scholarly journals User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study

10.2196/25771 ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. e25771
Author(s):  
Ali Darzi ◽  
Sean M McCrea ◽  
Domen Novak
Keyword(s):  
Intrinsic Motivation ◽  
User Experience ◽  
Performance Measures ◽  
Open Loop ◽  
Psychological State ◽  
Flow Experience ◽  
Ball Speed ◽  
Percentage Match ◽  
Experience Measure ◽  
Intrinsic Motivation Inventory

Background In affective exergames, game difficulty is dynamically adjusted to match the user’s physical and psychological state. Such an adjustment is commonly made based on a combination of performance measures (eg, in-game scores) and physiological measurements, which provide insight into the player’s psychological state. However, although many prototypes of affective games have been presented and many studies have shown that physiological measurements allow more accurate classification of the player’s psychological state than performance measures, few studies have examined whether dynamic difficulty adjustment (DDA) based on physiological measurements (which requires additional sensors) results in a better user experience than performance-based DDA or manual difficulty adjustment. Objective This study aims to compare five DDA methods in an affective exergame: manual (player-controlled), random, performance-based, personality-performance–based, and physiology-personality-performance–based (all-data). Methods A total of 50 participants (N=50) were divided into five groups, corresponding to the five DDA methods. They played an exergame version of Pong for 18 minutes, starting at a medium difficulty; every 2 minutes, two game difficulty parameters (ball speed and paddle size) were adjusted using the participant’s assigned DDA method. The DDA rules for the performance-based, personality-performance–based, and all-data groups were developed based on data from a previous open-loop study. Seven physiological responses were recorded throughout the sessions, and participants self-reported their preferred changes to difficulty every 2 minutes. After playing the game, participants reported their in-game experience using two questionnaires: the Intrinsic Motivation Inventory and the Flow Experience Measure. Results Although the all-data method resulted in the most accurate changes to ball speed and paddle size (defined as the percentage match between DDA choice and participants’ preference), no significant differences between DDA methods were found on the Intrinsic Motivation Inventory and Flow Experience Measure. When the data from all four automated DDA methods were pooled together, the accuracy of changes in ball speed was significantly correlated with players’ enjoyment (r=0.38) and pressure (r=0.43). Conclusions Although our study is limited by the use of a between-subjects design and may not generalize to other exergame designs, the results do not currently support the inclusion of physiological measurements in affective exergames, as they did not result in an improved user experience. As the accuracy of difficulty changes is correlated with user experience, the results support the development of more effective DDA methods. However, they show that the inclusion of physiological measurements does not guarantee a better user experience even if it yields promising results in offline cross-validation.

scholarly journals User Experience With Dynamic Difficulty Adjustment Methods for an Affective Exergame: Comparative Laboratory-Based Study (Preprint)

2020 ◽  
Author(s):  
Ali Darzi ◽  
Sean M McCrea ◽  
Domen Novak
Keyword(s):  
Intrinsic Motivation ◽  
User Experience ◽  
Performance Measures ◽  
Open Loop ◽  
Psychological State ◽  
Flow Experience ◽  
Ball Speed ◽  
Percentage Match ◽  
Experience Measure ◽  
Intrinsic Motivation Inventory

BACKGROUND In affective exergames, game difficulty is dynamically adjusted to match the user’s physical and psychological state. Such an adjustment is commonly made based on a combination of performance measures (eg, in-game scores) and physiological measurements, which provide insight into the player’s psychological state. However, although many prototypes of affective games have been presented and many studies have shown that physiological measurements allow more accurate classification of the player’s psychological state than performance measures, few studies have examined whether dynamic difficulty adjustment (DDA) based on physiological measurements (which requires additional sensors) results in a better user experience than performance-based DDA or manual difficulty adjustment. OBJECTIVE This study aims to compare five DDA methods in an affective exergame: manual (player-controlled), random, performance-based, personality-performance–based, and physiology-personality-performance–based (all-data). METHODS A total of 50 participants (N=50) were divided into five groups, corresponding to the five DDA methods. They played an exergame version of Pong for 18 minutes, starting at a medium difficulty; every 2 minutes, two game difficulty parameters (ball speed and paddle size) were adjusted using the participant’s assigned DDA method. The DDA rules for the performance-based, personality-performance–based, and all-data groups were developed based on data from a previous open-loop study. Seven physiological responses were recorded throughout the sessions, and participants self-reported their preferred changes to difficulty every 2 minutes. After playing the game, participants reported their in-game experience using two questionnaires: the Intrinsic Motivation Inventory and the Flow Experience Measure. RESULTS Although the all-data method resulted in the most accurate changes to ball speed and paddle size (defined as the percentage match between DDA choice and participants’ preference), no significant differences between DDA methods were found on the Intrinsic Motivation Inventory and Flow Experience Measure. When the data from all four automated DDA methods were pooled together, the accuracy of changes in ball speed was significantly correlated with players’ enjoyment (<i>r</i>=0.38) and pressure (<i>r</i>=0.43). CONCLUSIONS Although our study is limited by the use of a between-subjects design and may not generalize to other exergame designs, the results do not currently support the inclusion of physiological measurements in affective exergames, as they did not result in an improved user experience. As the accuracy of difficulty changes is correlated with user experience, the results support the development of more effective DDA methods. However, they show that the inclusion of physiological measurements does not guarantee a better user experience even if it yields promising results in offline cross-validation. CLINICALTRIAL

Flow

2019 ◽  
pp. 167-185
Author(s):  
Jeanne Nakamura ◽  
Dwight C.K. Tse ◽  
Shannon Shankland
Keyword(s):  
Intrinsic Motivation ◽  
Temporal Dynamics ◽  
Psychological State ◽  
Flow Experience ◽  
Flow State ◽  
Shed Light

Flow is an optimal psychological state characterized by the enjoyment of deep absorption in what one is doing. This psychological state is autotelic (i.e., rewarding in itself); experiencing flow intrinsically motivates individuals to engage in activities that are conducive to it. Research on the flow experience has shed light on the phenomenology of intrinsic motivation since Csikszentmihalyi (1975) first introduced the flow concept. This chapter (a) describes the dimensions and conditions of the flow experience, (b) reviews research on its psychological covariates, (c) highlights conceptual and operational differences among four flow-related constructs, (d) discusses theory and research on the temporal dynamics of flow experience, and (e) summarizes research on the neurophysiology of the flow state.

scholarly journals Identification of the flow experience in gamified educational environment

2021 ◽  
pp. 167-176
Author(s):  
Veljko Aleksić ◽  
Olga Ristić
Keyword(s):  
Response Time ◽  
User Experience ◽  
Educational Environment ◽  
Assessment Tools ◽  
Flow Experience ◽  
Sense Of Control ◽  
Average Response ◽  
Average Response Time ◽  
Educational Environments ◽  
Experience Of Flow

Determining and understanding the user experience in gamified educational environments is a contemporary challenge, especially when analyzing the flow experience (balance of challenge and skills, conscious actions, clear goals, clear feedback, sense of control, etc.). The reason for this lies in the assessment tools that most often created and implemented to separate the user from the experience of flow and/or cannot be applied en masse.The paper presents the results of a study in which flow experience was modeled based on data logs (e.g. number of mouse actions or average response time) in gamified educational environment on a sample of 31HE students. The results indicate the existence of correlations between data logs and flow experience dimensions.

Intrinsic Motivation Inventory--Revised

2012 ◽  
Author(s):  
J. R. van Seters ◽  
M. A. Ossevoort ◽  
J. Tramper ◽  
M. J. Goedhart
Keyword(s):  
Intrinsic Motivation ◽  
Intrinsic Motivation Inventory

Investigating the Mechanisms Underlying the Effects of an Incidental Choice on Motor Learning

2017 ◽  
Vol 5 (2) ◽  
pp. 207-226 ◽  
Author(s):  
Kirk F. Grand ◽  
Marcos Daou ◽  
Keith R. Lohse ◽  
Matthew W. Miller
Keyword(s):  
Motor Learning ◽  
Intrinsic Motivation ◽  
Learning Motivation ◽  
Augmented Feedback ◽  
Feedback Processing ◽  
Choice Group ◽  
Accuracy And Precision ◽  
Practice Performance ◽  
Intrinsic Motivation Inventory

The present study investigated whether motivation and augmented feedback processing explain the effect of an incidental choice on motor learning, and examined whether motivation and feedback processing generally predict learning. Accordingly, participants were assigned to one of two groups, choice or yoked, then asked to practice a nondominant arm beanbag toss. The choice group was allowed to choose the color of the beanbag with which they made the toss, whereas the yoked group was not. Motor learning was determined by delayed-posttest accuracy and precision. Motivation and augmented feedback processing were indexed via the Intrinsic Motivation Inventory and electroencephalography, respectively. We predicted the choice group would exhibit greater motor learning, motivation, and augmented feedback processing, and that the latter two variables would predict learning. Results showed that an incidental choice failed to enhance motor learning, motivation, or augmented feedback processing. In addition, neither motivation nor augmented feedback processing predicted motor learning. However, motivation and augmented feedback processing were correlated, with both factors predicting changes in practice performance. Thus, results suggest the effect of incidental choices on motor learning may be tenuous, and indicate motivation and augmented feedback processing may be more closely linked to changes in practice performance than motor learning.

scholarly journals Connecting Athletes’ Self-Perceptions and Metaperceptions of Competence: a Structural Equation Modeling Approach

2015 ◽  
Vol 46 (1) ◽  
pp. 189-198 ◽  
Author(s):  
Jose A. Cecchini ◽  
Javier Fernández-Rio ◽  
Antonio Méndez-Giménez
Keyword(s):  
Structural Equation Modeling ◽  
Intrinsic Motivation ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Self Perceptions ◽  
Equation Modelling ◽  
Modelling Analysis ◽  
Intrinsic Motivation Inventory ◽  
And Task

AbstractThis study explored the relationships between athletes’ competence self-perceptions and metaperceptions. Two hundred and fifty one student-athletes (14.26 ± 1.89 years), members of twenty different teams (basketball, soccer) completed a questionnaire which included the Perception of Success Questionnaire, the Competence subscale of the Intrinsic Motivation Inventory, and modified versions of both questionnaires to assess athletes’ metaperceptions. Structural equation modelling analysis revealed that athletes’ task and ego metaperceptions positively predicted task and ego self-perceptions, respectively. Competence metaperceptions were strong predictors of competence selfperceptions, confirming the atypical metaperception formation in outcome-dependent contexts such as sport. Task and ego metaperceptions positively predicted athletes’ competence metaperceptions. How coaches value their athletes’ competence is more influential on what the athletes think of themselves than their own self-perceptions. Athletes’ ego and task metaperceptions influenced their competence metaperceptions (how coaches rate their competence). Therefore, athletes build their competence metaperceptions using all information available from their coaches. Finally, only taskself perfections positively predicted athletes’ competence self-perceptions.

scholarly journals The effect of digital platforms in the motivation of future primary education teachers towards mathematics

2020 ◽  
Vol 7 (3) ◽  
pp. 112-123
Author(s):  
David Mendez ◽  
Miriam Mendez ◽  
Juana Maria Anguita
Keyword(s):  
Intrinsic Motivation ◽  
Elementary School Teachers ◽  
Research Study ◽  
Self Determination Theory ◽  
Self Determination ◽  
School Teachers ◽  
Digital Platforms ◽  
Motivation Level ◽  
High Level ◽  
Intrinsic Motivation Inventory

Motivation is a key element of daily life. At present, ICTs are considered to be highly motivating elements that are of great importance in all sectors of the society. The objective of this research study is to measure and assess the intrinsic motivation level of university students aiming to become Elementary School teachers regarding the use of digital platforms in their math classes. Using the Self-Determination Theory and the Intrinsic Motivation Theory, these students were given a test with 20 questions based on the Intrinsic Motivation Inventory. The results support the conclusion that all participants had a high level of intrinsic motivation, which was highest in students with no previous experience in the use of said resources. It is important to improve, through motivation, the knowledge and skills of future teachers regarding the use of ICTs to enable them to awaken their students’ interest in mathematics and facilitate their learning process.   Keywords: Intrinsic motivation, ICTs, digital platforms, math classes, school teachers.

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