies During the Era of COVID-19 Pandemic, 2021

The negative effects of the COVID-19 pandemic are not limited to psychological, but also include ... more The negative effects of the COVID-19 pandemic are not limited to psychological, but also include social and economic effects. This study investigated psychological, social, and economic effects of COVID-19 pandemic on the Turkish population. COVID-19 Phobia Scale (C19P-S) was used to collect data from 2143 participants. Results indicated that women showed the highest phobic reactions on the economic subscale whereas men showed the highest phobic reactions on psycho-somatic subscale. Patterns of differences varied among geographical regions but in general, eastern regions scored higher than western regions. Significant differences were also observed based on educational attainment; lower-middle class showed the highest scores on all the subscales.

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Death Studies, 2021

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International Journal of Emerging Technologies in Learning (iJET), 2020

Learning to code is considered as a difficult and challenging task for a significant number of no... more Learning to code is considered as a difficult and challenging task for a significant number of novice programmers in programming education. Novice programmers have to acquire different skills such as problem solving, program design, comprehension, and debugging at the same time. On the other hand, most introductory programming courses focus more on syntax of the programming language. In this study, we developed and introduced a ‘PROBSOL’ application in three different learning systems (E-learning, M-learning and Game-based learning) to enhance the problem solving skills of novice programmers in an introductory programming (IP) course. A survey was conducted with the IP students to determine their perception about all the three applications in the IP course. Gender differences were determined by comparing both female and male students’ responses for each question in the survey. The results of comparison show that male students were more satisfied with all the three applications compa...

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BACKGROUND COVID-19 has not only psychological but also economic and social effects and social me... more BACKGROUND COVID-19 has not only psychological but also economic and social effects and social media increased the negative effects by disseminating COVID-19 infodemic. OBJECTIVE This study aims to investigate impact of the global infection rate on social media posting during the COVID-19 pandemic. METHODS The study analyzed 179+ million tweets collected between March 22nd and April 13th, 2020, and global COVID-19 infection rate by using evolutionary clustering analysis. RESULTS The results indicated six clusters constructed for each term type, including three-level n-grams (unigrams, bigrams, and trigrams). The frequent occurrences of unigrams (“COVID-19”, “virus”, “government”, “people”, etc.), bigrams (“COVID-19”, “COVID-19 cases”, “times share”, etc.), and trigrams (“COVID 19 crisis”, “things help stop”, “trying times share”). The results demonstrated that the unigram trends on Twitter were up to about two times and 54 times more common than bigram and trigram terms, respectivel...

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Education and Information Technologies, 2020

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Education and Information Technologies, 2020

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Computers in Human Behavior, 2019

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Personality and Individual Differences, 2018

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Turkish Online Journal of Distance Education, 2017

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Sustainability, 2023

This article is an open access article

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Sustainability, 2023

This article is an open access article.

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Computers in Human Behavior, 2023

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Interactive Learning Environments, 2023

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Current Psychology, 2023

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Interactive Learning Environments

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Studies in Systems, Decision and Control, 2021

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Information Development, 2021

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International Journal of Mental Health and Addiction, 2021

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Proceedings of International Conference on Emerging Technologies and Intelligent Systems, 2021

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Emerging Technologies During the Era of COVID-19 Pandemic, 2021

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Death Studies, 2021

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International Journal of Emerging Technologies in Learning (iJET), 2020

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Education and Information Technologies, 2020

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Education and Information Technologies, 2020

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Computers in Human Behavior, 2019

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Personality and Individual Differences, 2018

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Turkish Online Journal of Distance Education, 2017

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$Research paper thumbnail of What drives students' online self-disclosure behaviour on social media? A hybrid \textsc {SEM} and artificial intelligence approach$

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$Research paper thumbnail of \textsc {COVID-19} phobia in the \textsc {U}nited \textsc {S}tates: Validation of the \textsc {COVID-19} Phobia Scale \textsc {(C19P-SE)$

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$Research paper thumbnail of Validity, reliability, and optimal cut-off scores of the \textsc {WHO-5}, \textsc {PHQ-9}, and \textsc {PHQ-2} to screen depression among university students in \textsc {I}ran$

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$Research paper thumbnail of Development of the cybersecurity scale \textsc {(CS-S)}: Evidence of validity and reliability$

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$Research paper thumbnail of \textsc {P}ersian Version of the Smartphone Addiction Inventory \textsc {(SPAI-PV)}: Psychometric Evidence of Validity and Reliability$

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$Research paper thumbnail of Understanding the impact of knowledge management factors on the sustainable use of \textsc {AI}-based chatbots for educational purposes using a hybrid \textsc {SEM-ANN} approach$

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$Research paper thumbnail of Development of the cybercrime awareness scale (\textsc {CAS}): A validity and reliability study in a \textsc {T}urkish sample$

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$Research paper thumbnail of Understanding the social sustainability of the Metaverse by integrating \textsc {UTAUT2} and big five personality traits: A hybrid \textsc {SEM-ANN} approach$

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$Research paper thumbnail of Reliability and validity of the \textsc {C}hinese version of the \textsc {COVID-19} Phobia Scale$

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$Research paper thumbnail of Generation \textsc {Z} use of artificial intelligence products and its impact on environmental sustainability: A cross-cultural comparison$

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Purpose-Cybercrimes increase day by day in parallel to cyber-attacks and cyber-threats. Due to su... more Purpose-Cybercrimes increase day by day in parallel to cyber-attacks and cyber-threats. Due to such an increase, required cybersecurity precautions against all kinds of cyber-attacks and cyber-threats should be taken by both organizations and individuals. This study aims to develop a reliable and valid measurement tool to measure cybercrime awareness levels of individuals. Design/methodology/approach-In this study, a scale named as Cybercrime Awareness Scale (CAS) has been developed and psychometric properties of the scale have been tested by two separate studies. Findings-The first study included a total of 500 respondents (294 female and 206 male). In the first study, factor structure of the proposed scale has been determined through an exploratory factor analysis. The results revealed a three-factor structure (i.e. information systems crimes, personal data crimes, and privacy and security). Cronbach's alpha reliability coefficients for the subdimensions were 0.95, 0.92, and 0.90, respectively. The sample of the second study consisted of 494 respondents (281 female and 213 male). The confirmatory-factor-analysis results revealed that three-factor structure is valid and optimal model. Further, the proposed scale demonstrated moderate concurrent validity results in relation to the Digital Data Security Awareness Scale. Originality/value-Findings indicated that the CAS is a valid and reliable measurement tool to measure individuals' cybercrime awareness level. This study makes a novel contribution to the existing cybersecurity literature by providing the CAS, which is developed by following rigorous methodological standards.

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This study aimed to predict problematic smartphone use based on early maladaptive schemas (EMS) a... more This study aimed to predict problematic smartphone use based on early maladaptive schemas (EMS) and five schema domains. Machine learning algorithms were used to test the predictive models based on data collected from 1000 smartphone users. The study tested the predictive models by employing six machine learning classification algorithms (i.e., Bayes Net, SMO, IBk, Multi-Class Classifier, Decision Table, and Random Forest). The first predictive model was built on 14 schemas and tested by using 10-fold cross validation method. Results indicated that Multi-Class Classifier achieve a better prediction than other classifiers in classifying low-risk and high-risk smartphone users based on 14 schemas with an accuracy of 68.2%. The second model, which was built on five schema domains, was tested by using the best performance algorithm. Multi-Class Classifier predicted the users based on schemas related to the "impaired autonomy and performance" domain (i.e., "enmeshment/dependence, vulnerability to harm, and failure") with an accuracy of 66.2%. Further, the classifier predicted the users based on schemas related to the "disconnection and rejection" domain (i.e., "abandonment, emotional deprivation, defectiveness, and social isolation/mistrust") with an accuracy of 65.2%. Results emphasize the significance of EMS in predicting problematic smartphone use.

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Virtual meeting platforms have been identified as the golden bullet to deliver the learning mater... more Virtual meeting platforms have been identified as the golden bullet to deliver the learning materials to students during the COVID-19 pandemic. While this is evident across thousands of universities across the globe, the literature is scarce on what impacts the continued use of these platforms during and beyond the COVID-19 pandemic. Therefore, this research develops a theoretical model to examine the impact of psychological, social, and quality factors on the continuous intention to use these platforms. Unlike the previous adoption studies, which mainly relied on structural equation modeling (SEM) analysis, the developed model was validated through a hybrid approach using SEM and artificial neural network (ANN) based on data collected from 470 students. The hypotheses testing results indicated that psychological, social, and quality factors have significant positive impacts on the continuous intention to use virtual meeting platforms. The sensitivity analysis results revealed that psychological factors have the most considerable effect on the continuous intention to use virtual meeting platforms with 100% normalized importance, followed by quality factors (72%), and social factors (31%). The contribution of this study lies behind the development of an integrated model that considers the psychological, social, and quality factors in understanding the continuous intention to use virtual meeting platforms during and beyond the COVID-19 pandemic.

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Interactive Learning Environments

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The Metaverse is an immersive virtual universe where users interact with each other using an avat... more The Metaverse is an immersive virtual universe where users interact with each other using an avatar. The Metaverse is promised to offer numerous opportunities for many sectors. While the Metaverse promotes the social interaction between users, there is a scarcity of knowledge on what affects its social sustainability. Hence, this research develops a model by integrating the UTAUT2 constructs and big five personality traits to understand the social sustainability of the Metaverse. The model is tested by employing a hybrid covariance-based structural equation modeling (CB-SEM) and artificial neural network (ANN) approach based on collecting data from 446 Metaverse users. The CB-SEM results showed that performance expectancy, social influence, hedonic motivation, price value, habit, agreeableness, neuroticism, and openness significantly impact the social sustainability of the Metaverse, while no significant effect is reported regarding effort expectancy, facilitating conditions, conscientiousness, and extraversion. All these factors explained 80% of the variance in social sustainability. The ANN results showed that habit is the most important factor in predicting social sustainability. Drawing on these findings, the study offers several theoretical contributions and sheds light on several practical implications for developers, designers, and decision-makers promoting the use of the Metaverse.

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The emergence of wearable technologies, including smartwatches, has received a considerable atten... more The emergence of wearable technologies, including smartwatches, has received a considerable attention from scholars across several sectors. However, there is a scarcity of knowledge regarding the determinants affecting the adoption of these wearables in education. Therefore, this research aims to propose a theoretical research model through the integration of the theory of planned behavior (TPB) and protection motivation theory (PMT) to understand the students' behavioral intention to use smartwatches in learning activities. Through the use of machine learning classification algorithms, the proposed model has been validated using data collected via an online survey from 511 university students. The results indicated that perceived severity, perceived vulnerability, self-efficacy, response efficacy, subjective norm, attitude, and perceived behavioral control have a significant positive impact on students' behavioral intention to use smartwatches for educational purposes. Besides, response cost was found to have a significant negative effect on students' behavioral intention. The evidence from these findings provides the policy-makers in higher educational institutions with a clear vision of the most effective policies and best practices to enhance the capacity and potential use of these wearables in educational activities. The theoretical contributions and practical implications were also discussed.

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