Taking “Fun and Games” Seriously: Proposing the Hedonic-Motivation System Adoption Model (HMSAM)

Lowry, Paul Benjamin; Gaskin, James; Twyman, Nathan W.; Hammer, Bryan I.; Roberts, Tom

doi:10.17705/1jais.00347

Cited by 308 publications

(387 citation statements)

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“…They examine the different dimensions of CA to a state of deep involvement for learning and find out that CA plays a significant role. Within a hedonic motivation system, CA has been split and been examined as first-order constructs [21]. Results reveal that curiosity, enjoyment, and control are antecedents of immersion and are positively related.…”

Section: Discussionmentioning

confidence: 99%

“…In case of hedonic systems, besides CA, classical Technology Acceptance Model (TAM) constructs, such as perceived usefulness and perceived ease of use, are included into a theoretical model to explain use intentions [21]. Additional research which also includes TAM constructs, but in the context of mixed-motivation systems (i.e.…”

Section: Individual Learning Flow Cognitive Absorption and Virtualmentioning

confidence: 99%

“…Immersion is the total engagement to a specific task or activity [1,21] and within a VR setting it refers to a feeling of a realistic scenario. If it is more realistic, people will be more immersed.…”

Section: Implications For Theory and Designmentioning

confidence: 99%

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The Role of Immersive Virtual Reality in Individual Learning

Kampling¹

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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Section: Discussionmentioning

confidence: 99%

Section: Individual Learning Flow Cognitive Absorption and Virtualmentioning

confidence: 99%

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The Role of Immersive Virtual Reality in Individual Learning

Kampling¹

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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“…Third, self-report measures are subjective and may be susceptible to self-report biases such as acquiescence and desirability (Wilson & Nisbett, 1978). Self-reporting biases may increase when individuals discuss their failures (Ravaja, 2004 engagement and a simultaneous decrease in another type (see Flowerday & Schraw, 2003;Lowry, Gaskin, Twyman, Hammer, & Roberts, 2012;Skinner & Belmont, 1993).…”

Section: Measuring Engagementmentioning

confidence: 99%

Exploring Failure and Engagement in a Complex Digital Training Game: A Multi-method Examination

Jensen¹,

Piercy²,

Elzondo³

et al. 2016

THCI

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Abstract:Digital games are ideal for training complex decision making skills because they allow players to experience decision making processes and consequences. However, training complex skills often results in failure, which may undermine learning engagement. Traditional training methods employing observational learning (e.g., training videos) do not cause learners to fail but forfeit experiential learning that makes training games so engaging. Our exploratory work addresses the trade-off between experiencing and observing failure and explores their effect on the level of training engagement. Building on past engagement research, we argue that learning engagement contains both cognitive and affective facets and that these facets may diverge, especially when individuals experience failure. To test these ideas, we conducted an experiment (N = 156) comparing engagement in game-based training, in which participants experienced failure, and video-based training, in which participants observed failure. We collected cognitive and affective indicators of engagement using physiological and self-report measures. We found game-based experiential learning increased such indicators of engagement as attention and temporal disassociation even though players widely failed to meet game objectives. Players also experienced elevated arousal and decreased positive affect. In addition, we compared physiological measures of engagement with self-reported measures and discuss their merits and limitations.

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“…Within the broad field of computing, autotelic states such as flow have been studied in a range of contexts such as immersive gaming [13,14] game-based learning [15] instructional design [16] Information Systems adoption [17] and HCI [18,19,20].…”

Section: Introductionmentioning

confidence: 99%

Motivation, Optimal Experience and Flow in First Year Computing Science

McDermott

Zarb

Daniels

et al. 2016

Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education

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We examine the concept of motivation from the perspective of Self Determination Theory and give a brief overview of relevant results. We also consider the optimal state known as "Flow" and give an account of its conceptualisation in the theory due to Csikszentmihalyi. After discussion of ways in which these concepts can be measured, we describe a set of preliminary studies which looks at motivation and flow in the context of a first year computing class. We analyse student responses to enquiries about perceptions of motivation and flow experiences and look at links between them. We also discuss intrinsic motivation within the subject.

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Taking “Fun and Games” Seriously: Proposing the Hedonic-Motivation System Adoption Model (HMSAM)

Cited by 308 publications

References 0 publications

The Role of Immersive Virtual Reality in Individual Learning

The Role of Immersive Virtual Reality in Individual Learning

Exploring Failure and Engagement in a Complex Digital Training Game: A Multi-method Examination

Motivation, Optimal Experience and Flow in First Year Computing Science

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