Modeling Gameplay Enjoyment, Goal Orientations, and Individual Characteristics

Gamification ◽  
2015 ◽  
pp. 1451-1478
Author(s):  
John M. Quick ◽  
Robert K. Atkinson
Keyword(s):  
Structural Equation Modeling ◽  
Game Design ◽  
Structural Equation ◽  
Goal Orientations ◽  
Individual Characteristics ◽  
Equation Modeling ◽  
Design Features ◽  
Important Work ◽  
Six Dimensions ◽  
Player Enjoyment

The purpose of this study was to investigate the relationships between gameplay enjoyment, gaming goal orientations, and individual characteristics. A total of 301 participants were surveyed and the data were analyzed using structural equation modeling. This led to an expanded Gameplay Enjoyment Model (GEM) with 41 game design features that influence player enjoyment. Furthermore, a 3x2 Gaming Goal Orientations model was established with six dimensions that describe players' motivations for gaming. In addition, players' individual characteristics were used to predict gameplay enjoyment in the GEM-Individual Characteristics model. The six Gaming Goal Orientations dimensions were the strongest predictors, while the commonly used gender and hours played per week variables failed to predict enjoyment. The results of this study enable important work to be conducted surrounding gameplay experiences and individual characteristics. Ultimately, it is believed that the Gameplay Enjoyment Model, Gaming Goal Orientations, and the GEM-Individual Characteristics model will be useful tools for researchers and designers who seek to create effective gameplay experiences that meet the needs of players.

Modeling Gameplay Enjoyment, Goal Orientations, and Individual Characteristics

2014 ◽  
Vol 4 (2) ◽  
pp. 51-77 ◽  
Author(s):  
John M. Quick ◽  
Robert K. Atkinson
Keyword(s):  
Structural Equation Modeling ◽  
Game Design ◽  
Structural Equation ◽  
Goal Orientations ◽  
Individual Characteristics ◽  
Equation Modeling ◽  
Design Features ◽  
Important Work ◽  
Six Dimensions ◽  
Player Enjoyment

The purpose of this study was to investigate the relationships between gameplay enjoyment, gaming goal orientations, and individual characteristics. A total of 301 participants were surveyed and the data were analyzed using structural equation modeling. This led to an expanded Gameplay Enjoyment Model (GEM) with 41 game design features that influence player enjoyment. Furthermore, a 3x2 Gaming Goal Orientations model was established with six dimensions that describe players' motivations for gaming. In addition, players' individual characteristics were used to predict gameplay enjoyment in the GEM-Individual Characteristics model. The six Gaming Goal Orientations dimensions were the strongest predictors, while the commonly used gender and hours played per week variables failed to predict enjoyment. The results of this study enable important work to be conducted surrounding gameplay experiences and individual characteristics. Ultimately, it is believed that the Gameplay Enjoyment Model, Gaming Goal Orientations, and the GEM-Individual Characteristics model will be useful tools for researchers and designers who seek to create effective gameplay experiences that meet the needs of players.

scholarly journals Individual Characteristics as Prognostic Factors of the Evolution of Hospitalized COVID-19 Romanian Patients: A Comparative Observational Study between the First and Second Waves Based on Gaussian Graphical Models and Structural Equation Modeling

2021 ◽  
Vol 10 (9) ◽  
pp. 1958
Author(s):  
Alexandra Mocanu ◽  
Gratiela Georgiana Noja ◽  
Alin Viorel Istodor ◽  
Georgiana Moise ◽  
Marius Leretter ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Observational Study ◽  
Graphical Models ◽  
Structural Equation ◽  
Specific Treatment ◽  
Individual Characteristics ◽  
Equation Modeling ◽  
Gaussian Graphical Models ◽  
Treatment Methods ◽  
Second Wave

This study examines the role played by individual characteristics and specific treatment methods in the evolution of hospitalized patients with coronavirus disease 2019 (COVID-19), through the lens of an observational study performed in a comparative approach between the first and second waves of coronavirus pandemic in Romania. The research endeavor is configured on a two-fold approach, including a detailed observation of the evolution of 274 hospitalized patients with COVID-19 (145 in the first wave and 129 in the second wave of infection) according to specific treatment methods applied and patients’ individual features, as well as an econometric (quantitative) analysis through structural equation modeling and Gaussian graphical models designed to acknowledge the correlations and causal relationship between all considered coordinates. The main results highlight that the specific treatment methods applied had a positive influence on the evolution of COVID-19 patients, particularly in the second wave of coronavirus pandemic. In case of the first wave of COVID-19 infection, GGM results entail that there is a strong positive correlation between the evolution of the patients and the COVID-19 disease form, which is further positively correlated with the treatment scheme. The evolution of the patients is strongly and inversely correlated with the symptomatology and the ICU hospitalization. Moreover, the disease form is strongly and inversely correlated with oxygen saturation and the residence of patients (urban/rural). The symptomatology at first appearance also strongly depends on the age of the patients (positive correlation) and of the fact that the patient is a smoker or non-smoker and has other comorbidities. Age and gender are also important credentials that shape the disease degree and patient evolution in responding to treatment as well, our study attesting strong interconnections between these coordinates, the form of disease, symptomatology and overall evolution of the patients.

scholarly journals Temperamental Sensitivities Differentially Linked With Interest, Strain, and Effort Appraisals

2021 ◽  
Vol 11 ◽  
Author(s):  
Anna Maria Rawlings ◽  
Anna Tapola ◽  
Markku Niemivirta
Keyword(s):  
Structural Equation Modeling ◽  
Secondary Students ◽  
Structural Equation ◽  
Individual Characteristics ◽  
Reward Sensitivity ◽  
Equation Modeling ◽  
Course Grades ◽  
Lower Strain ◽  
Punishment Sensitivity ◽  
And Performance

The present research examined the connections between temperament (punishment sensitivity; interindividual reward sensitivity; intraindividual reward sensitivity), students’ domain- and course-specific motivational appraisals (interest, strain, effort), and performance, in two studies. Study 1 explored the relationships between temperamental sensitivities, motivational appraisals, and task achievement among secondary students (N = 268) in the domain of mathematics, using Exploratory Structural Equation Modeling (ESEM) for the analyses. Study 2 was conducted longitudinally among upper-secondary students (N = 155) during a course in four key school subjects. Subject interest was included alongside the temperamental sensitivities as a predictor of course-specific motivation and course grades, and the data were analysed with Partial Least Squares Structural Equation Modeling (PLS-SEM). Previous achievement was controlled in both studies. The findings showed temperamental sensitivities to be differentially linked with motivational appraisals. Punishment sensitivity in Study 1, and interindividual reward sensitivity (sensitivity to reward dependent on others’ approval or attention) in Study 2 were found to have an effect on psychological strain. In both studies, interest and effort were predicted by intraindividual reward sensitivity (positive responsiveness to novelty and own successes). In Study 2, subject interest was a consistent predictor of higher course interest and lower strain. In both studies, connections were found between strain and lower performance. The findings suggest individual characteristics may predispose students to certain motivational experiences, and contribute to educational outcomes, in both domain and course contexts and across subject content.

scholarly journals Temperamental Sensitivities Differentially Linked with Interest, Strain, and Effort Appraisals

2020 ◽  
Author(s):  
Anna Maria Rawlings ◽  
Anna Tapola ◽  
Markku Niemivirta
Keyword(s):  
Structural Equation Modeling ◽  
Secondary Students ◽  
Structural Equation ◽  
Individual Characteristics ◽  
Reward Sensitivity ◽  
Equation Modeling ◽  
Course Grades ◽  
Lower Strain ◽  
Punishment Sensitivity ◽  
And Performance

The present research examined the connections between temperament (punishment sensitivity; interindividual reward sensitivity; intraindividual reward sensitivity), students’ domain- and course-specific motivational appraisals (interest, strain, effort), and performance, in two studies. Study 1 explored the relationships between temperamental sensitivities, motivational appraisals, and task achievement among secondary students (N = 268) in the domain of mathematics, using Exploratory Structural Equation Modeling (ESEM) for the analyses. Study 2 was conducted longitudinally among upper-secondary students (N = 155) during a course in four key school subjects. Subject interest was included alongside the temperamental sensitivities as a predictor of course-specific motivation and course grades, and the data were analysed with Partial Least Squares Structural Equation Modeling (PLS-SEM). Previous achievement was controlled in both studies.The findings showed temperamental sensitivities to be differentially linked with motivational appraisals. Punishment sensitivity in Study 1, and interindividual reward sensitivity (sensitivity to reward dependent on others’ approval or attention) in Study 2 were found to have an effect on psychological strain. In both studies, interest and effort were predicted by intraindividual reward sensitivity (positive responsiveness to novelty and own successes). In Study 2, subject interest was a consistent predictor of higher course interest and lower strain. In both studies, connections were found between strain and lower performance. The findings suggest individual characteristics may predispose students to certain motivational experiences, and contribute to educational outcomes, in both domain and course contexts and across subject content.

The Gameplay Enjoyment Model

2012 ◽  
Vol 4 (4) ◽  
pp. 64-80 ◽  
Author(s):  
John M. Quick ◽  
Robert K. Atkinson ◽  
Lijia Lin
Keyword(s):  
Game Design ◽  
Structural Equation ◽  
Empirical Studies ◽  
Educational Game ◽  
Survey Study ◽  
Equation Modeling ◽  
Future Directions ◽  
Player Enjoyment ◽  
Model Components ◽  
Made In

To date, reviews of the games literature have noted a lack of empirical studies examining the relationships between games and their purported benefits (Huizenga, Admiraal, & Dam, 2011; Vandercruysse, Vanderwaetere, & Clarebout, 2012; Young et al., 2012). Furthermore, researchers have called for a better understanding of the specific game features that may lead to beneficial outcomes (Hartmann & Klimmt, 2006; Klimmt, Schmid, & Orthmann, 2009; McNamara, Jackson, & Graesser, 2010; Vorderer, Bryant, Pieper, & Weber, 2006; Wilson et al., 2009). In this survey study, a structural equation modeling (SEM) approach was employed to better understand the specific features that influence player enjoyment of video games. The resulting Gameplay Enjoyment Model (GEM) explains players’ overall Enjoyment of games, as well as their preferences for six specific types of enjoyment, including Challenge, Companionship, Competition, Exploration, Fantasy, and Fidelity. The implications of these model components are discussed in the context of educational game design and future directions for research are offered. GEM provides an empirical framework within which vital progress can be made in understanding the enjoyment of games and the role that games play in education.

scholarly journals PENGARUH KOMITMEN ORGANISASIONAL, PENGEMBANGAN KARIER, MOTIVASI KERJA DAN KARAKTERISTIK INDIVIDUAL TERHADAP KEPUASAN KERJA DAN KINERJA PEGAWAI PEMERINTAH KABUPATEN HALMAHERA TIMUR

2009 ◽  
Vol 5 (2) ◽  
Author(s):  
Musa Djamaludin
Keyword(s):  
Structural Equation Modeling ◽  
Organizational Commitment ◽  
Career Development ◽  
Structural Equation ◽  
Work Motivation ◽  
Critical Value ◽  
Individual Characteristics ◽  
Individual Characteristic ◽  
Equation Modeling ◽  
Development Work

Along with the forming of East Halmahera Regency at 2003, development activities develop rapidly. One of several determining factors of development success is determined by nation apparatus resource. The number of PNS that become the population in this research are employees in the Capital of East Halmahera Regency that isMabaCitywhich total population is 617 persons.           Human resources management influences organizational performance by increasing employee’s commitment that supported by good behavior of all employees. When each employee has commitment, good individual characteristics and good motivation, every employee is hopefully will be able to get working satisfaction and then, these satisfied employee will be able to increase their performance.           In this research, there is 200 employees or 31,32 percent (200/617 x 100%) from the whole population. However, the fact in the field shows that the number of questionnaire as the result of respondents’ answer cannot be tabulated completely, because there is only 194 questionnaire that considered appropriate. It is because 6 of them are destroyed and cannot be interpreted. Sample collection is done by using proportional stratified random sampling technique. Relation among variables in this research is analyzed with SEM (Structural Equation Modeling) with AMOS 4.01 program.          The result of examination to Goodness of Fit Index (GFI) criteria after model is modified shows that confirmatory analysis and structural Equation Modeling in this research can be accepted because of model fit with Chi-square score = 164.94 (critical value < 124.34); GFI = 0,924 (critical value > 0,90); and AGFI = 0,841 (critical value > 0,90). From the result of this research model, it is found out that organizational commitment, career development and work motivation is effective enough when it is used as stimulator of jobb satisfaction and employee’s performance. In other words, work satisfaction and employee’s performance can be improved through organizational commitment, career development; work motivation and individual characteristics. Among organization commitment, career development, work motivation and individual characteristic variables in the forming of jobb satisfaction and employee’s performance, individual characteristic gives the lowest contribution. It shows that individual characteristic is a factor that needs to receive better attention in order to support employee working achievement. Keywords:    organizational commitment, career development, work motivation, individual characteristics, job satisfaction, employee performance, East Halmahera Regency.

scholarly journals PENGARUH KARAKTERISTIK INDIVIDU DAN KEPEMIMPINAN TRANSFORMASIONAL TERHADAP KOMITMEN ORGANISASI DENGAN KEPUASAN KERJA SEBAGAI VARIABEL INTERVENING PADA DINAS SYARI’AT ISLAM KABUPATEN ACEH UTARA

2021 ◽  
Vol 6 (2) ◽  
pp. 11
Author(s):  
Rahmawati Rahmawati ◽  
Mariyudi Mariyudi ◽  
Ibrahim Qamarius
Keyword(s):  
Job Satisfaction ◽  
Transformational Leadership ◽  
Structural Equation Modeling ◽  
Organizational Commitment ◽  
Structural Equation ◽  
Individual Characteristics ◽  
Analytical Tool ◽  
Equation Modeling ◽  
Indirect Relationship

This study examined the effect of individual characteristics and transformational leadership on job satisfaction and organizational commitment of the employees at the Department of Islamic Shari'a. The samples were 114 employees. The analytical tool used was Structural Equation Modeling (SEM) using AMOS (Analysis of Moment Structure) tools. The results showed that individual characteristics and transformational leadership affected job satisfaction. Individual characteristics and job satisfaction also significantly affected organizational commitment. However, transformational leadership did not influence organizational commitment. Then, in testing the indirect relationship, job satisfaction did not mediate the effect of transformational leadership on organizational commitment. But job satisfaction fully mediated the effect of individual characteristics on organizational commitment

scholarly journals Emotion Regulation Predicts Imagery Ability

2016 ◽  
Vol 36 (3) ◽  
pp. 254-269 ◽  
Author(s):  
Nurwina Anuar ◽  
Jennifer Cumming ◽  
Sarah Williams
Keyword(s):  
Emotion Regulation ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Individual Characteristics ◽  
Equation Modeling ◽  
Imagery Ability ◽  
Negatively Associated ◽  
Applied Model ◽  
The Relationship

This study explored the relationship between athletes’ emotion regulation and imagery ability. A total of 648 athletes (57% female; Mage = 20.79 years, SD = 4.36) completed the Sport Imagery Ability Questionnaire (SIAQ) and Emotion Regulation Questionnaire (ERQ). Structural equation modeling supported the hypothesized model in which reappraisal positively predicted all SIAQ subscales. However, suppression had no significant association with imagery ability despite being predicted to be negatively associated. Results support the revised applied model of deliberate imagery use that individual characteristics will influence the imagery experience. Specifically, athletes who reappraise their emotions more frequently find it easier to image sport related content.

Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue
Keyword(s):  
Structural Equation Modeling ◽  
Negative Correlation ◽  
Structural Equation ◽  
Error Score ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equation Modeling ◽  
Eysenck Personality Questionnaire ◽  
Personality Questionnaire ◽  
True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

The Measurement Invariance of the Short Dark Triad

2020 ◽  
Vol 41 (4) ◽  
pp. 207-218
Author(s):  
Mihaela Grigoraș ◽  
Andreea Butucescu ◽  
Amalia Miulescu ◽  
Cristian Opariuc-Dan ◽  
Dragoș Iliescu
Keyword(s):  
Structural Equation Modeling ◽  
Item Response ◽  
Structural Equation ◽  
Dark Triad ◽  
Theory And Practice ◽  
Equation Modeling ◽  
Scale Level ◽  
High Stake ◽  
Differential Functioning ◽  
Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

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